WorldWideScience

Sample records for scale-free memory model

  1. Walking Across Wikipedia: A Scale-Free Network Model of Semantic Memory Retrieval

    Directory of Open Access Journals (Sweden)

    Graham William Thompson

    2014-02-01

    Full Text Available Semantic knowledge has been investigated using both online and offline methods. One common online method is category recall, in which members of a semantic category like animals are retrieved in a given period of time. The order, timing, and number of retrievals are used as assays of semantic memory processes. One common offline method is corpus analysis, in which the structure of semantic knowledge is extracted from texts using co-occurrence or encyclopedic methods. Online measures of semantic processing, as well as offline measures of semantic structure, have yielded data resembling inverse power law distributions. The aim of the present study is to investigate whether these patterns in data might be related. A semantic network model of animal knowledge is formulated on the basis of Wikipedia pages and their overlap in word probability distributions. The network is scale-free, in that node degree is related to node frequency as an inverse power law. A random walk over this network is shown to simulate a number of results from a category recall experiment, including power law-like distributions of inter-response intervals. Results are discussed in terms of theories of semantic structure and processing.

  2. Scale-free memory model for multiagent reinforcement learning. Mean field approximation and rock-paper-scissors dynamics

    Science.gov (United States)

    Lubashevsky, I.; Kanemoto, S.

    2010-07-01

    A continuous time model for multiagent systems governed by reinforcement learning with scale-free memory is developed. The agents are assumed to act independently of one another in optimizing their choice of possible actions via trial-and-error search. To gain awareness about the action value the agents accumulate in their memory the rewards obtained from taking a specific action at each moment of time. The contribution of the rewards in the past to the agent current perception of action value is described by an integral operator with a power-law kernel. Finally a fractional differential equation governing the system dynamics is obtained. The agents are considered to interact with one another implicitly via the reward of one agent depending on the choice of the other agents. The pairwise interaction model is adopted to describe this effect. As a specific example of systems with non-transitive interactions, a two agent and three agent systems of the rock-paper-scissors type are analyzed in detail, including the stability analysis and numerical simulation. Scale-free memory is demonstrated to cause complex dynamics of the systems at hand. In particular, it is shown that there can be simultaneously two modes of the system instability undergoing subcritical and supercritical bifurcation, with the latter one exhibiting anomalous oscillations with the amplitude and period growing with time. Besides, the instability onset via this supercritical mode may be regarded as “altruism self-organization”. For the three agent system the instability dynamics is found to be rather irregular and can be composed of alternate fragments of oscillations different in their properties.

  3. Scaling Techniques for Massive Scale-Free Graphs in Distributed (External) Memory

    KAUST Repository

    Pearce, Roger; Gokhale, Maya; Amato, Nancy M.

    2013-01-01

    We present techniques to process large scale-free graphs in distributed memory. Our aim is to scale to trillions of edges, and our research is targeted at leadership class supercomputers and clusters with local non-volatile memory, e.g., NAND Flash

  4. Scale-free, axisymmetry galaxy models with little angular momentum

    International Nuclear Information System (INIS)

    Richstone, D.O.

    1980-01-01

    Two scale-free models of elliptical galaxies are constructed using a self-consistent field approach developed by Schwarschild. Both models have concentric, oblate spheroidal, equipotential surfaces, with a logarithmic potential dependence on central distance. The axial ratio of the equipotential surfaces is 4:3, and the extent ratio of density level surfaces id 2.5:1 (corresponding to an E6 galaxy). Each model satisfies the Poisson and steady state Boltzmann equaion for time scales of order 100 galactic years

  5. Scaling Techniques for Massive Scale-Free Graphs in Distributed (External) Memory

    KAUST Repository

    Pearce, Roger

    2013-05-01

    We present techniques to process large scale-free graphs in distributed memory. Our aim is to scale to trillions of edges, and our research is targeted at leadership class supercomputers and clusters with local non-volatile memory, e.g., NAND Flash. We apply an edge list partitioning technique, designed to accommodate high-degree vertices (hubs) that create scaling challenges when processing scale-free graphs. In addition to partitioning hubs, we use ghost vertices to represent the hubs to reduce communication hotspots. We present a scaling study with three important graph algorithms: Breadth-First Search (BFS), K-Core decomposition, and Triangle Counting. We also demonstrate scalability on BG/P Intrepid by comparing to best known Graph500 results. We show results on two clusters with local NVRAM storage that are capable of traversing trillion-edge scale-free graphs. By leveraging node-local NAND Flash, our approach can process thirty-two times larger datasets with only a 39% performance degradation in Traversed Edges Per Second (TEPS). © 2013 IEEE.

  6. Self-Organized Criticality in a Simple Neuron Model Based on Scale-Free Networks

    International Nuclear Information System (INIS)

    Lin Min; Wang Gang; Chen Tianlun

    2006-01-01

    A simple model for a set of interacting idealized neurons in scale-free networks is introduced. The basic elements of the model are endowed with the main features of a neuron function. We find that our model displays power-law behavior of avalanche sizes and generates long-range temporal correlation. More importantly, we find different dynamical behavior for nodes with different connectivity in the scale-free networks.

  7. A novel evolving scale-free model with tunable attractiveness

    International Nuclear Information System (INIS)

    Xuan, Liu; Tian-Qi, Liu; Xing-Yuan, Li; Hao, Wang

    2010-01-01

    In this paper, a new evolving model with tunable attractiveness is presented. Based on the Barabasi–Albert (BA) model, we introduce the attractiveness of node which can change with node degree. Using the mean-field theory, we obtain the analytical expression of power-law degree distribution with the exponent γ in (3, ∞). The new model is more homogeneous and has a lower clustering coefficient and bigger average path length than the BA model. (general)

  8. Weighted Distances in Scale-Free Configuration Models

    Science.gov (United States)

    Adriaans, Erwin; Komjáthy, Júlia

    2018-01-01

    In this paper we study first-passage percolation in the configuration model with empirical degree distribution that follows a power-law with exponent τ \\in (2,3) . We assign independent and identically distributed (i.i.d.) weights to the edges of the graph. We investigate the weighted distance (the length of the shortest weighted path) between two uniformly chosen vertices, called typical distances. When the underlying age-dependent branching process approximating the local neighborhoods of vertices is found to produce infinitely many individuals in finite time—called explosive branching process—Baroni, Hofstad and the second author showed in Baroni et al. (J Appl Probab 54(1):146-164, 2017) that typical distances converge in distribution to a bounded random variable. The order of magnitude of typical distances remained open for the τ \\in (2,3) case when the underlying branching process is not explosive. We close this gap by determining the first order of magnitude of typical distances in this regime for arbitrary, not necessary continuous edge-weight distributions that produce a non-explosive age-dependent branching process with infinite mean power-law offspring distributions. This sequence tends to infinity with the amount of vertices, and, by choosing an appropriate weight distribution, can be tuned to be any growing function that is O(log log n) , where n is the number of vertices in the graph. We show that the result remains valid for the the erased configuration model as well, where we delete loops and any second and further edges between two vertices.

  9. A scale-free structure prior for graphical models with applications in functional genomics.

    Directory of Open Access Journals (Sweden)

    Paul Sheridan

    Full Text Available The problem of reconstructing large-scale, gene regulatory networks from gene expression data has garnered considerable attention in bioinformatics over the past decade with the graphical modeling paradigm having emerged as a popular framework for inference. Analysis in a full Bayesian setting is contingent upon the assignment of a so-called structure prior-a probability distribution on networks, encoding a priori biological knowledge either in the form of supplemental data or high-level topological features. A key topological consideration is that a wide range of cellular networks are approximately scale-free, meaning that the fraction, , of nodes in a network with degree is roughly described by a power-law with exponent between and . The standard practice, however, is to utilize a random structure prior, which favors networks with binomially distributed degree distributions. In this paper, we introduce a scale-free structure prior for graphical models based on the formula for the probability of a network under a simple scale-free network model. Unlike the random structure prior, its scale-free counterpart requires a node labeling as a parameter. In order to use this prior for large-scale network inference, we design a novel Metropolis-Hastings sampler for graphical models that includes a node labeling as a state space variable. In a simulation study, we demonstrate that the scale-free structure prior outperforms the random structure prior at recovering scale-free networks while at the same time retains the ability to recover random networks. We then estimate a gene association network from gene expression data taken from a breast cancer tumor study, showing that scale-free structure prior recovers hubs, including the previously unknown hub SLC39A6, which is a zinc transporter that has been implicated with the spread of breast cancer to the lymph nodes. Our analysis of the breast cancer expression data underscores the value of the scale-free

  10. Truncation of power law behavior in 'scale-free' network models due to information filtering

    International Nuclear Information System (INIS)

    Mossa, Stefano; Barthelemy, Marc; Eugene Stanley, H.; Nunes Amaral, Luis A.

    2002-01-01

    We formulate a general model for the growth of scale-free networks under filtering information conditions--that is, when the nodes can process information about only a subset of the existing nodes in the network. We find that the distribution of the number of incoming links to a node follows a universal scaling form, i.e., that it decays as a power law with an exponential truncation controlled not only by the system size but also by a feature not previously considered, the subset of the network 'accessible' to the node. We test our model with empirical data for the World Wide Web and find agreement

  11. Small-World and Scale-Free Network Models for IoT Systems

    Directory of Open Access Journals (Sweden)

    Insoo Sohn

    2017-01-01

    Full Text Available It is expected that Internet of Things (IoT revolution will enable new solutions and business for consumers and entrepreneurs by connecting billions of physical world devices with varying capabilities. However, for successful realization of IoT, challenges such as heterogeneous connectivity, ubiquitous coverage, reduced network and device complexity, enhanced power savings, and enhanced resource management have to be solved. All these challenges are heavily impacted by the IoT network topology supported by massive number of connected devices. Small-world networks and scale-free networks are important complex network models with massive number of nodes and have been actively used to study the network topology of brain networks, social networks, and wireless networks. These models, also, have been applied to IoT networks to enhance synchronization, error tolerance, and more. However, due to interdisciplinary nature of the network science, with heavy emphasis on graph theory, it is not easy to study the various tools provided by complex network models. Therefore, in this paper, we attempt to introduce basic concepts of graph theory, including small-world networks and scale-free networks, and provide system models that can be easily implemented to be used as a powerful tool in solving various research problems related to IoT.

  12. Scale-free models for the structure of business firm networks.

    Science.gov (United States)

    Kitsak, Maksim; Riccaboni, Massimo; Havlin, Shlomo; Pammolli, Fabio; Stanley, H Eugene

    2010-03-01

    We study firm collaborations in the life sciences and the information and communication technology sectors. We propose an approach to characterize industrial leadership using k -shell decomposition, with top-ranking firms in terms of market value in higher k -shell layers. We find that the life sciences industry network consists of three distinct components: a "nucleus," which is a small well-connected subgraph, "tendrils," which are small subgraphs consisting of small degree nodes connected exclusively to the nucleus, and a "bulk body," which consists of the majority of nodes. Industrial leaders, i.e., the largest companies in terms of market value, are in the highest k -shells of both networks. The nucleus of the life sciences sector is very stable: once a firm enters the nucleus, it is likely to stay there for a long time. At the same time we do not observe the above three components in the information and communication technology sector. We also conduct a systematic study of these three components in random scale-free networks. Our results suggest that the sizes of the nucleus and the tendrils in scale-free networks decrease as the exponent of the power-law degree distribution lambda increases, and disappear for lambda>or=3 . We compare the k -shell structure of random scale-free model networks with two real-world business firm networks in the life sciences and in the information and communication technology sectors. We argue that the observed behavior of the k -shell structure in the two industries is consistent with the coexistence of both preferential and random agreements in the evolution of industrial networks.

  13. Hysteresis-controlled instability waves in a scale-free driven current sheet model

    Directory of Open Access Journals (Sweden)

    V. M. Uritsky

    2005-01-01

    Full Text Available Magnetospheric dynamics is a complex multiscale process whose statistical features can be successfully reproduced using high-dimensional numerical transport models exhibiting the phenomenon of self-organized criticality (SOC. Along this line of research, a 2-dimensional driven current sheet (DCS model has recently been developed that incorporates an idealized current-driven instability with a resistive MHD plasma system (Klimas et al., 2004a, b. The dynamics of the DCS model is dominated by the scale-free diffusive energy transport characterized by a set of broadband power-law distribution functions similar to those governing the evolution of multiscale precipitation regions of energetic particles in the nighttime sector of aurora (Uritsky et al., 2002b. The scale-free DCS behavior is supported by localized current-driven instabilities that can communicate in an avalanche fashion over arbitrarily long distances thus producing current sheet waves (CSW. In this paper, we derive the analytical expression for CSW speed as a function of plasma parameters controlling local anomalous resistivity dynamics. The obtained relation indicates that the CSW propagation requires sufficiently high initial current densities, and predicts a deceleration of CSWs moving from inner plasma sheet regions toward its northern and southern boundaries. We also show that the shape of time-averaged current density profile in the DCS model is in agreement with steady-state spatial configuration of critical avalanching models as described by the singular diffusion theory of the SOC. Over shorter time scales, SOC dynamics is associated with rather complex spatial patterns and, in particular, can produce bifurcated current sheets often seen in multi-satellite observations.

  14. Dynamics of epidemic spreading model with drug-resistant variation on scale-free networks

    Science.gov (United States)

    Wan, Chen; Li, Tao; Zhang, Wu; Dong, Jing

    2018-03-01

    Considering the influence of the virus' drug-resistant variation, a novel SIVRS (susceptible-infected-variant-recovered-susceptible) epidemic spreading model with variation characteristic on scale-free networks is proposed in this paper. By using the mean-field theory, the spreading dynamics of the model is analyzed in detail. Then, the basic reproductive number R0 and equilibriums are derived. Studies show that the existence of disease-free equilibrium is determined by the basic reproductive number R0. The relationships between the basic reproductive number R0, the variation characteristic and the topology of the underlying networks are studied in detail. Furthermore, our studies prove the global stability of the disease-free equilibrium, the permanence of epidemic and the global attractivity of endemic equilibrium. Numerical simulations are performed to confirm the analytical results.

  15. Quantum phase transition of the transverse-field quantum Ising model on scale-free networks.

    Science.gov (United States)

    Yi, Hangmo

    2015-01-01

    I investigate the quantum phase transition of the transverse-field quantum Ising model in which nearest neighbors are defined according to the connectivity of scale-free networks. Using a continuous-time quantum Monte Carlo simulation method and the finite-size scaling analysis, I identify the quantum critical point and study its scaling characteristics. For the degree exponent λ=6, I obtain results that are consistent with the mean-field theory. For λ=4.5 and 4, however, the results suggest that the quantum critical point belongs to a non-mean-field universality class. Further simulations indicate that the quantum critical point remains mean-field-like if λ>5, but it continuously deviates from the mean-field theory as λ becomes smaller.

  16. Spreading dynamics of an e-commerce preferential information model on scale-free networks

    Science.gov (United States)

    Wan, Chen; Li, Tao; Guan, Zhi-Hong; Wang, Yuanmei; Liu, Xiongding

    2017-02-01

    In order to study the influence of the preferential degree and the heterogeneity of underlying networks on the spread of preferential e-commerce information, we propose a novel susceptible-infected-beneficial model based on scale-free networks. The spreading dynamics of the preferential information are analyzed in detail using the mean-field theory. We determine the basic reproductive number and equilibria. The theoretical analysis indicates that the basic reproductive number depends mainly on the preferential degree and the topology of the underlying networks. We prove the global stability of the information-elimination equilibrium. The permanence of preferential information and the global attractivity of the information-prevailing equilibrium are also studied in detail. Some numerical simulations are presented to verify the theoretical results.

  17. Spin glass behavior of the antiferromagnetic Heisenberg model on scale free network

    International Nuclear Information System (INIS)

    Surungan, Tasrief; Zen, Freddy P; Williams, Anthony G

    2015-01-01

    Randomness and frustration are considered to be the key ingredients for the existence of spin glass (SG) phase. In a canonical system, these ingredients are realized by the random mixture of ferromagnetic (FM) and antiferromagnetic (AF) couplings. The study by Bartolozzi et al. [Phys. Rev. B73, 224419 (2006)] who observed the presence of SG phase on the AF Ising model on scale free network (SFN) is stimulating. It is a new type of SG system where randomness and frustration are not caused by the presence of FM and AF couplings. To further elaborate this type of system, here we study Heisenberg model on AF SFN and search for the SG phase. The canonical SG Heisenberg model is not observed in d-dimensional regular lattices for (d ≤ 3). We can make an analogy for the connectivity density (m) of SFN with the dimensionality of the regular lattice. It should be plausible to find the critical value of m for the existence of SG behaviour, analogous to the lower critical dimension (d l ) for the canonical SG systems. Here we study system with m = 2, 3, 4 and 5. We used Replica Exchange algorithm of Monte Carlo Method and calculated the SG order parameter. We observed SG phase for each value of m and estimated its corersponding critical temperature. (paper)

  18. Dynamics of an epidemic model with quarantine on scale-free networks

    Science.gov (United States)

    Kang, Huiyan; Liu, Kaihui; Fu, Xinchu

    2017-12-01

    Quarantine strategies are frequently used to control or reduce the transmission risks of epidemic diseases such as SARS, tuberculosis and cholera. In this paper, we formulate a susceptible-exposed-infected-quarantined-recovered model on a scale-free network incorporating the births and deaths of individuals. Considering that the infectivity is related to the degrees of infectious nodes, we introduce quarantined rate as a function of degree into the model, and quantify the basic reproduction number, which is shown to be dependent on some parameters, such as quarantined rate, infectivity and network structures. A theoretical result further indicates the heterogeneity of networks and higher infectivity will raise the disease transmission risk while quarantine measure will contribute to the prevention of epidemic spreading. Meanwhile, the contact assumption between susceptibles and infectives may impact the disease transmission. Furthermore, we prove that the basic reproduction number serves as a threshold value for the global stability of the disease-free and endemic equilibria and the uniform persistence of the disease on the network by constructing appropriate Lyapunov functions. Finally, some numerical simulations are illustrated to perform and complement our analytical results.

  19. Self-organized Criticality in a Modified Evolution Model on Generalized Barabasi-Albert Scale-Free Networks

    International Nuclear Information System (INIS)

    Lin Min; Wang Gang; Chen Tianlun

    2007-01-01

    A modified evolution model of self-organized criticality on generalized Barabasi-Albert (GBA) scale-free networks is investigated. In our model, we find that spatial and temporal correlations exhibit critical behaviors. More importantly, these critical behaviors change with the parameter b, which weights the distance in comparison with the degree in the GBA network evolution.

  20. Stability of an SAIRS alcoholism model on scale-free networks

    Science.gov (United States)

    Xiang, Hong; Liu, Ying-Ping; Huo, Hai-Feng

    2017-05-01

    A new SAIRS alcoholism model with birth and death on complex heterogeneous networks is proposed. The total population of our model is partitioned into four compartments: the susceptible individual, the light problem alcoholic, the heavy problem alcoholic and the recovered individual. The spread of alcoholism threshold R0 is calculated by the next generation matrix method. When R0 alcohol free equilibrium is globally asymptotically stable, then the alcoholics will disappear. When R0 > 1, the alcoholism equilibrium is global attractivity, then the number of alcoholics will remain stable and alcoholism will become endemic. Furthermore, the modified SAIRS alcoholism model on weighted contact network is introduced. Dynamical behavior of the modified model is also studied. Numerical simulations are also presented to verify and extend theoretical results. Our results show that it is very important to treat alcoholics to control the spread of the alcoholism.

  1. Epidemic metapopulation model with traffic routing in scale-free networks

    International Nuclear Information System (INIS)

    Huang, Wei; Chen, Shengyong

    2011-01-01

    In this paper, we propose a model incorporating both the traffic routing dynamics and the virus prevalence dynamics. In this model, each packet may be isolated from the network on its transporting path, which means that the packet cannot be successfully delivered to its destination. In contrast, a successful transport means that a packet can be delivered from source to destination without being isolated. The effects of model parameters on the delivery success rate and the delivery failure rate are intensively studied and analyzed. Several routing strategies are performed for our model. Results show that the shortest path routing strategy is the most effective for enhancing the delivery success rate, especially when each packet is only allowed to be delivered to the neighbor with the lowest degree along the shortest path. We also find that, by minimizing the sum of the nodes' degree along the transporting path, we can also obtain a satisfactory delivery success rate

  2. Multi-granularity immunization strategy based on SIRS model in scale-free network

    Science.gov (United States)

    Nian, Fuzhong; Wang, Ke

    2015-04-01

    In this paper, a new immunization strategy was established to prevent the epidemic spreading based on the principle of "Multi-granularity" and "Pre-warning Mechanism", which send different pre-warning signal with the risk rank of the susceptible node to be infected. The pre-warning means there is a higher risk that the susceptible node is more likely to be infected. The multi-granularity means the susceptible node is linked with multi-infected nodes. In our model, the effect of the different situation of the multi-granularity immunizations is compared and different spreading rates are adopted to describe the epidemic behavior of nodes. In addition the threshold value of epidemic outbreak is investigated, which makes the result more convincing. The theoretical analysis and the simulations indicate that the proposed immunization strategy is effective and it is also economic and feasible.

  3. Generating Billion-Edge Scale-Free Networks in Seconds: Performance Study of a Novel GPU-based Preferential Attachment Model

    Energy Technology Data Exchange (ETDEWEB)

    Perumalla, Kalyan S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Alam, Maksudul [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2017-10-01

    A novel parallel algorithm is presented for generating random scale-free networks using the preferential-attachment model. The algorithm, named cuPPA, is custom-designed for single instruction multiple data (SIMD) style of parallel processing supported by modern processors such as graphical processing units (GPUs). To the best of our knowledge, our algorithm is the first to exploit GPUs, and also the fastest implementation available today, to generate scale free networks using the preferential attachment model. A detailed performance study is presented to understand the scalability and runtime characteristics of the cuPPA algorithm. In one of the best cases, when executed on an NVidia GeForce 1080 GPU, cuPPA generates a scale free network of a billion edges in less than 2 seconds.

  4. The scale-free dynamics of eukaryotic cells.

    Directory of Open Access Journals (Sweden)

    Miguel A Aon

    Full Text Available Temporal organization of biological processes requires massively parallel processing on a synchronized time-base. We analyzed time-series data obtained from the bioenergetic oscillatory outputs of Saccharomyces cerevisiae and isolated cardiomyocytes utilizing Relative Dispersional (RDA and Power Spectral (PSA analyses. These analyses revealed broad frequency distributions and evidence for long-term memory in the observed dynamics. Moreover RDA and PSA showed that the bioenergetic dynamics in both systems show fractal scaling over at least 3 orders of magnitude, and that this scaling obeys an inverse power law. Therefore we conclude that in S. cerevisiae and cardiomyocytes the dynamics are scale-free in vivo. Applying RDA and PSA to data generated from an in silico model of mitochondrial function indicated that in yeast and cardiomyocytes the underlying mechanisms regulating the scale-free behavior are similar. We validated this finding in vivo using single cells, and attenuating the activity of the mitochondrial inner membrane anion channel with 4-chlorodiazepam to show that the oscillation of NAD(PH and reactive oxygen species (ROS can be abated in these two evolutionarily distant species. Taken together these data strongly support our hypothesis that the generation of ROS, coupled to redox cycling, driven by cytoplasmic and mitochondrial processes, are at the core of the observed rhythmicity and scale-free dynamics. We argue that the operation of scale-free bioenergetic dynamics plays a fundamental role to integrate cellular function, while providing a framework for robust, yet flexible, responses to the environment.

  5. A recursive method for calculating the total number of spanning trees and its applications in self-similar small-world scale-free network models

    Science.gov (United States)

    Ma, Fei; Su, Jing; Yao, Bing

    2018-05-01

    The problem of determining and calculating the number of spanning trees of any finite graph (model) is a great challenge, and has been studied in various fields, such as discrete applied mathematics, theoretical computer science, physics, chemistry and the like. In this paper, firstly, thank to lots of real-life systems and artificial networks built by all kinds of functions and combinations among some simpler and smaller elements (components), we discuss some helpful network-operation, including link-operation and merge-operation, to design more realistic and complicated network models. Secondly, we present a method for computing the total number of spanning trees. As an accessible example, we apply this method to space of trees and cycles respectively, and our results suggest that it is indeed a better one for such models. In order to reflect more widely practical applications and potentially theoretical significance, we study the enumerating method in some existing scale-free network models. On the other hand, we set up a class of new models displaying scale-free feature, that is to say, following P(k) k-γ, where γ is the degree exponent. Based on detailed calculation, the degree exponent γ of our deterministic scale-free models satisfies γ > 3. In the rest of our discussions, we not only calculate analytically the solutions of average path length, which indicates our models have small-world property being prevailing in amounts of complex systems, but also derive the number of spanning trees by means of the recursive method described in this paper, which clarifies our method is convenient to research these models.

  6. The prisoner's dilemma in structured scale-free networks

    International Nuclear Information System (INIS)

    Li Xing; Wu Yonghui; Zhang Zhongzhi; Zhou Shuigeng; Rong Zhihai

    2009-01-01

    The conventional wisdom is that scale-free networks are prone to cooperation spreading. In this paper we investigate the cooperative behavior on the structured scale-free network. In contrast to the conventional wisdom that scale-free networks are prone to cooperation spreading, the evolution of cooperation is inhibited on the structured scale-free network when the prisoner's dilemma (PD) game is modeled. First, we demonstrate that neither the scale-free property nor the high clustering coefficient is responsible for the inhibition of cooperation spreading on the structured scale-free network. Then we provide one heuristic method to argue that the lack of age correlations and its associated 'large-world' behavior in the structured scale-free network inhibit the spread of cooperation. These findings may help enlighten further studies on the evolutionary dynamics of the PD game in scale-free networks

  7. Modeling Flight: The Role of Dynamically Scaled Free-Flight Models in Support of NASA's Aerospace Programs

    Science.gov (United States)

    Chambers, Joseph

    2010-01-01

    The state of the art in aeronautical engineering has been continually accelerated by the development of advanced analysis and design tools. Used in the early design stages for aircraft and spacecraft, these methods have provided a fundamental understanding of physical phenomena and enabled designers to predict and analyze critical characteristics of new vehicles, including the capability to control or modify unsatisfactory behavior. For example, the relatively recent emergence and routine use of extremely powerful digital computer hardware and software has had a major impact on design capabilities and procedures. Sophisticated new airflow measurement and visualization systems permit the analyst to conduct micro- and macro-studies of properties within flow fields on and off the surfaces of models in advanced wind tunnels. Trade studies of the most efficient geometrical shapes for aircraft can be conducted with blazing speed within a broad scope of integrated technical disciplines, and the use of sophisticated piloted simulators in the vehicle development process permits the most important segment of operations the human pilot to make early assessments of the acceptability of the vehicle for its intended mission. Knowledgeable applications of these tools of the trade dramatically reduce risk and redesign, and increase the marketability and safety of new aerospace vehicles. Arguably, one of the more viable and valuable design tools since the advent of flight has been testing of subscale models. As used herein, the term "model" refers to a physical article used in experimental analyses of a larger full-scale vehicle. The reader is probably aware that many other forms of mathematical and computer-based models are also used in aerospace design; however, such topics are beyond the intended scope of this document. Model aircraft have always been a source of fascination, inspiration, and recreation for humans since the earliest days of flight. Within the scientific

  8. A class of vertex-edge-growth small-world network models having scale-free, self-similar and hierarchical characters

    Science.gov (United States)

    Ma, Fei; Su, Jing; Hao, Yongxing; Yao, Bing; Yan, Guanghui

    2018-02-01

    The problem of uncovering the internal operating function of network models is intriguing, demanded and attractive in researches of complex networks. Notice that, in the past two decades, a great number of artificial models are built to try to answer the above mentioned task. Based on the different growth ways, these previous models can be divided into two categories, one type, possessing the preferential attachment, follows a power-law P(k) ∼k-γ, 2 motivated from a new attachment way, vertex-edge-growth network-operation, more precisely, the couple of both them. We report that this model is sparse, small world and hierarchical. And then, not only is scale-free feature in our model, but also lies the degree parameter γ(≈ 3 . 242) out the typical range. Note that, we suggest that the coexistence of multiple vertex growth ways will have a prominent effect on the power-law parameter γ, and the preferential attachment plays a dominate role on the development of networks over time. At the end of this paper, we obtain an exact analytical expression for the total number of spanning trees of models and also capture spanning trees entropy which we have compared with those of their corresponding component elements.

  9. Modelling high Reynolds number wall-turbulence interactions in laboratory experiments using large-scale free-stream turbulence.

    Science.gov (United States)

    Dogan, Eda; Hearst, R Jason; Ganapathisubramani, Bharathram

    2017-03-13

    A turbulent boundary layer subjected to free-stream turbulence is investigated in order to ascertain the scale interactions that dominate the near-wall region. The results are discussed in relation to a canonical high Reynolds number turbulent boundary layer because previous studies have reported considerable similarities between these two flows. Measurements were acquired simultaneously from four hot wires mounted to a rake which was traversed through the boundary layer. Particular focus is given to two main features of both canonical high Reynolds number boundary layers and boundary layers subjected to free-stream turbulence: (i) the footprint of the large scales in the logarithmic region on the near-wall small scales, specifically the modulating interaction between these scales, and (ii) the phase difference in amplitude modulation. The potential for a turbulent boundary layer subjected to free-stream turbulence to 'simulate' high Reynolds number wall-turbulence interactions is discussed. The results of this study have encouraging implications for future investigations of the fundamental scale interactions that take place in high Reynolds number flows as it demonstrates that these can be achieved at typical laboratory scales.This article is part of the themed issue 'Toward the development of high-fidelity models of wall turbulence at large Reynolds number'. © 2017 The Author(s).

  10. A measurement strategy and an error-compensation model for the on-machine laser measurement of large-scale free-form surfaces

    International Nuclear Information System (INIS)

    Li, Bin; Li, Feng; Liu, Hongqi; Cai, Hui; Mao, Xinyong; Peng, Fangyu

    2014-01-01

    This study presents a novel measurement strategy and an error-compensation model for the measurement of large-scale free-form surfaces in on-machine laser measurement systems. To improve the measurement accuracy, the effects of the scan depth, surface roughness, incident angle and azimuth angle on the measurement results were investigated experimentally, and a practical measurement strategy considering the position and orientation of the sensor is presented. Also, a semi-quantitative model based on geometrical optics is proposed to compensate for the measurement error associated with the incident angle. The normal vector of the measurement point is determined using a cross-curve method from the acquired surface data. Then, the azimuth angle and incident angle are calculated to inform the measurement strategy and error-compensation model, respectively. The measurement strategy and error-compensation model are verified through the measurement of a large propeller blade on a heavy machine tool in a factory environment. The results demonstrate that the strategy and the model are effective in increasing the measurement accuracy. (paper)

  11. Fractal scale-free networks resistant to disease spread

    International Nuclear Information System (INIS)

    Zhang, Zhongzhi; Zhou, Shuigeng; Zou, Tao; Chen, Guisheng

    2008-01-01

    The conventional wisdom is that scale-free networks are prone to epidemic propagation; in the paper we demonstrate that, on the contrary, disease spreading is inhibited in fractal scale-free networks. We first propose a novel network model and show that it simultaneously has the following rich topological properties: scale-free degree distribution, tunable clustering coefficient, 'large-world' behavior, and fractal scaling. Existing network models do not display these characteristics. Then, we investigate the susceptible–infected–removed (SIR) model of the propagation of diseases in our fractal scale-free networks by mapping it to the bond percolation process. We establish the existence of non-zero tunable epidemic thresholds by making use of the renormalization group technique, which implies that power law degree distribution does not suffice to characterize the epidemic dynamics on top of scale-free networks. We argue that the epidemic dynamics are determined by the topological properties, especially the fractality and its accompanying 'large-world' behavior

  12. Models of wave memory

    CERN Document Server

    Kashchenko, Serguey

    2015-01-01

    This monograph examines in detail models of neural systems described by delay-differential equations. Each element of the medium (neuron) is an oscillator that generates, in standalone mode, short impulses also known as spikes. The book discusses models of synaptic interaction between neurons, which lead to complex oscillatory modes in the system. In addition, it presents a solution to the problem of choosing the parameters of interaction in order to obtain attractors with predetermined structure. These attractors are represented as images encoded in the form of autowaves (wave memory). The target audience primarily comprises researchers and experts in the field, but it will also be beneficial for graduate students.

  13. Generating hierarchical scale free-graphs from fractals

    NARCIS (Netherlands)

    Komjáthy, J.; Simon, K.

    2011-01-01

    Motivated by the hierarchial network model of E. Ravasz, A.-L. Barabási, and T. Vicsek, we introduce deterministic scale-free networks derived from a graph directed self-similar fractal ¿. With rigorous mathematical results we verify that our model captures some of the most important features of

  14. Gradient networks on uncorrelated random scale-free networks

    International Nuclear Information System (INIS)

    Pan Guijun; Yan Xiaoqing; Huang Zhongbing; Ma Weichuan

    2011-01-01

    Uncorrelated random scale-free (URSF) networks are useful null models for checking the effects of scale-free topology on network-based dynamical processes. Here, we present a comparative study of the jamming level of gradient networks based on URSF networks and Erdos-Renyi (ER) random networks. We find that the URSF networks are less congested than ER random networks for the average degree (k)>k c (k c ∼ 2 denotes a critical connectivity). In addition, by investigating the topological properties of the two kinds of gradient networks, we discuss the relations between the topological structure and the transport efficiency of the gradient networks. These findings show that the uncorrelated scale-free structure might allow more efficient transport than the random structure.

  15. Emergence of cooperation in non-scale-free networks

    International Nuclear Information System (INIS)

    Zhang, Yichao; Aziz-Alaoui, M A; Bertelle, Cyrille; Zhou, Shi; Wang, Wenting

    2014-01-01

    Evolutionary game theory is one of the key paradigms behind many scientific disciplines from science to engineering. Previous studies proposed a strategy updating mechanism, which successfully demonstrated that the scale-free network can provide a framework for the emergence of cooperation. Instead, individuals in random graphs and small-world networks do not favor cooperation under this updating rule. However, a recent empirical result shows the heterogeneous networks do not promote cooperation when humans play a prisoner’s dilemma. In this paper, we propose a strategy updating rule with payoff memory. We observe that the random graphs and small-world networks can provide even better frameworks for cooperation than the scale-free networks in this scenario. Our observations suggest that the degree heterogeneity may be neither a sufficient condition nor a necessary condition for the widespread cooperation in complex networks. Also, the topological structures are not sufficed to determine the level of cooperation in complex networks. (paper)

  16. Emergence of Scale-Free Syntax Networks

    Science.gov (United States)

    Corominas-Murtra, Bernat; Valverde, Sergi; Solé, Ricard V.

    The evolution of human language allowed the efficient propagation of nongenetic information, thus creating a new form of evolutionary change. Language development in children offers the opportunity of exploring the emergence of such complex communication system and provides a window to understanding the transition from protolanguage to language. Here we present the first analysis of the emergence of syntax in terms of complex networks. A previously unreported, sharp transition is shown to occur around two years of age from a (pre-syntactic) tree-like structure to a scale-free, small world syntax network. The observed combinatorial patterns provide valuable data to understand the nature of the cognitive processes involved in the acquisition of syntax, introducing a new ingredient to understand the possible biological endowment of human beings which results in the emergence of complex language. We explore this problem by using a minimal, data-driven model that is able to capture several statistical traits, but some key features related to the emergence of syntactic complexity display important divergences.

  17. Modeling the Cray memory scheduler

    Energy Technology Data Exchange (ETDEWEB)

    Wickham, K.L.; Litteer, G.L.

    1992-04-01

    This report documents the results of a project to evaluate low cost modeling and simulation tools when applied to modeling the Cray memory scheduler. The specific tool used is described and the basics of the memory scheduler are covered. Results of simulations using the model are discussed and a favorable recommendation is made to make more use of this inexpensive technology.

  18. Modeling Implicit and Explicit Memory.

    NARCIS (Netherlands)

    Raaijmakers, J.G.W.; Ohta, N.; Izawa, C.

    2005-01-01

    Mathematical models of memory are useful for describing basic processes of memory in a way that enables generalization across a number of experimental paradigms. Models that have these characteristics do not just engage in empirical curve-fitting, but may also provide explanations for puzzling

  19. Models of Working Memory

    National Research Council Canada - National Science Library

    Miyake, Akira

    1997-01-01

    .... Understanding the mechanisms and structures underlying working memory is, hence, one of the most important scientific issues that need to be addressed to improve the efficiency and performance...

  20. Innovation diffusion equations on correlated scale-free networks

    Energy Technology Data Exchange (ETDEWEB)

    Bertotti, M.L., E-mail: marialetizia.bertotti@unibz.it [Free University of Bozen–Bolzano, Faculty of Science and Technology, Bolzano (Italy); Brunner, J., E-mail: johannes.brunner@tis.bz.it [TIS Innovation Park, Bolzano (Italy); Modanese, G., E-mail: giovanni.modanese@unibz.it [Free University of Bozen–Bolzano, Faculty of Science and Technology, Bolzano (Italy)

    2016-07-29

    Highlights: • The Bass diffusion model can be formulated on scale-free networks. • In the trickle-down version, the hubs adopt earlier and act as monitors. • We improve the equations in order to describe trickle-up diffusion. • Innovation is generated at the network periphery, and hubs can act as stiflers. • We compare diffusion times, in dependence on the scale-free exponent. - Abstract: We introduce a heterogeneous network structure into the Bass diffusion model, in order to study the diffusion times of innovation or information in networks with a scale-free structure, typical of regions where diffusion is sensitive to geographic and logistic influences (like for instance Alpine regions). We consider both the diffusion peak times of the total population and of the link classes. In the familiar trickle-down processes the adoption curve of the hubs is found to anticipate the total adoption in a predictable way. In a major departure from the standard model, we model a trickle-up process by introducing heterogeneous publicity coefficients (which can also be negative for the hubs, thus turning them into stiflers) and a stochastic term which represents the erratic generation of innovation at the periphery of the network. The results confirm the robustness of the Bass model and expand considerably its range of applicability.

  1. Innovation diffusion equations on correlated scale-free networks

    International Nuclear Information System (INIS)

    Bertotti, M.L.; Brunner, J.; Modanese, G.

    2016-01-01

    Highlights: • The Bass diffusion model can be formulated on scale-free networks. • In the trickle-down version, the hubs adopt earlier and act as monitors. • We improve the equations in order to describe trickle-up diffusion. • Innovation is generated at the network periphery, and hubs can act as stiflers. • We compare diffusion times, in dependence on the scale-free exponent. - Abstract: We introduce a heterogeneous network structure into the Bass diffusion model, in order to study the diffusion times of innovation or information in networks with a scale-free structure, typical of regions where diffusion is sensitive to geographic and logistic influences (like for instance Alpine regions). We consider both the diffusion peak times of the total population and of the link classes. In the familiar trickle-down processes the adoption curve of the hubs is found to anticipate the total adoption in a predictable way. In a major departure from the standard model, we model a trickle-up process by introducing heterogeneous publicity coefficients (which can also be negative for the hubs, thus turning them into stiflers) and a stochastic term which represents the erratic generation of innovation at the periphery of the network. The results confirm the robustness of the Bass model and expand considerably its range of applicability.

  2. Models of Working Memory

    National Research Council Canada - National Science Library

    Miyake, Akira

    1997-01-01

    Working memory is a basic cognitive mechanism (or set of mechanisms) that is responsible for keeping track of multiple task related goals and subgoals, or integrating multiple sources of information...

  3. Thermodynamic Model of Spatial Memory

    Science.gov (United States)

    Kaufman, Miron; Allen, P.

    1998-03-01

    We develop and test a thermodynamic model of spatial memory. Our model is an application of statistical thermodynamics to cognitive science. It is related to applications of the statistical mechanics framework in parallel distributed processes research. Our macroscopic model allows us to evaluate an entropy associated with spatial memory tasks. We find that older adults exhibit higher levels of entropy than younger adults. Thurstone's Law of Categorical Judgment, according to which the discriminal processes along the psychological continuum produced by presentations of a single stimulus are normally distributed, is explained by using a Hooke spring model of spatial memory. We have also analyzed a nonlinear modification of the ideal spring model of spatial memory. This work is supported by NIH/NIA grant AG09282-06.

  4. Power Laws, Scale-Free Networks and Genome Biology

    CERN Document Server

    Koonin, Eugene V; Karev, Georgy P

    2006-01-01

    Power Laws, Scale-free Networks and Genome Biology deals with crucial aspects of the theoretical foundations of systems biology, namely power law distributions and scale-free networks which have emerged as the hallmarks of biological organization in the post-genomic era. The chapters in the book not only describe the interesting mathematical properties of biological networks but moves beyond phenomenology, toward models of evolution capable of explaining the emergence of these features. The collection of chapters, contributed by both physicists and biologists, strives to address the problems in this field in a rigorous but not excessively mathematical manner and to represent different viewpoints, which is crucial in this emerging discipline. Each chapter includes, in addition to technical descriptions of properties of biological networks and evolutionary models, a more general and accessible introduction to the respective problems. Most chapters emphasize the potential of theoretical systems biology for disco...

  5. Bursting synchronization in scale-free networks

    International Nuclear Information System (INIS)

    Batista, C.A.S.; Batista, A.M.; Pontes, J.C.A. de; Lopes, S.R.; Viana, R.L.

    2009-01-01

    Neuronal networks in some areas of the brain cortex present the scale-free property, i.e., the neuron connectivity is distributed according to a power-law, such that neurons are more likely to couple with other already well-connected ones. Neuron activity presents two timescales, a fast one related to action-potential spiking, and a slow timescale in which bursting takes place. Some pathological conditions are related with the synchronization of the bursting activity in a weak sense, meaning the adjustment of the bursting phase due to coupling. Hence it has been proposed that an externally applied time-periodic signal be applied in order to control undesirable synchronized bursting rhythms. We investigated this kind of intervention using a two-dimensional map to describe neurons with spiking-bursting activity in a scale-free network.

  6. Generating hierarchial scale-free graphs from fractals

    Energy Technology Data Exchange (ETDEWEB)

    Komjathy, Julia, E-mail: komyju@math.bme.hu [Department of Stochastics, Institute of Mathematics, Technical University of Budapest, H-1529 P.O. Box 91 (Hungary); Simon, Karoly, E-mail: simonk@math.bme.hu [Department of Stochastics, Institute of Mathematics, Technical University of Budapest, H-1529 P.O. Box 91 (Hungary)

    2011-08-15

    Highlights: > We generate deterministic scale-free networks using graph-directed self similar IFS. > Our model exhibits similar clustering, power law decay properties to real networks. > The average length of shortest path and the diameter of the graph are determined. > Using this model, we generate random graphs with prescribed power law exponent. - Abstract: Motivated by the hierarchial network model of E. Ravasz, A.-L. Barabasi, and T. Vicsek, we introduce deterministic scale-free networks derived from a graph directed self-similar fractal {Lambda}. With rigorous mathematical results we verify that our model captures some of the most important features of many real networks: the scale-free and the high clustering properties. We also prove that the diameter is the logarithm of the size of the system. We point out a connection between the power law exponent of the degree distribution and some intrinsic geometric measure theoretical properties of the underlying fractal. Using our (deterministic) fractal {Lambda} we generate random graph sequence sharing similar properties.

  7. Chaotic Modes in Scale Free Opinion Networks

    Science.gov (United States)

    Kusmartsev, Feo V.; Kürten, Karl E.

    2010-12-01

    In this paper, we investigate processes associated with formation of public opinion in varies directed random, scale free and small-world social networks. The important factor of the opinion formation is the existence of contrarians which were discovered by Granovetter in various social psychology experiments1,2,3 long ago and later introduced in sociophysics by Galam.4 When the density of contrarians increases the system behavior drastically changes at some critical value. At high density of contrarians the system can never arrive to a consensus state and periodically oscillates with different periods depending on specific structure of the network. At small density of the contrarians the behavior is manifold. It depends primary on the initial state of the system. If initially the majority of the population agrees with each other a state of stable majority may be easily reached. However when originally the population is divided in nearly equal parts consensus can never be reached. We model the emergence of collective decision making by considering N interacting agents, whose opinions are described by two state Ising spin variable associated with YES and NO. We show that the dynamical behaviors are very sensitive not only to the density of the contrarians but also to the network topology. We find that a phase of social chaos may arise in various dynamical processes of opinion formation in many realistic models. We compare the prediction of the theory with data describing the dynamics of the average opinion of the USA population collected on a day-by-day basis by varies media sources during the last six month before the final Obama-McCain election. The qualitative ouctome is in reasonable agreement with the prediction of our theory. In fact, the analyses of these data made within the paradigm of our theory indicates that even in this campaign there were chaotic elements where the public opinion migrated in an unpredictable chaotic way. The existence of such a phase

  8. Sensory Dissonance Using Memory Model

    DEFF Research Database (Denmark)

    Jensen, Karl Kristoffer

    2015-01-01

    Music may occur concurrently or in temporal sequences. Current machine-based methods for the estimation of qualities of the music are unable to take into account the influence of temporal context. A method for calculating dissonance from audio, called sensory dissonance is improved by the use of ...... of a memory model. This approach is validated here by the comparison of the sensory dissonance using memory model to data obtained using human subjects....

  9. Cascading failure in the wireless sensor scale-free networks

    Science.gov (United States)

    Liu, Hao-Ran; Dong, Ming-Ru; Yin, Rong-Rong; Han, Li

    2015-05-01

    In the practical wireless sensor networks (WSNs), the cascading failure caused by a failure node has serious impact on the network performance. In this paper, we deeply research the cascading failure of scale-free topology in WSNs. Firstly, a cascading failure model for scale-free topology in WSNs is studied. Through analyzing the influence of the node load on cascading failure, the critical load triggering large-scale cascading failure is obtained. Then based on the critical load, a control method for cascading failure is presented. In addition, the simulation experiments are performed to validate the effectiveness of the control method. The results show that the control method can effectively prevent cascading failure. Project supported by the Natural Science Foundation of Hebei Province, China (Grant No. F2014203239), the Autonomous Research Fund of Young Teacher in Yanshan University (Grant No. 14LGB017) and Yanshan University Doctoral Foundation, China (Grant No. B867).

  10. Relaxed memory models: an operational approach

    OpenAIRE

    Boudol , Gérard; Petri , Gustavo

    2009-01-01

    International audience; Memory models define an interface between programs written in some language and their implementation, determining which behaviour the memory (and thus a program) is allowed to have in a given model. A minimal guarantee memory models should provide to the programmer is that well-synchronized, that is, data-race free code has a standard semantics. Traditionally, memory models are defined axiomatically, setting constraints on the order in which memory operations are allow...

  11. A Temporal Ratio Model of Memory

    Science.gov (United States)

    Brown, Gordon D. A.; Neath, Ian; Chater, Nick

    2007-01-01

    A model of memory retrieval is described. The model embodies four main claims: (a) temporal memory--traces of items are represented in memory partly in terms of their temporal distance from the present; (b) scale-similarity--similar mechanisms govern retrieval from memory over many different timescales; (c) local distinctiveness--performance on a…

  12. Opinion Spreading with Mobility on Scale-Free Networks

    International Nuclear Information System (INIS)

    Qiang, Guo; Xing-Wen, Chen; Jian-Guo, Liu; Bing-Hong, Wang; Tao, Zhou; Yu-Hua, Yao

    2008-01-01

    A continuum opinion dynamic model is presented based on two rules. The first one considers the mobilities of the individuals, the second one supposes that the individuals update their opinions independently. The results of the model indicate that the bounded confidence in c , separating consensus and incoherent states, of a scale-free network is much smaller than the one of a lattice. If the system can reach the consensus state, the sum of all individuals' opinion change O c (t) quickly decreases in an exponential form, while if it reaches the incoherent state finally O c (t) decreases slowly and has the punctuated equilibrium characteristic

  13. Generate the scale-free brain music from BOLD signals.

    Science.gov (United States)

    Lu, Jing; Guo, Sijia; Chen, Mingming; Wang, Weixia; Yang, Hua; Guo, Daqing; Yao, Dezhong

    2018-01-01

    Many methods have been developed to translate a human electroencephalogram (EEG) into music. In addition to EEG, functional magnetic resonance imaging (fMRI) is another method used to study the brain and can reflect physiological processes. In 2012, we established a method to use simultaneously recorded fMRI and EEG signals to produce EEG-fMRI music, which represents a step toward scale-free brain music. In this study, we used a neural mass model, the Jansen-Rit model, to simulate activity in several cortical brain regions. The interactions between different brain regions were represented by the average normalized diffusion tensor imaging (DTI) structural connectivity with a coupling coefficient that modulated the coupling strength. Seventy-eight brain regions were adopted from the Automated Anatomical Labeling (AAL) template. Furthermore, we used the Balloon-Windkessel hemodynamic model to transform neural activity into a blood-oxygen-level dependent (BOLD) signal. Because the fMRI BOLD signal changes slowly, we used a sampling rate of 250 Hz to produce the temporal series for music generation. Then, the BOLD music was generated for each region using these simulated BOLD signals. Because the BOLD signal is scale free, these music pieces were also scale free, which is similar to classic music. Here, to simulate the case of an epileptic patient, we changed the parameter that determined the amplitude of the excitatory postsynaptic potential (EPSP) in the neural mass model. Finally, we obtained BOLD music for healthy and epileptic patients. The differences in levels of arousal between the 2 pieces of music may provide a potential tool for discriminating the different populations if the differences can be confirmed by more real data. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.

  14. A simplified memory network model based on pattern formations

    Science.gov (United States)

    Xu, Kesheng; Zhang, Xiyun; Wang, Chaoqing; Liu, Zonghua

    2014-12-01

    Many experiments have evidenced the transition with different time scales from short-term memory (STM) to long-term memory (LTM) in mammalian brains, while its theoretical understanding is still under debate. To understand its underlying mechanism, it has recently been shown that it is possible to have a long-period rhythmic synchronous firing in a scale-free network, provided the existence of both the high-degree hubs and the loops formed by low-degree nodes. We here present a simplified memory network model to show that the self-sustained synchronous firing can be observed even without these two necessary conditions. This simplified network consists of two loops of coupled excitable neurons with different synaptic conductance and with one node being the sensory neuron to receive an external stimulus signal. This model can be further used to show how the diversity of firing patterns can be selectively formed by varying the signal frequency, duration of the stimulus and network topology, which corresponds to the patterns of STM and LTM with different time scales. A theoretical analysis is presented to explain the underlying mechanism of firing patterns.

  15. Scale-free music of the brain.

    Directory of Open Access Journals (Sweden)

    Dan Wu

    Full Text Available BACKGROUND: There is growing interest in the relation between the brain and music. The appealing similarity between brainwaves and the rhythms of music has motivated many scientists to seek a connection between them. A variety of transferring rules has been utilized to convert the brainwaves into music; and most of them are mainly based on spectra feature of EEG. METHODOLOGY/PRINCIPAL FINDINGS: In this study, audibly recognizable scale-free music was deduced from individual Electroencephalogram (EEG waveforms. The translation rules include the direct mapping from the period of an EEG waveform to the duration of a note, the logarithmic mapping of the change of average power of EEG to music intensity according to the Fechner's law, and a scale-free based mapping from the amplitude of EEG to music pitch according to the power law. To show the actual effect, we applied the deduced sonification rules to EEG segments recorded during rapid-eye movement sleep (REM and slow-wave sleep (SWS. The resulting music is vivid and different between the two mental states; the melody during REM sleep sounds fast and lively, whereas that in SWS sleep is slow and tranquil. 60 volunteers evaluated 25 music pieces, 10 from REM, 10 from SWS and 5 from white noise (WN, 74.3% experienced a happy emotion from REM and felt boring and drowsy when listening to SWS, and the average accuracy for all the music pieces identification is 86.8%(kappa = 0.800, P<0.001. We also applied the method to the EEG data from eyes closed, eyes open and epileptic EEG, and the results showed these mental states can be identified by listeners. CONCLUSIONS/SIGNIFICANCE: The sonification rules may identify the mental states of the brain, which provide a real-time strategy for monitoring brain activities and are potentially useful to neurofeedback therapy.

  16. Attempting to model dissociations of memory.

    Science.gov (United States)

    Reber, Paul J.

    2002-05-01

    Kinder and Shanks report simulations aimed at describing a single-system model of the dissociation between declarative and non-declarative memory. This model attempts to capture both Artificial Grammar Learning (AGL) and recognition memory with a single underlying representation. However, the model fails to reflect an essential feature of recognition memory - that it occurs after a single exposure - and the simulations may instead describe a potentially interesting property of over-training non-declarative memory.

  17. Neutral Theory and Scale-Free Neural Dynamics

    Science.gov (United States)

    Martinello, Matteo; Hidalgo, Jorge; Maritan, Amos; di Santo, Serena; Plenz, Dietmar; Muñoz, Miguel A.

    2017-10-01

    Neural tissues have been consistently observed to be spontaneously active and to generate highly variable (scale-free distributed) outbursts of activity in vivo and in vitro. Understanding whether these heterogeneous patterns of activity stem from the underlying neural dynamics operating at the edge of a phase transition is a fascinating possibility, as criticality has been argued to entail many possible important functional advantages in biological computing systems. Here, we employ a well-accepted model for neural dynamics to elucidate an alternative scenario in which diverse neuronal avalanches, obeying scaling, can coexist simultaneously, even if the network operates in a regime far from the edge of any phase transition. We show that perturbations to the system state unfold dynamically according to a "neutral drift" (i.e., guided only by stochasticity) with respect to the background of endogenous spontaneous activity, and that such a neutral dynamics—akin to neutral theories of population genetics and of biogeography—implies marginal propagation of perturbations and scale-free distributed causal avalanches. We argue that causal information, not easily accessible to experiments, is essential to elucidate the nature and statistics of neural avalanches, and that neutral dynamics is likely to play an important role in the cortex functioning. We discuss the implications of these findings to design new empirical approaches to shed further light on how the brain processes and stores information.

  18. Effects of degree correlation on scale-free gradient networks

    International Nuclear Information System (INIS)

    Pan Guijun; Yan Xiaoqing; Ma Weichuan; Luo Yihui; Huang Zhongbing

    2010-01-01

    We have studied the effects of degree correlation on congestion pressure in scale-free gradient networks. It is observed that the jamming coefficient J is insensitive to the degree correlation coefficient r for assortative and strongly disassortative scale-free networks, and J markedly decreases with an increase in r for weakly disassortative scale-free networks. We have also investigated the effects of degree correlation on the topology structure of scale-free gradient networks, and discussed the relation between the topology structure properties and transport efficiency of gradient networks.

  19. Modeling reconsolidation in kernel associative memory.

    Directory of Open Access Journals (Sweden)

    Dimitri Nowicki

    Full Text Available Memory reconsolidation is a central process enabling adaptive memory and the perception of a constantly changing reality. It causes memories to be strengthened, weakened or changed following their recall. A computational model of memory reconsolidation is presented. Unlike Hopfield-type memory models, our model introduces an unbounded number of attractors that are updatable and can process real-valued, large, realistic stimuli. Our model replicates three characteristic effects of the reconsolidation process on human memory: increased association, extinction of fear memories, and the ability to track and follow gradually changing objects. In addition to this behavioral validation, a continuous time version of the reconsolidation model is introduced. This version extends average rate dynamic models of brain circuits exhibiting persistent activity to include adaptivity and an unbounded number of attractors.

  20. Epidemic spreading on adaptively weighted scale-free networks.

    Science.gov (United States)

    Sun, Mengfeng; Zhang, Haifeng; Kang, Huiyan; Zhu, Guanghu; Fu, Xinchu

    2017-04-01

    We introduce three modified SIS models on scale-free networks that take into account variable population size, nonlinear infectivity, adaptive weights, behavior inertia and time delay, so as to better characterize the actual spread of epidemics. We develop new mathematical methods and techniques to study the dynamics of the models, including the basic reproduction number, and the global asymptotic stability of the disease-free and endemic equilibria. We show the disease-free equilibrium cannot undergo a Hopf bifurcation. We further analyze the effects of local information of diseases and various immunization schemes on epidemic dynamics. We also perform some stochastic network simulations which yield quantitative agreement with the deterministic mean-field approach.

  1. Sandpile on scale-free networks with assortative mixing

    International Nuclear Information System (INIS)

    Yin Yanping; Zhang Duanming; Pan Guijun; He Minhua; Tan Jin

    2007-01-01

    We numerically investigate the Bak-Tang-Wiesenfeld sandpile model on scale-free networks with assortative mixing, where the threshold height of each node is equal to its degree. It is observed that a large fraction of multiple topplings are included in avalanches on assortative networks, which is absent on uncorrelated networks. We introduce a parameter F-bar(a) to characterize the fraction of multiple topplings in avalanches of area a. The fraction of multiple topplings increases dramatically with the degree of assortativity and has a peak for small a whose height also increase with the assortativity of the networks. Unlike the case on uncorrelated networks, the distributions of avalanche size, area and duration do not follow pure power law, but deviate more obviously from pure power law with the growing degree of assortativity. The results show that the assortative mixing has a strong influence on the behavior of avalanche dynamics on complex networks

  2. Cooperative Dynamics in Lattice-Embedded Scale-Free Networks

    International Nuclear Information System (INIS)

    Shang Lihui; Zhang Mingji; Yang Yanqing

    2009-01-01

    We investigate cooperative behaviors of lattice-embedded scale-free networking agents in the prisoner's dilemma game model by employing two initial strategy distribution mechanisms, which are specific distribution to the most connected sites (hubs) and random distribution. Our study indicates that the game dynamics crucially depends on the underlying spatial network structure with different strategy distribution mechanism. The cooperators' specific distribution contributes to an enhanced level of cooperation in the system compared with random one, and cooperation is robust to cooperators' specific distribution but fragile to defectors' specific distribution. Especially, unlike the specific case, increasing heterogeneity of network does not always favor the emergence of cooperation under random mechanism. Furthermore, we study the geographical effects and find that the graphically constrained network structure tends to improve the evolution of cooperation in random case and in specific one for a large temptation to defect.

  3. Degree and connectivity of the Internet's scale-free topology

    International Nuclear Information System (INIS)

    Zhang Lian-Ming; Wu Xiang-Sheng; Deng Xiao-Heng; Yu Jian-Ping

    2011-01-01

    This paper theoretically and empirically studies the degree and connectivity of the Internet's scale-free topology at an autonomous system (AS) level. The basic features of scale-free networks influence the normalization constant of degree distribution p(k). It develops a new mathematic model for describing the power-law relationships of Internet topology. From this model we theoretically obtain formulas to calculate the average degree, the ratios of the k min -degree (minimum degree) nodes and the k max -degree (maximum degree) nodes, and the fraction of the degrees (or links) in the hands of the richer (top best-connected) nodes. It finds that the average degree is larger for a smaller power-law exponent λ and a larger minimum or maximum degree. The ratio of the k min -degree nodes is larger for larger λ and smaller k min or k max . The ratio of the k max -degree ones is larger for smaller λ and k max or larger k min . The richer nodes hold most of the total degrees of Internet AS-level topology. In addition, it is revealed that the increased rate of the average degree or the ratio of the k min -degree nodes has power-law decay with the increase of k min . The ratio of the k max -degree nodes has a power-law decay with the increase of k max , and the fraction of the degrees in the hands of the richer 27% nodes is about 73% (the ‘73/27 rule’). Finally, empirically calculations are made, based on the empirical data extracted from the Border Gateway Protocol, of the average degree, ratio and fraction using this method and other methods, and find that this method is rigorous and effective for Internet AS-level topology. (interdisciplinary physics and related areas of science and technology)

  4. Cache memory modelling method and system

    OpenAIRE

    Posadas Cobo, Héctor; Villar Bonet, Eugenio; Díaz Suárez, Luis

    2011-01-01

    The invention relates to a method for modelling a data cache memory of a destination processor, in order to simulate the behaviour of said data cache memory during the execution of a software code on a platform comprising said destination processor. According to the invention, the simulation is performed on a native platform having a processor different from the destination processor comprising the aforementioned data cache memory to be modelled, said modelling being performed by means of the...

  5. Thermomechanical macroscopic model of shape memory alloys

    International Nuclear Information System (INIS)

    Volkov, A.E.; Sakharov, V.Yu.

    2003-01-01

    The phenomenological macroscopic model of the mechanical behaviour of the titanium nickelide-type shape memory alloys is proposed. The model contains as a parameter the average phase shear deformation accompanying the martensite formation. It makes i possible to describe correctly a number of functional properties of the shape memory alloys, in particular, the pseudoelasticity ferroplasticity, plasticity transformation and shape memory effects in the stressed and unstressed samples [ru

  6. Logistic map with memory from economic model

    International Nuclear Information System (INIS)

    Tarasova, Valentina V.; Tarasov, Vasily E.

    2017-01-01

    A generalization of the economic model of logistic growth, which takes into account the effects of memory and crises, is suggested. Memory effect means that the economic factors and parameters at any given time depend not only on their values at that time, but also on their values at previous times. For the mathematical description of the memory effects, we use the theory of derivatives of non-integer order. Crises are considered as sharp splashes (bursts) of the price, which are mathematically described by the delta-functions. Using the equivalence of fractional differential equations and the Volterra integral equations, we obtain discrete maps with memory that are exact discrete analogs of fractional differential equations of economic processes. We derive logistic map with memory, its generalizations, and “economic” discrete maps with memory from the fractional differential equations, which describe the economic natural growth with competition, power-law memory and crises.

  7. Modeling soil moisture memory in savanna ecosystems

    Science.gov (United States)

    Gou, S.; Miller, G. R.

    2011-12-01

    Antecedent soil conditions create an ecosystem's "memory" of past rainfall events. Such soil moisture memory effects may be observed over a range of timescales, from daily to yearly, and lead to feedbacks between hydrological and ecosystem processes. In this study, we modeled the soil moisture memory effect on savanna ecosystems in California, Arizona, and Africa, using a system dynamics model created to simulate the ecohydrological processes at the plot-scale. The model was carefully calibrated using soil moisture and evapotranspiration data collected at three study sites. The model was then used to simulate scenarios with various initial soil moisture conditions and antecedent precipitation regimes, in order to study the soil moisture memory effects on the evapotranspiration of understory and overstory species. Based on the model results, soil texture and antecedent precipitation regime impact the redistribution of water within soil layers, potentially causing deeper soil layers to influence the ecosystem for a longer time. Of all the study areas modeled, soil moisture memory of California savanna ecosystem site is replenished and dries out most rapidly. Thus soil moisture memory could not maintain the high rate evapotranspiration for more than a few days without incoming rainfall event. On the contrary, soil moisture memory of Arizona savanna ecosystem site lasts the longest time. The plants with different root depths respond to different memory effects; shallow-rooted species mainly respond to the soil moisture memory in the shallow soil. The growing season of grass is largely depended on the soil moisture memory of the top 25cm soil layer. Grass transpiration is sensitive to the antecedent precipitation events within daily to weekly timescale. Deep-rooted plants have different responses since these species can access to the deeper soil moisture memory with longer time duration Soil moisture memory does not have obvious impacts on the phenology of woody plants

  8. Modeling of SONOS Memory Cell Erase Cycle

    Science.gov (United States)

    Phillips, Thomas A.; MacLeod, Todd C.; Ho, Fat H.

    2011-01-01

    Utilization of Silicon-Oxide-Nitride-Oxide-Silicon (SONOS) nonvolatile semiconductor memories as a flash memory has many advantages. These electrically erasable programmable read-only memories (EEPROMs) utilize low programming voltages, have a high erase/write cycle lifetime, are radiation hardened, and are compatible with high-density scaled CMOS for low power, portable electronics. In this paper, the SONOS memory cell erase cycle was investigated using a nonquasi-static (NQS) MOSFET model. Comparisons were made between the model predictions and experimental data.

  9. A high-level and scalable approach for generating scale-free graphs using active objects

    NARCIS (Netherlands)

    K. Azadbakht (Keyvan); N. Bezirgiannis (Nikolaos); F.S. de Boer (Frank); Aliakbary, S. (Sadegh)

    2016-01-01

    textabstractThe Barabasi-Albert model (BA) is designed to generate scale-free networks using the preferential attachment mechanism. In the preferential attachment (PA) model, new nodes are sequentially introduced to the network and they attach preferentially to existing nodes. PA is a classical

  10. Emergence of fractal scale-free networks from stochastic evolution on the Cayley tree

    Energy Technology Data Exchange (ETDEWEB)

    Chełminiak, Przemysław, E-mail: geronimo@amu.edu.pl

    2013-11-29

    An unexpected recognition of fractal topology in some real-world scale-free networks has evoked again an interest in the mechanisms stimulating their evolution. To explain this phenomenon a few models of a deterministic construction as well as a probabilistic growth controlled by a tunable parameter have been proposed so far. A quite different approach based on the fully stochastic evolution of the fractal scale-free networks presented in this Letter counterpoises these former ideas. It is argued that the diffusive evolution of the network on the Cayley tree shapes its fractality, self-similarity and the branching number criticality without any control parameter. The last attribute of the scale-free network is an intrinsic property of the skeleton, a special type of spanning tree which determines its fractality.

  11. Different behaviors of epidemic spreading in scale-free networks with identical degree sequence

    Energy Technology Data Exchange (ETDEWEB)

    Chu Xiangwei; Guan Jihong [School of Electronics and Information, Tongji University, 4800 Cao' an Road, Shanghai 201804 (China); Zhang Zhongzhi; Zhou Shuigeng [School of Computer Science, Fudan University, Shanghai 200433 (China); Li Mo, E-mail: zhangzz@fudan.edu.c, E-mail: jhguan@tongj.edu.c, E-mail: sgzhou@fudan.edu.c [Software School, Fudan University, Shanghai 200433 (China)

    2010-02-12

    Recently, the study of dynamical behaviors of the susceptible-infected (SI) disease model in complex networks, especially in Barabasi-Albert (BA) scale-free networks, has attracted much attention. Although some interesting phenomena have been observed, the formative reasons for those particular dynamical behaviors are still not well understood, despite the speculation that topological properties (for example the degree distribution) have a strong impact on epidemic spreading. In this paper, we study the evolution behaviors of epidemic spreading on a class of scale-free networks sharing identical degree sequence, and observe significantly different evolution behaviors in the whole family of networks. We show that the power-law degree distribution does not suffice to characterize the dynamical behaviors of disease diffusion on scale-free networks.

  12. Different behaviors of epidemic spreading in scale-free networks with identical degree sequence

    International Nuclear Information System (INIS)

    Chu Xiangwei; Guan Jihong; Zhang Zhongzhi; Zhou Shuigeng; Li Mo

    2010-01-01

    Recently, the study of dynamical behaviors of the susceptible-infected (SI) disease model in complex networks, especially in Barabasi-Albert (BA) scale-free networks, has attracted much attention. Although some interesting phenomena have been observed, the formative reasons for those particular dynamical behaviors are still not well understood, despite the speculation that topological properties (for example the degree distribution) have a strong impact on epidemic spreading. In this paper, we study the evolution behaviors of epidemic spreading on a class of scale-free networks sharing identical degree sequence, and observe significantly different evolution behaviors in the whole family of networks. We show that the power-law degree distribution does not suffice to characterize the dynamical behaviors of disease diffusion on scale-free networks.

  13. Search in spatial scale-free networks

    International Nuclear Information System (INIS)

    Thadakamalla, H P; Albert, R; Kumara, S R T

    2007-01-01

    We study the decentralized search problem in a family of parameterized spatial network models that are heterogeneous in node degree. We investigate several algorithms and illustrate that some of these algorithms exploit the heterogeneity in the network to find short paths by using only local information. In addition, we demonstrate that the spatial network model belongs to a classof searchable networks for a wide range of parameter space. Further, we test these algorithms on the US airline network which belongs to this class of networks and demonstrate that searchability is a generic property of the US airline network. These results provide insights on designing the structure of distributed networks that need effective decentralized search algorithms

  14. Universal Scaling Relations in Scale-Free Structure Formation

    Science.gov (United States)

    Guszejnov, Dávid; Hopkins, Philip F.; Grudić, Michael Y.

    2018-04-01

    A large number of astronomical phenomena exhibit remarkably similar scaling relations. The most well-known of these is the mass distribution dN/dM∝M-2 which (to first order) describes stars, protostellar cores, clumps, giant molecular clouds, star clusters and even dark matter halos. In this paper we propose that this ubiquity is not a coincidence and that it is the generic result of scale-free structure formation where the different scales are uncorrelated. We show that all such systems produce a mass function proportional to M-2 and a column density distribution with a power law tail of dA/d lnΣ∝Σ-1. In the case where structure formation is controlled by gravity the two-point correlation becomes ξ2D∝R-1. Furthermore, structures formed by such processes (e.g. young star clusters, DM halos) tend to a ρ∝R-3 density profile. We compare these predictions with observations, analytical fragmentation cascade models, semi-analytical models of gravito-turbulent fragmentation and detailed "full physics" hydrodynamical simulations. We find that these power-laws are good first order descriptions in all cases.

  15. Phone Routing using the Dynamic Memory Model

    DEFF Research Database (Denmark)

    Bendtsen, Claus Nicolaj; Krink, Thiemo

    2002-01-01

    In earlier studies a genetic algorithm (GA) extended with the dynamic memory model has shown remarkable performance on real-world-like problems. In this paper we experiment with routing in communication networks and show that the dynamic memory GA performs remarkable well compared to ant colony...

  16. Scale free effects in world currency exchange network

    Science.gov (United States)

    Górski, A. Z.; Drożdż, S.; Kwapień, J.

    2008-11-01

    A large collection of daily time series for 60 world currencies' exchange rates is considered. The correlation matrices are calculated and the corresponding Minimal Spanning Tree (MST) graphs are constructed for each of those currencies used as reference for the remaining ones. It is shown that multiplicity of the MST graphs' nodes to a good approximation develops a power like, scale free distribution with the scaling exponent similar as for several other complex systems studied so far. Furthermore, quantitative arguments in favor of the hierarchical organization of the world currency exchange network are provided by relating the structure of the above MST graphs and their scaling exponents to those that are derived from an exactly solvable hierarchical network model. A special status of the USD during the period considered can be attributed to some departures of the MST features, when this currency (or some other tied to it) is used as reference, from characteristics typical to such a hierarchical clustering of nodes towards those that correspond to the random graphs. Even though in general the basic structure of the MST is robust with respect to changing the reference currency some trace of a systematic transition from somewhat dispersed - like the USD case - towards more compact MST topology can be observed when correlations increase.

  17. Power-law citation distributions are not scale-free.

    Science.gov (United States)

    Golosovsky, Michael

    2017-09-01

    We analyze time evolution of statistical distributions of citations to scientific papers published in the same year. While these distributions seem to follow the power-law dependence we find that they are nonstationary and the exponent of the power-law fit decreases with time and does not come to saturation. We attribute the nonstationarity of citation distributions to different longevity of the low-cited and highly cited papers. By measuring citation trajectories of papers we found that citation careers of the low-cited papers come to saturation after 10-15 years while those of the highly cited papers continue to increase indefinitely: The papers that exceed some citation threshold become runaways. Thus, we show that although citation distribution can look as a power-law dependence, it is not scale free and there is a hidden dynamic scale associated with the onset of runaways. We compare our measurements to our recently developed model of citation dynamics based on copying-redirection-triadic closure and find explanations to our empirical observations.

  18. Generating clustered scale-free networks using Poisson based localization of edges

    Science.gov (United States)

    Türker, İlker

    2018-05-01

    We introduce a variety of network models using a Poisson-based edge localization strategy, which result in clustered scale-free topologies. We first verify the success of our localization strategy by realizing a variant of the well-known Watts-Strogatz model with an inverse approach, implying a small-world regime of rewiring from a random network through a regular one. We then apply the rewiring strategy to a pure Barabasi-Albert model and successfully achieve a small-world regime, with a limited capacity of scale-free property. To imitate the high clustering property of scale-free networks with higher accuracy, we adapted the Poisson-based wiring strategy to a growing network with the ingredients of both preferential attachment and local connectivity. To achieve the collocation of these properties, we used a routine of flattening the edges array, sorting it, and applying a mixing procedure to assemble both global connections with preferential attachment and local clusters. As a result, we achieved clustered scale-free networks with a computational fashion, diverging from the recent studies by following a simple but efficient approach.

  19. Scale-Free Networks and Commercial Air Carrier Transportation in the United States

    Science.gov (United States)

    Conway, Sheila R.

    2004-01-01

    Network science, or the art of describing system structure, may be useful for the analysis and control of large, complex systems. For example, networks exhibiting scale-free structure have been found to be particularly well suited to deal with environmental uncertainty and large demand growth. The National Airspace System may be, at least in part, a scalable network. In fact, the hub-and-spoke structure of the commercial segment of the NAS is an often-cited example of an existing scale-free network After reviewing the nature and attributes of scale-free networks, this assertion is put to the test: is commercial air carrier transportation in the United States well explained by this model? If so, are the positive attributes of these networks, e.g. those of efficiency, flexibility and robustness, fully realized, or could we effect substantial improvement? This paper first outlines attributes of various network types, then looks more closely at the common carrier air transportation network from perspectives of the traveler, the airlines, and Air Traffic Control (ATC). Network models are applied within each paradigm, including discussion of implied strengths and weaknesses of each model. Finally, known limitations of scalable networks are discussed. With an eye towards NAS operations, utilizing the strengths and avoiding the weaknesses of scale-free networks are addressed.

  20. Quantifying the connectivity of scale-free and biological networks

    Energy Technology Data Exchange (ETDEWEB)

    Shiner, J.S. E-mail: shiner@alumni.duke.edu; Davison, Matt E-mail: mdavison@uwo.ca

    2004-07-01

    Scale-free and biological networks follow a power law distribution p{sub k}{proportional_to}k{sup -{alpha}} for the probability that a node is connected to k other nodes; the corresponding ranges for {alpha} (biological: 1<{alpha}<2; scale-free: 2<{alpha}{<=}3) yield a diverging variance for the connectivity k and lack of predictability for the average connectivity. Predictability can be achieved with the Renyi, Tsallis and Landsberg-Vedral extended entropies and corresponding 'disorders' for correctly chosen values of the entropy index q. Escort distributions p{sub k}{proportional_to}k{sup -{alpha}}{sup q} with q>3/{alpha} also yield a nondiverging variance and predictability. It is argued that the Tsallis entropies may be the appropriate quantities for the study of scale-free and biological networks.

  1. An interference model of visual working memory.

    Science.gov (United States)

    Oberauer, Klaus; Lin, Hsuan-Yu

    2017-01-01

    The article introduces an interference model of working memory for information in a continuous similarity space, such as the features of visual objects. The model incorporates the following assumptions: (a) Probability of retrieval is determined by the relative activation of each retrieval candidate at the time of retrieval; (b) activation comes from 3 sources in memory: cue-based retrieval using context cues, context-independent memory for relevant contents, and noise; (c) 1 memory object and its context can be held in the focus of attention, where it is represented with higher precision, and partly shielded against interference. The model was fit to data from 4 continuous-reproduction experiments testing working memory for colors or orientations. The experiments involved variations of set size, kind of context cues, precueing, and retro-cueing of the to-be-tested item. The interference model fit the data better than 2 competing models, the Slot-Averaging model and the Variable-Precision resource model. The interference model also fared well in comparison to several new models incorporating alternative theoretical assumptions. The experiments confirm 3 novel predictions of the interference model: (a) Nontargets intrude in recall to the extent that they are close to the target in context space; (b) similarity between target and nontarget features improves recall, and (c) precueing-but not retro-cueing-the target substantially reduces the set-size effect. The success of the interference model shows that working memory for continuous visual information works according to the same principles as working memory for more discrete (e.g., verbal) contents. Data and model codes are available at https://osf.io/wgqd5/. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  2. Faster Parallel Traversal of Scale Free Graphs at Extreme Scale with Vertex Delegates

    KAUST Repository

    Pearce, Roger

    2014-11-01

    © 2014 IEEE. At extreme scale, irregularities in the structure of scale-free graphs such as social network graphs limit our ability to analyze these important and growing datasets. A key challenge is the presence of high-degree vertices (hubs), that leads to parallel workload and storage imbalances. The imbalances occur because existing partitioning techniques are not able to effectively partition high-degree vertices. We present techniques to distribute storage, computation, and communication of hubs for extreme scale graphs in distributed memory supercomputers. To balance the hub processing workload, we distribute hub data structures and related computation among a set of delegates. The delegates coordinate using highly optimized, yet portable, asynchronous broadcast and reduction operations. We demonstrate scalability of our new algorithmic technique using Breadth-First Search (BFS), Single Source Shortest Path (SSSP), K-Core Decomposition, and Page-Rank on synthetically generated scale-free graphs. Our results show excellent scalability on large scale-free graphs up to 131K cores of the IBM BG/P, and outperform the best known Graph500 performance on BG/P Intrepid by 15%

  3. Faster Parallel Traversal of Scale Free Graphs at Extreme Scale with Vertex Delegates

    KAUST Repository

    Pearce, Roger; Gokhale, Maya; Amato, Nancy M.

    2014-01-01

    © 2014 IEEE. At extreme scale, irregularities in the structure of scale-free graphs such as social network graphs limit our ability to analyze these important and growing datasets. A key challenge is the presence of high-degree vertices (hubs), that leads to parallel workload and storage imbalances. The imbalances occur because existing partitioning techniques are not able to effectively partition high-degree vertices. We present techniques to distribute storage, computation, and communication of hubs for extreme scale graphs in distributed memory supercomputers. To balance the hub processing workload, we distribute hub data structures and related computation among a set of delegates. The delegates coordinate using highly optimized, yet portable, asynchronous broadcast and reduction operations. We demonstrate scalability of our new algorithmic technique using Breadth-First Search (BFS), Single Source Shortest Path (SSSP), K-Core Decomposition, and Page-Rank on synthetically generated scale-free graphs. Our results show excellent scalability on large scale-free graphs up to 131K cores of the IBM BG/P, and outperform the best known Graph500 performance on BG/P Intrepid by 15%

  4. A model of memory impairment in schizophrenia: cognitive and clinical factors associated with memory efficiency and memory errors.

    Science.gov (United States)

    Brébion, Gildas; Bressan, Rodrigo A; Ohlsen, Ruth I; David, Anthony S

    2013-12-01

    Memory impairments in patients with schizophrenia have been associated with various cognitive and clinical factors. Hallucinations have been more specifically associated with errors stemming from source monitoring failure. We conducted a broad investigation of verbal memory and visual memory as well as source memory functioning in a sample of patients with schizophrenia. Various memory measures were tallied, and we studied their associations with processing speed, working memory span, and positive, negative, and depressive symptoms. Superficial and deep memory processes were differentially associated with processing speed, working memory span, avolition, depression, and attention disorders. Auditory/verbal and visual hallucinations were differentially associated with specific types of source memory error. We integrated all the results into a revised version of a previously published model of memory functioning in schizophrenia. The model describes the factors that affect memory efficiency, as well as the cognitive underpinnings of hallucinations within the source monitoring framework. © 2013.

  5. The Generalized Quantum Episodic Memory Model.

    Science.gov (United States)

    Trueblood, Jennifer S; Hemmer, Pernille

    2017-11-01

    Recent evidence suggests that experienced events are often mapped to too many episodic states, including those that are logically or experimentally incompatible with one another. For example, episodic over-distribution patterns show that the probability of accepting an item under different mutually exclusive conditions violates the disjunction rule. A related example, called subadditivity, occurs when the probability of accepting an item under mutually exclusive and exhaustive instruction conditions sums to a number >1. Both the over-distribution effect and subadditivity have been widely observed in item and source-memory paradigms. These phenomena are difficult to explain using standard memory frameworks, such as signal-detection theory. A dual-trace model called the over-distribution (OD) model (Brainerd & Reyna, 2008) can explain the episodic over-distribution effect, but not subadditivity. Our goal is to develop a model that can explain both effects. In this paper, we propose the Generalized Quantum Episodic Memory (GQEM) model, which extends the Quantum Episodic Memory (QEM) model developed by Brainerd, Wang, and Reyna (2013). We test GQEM by comparing it to the OD model using data from a novel item-memory experiment and a previously published source-memory experiment (Kellen, Singmann, & Klauer, 2014) examining the over-distribution effect. Using the best-fit parameters from the over-distribution experiments, we conclude by showing that the GQEM model can also account for subadditivity. Overall these results add to a growing body of evidence suggesting that quantum probability theory is a valuable tool in modeling recognition memory. Copyright © 2016 Cognitive Science Society, Inc.

  6. Trading leads to scale-free self-organization

    Science.gov (United States)

    Ebert, M.; Paul, W.

    2012-12-01

    Financial markets display scale-free behavior in many different aspects. The power-law behavior of part of the distribution of individual wealth has been recognized by Pareto as early as the nineteenth century. Heavy-tailed and scale-free behavior of the distribution of returns of different financial assets have been confirmed in a series of works. The existence of a Pareto-like distribution of the wealth of market participants has been connected with the scale-free distribution of trading volumes and price-returns. The origin of the Pareto-like wealth distribution, however, remained obscure. Here we show that in a market where the imbalance of supply and demand determines the direction of prize changes, it is the process of trading itself that spontaneously leads to a self-organization of the market with a Pareto-like wealth distribution for the market participants and at the same time to a scale-free behavior of return fluctuations and trading volume distributions.

  7. Strategic Factor Markets Scale Free Resources and Economic Performance

    DEFF Research Database (Denmark)

    Geisler Asmussen, Christian

    2015-01-01

    This paper analyzes how scale free resources, which can be acquired by multiple firms simultaneously and deployed against one another in product market competition, will be priced in strategic factor markets, and what the consequences are for the acquiring firms' performance. Based on a game-theo...

  8. Programming scale-free optics in disordered ferroelectrics.

    Science.gov (United States)

    Parravicini, Jacopo; Conti, Claudio; Agranat, Aharon J; DelRe, Eugenio

    2012-06-15

    Using the history dependence of a dipolar glass hosted in a compositionally disordered lithium-enriched potassium tantalate niobate (KTN:Li) crystal, we demonstrate scale-free optical propagation at tunable temperatures. The operating equilibration temperature is determined by previous crystal spiralling in the temperature/cooling-rate phase space.

  9. Programming scale-free optics in disordered ferroelectrics

    OpenAIRE

    Parravicini, Jacopo; Conti, Claudio; Agranat, Aharon J.; DelRe, Eugenio

    2012-01-01

    Using the history-dependence of a dipolar glass hosted in a compositionally-disordered lithium-enriched potassium-tantalate-niobate (KTN:Li) crystal, we demonstrate scale-free optical propagation at tunable temperatures. The operating equilibration temperature is determined by previous crystal spiralling in the temperature/cooling-rate phase-space.

  10. Opinion formation on multiplex scale-free networks

    Science.gov (United States)

    Nguyen, Vu Xuan; Xiao, Gaoxi; Xu, Xin-Jian; Li, Guoqi; Wang, Zhen

    2018-01-01

    Most individuals, if not all, live in various social networks. The formation of opinion systems is an outcome of social interactions and information propagation occurring in such networks. We study the opinion formation with a new rule of pairwise interactions in the novel version of the well-known Deffuant model on multiplex networks composed of two layers, each of which is a scale-free network. It is found that in a duplex network composed of two identical layers, the presence of the multiplexity helps either diminish or enhance opinion diversity depending on the relative magnitudes of tolerance ranges characterizing the degree of openness/tolerance on both layers: there is a steady separation between different regions of tolerance range values on two network layers where multiplexity plays two different roles, respectively. Additionally, the two critical tolerance ranges follow a one-sum rule; that is, each of the layers reaches a complete consensus only if the sum of the tolerance ranges on the two layers is greater than a constant approximately equaling 1, the double of the critical bound on a corresponding isolated network. A further investigation of the coupling between constituent layers quantified by a link overlap parameter reveals that as the layers are loosely coupled, the two opinion systems co-evolve independently, but when the inter-layer coupling is sufficiently strong, a monotonic behavior is observed: an increase in the tolerance range of a layer causes a decline in the opinion diversity on the other layer regardless of the magnitudes of tolerance ranges associated with the layers in question.

  11. Fluctuation-driven flocking movement in three dimensions and scale-free correlation.

    Science.gov (United States)

    Niizato, Takayuki; Gunji, Yukio-Pegio

    2012-01-01

    Recent advances in the study of flocking behavior have permitted more sophisticated analyses than previously possible. The concepts of "topological distances" and "scale-free correlations" are important developments that have contributed to this improvement. These concepts require us to reconsider the notion of a neighborhood when applied to theoretical models. Previous work has assumed that individuals interact with neighbors within a certain radius (called the "metric distance"). However, other work has shown that, assuming topological interactions, starlings interact on average with the six or seven nearest neighbors within a flock. Accounting for this observation, we previously proposed a metric-topological interaction model in two dimensions. The goal of our model was to unite these two interaction components, the metric distance and the topological distance, into one rule. In our previous study, we demonstrated that the metric-topological interaction model could explain a real bird flocking phenomenon called scale-free correlation, which was first reported by Cavagna et al. In this study, we extended our model to three dimensions while also accounting for variations in speed. This three-dimensional metric-topological interaction model displayed scale-free correlation for velocity and orientation. Finally, we introduced an additional new feature of the model, namely, that a flock can store and release its fluctuations.

  12. Fluctuation-driven flocking movement in three dimensions and scale-free correlation.

    Directory of Open Access Journals (Sweden)

    Takayuki Niizato

    Full Text Available Recent advances in the study of flocking behavior have permitted more sophisticated analyses than previously possible. The concepts of "topological distances" and "scale-free correlations" are important developments that have contributed to this improvement. These concepts require us to reconsider the notion of a neighborhood when applied to theoretical models. Previous work has assumed that individuals interact with neighbors within a certain radius (called the "metric distance". However, other work has shown that, assuming topological interactions, starlings interact on average with the six or seven nearest neighbors within a flock. Accounting for this observation, we previously proposed a metric-topological interaction model in two dimensions. The goal of our model was to unite these two interaction components, the metric distance and the topological distance, into one rule. In our previous study, we demonstrated that the metric-topological interaction model could explain a real bird flocking phenomenon called scale-free correlation, which was first reported by Cavagna et al. In this study, we extended our model to three dimensions while also accounting for variations in speed. This three-dimensional metric-topological interaction model displayed scale-free correlation for velocity and orientation. Finally, we introduced an additional new feature of the model, namely, that a flock can store and release its fluctuations.

  13. Mobile user forecast and power-law acceleration invariance of scale-free networks

    International Nuclear Information System (INIS)

    Guo Jin-Li; Guo Zhao-Hua; Liu Xue-Jiao

    2011-01-01

    This paper studies and predicts the number growth of China's mobile users by using the power-law regression. We find that the number growth of the mobile users follows a power law. Motivated by the data on the evolution of the mobile users, we consider scenarios of self-organization of accelerating growth networks into scale-free structures and propose a directed network model, in which the nodes grow following a power-law acceleration. The expressions for the transient and the stationary average degree distributions are obtained by using the Poisson process. This result shows that the model generates appropriate power-law connectivity distributions. Therefore, we find a power-law acceleration invariance of the scale-free networks. The numerical simulations of the models agree with the analytical results well. (interdisciplinary physics and related areas of science and technology)

  14. A model for visual memory encoding.

    Directory of Open Access Journals (Sweden)

    Rodolphe Nenert

    Full Text Available Memory encoding engages multiple concurrent and sequential processes. While the individual processes involved in successful encoding have been examined in many studies, a sequence of events and the importance of modules associated with memory encoding has not been established. For this reason, we sought to perform a comprehensive examination of the network for memory encoding using data driven methods and to determine the directionality of the information flow in order to build a viable model of visual memory encoding. Forty healthy controls ages 19-59 performed a visual scene encoding task. FMRI data were preprocessed using SPM8 and then processed using independent component analysis (ICA with the reliability of the identified components confirmed using ICASSO as implemented in GIFT. The directionality of the information flow was examined using Granger causality analyses (GCA. All participants performed the fMRI task well above the chance level (>90% correct on both active and control conditions and the post-fMRI testing recall revealed correct memory encoding at 86.33 ± 5.83%. ICA identified involvement of components of five different networks in the process of memory encoding, and the GCA allowed for the directionality of the information flow to be assessed, from visual cortex via ventral stream to the attention network and then to the default mode network (DMN. Two additional networks involved in this process were the cerebellar and the auditory-insular network. This study provides evidence that successful visual memory encoding is dependent on multiple modules that are part of other networks that are only indirectly related to the main process. This model may help to identify the node(s of the network that are affected by a specific disease processes and explain the presence of memory encoding difficulties in patients in whom focal or global network dysfunction exists.

  15. A model for visual memory encoding.

    Science.gov (United States)

    Nenert, Rodolphe; Allendorfer, Jane B; Szaflarski, Jerzy P

    2014-01-01

    Memory encoding engages multiple concurrent and sequential processes. While the individual processes involved in successful encoding have been examined in many studies, a sequence of events and the importance of modules associated with memory encoding has not been established. For this reason, we sought to perform a comprehensive examination of the network for memory encoding using data driven methods and to determine the directionality of the information flow in order to build a viable model of visual memory encoding. Forty healthy controls ages 19-59 performed a visual scene encoding task. FMRI data were preprocessed using SPM8 and then processed using independent component analysis (ICA) with the reliability of the identified components confirmed using ICASSO as implemented in GIFT. The directionality of the information flow was examined using Granger causality analyses (GCA). All participants performed the fMRI task well above the chance level (>90% correct on both active and control conditions) and the post-fMRI testing recall revealed correct memory encoding at 86.33 ± 5.83%. ICA identified involvement of components of five different networks in the process of memory encoding, and the GCA allowed for the directionality of the information flow to be assessed, from visual cortex via ventral stream to the attention network and then to the default mode network (DMN). Two additional networks involved in this process were the cerebellar and the auditory-insular network. This study provides evidence that successful visual memory encoding is dependent on multiple modules that are part of other networks that are only indirectly related to the main process. This model may help to identify the node(s) of the network that are affected by a specific disease processes and explain the presence of memory encoding difficulties in patients in whom focal or global network dysfunction exists.

  16. Discrete scale-free distributions and associated limit theorems

    International Nuclear Information System (INIS)

    Hopcraft, K I; Jakeman, E; Matthews, J O

    2004-01-01

    Consideration is given to the convergence properties of sums of identical, independently distributed random variables drawn from a class of discrete distributions with power-law tails, which are relevant to scale-free networks. Different limiting distributions, and rates of convergence to these limits, are identified and depend on the index of the tail. For indices ≥2, the topology evolves to a random Poisson network, but the rate of convergence can be extraordinarily slow and unlikely to be yet evident for the current size of the WWW for example. It is shown that treating discrete scale-free behaviour with continuum or mean-field approximations can lead to incorrect results. (letter to the editor)

  17. Optimal defense resource allocation in scale-free networks

    Science.gov (United States)

    Zhang, Xuejun; Xu, Guoqiang; Xia, Yongxiang

    2018-02-01

    The robustness research of networked systems has drawn widespread attention in the past decade, and one of the central topics is to protect the network from external attacks through allocating appropriate defense resource to different nodes. In this paper, we apply a specific particle swarm optimization (PSO) algorithm to optimize the defense resource allocation in scale-free networks. Results reveal that PSO based resource allocation shows a higher robustness than other resource allocation strategies such as uniform, degree-proportional, and betweenness-proportional allocation strategies. Furthermore, we find that assigning less resource to middle-degree nodes under small-scale attack while more resource to low-degree nodes under large-scale attack is conductive to improving the network robustness. Our work provides an insight into the optimal defense resource allocation pattern in scale-free networks and is helpful for designing a more robust network.

  18. Label-based routing for a family of scale-free, modular, planar and unclustered graphs

    International Nuclear Information System (INIS)

    Comellas, Francesc; Miralles, Alicia

    2011-01-01

    We give an optimal labeling and routing algorithm for a family of scale-free, modular and planar graphs with zero clustering. The relevant properties of this family match those of some networks associated with technological and biological systems with a low clustering, including some electronic circuits and protein networks. The existence of an efficient routing protocol for this graph model should help when designing communication algorithms in real networks and also in the understanding of their dynamic processes.

  19. Adaptive local routing strategy on a scale-free network

    International Nuclear Information System (INIS)

    Feng, Liu; Han, Zhao; Ming, Li; Yan-Bo, Zhu; Feng-Yuan, Ren

    2010-01-01

    Due to the heterogeneity of the structure on a scale-free network, making the betweennesses of all nodes become homogeneous by reassigning the weights of nodes or edges is very difficult. In order to take advantage of the important effect of high degree nodes on the shortest path communication and preferentially deliver packets by them to increase the probability to destination, an adaptive local routing strategy on a scale-free network is proposed, in which the node adjusts the forwarding probability with the dynamical traffic load (packet queue length) and the degree distribution of neighbouring nodes. The critical queue length of a node is set to be proportional to its degree, and the node with high degree has a larger critical queue length to store and forward more packets. When the queue length of a high degree node is shorter than its critical queue length, it has a higher probability to forward packets. After higher degree nodes are saturated (whose queue lengths are longer than their critical queue lengths), more packets will be delivered by the lower degree nodes around them. The adaptive local routing strategy increases the probability of a packet finding its destination quickly, and improves the transmission capacity on the scale-free network by reducing routing hops. The simulation results show that the transmission capacity of the adaptive local routing strategy is larger than that of three previous local routing strategies. (general)

  20. Emergence of scale-free characteristics in socio-ecological systems with bounded rationality.

    Science.gov (United States)

    Kasthurirathna, Dharshana; Piraveenan, Mahendra

    2015-06-11

    Socio-ecological systems are increasingly modelled by games played on complex networks. While the concept of Nash equilibrium assumes perfect rationality, in reality players display heterogeneous bounded rationality. Here we present a topological model of bounded rationality in socio-ecological systems, using the rationality parameter of the Quantal Response Equilibrium. We argue that system rationality could be measured by the average Kullback--Leibler divergence between Nash and Quantal Response Equilibria, and that the convergence towards Nash equilibria on average corresponds to increased system rationality. Using this model, we show that when a randomly connected socio-ecological system is topologically optimised to converge towards Nash equilibria, scale-free and small world features emerge. Therefore, optimising system rationality is an evolutionary reason for the emergence of scale-free and small-world features in socio-ecological systems. Further, we show that in games where multiple equilibria are possible, the correlation between the scale-freeness of the system and the fraction of links with multiple equilibria goes through a rapid transition when the average system rationality increases. Our results explain the influence of the topological structure of socio-ecological systems in shaping their collective cognitive behaviour, and provide an explanation for the prevalence of scale-free and small-world characteristics in such systems.

  1. Poor—rich demarcation of Matthew effect on scale-free systems and its application

    International Nuclear Information System (INIS)

    Dong, Yan; Sui-Ran, Yu; Ming, Dong; Bouras, Abdelaziz

    2011-01-01

    In a scale-free network, only a minority of nodes are connected very often, while the majority of nodes are connected rarely. However, what is the ratio of minority nodes to majority nodes resulting from the Matthew effect? In this paper, based on a simple preferential random model, the poor-rich demarcation points are found to vary in a limited range, and form a poor-rich demarcation interval that approximates to k/m in [3,4]. As a result, the (cumulative) degree distribution of a scale-free network can be divided into three intervals: the poor interval, the demarcation interval and the rich interval. The inequality of the degree distribution in each interval is measured. Finally, the Matthew effect is applied to the ABC analysis of project management. (general)

  2. Node-node correlations and transport properties in scale-free networks

    Science.gov (United States)

    Obregon, Bibiana; Guzman, Lev

    2011-03-01

    We study some transport properties of complex networks. We focus our attention on transport properties of scale-free and small-world networks and compare two types of transport: Electric and max-flow cases. In particular, we construct scale-free networks, with a given degree sequence, to estimate the distribution of conductances for different values of assortative/dissortative mixing. For the electric case we find that the distributions of conductances are affect ed by the assortative mixing of the network whereas for the max-flow case, the distributions almost do not show changes when node-node correlations are altered. Finally, we compare local and global transport in terms of the average conductance for the small-world (Watts-Strogatz) model

  3. Operational Semantics of a Weak Memory Model inspired by Go

    OpenAIRE

    Fava, Daniel Schnetzer; Stolz, Volker; Valle, Stian

    2017-01-01

    A memory model dictates which values may be returned when reading from memory. In a parallel computing setting, the memory model affects how processes communicate through shared memory. The design of a proper memory model is a balancing act. On one hand, memory models must be lax enough to allow common hardware and compiler optimizations. On the other, the more lax the model, the harder it is for developers to reason about their programs. In order to alleviate the burden on programmers, a wea...

  4. Inferring spatial memory and spatiotemporal scaling from GPS data: comparing red deer Cervus elaphus movements with simulation models.

    Science.gov (United States)

    Gautestad, Arild O; Loe, Leif E; Mysterud, Atle

    2013-05-01

    1. Increased inference regarding underlying behavioural mechanisms of animal movement can be achieved by comparing GPS data with statistical mechanical movement models such as random walk and Lévy walk with known underlying behaviour and statistical properties. 2. GPS data are typically collected with ≥ 1 h intervals not exactly tracking every mechanistic step along the movement path, so a statistical mechanical model approach rather than a mechanistic approach is appropriate. However, comparisons require a coherent framework involving both scaling and memory aspects of the underlying process. Thus, simulation models have recently been extended to include memory-guided returns to previously visited patches, that is, site fidelity. 3. We define four main classes of movement, differing in incorporation of memory and scaling (based on respective intervals of the statistical fractal dimension D and presence/absence of site fidelity). Using three statistical protocols to estimate D and site fidelity, we compare these main movement classes with patterns observed in GPS data from 52 females of red deer (Cervus elaphus). 4. The results show best compliance with a scale-free and memory-enhanced kind of space use; that is, a power law distribution of step lengths, a fractal distribution of the spatial scatter of fixes and site fidelity. 5. Our study thus demonstrates how inference regarding memory effects and a hierarchical pattern of space use can be derived from analysis of GPS data. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

  5. A general model for memory interference in a multiprocessor system with memory hierarchy

    Science.gov (United States)

    Taha, Badie A.; Standley, Hilda M.

    1989-01-01

    The problem of memory interference in a multiprocessor system with a hierarchy of shared buses and memories is addressed. The behavior of the processors is represented by a sequence of memory requests with each followed by a determined amount of processing time. A statistical queuing network model for determining the extent of memory interference in multiprocessor systems with clusters of memory hierarchies is presented. The performance of the system is measured by the expected number of busy memory clusters. The results of the analytic model are compared with simulation results, and the correlation between them is found to be very high.

  6. A Preisach type model for temperature driven hysteresis memory erasure in shape memory materials

    OpenAIRE

    Kopfová, J.; Krejčí, P. (Pavel)

    2011-01-01

    We establish the well-posedness and thermodynamic consistency of a variational inequality modeling temperature-induced memory erasure in shape memory materials. It is shown that the input-output operator is continuous with respect to uniform convergence.

  7. Evaluating the transport in small-world and scale-free networks

    International Nuclear Information System (INIS)

    Juárez-López, R.; Obregón-Quintana, B.; Hernández-Pérez, R.; Reyes-Ramírez, I.; Guzmán-Vargas, L.

    2014-01-01

    We present a study of some properties of transport in small-world and scale-free networks. Particularly, we compare two types of transport: subject to friction (electrical case) and in the absence of friction (maximum flow). We found that in clustered networks based on the Watts–Strogatz (WS) model, for both transport types the small-world configurations exhibit the best trade-off between local and global levels. For non-clustered WS networks the local transport is independent of the rewiring parameter, while the transport improves globally. Moreover, we analyzed both transport types in scale-free networks considering tendencies in the assortative or disassortative mixing of nodes. We construct the distribution of the conductance G and flow F to evaluate the effects of the assortative (disassortative) mixing, finding that for scale-free networks, as we introduce different levels of the degree–degree correlations, the power-law decay in the conductances is altered, while for the flow, the power-law tail remains unchanged. In addition, we analyze the effect on the conductance and the flow of the minimum degree and the shortest path between the source and destination nodes, finding notable differences between these two types of transport

  8. Epidemic spreading in weighted scale-free networks with community structure

    International Nuclear Information System (INIS)

    Chu, Xiangwei; Guan, Jihong; Zhang, Zhongzhi; Zhou, Shuigeng

    2009-01-01

    Many empirical studies reveal that the weights and community structure are ubiquitous in various natural and artificial networks. In this paper, based on the SI disease model, we investigate the epidemic spreading in weighted scale-free networks with community structure. Two exponents, α and β, are introduced to weight the internal edges and external edges, respectively; and a tunable probability parameter q is also introduced to adjust the strength of community structure. We find the external weighting exponent β plays a much more important role in slackening the epidemic spreading and reducing the danger brought by the epidemic than the internal weighting exponent α. Moreover, a novel result we find is that the strong community structure is no longer helpful for slackening the danger brought by the epidemic in the weighted cases. In addition, we show the hierarchical dynamics of the epidemic spreading in the weighted scale-free networks with communities which is also displayed in the famous BA scale-free networks

  9. Sparse cliques trump scale-free networks in coordination and competition

    Science.gov (United States)

    Gianetto, David A.; Heydari, Babak

    2016-02-01

    Cooperative behavior, a natural, pervasive and yet puzzling phenomenon, can be significantly enhanced by networks. Many studies have shown how global network characteristics affect cooperation; however, it is difficult to understand how this occurs based on global factors alone, low-level network building blocks, or motifs are necessary. In this work, we systematically alter the structure of scale-free and clique networks and show, through a stochastic evolutionary game theory model, that cooperation on cliques increases linearly with community motif count. We further show that, for reactive stochastic strategies, network modularity improves cooperation in the anti-coordination Snowdrift game and the Prisoner’s Dilemma game but not in the Stag Hunt coordination game. We also confirm the negative effect of the scale-free graph on cooperation when effective payoffs are used. On the flip side, clique graphs are highly cooperative across social environments. Adding cycles to the acyclic scale-free graph increases cooperation when multiple games are considered; however, cycles have the opposite effect on how forgiving agents are when playing the Prisoner’s Dilemma game.

  10. Weak Memory Models: Balancing Definitional Simplicity and Implementation Flexibility

    OpenAIRE

    Zhang, Sizhuo; Vijayaraghavan, Muralidaran; Arvind

    2017-01-01

    The memory model for RISC-V, a newly developed open source ISA, has not been finalized yet and thus, offers an opportunity to evaluate existing memory models. We believe RISC-V should not adopt the memory models of POWER or ARM, because their axiomatic and operational definitions are too complicated. We propose two new weak memory models: WMM and WMM-S, which balance definitional simplicity and implementation flexibility differently. Both allow all instruction reorderings except overtaking of...

  11. Self-Organization in Coupled Map Scale-Free Networks

    International Nuclear Information System (INIS)

    Xiao-Ming, Liang; Zong-Hua, Liu; Hua-Ping, Lü

    2008-01-01

    We study the self-organization of phase synchronization in coupled map scale-free networks with chaotic logistic map at each node and find that a variety of ordered spatiotemporal patterns emerge spontaneously in a regime of coupling strength. These ordered behaviours will change with the increase of the average links and are robust to both the system size and parameter mismatch. A heuristic theory is given to explain the mechanism of self-organization and to figure out the regime of coupling for the ordered spatiotemporal patterns

  12. Particle swarm optimization with scale-free interactions.

    Directory of Open Access Journals (Sweden)

    Chen Liu

    Full Text Available The particle swarm optimization (PSO algorithm, in which individuals collaborate with their interacted neighbors like bird flocking to search for the optima, has been successfully applied in a wide range of fields pertaining to searching and convergence. Here we employ the scale-free network to represent the inter-individual interactions in the population, named SF-PSO. In contrast to the traditional PSO with fully-connected topology or regular topology, the scale-free topology used in SF-PSO incorporates the diversity of individuals in searching and information dissemination ability, leading to a quite different optimization process. Systematic results with respect to several standard test functions demonstrate that SF-PSO gives rise to a better balance between the convergence speed and the optimum quality, accounting for its much better performance than that of the traditional PSO algorithms. We further explore the dynamical searching process microscopically, finding that the cooperation of hub nodes and non-hub nodes play a crucial role in optimizing the convergence process. Our work may have implications in computational intelligence and complex networks.

  13. Constitutive Models for Shape Memory Alloy Polycrystals

    Science.gov (United States)

    Comstock, R. J., Jr.; Somerday, M.; Wert, J. A.

    1996-01-01

    Shape memory alloys (SMA) exhibiting the superelastic or one-way effects can produce large recoverable strains upon application of a stress. In single crystals this stress and resulting strain are very orientation dependent. We show experimental stress/strain curves for a Ni-Al single crystal for various loading orientations. Also shown are model predictions; the open and closed circles indicate recoverable strains obtained at various stages in the transformation process. Because of the strong orientation dependence of shape memory properties, crystallographic texture can be expected to play an important role in the mechanical behavior of polycrystalline SMA. It is desirable to formulate a constitutive model to better understand and exploit the unique properties of SMA.

  14. Parallel models of associative memory

    CERN Document Server

    Hinton, Geoffrey E

    2014-01-01

    This update of the 1981 classic on neural networks includes new commentaries by the authors that show how the original ideas are related to subsequent developments. As researchers continue to uncover ways of applying the complex information processing abilities of neural networks, they give these models an exciting future which may well involve revolutionary developments in understanding the brain and the mind -- developments that may allow researchers to build adaptive intelligent machines. The original chapters show where the ideas came from and the new commentaries show where they are going

  15. Working memory: theories, models, and controversies.

    Science.gov (United States)

    Baddeley, Alan

    2012-01-01

    I present an account of the origins and development of the multicomponent approach to working memory, making a distinction between the overall theoretical framework, which has remained relatively stable, and the attempts to build more specific models within this framework. I follow this with a brief discussion of alternative models and their relationship to the framework. I conclude with speculations on further developments and a comment on the value of attempting to apply models and theories beyond the laboratory studies on which they are typically based.

  16. A dual-trace model for visual sensory memory.

    Science.gov (United States)

    Cappiello, Marcus; Zhang, Weiwei

    2016-11-01

    Visual sensory memory refers to a transient memory lingering briefly after the stimulus offset. Although previous literature suggests that visual sensory memory is supported by a fine-grained trace for continuous representation and a coarse-grained trace of categorical information, simultaneous separation and assessment of these traces can be difficult without a quantitative model. The present study used a continuous estimation procedure to test a novel mathematical model of the dual-trace hypothesis of visual sensory memory according to which visual sensory memory could be modeled as a mixture of 2 von Mises (2VM) distributions differing in standard deviation. When visual sensory memory and working memory (WM) for colors were distinguished using different experimental manipulations in the first 3 experiments, the 2VM model outperformed Zhang and Luck (2008) standard mixture model (SM) representing a mixture of a single memory trace and random guesses, even though SM outperformed 2VM for WM. Experiment 4 generalized 2VM's advantages of fitting visual sensory memory data over SM from color to orientation. Furthermore, a single trace model and 4 other alternative models were ruled out, suggesting the necessity and sufficiency of dual traces for visual sensory memory. Together these results support the dual-trace model of visual sensory memory and provide a preliminary inquiry into the nature of information loss from visual sensory memory to WM. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  17. A simplified computational memory model from information processing

    Science.gov (United States)

    Zhang, Lanhua; Zhang, Dongsheng; Deng, Yuqin; Ding, Xiaoqian; Wang, Yan; Tang, Yiyuan; Sun, Baoliang

    2016-01-01

    This paper is intended to propose a computational model for memory from the view of information processing. The model, called simplified memory information retrieval network (SMIRN), is a bi-modular hierarchical functional memory network by abstracting memory function and simulating memory information processing. At first meta-memory is defined to express the neuron or brain cortices based on the biology and graph theories, and we develop an intra-modular network with the modeling algorithm by mapping the node and edge, and then the bi-modular network is delineated with intra-modular and inter-modular. At last a polynomial retrieval algorithm is introduced. In this paper we simulate the memory phenomena and functions of memorization and strengthening by information processing algorithms. The theoretical analysis and the simulation results show that the model is in accordance with the memory phenomena from information processing view. PMID:27876847

  18. A simplified computational memory model from information processing.

    Science.gov (United States)

    Zhang, Lanhua; Zhang, Dongsheng; Deng, Yuqin; Ding, Xiaoqian; Wang, Yan; Tang, Yiyuan; Sun, Baoliang

    2016-11-23

    This paper is intended to propose a computational model for memory from the view of information processing. The model, called simplified memory information retrieval network (SMIRN), is a bi-modular hierarchical functional memory network by abstracting memory function and simulating memory information processing. At first meta-memory is defined to express the neuron or brain cortices based on the biology and graph theories, and we develop an intra-modular network with the modeling algorithm by mapping the node and edge, and then the bi-modular network is delineated with intra-modular and inter-modular. At last a polynomial retrieval algorithm is introduced. In this paper we simulate the memory phenomena and functions of memorization and strengthening by information processing algorithms. The theoretical analysis and the simulation results show that the model is in accordance with the memory phenomena from information processing view.

  19. Attention-based Memory Selection Recurrent Network for Language Modeling

    OpenAIRE

    Liu, Da-Rong; Chuang, Shun-Po; Lee, Hung-yi

    2016-01-01

    Recurrent neural networks (RNNs) have achieved great success in language modeling. However, since the RNNs have fixed size of memory, their memory cannot store all the information about the words it have seen before in the sentence, and thus the useful long-term information may be ignored when predicting the next words. In this paper, we propose Attention-based Memory Selection Recurrent Network (AMSRN), in which the model can review the information stored in the memory at each previous time ...

  20. COMBINING LONG MEMORY AND NONLINEAR MODEL OUTPUTS FOR INFLATION FORECAST

    OpenAIRE

    Heri Kuswanto; Irhamah Alimuhajin; Laylia Afidah

    2014-01-01

    Long memory and nonlinearity have been proven as two models that are easily to be mistaken. In other words, nonlinearity is a strong candidate of spurious long memory by introducing a certain degree of fractional integration that lies in the region of long memory. Indeed, nonlinear process belongs to short memory with zero integration order. The idea of the forecast is to obtain the future condition with minimum error. Some researches argued that no matter what the model is, the important thi...

  1. Resource allocation models of auditory working memory.

    Science.gov (United States)

    Joseph, Sabine; Teki, Sundeep; Kumar, Sukhbinder; Husain, Masud; Griffiths, Timothy D

    2016-06-01

    Auditory working memory (WM) is the cognitive faculty that allows us to actively hold and manipulate sounds in mind over short periods of time. We develop here a particular perspective on WM for non-verbal, auditory objects as well as for time based on the consideration of possible parallels to visual WM. In vision, there has been a vigorous debate on whether WM capacity is limited to a fixed number of items or whether it represents a limited resource that can be allocated flexibly across items. Resource allocation models predict that the precision with which an item is represented decreases as a function of total number of items maintained in WM because a limited resource is shared among stored objects. We consider here auditory work on sequentially presented objects of different pitch as well as time intervals from the perspective of dynamic resource allocation. We consider whether the working memory resource might be determined by perceptual features such as pitch or timbre, or bound objects comprising multiple features, and we speculate on brain substrates for these behavioural models. This article is part of a Special Issue entitled SI: Auditory working memory. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Neural network modeling of associative memory: Beyond the Hopfield model

    Science.gov (United States)

    Dasgupta, Chandan

    1992-07-01

    A number of neural network models, in which fixed-point and limit-cycle attractors of the underlying dynamics are used to store and associatively recall information, are described. In the first class of models, a hierarchical structure is used to store an exponentially large number of strongly correlated memories. The second class of models uses limit cycles to store and retrieve individual memories. A neurobiologically plausible network that generates low-amplitude periodic variations of activity, similar to the oscillations observed in electroencephalographic recordings, is also described. Results obtained from analytic and numerical studies of the properties of these networks are discussed.

  3. Model-Driven Study of Visual Memory

    National Research Council Canada - National Science Library

    Sekuler, Robert

    2004-01-01

    .... We synthesized concepts, insights, and methods from memory research, and from vision research, working within a coherent, quantitative framework for understanding episodic visual recognition memory...

  4. Scale-free networks of earthquakes and aftershocks

    International Nuclear Information System (INIS)

    Baiesi, Marco; Paczuski, Maya

    2004-01-01

    We propose a metric to quantify correlations between earthquakes. The metric consists of a product involving the time interval and spatial distance between two events, as well as the magnitude of the first one. According to this metric, events typically are strongly correlated to only one or a few preceding ones. Thus a classification of events as foreshocks, main shocks, or aftershocks emerges automatically without imposing predetermined space-time windows. In the simplest network construction, each earthquake receives an incoming link from its most correlated predecessor. The number of aftershocks for any event, identified by its outgoing links, is found to be scale free with exponent γ=2.0(1). The original Omori law with p=1 emerges as a robust feature of seismicity, holding up to years even for aftershock sequences initiated by intermediate magnitude events. The broad distribution of distances between earthquakes and their linked aftershocks suggests that aftershock collection with fixed space windows is not appropriate

  5. Network synchronization: optimal and pessimal scale-free topologies

    Energy Technology Data Exchange (ETDEWEB)

    Donetti, Luca [Departamento de Electronica y Tecnologia de Computadores and Instituto de Fisica Teorica y Computacional Carlos I, Facultad de Ciencias, Universidad de Granada, 18071 Granada (Spain); Hurtado, Pablo I; Munoz, Miguel A [Departamento de Electromagnetismo y Fisica de la Materia and Instituto Carlos I de Fisica Teorica y Computacional Facultad de Ciencias, Universidad de Granada, 18071 Granada (Spain)], E-mail: mamunoz@onsager.ugr.es

    2008-06-06

    By employing a recently introduced optimization algorithm we construct optimally synchronizable (unweighted) networks for any given scale-free degree distribution. We explore how the optimization process affects degree-degree correlations and observe a generic tendency toward disassortativity. Still, we show that there is not a one-to-one correspondence between synchronizability and disassortativity. On the other hand, we study the nature of optimally un-synchronizable networks, that is, networks whose topology minimizes the range of stability of the synchronous state. The resulting 'pessimal networks' turn out to have a highly assortative string-like structure. We also derive a rigorous lower bound for the Laplacian eigenvalue ratio controlling synchronizability, which helps understanding the impact of degree correlations on network synchronizability.

  6. Network synchronization: optimal and pessimal scale-free topologies

    International Nuclear Information System (INIS)

    Donetti, Luca; Hurtado, Pablo I; Munoz, Miguel A

    2008-01-01

    By employing a recently introduced optimization algorithm we construct optimally synchronizable (unweighted) networks for any given scale-free degree distribution. We explore how the optimization process affects degree-degree correlations and observe a generic tendency toward disassortativity. Still, we show that there is not a one-to-one correspondence between synchronizability and disassortativity. On the other hand, we study the nature of optimally un-synchronizable networks, that is, networks whose topology minimizes the range of stability of the synchronous state. The resulting 'pessimal networks' turn out to have a highly assortative string-like structure. We also derive a rigorous lower bound for the Laplacian eigenvalue ratio controlling synchronizability, which helps understanding the impact of degree correlations on network synchronizability

  7. Intermittent exploration on a scale-free network

    International Nuclear Information System (INIS)

    Ramezanpour, A

    2007-02-01

    We study an intermittent random walk on a random network of scale-free degree distribution. The walk is a combination of simple random walks of duration t w and random long-range jumps. While the time the walker needs to cover all the nodes increases with t w , the corresponding time for the edges displays a non monotonic behavior with a minimum for some nontrivial value of t w . This is a heterogeneity-induced effect that is not observed in homogeneous small-world networks. The optimal t w increases with the degree of assortativity in the network. Depending on the nature of degree correlations and the elapsed time the walker finds an over/underestimate of the degree distribution exponent. (author)

  8. Improved Efficient Routing Strategy on Scale-Free Networks

    Science.gov (United States)

    Jiang, Zhong-Yuan; Liang, Man-Gui

    Since the betweenness of nodes in complex networks can theoretically represent the traffic load of nodes under the currently used routing strategy, we propose an improved efficient (IE) routing strategy to enhance to the network traffic capacity based on the betweenness centrality. Any node with the highest betweenness is susceptible to traffic congestion. An efficient way to improve the network traffic capacity is to redistribute the heavy traffic load from these central nodes to non-central nodes, so in this paper, we firstly give a path cost function by considering the sum of node betweenness with a tunable parameter β along the actual path. Then, by minimizing the path cost, our IE routing strategy achieved obvious improvement on the network transport efficiency. Simulations on scale-free Barabási-Albert (BA) networks confirmed the effectiveness of our strategy, when compared with the efficient routing (ER) and the shortest path (SP) routing.

  9. Associative memory model with spontaneous neural activity

    Science.gov (United States)

    Kurikawa, Tomoki; Kaneko, Kunihiko

    2012-05-01

    We propose a novel associative memory model wherein the neural activity without an input (i.e., spontaneous activity) is modified by an input to generate a target response that is memorized for recall upon the same input. Suitable design of synaptic connections enables the model to memorize input/output (I/O) mappings equaling 70% of the total number of neurons, where the evoked activity distinguishes a target pattern from others. Spontaneous neural activity without an input shows chaotic dynamics but keeps some similarity with evoked activities, as reported in recent experimental studies.

  10. A dynamic model of reasoning and memory.

    Science.gov (United States)

    Hawkins, Guy E; Hayes, Brett K; Heit, Evan

    2016-02-01

    Previous models of category-based induction have neglected how the process of induction unfolds over time. We conceive of induction as a dynamic process and provide the first fine-grained examination of the distribution of response times observed in inductive reasoning. We used these data to develop and empirically test the first major quantitative modeling scheme that simultaneously accounts for inductive decisions and their time course. The model assumes that knowledge of similarity relations among novel test probes and items stored in memory drive an accumulation-to-bound sequential sampling process: Test probes with high similarity to studied exemplars are more likely to trigger a generalization response, and more rapidly, than items with low exemplar similarity. We contrast data and model predictions for inductive decisions with a recognition memory task using a common stimulus set. Hierarchical Bayesian analyses across 2 experiments demonstrated that inductive reasoning and recognition memory primarily differ in the threshold to trigger a decision: Observers required less evidence to make a property generalization judgment (induction) than an identity statement about a previously studied item (recognition). Experiment 1 and a condition emphasizing decision speed in Experiment 2 also found evidence that inductive decisions use lower quality similarity-based information than recognition. The findings suggest that induction might represent a less cautious form of recognition. We conclude that sequential sampling models grounded in exemplar-based similarity, combined with hierarchical Bayesian analysis, provide a more fine-grained and informative analysis of the processes involved in inductive reasoning than is possible solely through examination of choice data. PsycINFO Database Record (c) 2016 APA, all rights reserved.

  11. Non-equilibrium mean-field theories on scale-free networks

    International Nuclear Information System (INIS)

    Caccioli, Fabio; Dall'Asta, Luca

    2009-01-01

    Many non-equilibrium processes on scale-free networks present anomalous critical behavior that is not explained by standard mean-field theories. We propose a systematic method to derive stochastic equations for mean-field order parameters that implicitly account for the degree heterogeneity. The method is used to correctly predict the dynamical critical behavior of some binary spin models and reaction–diffusion processes. The validity of our non-equilibrium theory is further supported by showing its relation with the generalized Landau theory of equilibrium critical phenomena on networks

  12. Weak Memory Models with Matching Axiomatic and Operational Definitions

    OpenAIRE

    Zhang, Sizhuo; Vijayaraghavan, Muralidaran; Lustig, Dan; Arvind

    2017-01-01

    Memory consistency models are notorious for being difficult to define precisely, to reason about, and to verify. More than a decade of effort has gone into nailing down the definitions of the ARM and IBM Power memory models, and yet there still remain aspects of those models which (perhaps surprisingly) remain unresolved to this day. In response to these complexities, there has been somewhat of a recent trend in the (general-purpose) architecture community to limit new memory models to being ...

  13. User Preference-Based Dual-Memory Neural Model With Memory Consolidation Approach.

    Science.gov (United States)

    Nasir, Jauwairia; Yoo, Yong-Ho; Kim, Deok-Hwa; Kim, Jong-Hwan; Nasir, Jauwairia; Yong-Ho Yoo; Deok-Hwa Kim; Jong-Hwan Kim; Nasir, Jauwairia; Yoo, Yong-Ho; Kim, Deok-Hwa; Kim, Jong-Hwan

    2018-06-01

    Memory modeling has been a popular topic of research for improving the performance of autonomous agents in cognition related problems. Apart from learning distinct experiences correctly, significant or recurring experiences are expected to be learned better and be retrieved easier. In order to achieve this objective, this paper proposes a user preference-based dual-memory adaptive resonance theory network model, which makes use of a user preference to encode memories with various strengths and to learn and forget at various rates. Over a period of time, memories undergo a consolidation-like process at a rate proportional to the user preference at the time of encoding and the frequency of recall of a particular memory. Consolidated memories are easier to recall and are more stable. This dual-memory neural model generates distinct episodic memories and a flexible semantic-like memory component. This leads to an enhanced retrieval mechanism of experiences through two routes. The simulation results are presented to evaluate the proposed memory model based on various kinds of cues over a number of trials. The experimental results on Mybot are also presented. The results verify that not only are distinct experiences learned correctly but also that experiences associated with higher user preference and recall frequency are consolidated earlier. Thus, these experiences are recalled more easily relative to the unconsolidated experiences.

  14. THE BUILDUP OF A SCALE-FREE PHOTOSPHERIC MAGNETIC NETWORK

    Energy Technology Data Exchange (ETDEWEB)

    Thibault, K.; Charbonneau, P. [Departement de Physique, Universite de Montreal, 2900 Edouard-Montpetit, Montreal, Quebec H3C 3J7 (Canada); Crouch, A. D., E-mail: kim@astro.umontreal.ca-a, E-mail: paulchar@astro.umontreal.ca-b, E-mail: ash@cora.nwra.com-c [CORA/NWRA, 3380 Mitchell Lane, Boulder, CO 80301 (United States)

    2012-10-01

    We use a global Monte Carlo simulation of the formation of the solar photospheric magnetic network to investigate the origin of the scale invariance characterizing magnetic flux concentrations visible on high-resolution magnetograms. The simulations include spatially and temporally homogeneous injection of small-scale magnetic elements over the whole photosphere, as well as localized episodic injection associated with the emergence and decay of active regions. Network elements form in response to cumulative pairwise aggregation or cancellation of magnetic elements, undergoing a random walk on the sphere and advected on large spatial scales by differential rotation and a poleward meridional flow. The resulting size distribution of simulated network elements is in very good agreement with observational inferences. We find that the fractal index and size distribution of network elements are determined primarily by these post-emergence surface mechanisms, and carry little or no memory of the scales at which magnetic flux is injected in the simulation. Implications for models of dynamo action in the Sun are briefly discussed.

  15. THE BUILDUP OF A SCALE-FREE PHOTOSPHERIC MAGNETIC NETWORK

    International Nuclear Information System (INIS)

    Thibault, K.; Charbonneau, P.; Crouch, A. D.

    2012-01-01

    We use a global Monte Carlo simulation of the formation of the solar photospheric magnetic network to investigate the origin of the scale invariance characterizing magnetic flux concentrations visible on high-resolution magnetograms. The simulations include spatially and temporally homogeneous injection of small-scale magnetic elements over the whole photosphere, as well as localized episodic injection associated with the emergence and decay of active regions. Network elements form in response to cumulative pairwise aggregation or cancellation of magnetic elements, undergoing a random walk on the sphere and advected on large spatial scales by differential rotation and a poleward meridional flow. The resulting size distribution of simulated network elements is in very good agreement with observational inferences. We find that the fractal index and size distribution of network elements are determined primarily by these post-emergence surface mechanisms, and carry little or no memory of the scales at which magnetic flux is injected in the simulation. Implications for models of dynamo action in the Sun are briefly discussed.

  16. The Buildup of a Scale-free Photospheric Magnetic Network

    Science.gov (United States)

    Thibault, K.; Charbonneau, P.; Crouch, A. D.

    2012-10-01

    We use a global Monte Carlo simulation of the formation of the solar photospheric magnetic network to investigate the origin of the scale invariance characterizing magnetic flux concentrations visible on high-resolution magnetograms. The simulations include spatially and temporally homogeneous injection of small-scale magnetic elements over the whole photosphere, as well as localized episodic injection associated with the emergence and decay of active regions. Network elements form in response to cumulative pairwise aggregation or cancellation of magnetic elements, undergoing a random walk on the sphere and advected on large spatial scales by differential rotation and a poleward meridional flow. The resulting size distribution of simulated network elements is in very good agreement with observational inferences. We find that the fractal index and size distribution of network elements are determined primarily by these post-emergence surface mechanisms, and carry little or no memory of the scales at which magnetic flux is injected in the simulation. Implications for models of dynamo action in the Sun are briefly discussed.

  17. Weighted Scale-Free Network Properties of Ecological Network

    International Nuclear Information System (INIS)

    Lee, Jae Woo; Maeng, Seong Eun

    2013-01-01

    We investigate the scale-free network properties of the bipartite ecological network, in particular, the plant-pollinator network. In plant-pollinator network, the pollinators visit the plant to get the nectars. In contrast to the other complex network, the plant-pollinator network has not only the trophic relationships among the interacting partners but also the complexities of the coevolutionary effects. The interactions between the plant and pollinators are beneficial relations. The plant-pollinator network is a bipartite and weighted network. The networks have two types of the nodes: plant and pollinator. We consider the visiting frequency of a pollinator to a plant as the weighting value of the link. We defined the strength of a node as the sum of the weighting value of the links. We reported the cumulative distribution function (CDF) of the degree and the strength of the plant-pollinator network. The CDF of the plants followed stretched exponential functions for both degree and strength, but the CDF of the pollinators showed the power law for both degree and strength. The average strength of the links showed the nonlinear dependence on the degree of the networks.

  18. Complex networks with scale-free nature and hierarchical modularity

    Science.gov (United States)

    Shekatkar, Snehal M.; Ambika, G.

    2015-09-01

    Generative mechanisms which lead to empirically observed structure of networked systems from diverse fields like biology, technology and social sciences form a very important part of study of complex networks. The structure of many networked systems like biological cell, human society and World Wide Web markedly deviate from that of completely random networks indicating the presence of underlying processes. Often the main process involved in their evolution is the addition of links between existing nodes having a common neighbor. In this context we introduce an important property of the nodes, which we call mediating capacity, that is generic to many networks. This capacity decreases rapidly with increase in degree, making hubs weak mediators of the process. We show that this property of nodes provides an explanation for the simultaneous occurrence of the observed scale-free structure and hierarchical modularity in many networked systems. This also explains the high clustering and small-path length seen in real networks as well as non-zero degree-correlations. Our study also provides insight into the local process which ultimately leads to emergence of preferential attachment and hence is also important in understanding robustness and control of real networks as well as processes happening on real networks.

  19. Improving Estimation of Betweenness Centrality for Scale-Free Graphs

    Energy Technology Data Exchange (ETDEWEB)

    Bromberger, Seth A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Klymko, Christine F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Henderson, Keith A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pearce, Roger [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sanders, Geoff [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-11-07

    Betweenness centrality is a graph statistic used to nd vertices that are participants in a large number of shortest paths in a graph. This centrality measure is commonly used in path and network interdiction problems and its complete form requires the calculation of all-pairs shortest paths for each vertex. This leads to a time complexity of O(jV jjEj), which is impractical for large graphs. Estimation of betweenness centrality has focused on performing shortest-path calculations on a subset of randomly- selected vertices. This reduces the complexity of the centrality estimation to O(jSjjEj); jSj < jV j, which can be scaled appropriately based on the computing resources available. An estimation strategy that uses random selection of vertices for seed selection is fast and simple to implement, but may not provide optimal estimation of betweenness centrality when the number of samples is constrained. Our experimentation has identi ed a number of alternate seed-selection strategies that provide lower error than random selection in common scale-free graphs. These strategies are discussed and experimental results are presented.

  20. Generalized memory associativity in a network model for the neuroses

    Science.gov (United States)

    Wedemann, Roseli S.; Donangelo, Raul; de Carvalho, Luís A. V.

    2009-03-01

    We review concepts introduced in earlier work, where a neural network mechanism describes some mental processes in neurotic pathology and psychoanalytic working-through, as associative memory functioning, according to the findings of Freud. We developed a complex network model, where modules corresponding to sensorial and symbolic memories interact, representing unconscious and conscious mental processes. The model illustrates Freud's idea that consciousness is related to symbolic and linguistic memory activity in the brain. We have introduced a generalization of the Boltzmann machine to model memory associativity. Model behavior is illustrated with simulations and some of its properties are analyzed with methods from statistical mechanics.

  1. Modeling Recognition Memory Using the Similarity Structure of Natural Input

    Science.gov (United States)

    Lacroix, Joyca P. W.; Murre, Jaap M. J.; Postma, Eric O.; van den Herik, H. Jaap

    2006-01-01

    The natural input memory (NAM) model is a new model for recognition memory that operates on natural visual input. A biologically informed perceptual preprocessing method takes local samples (eye fixations) from a natural image and translates these into a feature-vector representation. During recognition, the model compares incoming preprocessed…

  2. Hypergraph-Based Recognition Memory Model for Lifelong Experience

    Science.gov (United States)

    2014-01-01

    Cognitive agents are expected to interact with and adapt to a nonstationary dynamic environment. As an initial process of decision making in a real-world agent interaction, familiarity judgment leads the following processes for intelligence. Familiarity judgment includes knowing previously encoded data as well as completing original patterns from partial information, which are fundamental functions of recognition memory. Although previous computational memory models have attempted to reflect human behavioral properties on the recognition memory, they have been focused on static conditions without considering temporal changes in terms of lifelong learning. To provide temporal adaptability to an agent, in this paper, we suggest a computational model for recognition memory that enables lifelong learning. The proposed model is based on a hypergraph structure, and thus it allows a high-order relationship between contextual nodes and enables incremental learning. Through a simulated experiment, we investigate the optimal conditions of the memory model and validate the consistency of memory performance for lifelong learning. PMID:25371665

  3. Synchronization in scale-free networks: The role of finite-size effects

    Science.gov (United States)

    Torres, D.; Di Muro, M. A.; La Rocca, C. E.; Braunstein, L. A.

    2015-06-01

    Synchronization problems in complex networks are very often studied by researchers due to their many applications to various fields such as neurobiology, e-commerce and completion of tasks. In particular, scale-free networks with degree distribution P(k)∼ k-λ , are widely used in research since they are ubiquitous in Nature and other real systems. In this paper we focus on the surface relaxation growth model in scale-free networks with 2.5< λ <3 , and study the scaling behavior of the fluctuations, in the steady state, with the system size N. We find a novel behavior of the fluctuations characterized by a crossover between two regimes at a value of N=N* that depends on λ: a logarithmic regime, found in previous research, and a constant regime. We propose a function that describes this crossover, which is in very good agreement with the simulations. We also find that, for a system size above N* , the fluctuations decrease with λ, which means that the synchronization of the system improves as λ increases. We explain this crossover analyzing the role of the network's heterogeneity produced by the system size N and the exponent of the degree distribution.

  4. Elements of episodic-like memory in animal models.

    Science.gov (United States)

    Crystal, Jonathon D

    2009-03-01

    Representations of unique events from one's past constitute the content of episodic memories. A number of studies with non-human animals have revealed that animals remember specific episodes from their past (referred to as episodic-like memory). The development of animal models of memory holds enormous potential for gaining insight into the biological bases of human memory. Specifically, given the extensive knowledge of the rodent brain, the development of rodent models of episodic memory would open new opportunities to explore the neuroanatomical, neurochemical, neurophysiological, and molecular mechanisms of memory. Development of such animal models holds enormous potential for studying functional changes in episodic memory in animal models of Alzheimer's disease, amnesia, and other human memory pathologies. This article reviews several approaches that have been used to assess episodic-like memory in animals. The approaches reviewed include the discrimination of what, where, and when in a radial arm maze, dissociation of recollection and familiarity, object recognition, binding, unexpected questions, and anticipation of a reproductive state. The diversity of approaches may promote the development of converging lines of evidence on the difficult problem of assessing episodic-like memory in animals.

  5. The AIP Model of EMDR Therapy and Pathogenic Memories

    Directory of Open Access Journals (Sweden)

    Michael Hase

    2017-09-01

    Full Text Available Eye Movement Desensitization and Reprocessing (EMDR therapy has been widely recognized as an efficacious treatment for post-traumatic stress disorder (PTSD. In the last years more insight has been gained regarding the efficacy of EMDR therapy in a broad field of mental disorders beyond PTSD. The cornerstone of EMDR therapy is its unique model of pathogenesis and change: the adaptive information processing (AIP model. The AIP model developed by F. Shapiro has found support and differentiation in recent studies on the importance of memories in the pathogenesis of a range of mental disorders beside PTSD. However, theoretical publications or research on the application of the AIP model are still rare. The increasing acceptance of ideas that relate the origin of many mental disorders to the formation and consolidation of implicit dysfunctional memory lead to formation of the theory of pathogenic memories. Within the theory of pathogenic memories these implicit dysfunctional memories are considered to form basis of a variety of mental disorders. The theory of pathogenic memories seems compatible to the AIP model of EMDR therapy, which offers strategies to effectively access and transmute these memories leading to amelioration or resolution of symptoms. Merging the AIP model with the theory of pathogenic memories may initiate research. In consequence, patients suffering from such memory-based disorders may be earlier diagnosed and treated more effectively.

  6. Behavioural Models of Motor Control and Short-Term Memory

    OpenAIRE

    Imanaka, Kuniyasu; Funase, Kozo; Yamauchi, Masaki

    1995-01-01

    We examined in this review article the behavioural and conceptual models of motor control and short-term memory which have intensively been investigated since the 1970s. First, we reviewed both the dual-storage model of short-term memory in which movement information is stored and a typical model of motor control which emphasizes the importance of efferent factors. We then examined two models of preselection effects: a cognitive model and a cognitive/ efferent model. Following this we reviewe...

  7. A Probabilistic Model of Visual Working Memory: Incorporating Higher Order Regularities into Working Memory Capacity Estimates

    Science.gov (United States)

    Brady, Timothy F.; Tenenbaum, Joshua B.

    2013-01-01

    When remembering a real-world scene, people encode both detailed information about specific objects and higher order information like the overall gist of the scene. However, formal models of change detection, like those used to estimate visual working memory capacity, assume observers encode only a simple memory representation that includes no…

  8. Micromechanical modelling of shape memory alloy composites

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Y.F.; Wang, X.M.; Yue, Z.F. [School of Mechanic, Civil Engineering and Architecture, Northwestern Polytechnical University, Xian, 710072 (China)

    2004-03-01

    An isothermal finite element method (FEM) model has been applied to study the behavior of two kinds of shape memory alloy (SMA) composites. For SMA-fiber reinforced normal metal composites, the FEM analysis shows that the mechanical behavior of the composites depends on the SMA volume fraction. For normal metal-fiber reinforced SMA matrix composites, the SMA phase transformation is affected by the increasing Young's modulus of the metal fiber. The phase transformation was also treated using a simple numerical analysis, which assumes that there are uniform stresses and strains distributions in the fiber and the matrix respectively. It is found that there is an obvious difference between the FEM analysis and the simple numerical assessment. Only FEM can provide reasonable predictions of phase transformations in SMA/normal metal composites. (Abstract Copyright [2004], Wiley Periodicals, Inc.)

  9. Optical Associative Memory Model With Threshold Modification Using Complementary Vector

    Science.gov (United States)

    Bian, Shaoping; Xu, Kebin; Hong, Jing

    1989-02-01

    A new criterion to evaluate the similarity between two vectors in associative memory is presented. According to it, an experimental research about optical associative memory model with threshold modification using complementary vector is carried out. This model is capable of eliminating the posibility to recall erroneously. Therefore the accuracy of reading out is improved.

  10. Modeling recognition memory using the similarity structure of natural input

    NARCIS (Netherlands)

    Lacroix, J.P.W.; Murre, J.M.J.; Postma, E.O.; van den Herik, H.J.

    2006-01-01

    The natural input memory (NIM) model is a new model for recognition memory that operates on natural visual input. A biologically informed perceptual preprocessing method takes local samples (eye fixations) from a natural image and translates these into a feature-vector representation. During

  11. Modeling Confidence and Response Time in Recognition Memory

    Science.gov (United States)

    Ratcliff, Roger; Starns, Jeffrey J.

    2009-01-01

    A new model for confidence judgments in recognition memory is presented. In the model, the match between a single test item and memory produces a distribution of evidence, with better matches corresponding to distributions with higher means. On this match dimension, confidence criteria are placed, and the areas between the criteria under the…

  12. A Java Reference Model of Transacted Memory for Smart Cards

    NARCIS (Netherlands)

    Poll, Erik; Hartel, Pieter H.; de Jong, Eduard

    Transacted Memory offers persistence, undoability and auditing. We present a Java/JML Reference Model of the Transacted Memory system on the basis of our earlier separate Z model and C implementation. We conclude that Java/JML combines the advantages of a high level specification in the JML part

  13. A Java Reference Model of Transacted Memory for Smart Cards

    NARCIS (Netherlands)

    Poll, Erik; Hartel, Pieter H.; de Jong, Eduard

    2002-01-01

    Transacted Memory offers persistence, undoability and auditing. We present a Java/JML Reference Model of the Transacted Memory system on the basis of our earlier separate Z model and C implementation. We conclude that Java/JML combines the advantages of a high level specification in the JML part

  14. A Memory-Based Model of Hick's Law

    Science.gov (United States)

    Schneider, Darryl W.; Anderson, John R.

    2011-01-01

    We propose and evaluate a memory-based model of Hick's law, the approximately linear increase in choice reaction time with the logarithm of set size (the number of stimulus-response alternatives). According to the model, Hick's law reflects a combination of associative interference during retrieval from declarative memory and occasional savings…

  15. Phase transitions in scale-free neural networks: Departure from the standard mean-field universality class

    International Nuclear Information System (INIS)

    Aldana, Maximino; Larralde, Hernan

    2004-01-01

    We investigate the nature of the phase transition from an ordered to a disordered state that occurs in a family of neural network models with noise. These models are closely related to the majority voter model, where a ferromagneticlike interaction between the elements prevails. Each member of the family is distinguished by the network topology, which is determined by the probability distribution of the number of incoming links. We show that for homogeneous random topologies, the phase transition belongs to the standard mean-field universality class, characterized by the order parameter exponent β=1/2. However, for scale-free networks we obtain phase transition exponents ranging from 1/2 to infinity. Furthermore, we show the existence of a phase transition even for values of the scale-free exponent in the interval (1.5,2], where the average network connectivity diverges

  16. Emergence of scale-free leadership structure in social recommender systems.

    Science.gov (United States)

    Zhou, Tao; Medo, Matúš; Cimini, Giulio; Zhang, Zi-Ke; Zhang, Yi-Cheng

    2011-01-01

    The study of the organization of social networks is important for the understanding of opinion formation, rumor spreading, and the emergence of trends and fashion. This paper reports empirical analysis of networks extracted from four leading sites with social functionality (Delicious, Flickr, Twitter and YouTube) and shows that they all display a scale-free leadership structure. To reproduce this feature, we propose an adaptive network model driven by social recommending. Artificial agent-based simulations of this model highlight a "good get richer" mechanism where users with broad interests and good judgments are likely to become popular leaders for the others. Simulations also indicate that the studied social recommendation mechanism can gradually improve the user experience by adapting to tastes of its users. Finally we outline implications for real online resource-sharing systems.

  17. Consensus of Multi-Agent Systems with Prestissimo Scale-Free Networks

    International Nuclear Information System (INIS)

    Yang Hongyong; Lu Lan; Cao Kecai; Zhang Siying

    2010-01-01

    In this paper, the relations of the network topology and the moving consensus of multi-agent systems are studied. A consensus-prestissimo scale-free network model with the static preferential-consensus attachment is presented on the rewired link of the regular network. The effects of the static preferential-consensus BA network on the algebraic connectivity of the topology graph are compared with the regular network. The robustness gain to delay is analyzed for variable network topology with the same scale. The time to reach the consensus is studied for the dynamic network with and without communication delays. By applying the computer simulations, it is validated that the speed of the convergence of multi-agent systems can be greatly improved in the preferential-consensus BA network model with different configuration. (interdisciplinary physics and related areas of science and technology)

  18. Epidemic spreading in scale-free networks including the effect of individual vigilance

    International Nuclear Information System (INIS)

    Gong Yong-Wang; Song Yu-Rong; Jiang Guo-Ping

    2012-01-01

    In this paper, we study the epidemic spreading in scale-free networks and propose a new susceptible-infected-recovered (SIR) model that includes the effect of individual vigilance. In our model, the effective spreading rate is dynamically adjusted with the time evolution at the vigilance period. Using the mean-field theory, an analytical result is derived. It shows that individual vigilance has no effect on the epidemic threshold. The numerical simulations agree well with the analytical result. Furthermore, we investigate the effect of individual vigilance on the epidemic spreading speed. It is shown that individual vigilance can slow the epidemic spreading speed effectively and delay the arrival of peak epidemic infection. (general)

  19. Microplane modelling of shape memory alloys

    International Nuclear Information System (INIS)

    Kadkhodaei, M; Salimi, M; Rajapakse, R K N D; Mahzoon, M

    2007-01-01

    A three-dimensional (3D) constitutive model based on a statically constrained microplane theory with volumetric-deviatoric split is proposed for polycrystalline shape memory alloys (SMAs) under multiaxial loading paths. Microplane governing equations are 1D stress-strain relations for normal and shear stresses on each microplane, in which suitable relationships between the microscopic and macroscopic quantities are considered so that switching between elastic and inelastic local responses automatically occurs according to the macroscopic response of SMA without additional constraint. Shear stress on each microplane is expressed by the resultant shear component within the plane to overcome directional bias and to prevent the appearance of shear strain in a pure axial loading or axial strain in a pure shear loading while microplane formulations based on two shear directions may predict such impractical results. The behaviour of SMA under simple and complicated loadings has been studied. In nonproportional loading paths, the model shows interaction between stress components, as well as deviation from normality. Predicted results from the model are in good agreement with those of the existing theoretical and experimental investigations

  20. Ising formulation of associative memory models and quantum annealing recall

    Science.gov (United States)

    Santra, Siddhartha; Shehab, Omar; Balu, Radhakrishnan

    2017-12-01

    Associative memory models, in theoretical neuro- and computer sciences, can generally store at most a linear number of memories. Recalling memories in these models can be understood as retrieval of the energy minimizing configuration of classical Ising spins, closest in Hamming distance to an imperfect input memory, where the energy landscape is determined by the set of stored memories. We present an Ising formulation for associative memory models and consider the problem of memory recall using quantum annealing. We show that allowing for input-dependent energy landscapes allows storage of up to an exponential number of memories (in terms of the number of neurons). Further, we show how quantum annealing may naturally be used for recall tasks in such input-dependent energy landscapes, although the recall time may increase with the number of stored memories. Theoretically, we obtain the radius of attractor basins R (N ) and the capacity C (N ) of such a scheme and their tradeoffs. Our calculations establish that for randomly chosen memories the capacity of our model using the Hebbian learning rule as a function of problem size can be expressed as C (N ) =O (eC1N) , C1≥0 , and succeeds on randomly chosen memory sets with a probability of (1 -e-C2N) , C2≥0 with C1+C2=(0.5-f ) 2/(1 -f ) , where f =R (N )/N , 0 ≤f ≤0.5 , is the radius of attraction in terms of the Hamming distance of an input probe from a stored memory as a fraction of the problem size. We demonstrate the application of this scheme on a programmable quantum annealing device, the D-wave processor.

  1. Generic Database Cost Models for Hierarchical Memory Systems

    OpenAIRE

    Manegold, Stefan; Boncz, Peter; Kersten, Martin

    2002-01-01

    textabstractAccurate prediction of operator execution time is a prerequisite for database query optimization. Although extensively studied for conventional disk-based DBMSs, cost modeling in main-memory DBMSs is still an open issue. Recent database research has demonstrated that memory access is more and more becoming a significant---if not the major---cost component of database operations. If used properly, fast but small cache memories---usually organized in cascading hierarchy between CPU ...

  2. Synthetic vision and memory model for virtual human - biomed 2010.

    Science.gov (United States)

    Zhao, Yue; Kang, Jinsheng; Wright, David

    2010-01-01

    This paper describes the methods and case studies of a novel synthetic vision and memory model for virtual human. The synthetic vision module simulates the biological / optical abilities and limitations of the human vision. The module is based on a series of collision detection between the boundary of virtual humans field of vision (FOV) volume and the surface of objects in a recreated 3D environment. The memory module simulates a short-term memory capability by employing a simplified memory structure (first-in-first-out stack). The synthetic vision and memory model has been integrated into a virtual human modelling project, Intelligent Virtual Modelling. The project aimed to improve the realism and autonomy of virtual humans.

  3. Modeling Coevolution between Language and Memory Capacity during Language Origin

    Science.gov (United States)

    Gong, Tao; Shuai, Lan

    2015-01-01

    Memory is essential to many cognitive tasks including language. Apart from empirical studies of memory effects on language acquisition and use, there lack sufficient evolutionary explorations on whether a high level of memory capacity is prerequisite for language and whether language origin could influence memory capacity. In line with evolutionary theories that natural selection refined language-related cognitive abilities, we advocated a coevolution scenario between language and memory capacity, which incorporated the genetic transmission of individual memory capacity, cultural transmission of idiolects, and natural and cultural selections on individual reproduction and language teaching. To illustrate the coevolution dynamics, we adopted a multi-agent computational model simulating the emergence of lexical items and simple syntax through iterated communications. Simulations showed that: along with the origin of a communal language, an initially-low memory capacity for acquired linguistic knowledge was boosted; and such coherent increase in linguistic understandability and memory capacities reflected a language-memory coevolution; and such coevolution stopped till memory capacities became sufficient for language communications. Statistical analyses revealed that the coevolution was realized mainly by natural selection based on individual communicative success in cultural transmissions. This work elaborated the biology-culture parallelism of language evolution, demonstrated the driving force of culturally-constituted factors for natural selection of individual cognitive abilities, and suggested that the degree difference in language-related cognitive abilities between humans and nonhuman animals could result from a coevolution with language. PMID:26544876

  4. Attention, Working Memory, and Long-Term Memory in Multimedia Learning: An Integrated Perspective Based on Process Models of Working Memory

    Science.gov (United States)

    Schweppe, Judith; Rummer, Ralf

    2014-01-01

    Cognitive models of multimedia learning such as the Cognitive Theory of Multimedia Learning (Mayer 2009) or the Cognitive Load Theory (Sweller 1999) are based on different cognitive models of working memory (e.g., Baddeley 1986) and long-term memory. The current paper describes a working memory model that has recently gained popularity in basic…

  5. Heuristic algorithm for determination of local properties of scale-free networks

    CERN Document Server

    Mitrovic, M

    2006-01-01

    Complex networks are everywhere. Many phenomena in nature can be modeled as networks: - brain structures - protein-protein interaction networks - social interactions - the Internet and WWW. They can be represented in terms of nodes and edges connecting them. Important characteristics: - these networks are not random; they have a structured architecture. Structure of different networks are similar: - all have power law degree distribution (scale-free property) - despite large size there is usually relatively short path between any two nodes (small world property). Global characteristics: - degree distribution, clustering coefficient and the diameter. Local structure: - frequency of subgraphs of given type (subgraph of order k is a part of the network consisting of k nodes and edges between them). There are different types of subgraphs of the same order.

  6. Spatial memory tasks in rodents: what do they model?

    Science.gov (United States)

    Morellini, Fabio

    2013-10-01

    The analysis of spatial learning and memory in rodents is commonly used to investigate the mechanisms underlying certain forms of human cognition and to model their dysfunction in neuropsychiatric and neurodegenerative diseases. Proper interpretation of rodent behavior in terms of spatial memory and as a model of human cognitive functions is only possible if various navigation strategies and factors controlling the performance of the animal in a spatial task are taken into consideration. The aim of this review is to describe the experimental approaches that are being used for the study of spatial memory in rats and mice and the way that they can be interpreted in terms of general memory functions. After an introduction to the classification of memory into various categories and respective underlying neuroanatomical substrates, I explain the concept of spatial memory and its measurement in rats and mice by analysis of their navigation strategies. Subsequently, I describe the most common paradigms for spatial memory assessment with specific focus on methodological issues relevant for the correct interpretation of the results in terms of cognitive function. Finally, I present recent advances in the use of spatial memory tasks to investigate episodic-like memory in mice.

  7. A bio-inspired memory model for structural health monitoring

    Science.gov (United States)

    Zheng, Wei; Zhu, Yong

    2009-04-01

    Long-term structural health monitoring (SHM) systems need intelligent management of the monitoring data. By analogy with the way the human brain processes memories, we present a bio-inspired memory model (BIMM) that does not require prior knowledge of the structure parameters. The model contains three time-domain areas: a sensory memory area, a short-term memory area and a long-term memory area. First, the initial parameters of the structural state are specified to establish safety criteria. Then the large amount of monitoring data that falls within the safety limits is filtered while the data outside the safety limits are captured instantly in the sensory memory area. Second, disturbance signals are distinguished from danger signals in the short-term memory area. Finally, the stable data of the structural balance state are preserved in the long-term memory area. A strategy for priority scheduling via fuzzy c-means for the proposed model is then introduced. An experiment on bridge tower deformation demonstrates that the proposed model can be applied for real-time acquisition, limited-space storage and intelligent mining of the monitoring data in a long-term SHM system.

  8. Generic Database Cost Models for Hierarchical Memory Systems

    NARCIS (Netherlands)

    S. Manegold (Stefan); P.A. Boncz (Peter); M.L. Kersten (Martin)

    2002-01-01

    textabstractAccurate prediction of operator execution time is a prerequisite for database query optimization. Although extensively studied for conventional disk-based DBMSs, cost modeling in main-memory DBMSs is still an open issue. Recent database research has demonstrated that memory access is

  9. Generic database cost models for hierarchical memory systems

    NARCIS (Netherlands)

    S. Manegold (Stefan); P.A. Boncz (Peter); M.L. Kersten (Martin)

    2002-01-01

    textabstractAccurate prediction of operator execution time is a prerequisite fordatabase query optimization. Although extensively studied for conventionaldisk-based DBMSs, cost modeling in main-memory DBMSs is still an openissue. Recent database research has demonstrated that memory access ismore

  10. A bio-inspired memory model for structural health monitoring

    International Nuclear Information System (INIS)

    Zheng, Wei; Zhu, Yong

    2009-01-01

    Long-term structural health monitoring (SHM) systems need intelligent management of the monitoring data. By analogy with the way the human brain processes memories, we present a bio-inspired memory model (BIMM) that does not require prior knowledge of the structure parameters. The model contains three time-domain areas: a sensory memory area, a short-term memory area and a long-term memory area. First, the initial parameters of the structural state are specified to establish safety criteria. Then the large amount of monitoring data that falls within the safety limits is filtered while the data outside the safety limits are captured instantly in the sensory memory area. Second, disturbance signals are distinguished from danger signals in the short-term memory area. Finally, the stable data of the structural balance state are preserved in the long-term memory area. A strategy for priority scheduling via fuzzy c-means for the proposed model is then introduced. An experiment on bridge tower deformation demonstrates that the proposed model can be applied for real-time acquisition, limited-space storage and intelligent mining of the monitoring data in a long-term SHM system

  11. Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models

    NARCIS (Netherlands)

    S. Peiris (Shelton); M. Asai (Manabu); M.J. McAleer (Michael)

    2016-01-01

    textabstractIn recent years fractionally differenced processes have received a great deal of attention due to its flexibility in financial applications with long memory. This paper considers a class of models generated by Gegenbauer polynomials, incorporating the long memory in stochastic volatility

  12. Chronic caffeine consumption prevents memory disturbance in different animal models of memory decline.

    Science.gov (United States)

    Cunha, Rodrigo A; Agostinho, Paula M

    2010-01-01

    Caffeine, the most widely consumed psychoactive drug, enhances attention/vigilance, stabilizes mood, and might also independently enhance cognitive performance. Notably, caffeine displays clearer and more robust beneficial effects on memory performance when memory is perturbed by stressful or noxious stimuli either in human or animal studies. Thus, caffeine restores memory performance in sleep-deprived or aged human individuals, a finding replicated in rodent animal models. Likewise, in animal models of Alzheimer's disease (AD), caffeine alleviates memory dysfunction, which is in accordance with the tentative inverse correlation between caffeine intake and the incidence of AD in different (but not all) cohorts. Caffeine also affords beneficial effects in animal models of conditions expected to impair memory performance such as Parkinson's disease, chronic stress, type 2 diabetes, attention deficit and hyperactivity disorder, early life convulsions, or alcohol-induced amnesia. Thus, caffeine should not be viewed as a cognitive enhancer but instead as a cognitive normalizer. Interestingly, these beneficial effects of caffeine on stress-induced memory disturbance are mimicked by antagonists of adenosine A2A receptors. This prominent role of A2A receptors in preventing memory deterioration is probably related to the synaptic localization of this receptor in limbic areas and its ability to control glutamatergic transmission, especially NMDA receptor-dependent plasticity, and to control apoptosis, brain metabolism, and the burden of neuroinflammation. This opens the real and exciting possibility that caffeine consumption might be a prophylactic strategy and A2A receptor antagonists may be a novel therapeutic option to manage memory dysfunction both in AD and in other chronic neurodegenerative disorders where memory deficits occur.

  13. An SPICE model for phase-change memory simulations

    International Nuclear Information System (INIS)

    Li Xi; Song Zhitang; Cai Daolin; Chen Xiaogang; Chen Houpeng

    2011-01-01

    Along with a series of research works on the physical prototype and properties of the memory cell, an SPICE model for phase-change memory (PCM) simulations based on Verilog-A language is presented. By handling it with the heat distribution algorithm, threshold switching theory and the crystallization kinetic model, the proposed SPICE model can effectively reproduce the physical behaviors of the phase-change memory cell. In particular, it can emulate the cell's temperature curve and crystallinity profile during the programming process, which can enable us to clearly understand the PCM's working principle and program process. (semiconductor devices)

  14. An SPICE model for phase-change memory simulations

    Energy Technology Data Exchange (ETDEWEB)

    Li Xi; Song Zhitang; Cai Daolin; Chen Xiaogang; Chen Houpeng, E-mail: ituluck@mail.sim.ac.cn [State Key Laboratory of Functional Materials for Informatics, Laboratory of Nanotechnology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050 (China)

    2011-09-15

    Along with a series of research works on the physical prototype and properties of the memory cell, an SPICE model for phase-change memory (PCM) simulations based on Verilog-A language is presented. By handling it with the heat distribution algorithm, threshold switching theory and the crystallization kinetic model, the proposed SPICE model can effectively reproduce the physical behaviors of the phase-change memory cell. In particular, it can emulate the cell's temperature curve and crystallinity profile during the programming process, which can enable us to clearly understand the PCM's working principle and program process. (semiconductor devices)

  15. Dynamic intersectoral models with power-law memory

    Science.gov (United States)

    Tarasova, Valentina V.; Tarasov, Vasily E.

    2018-01-01

    Intersectoral dynamic models with power-law memory are proposed. The equations of open and closed intersectoral models, in which the memory effects are described by the Caputo derivatives of non-integer orders, are derived. We suggest solutions of these equations, which have the form of linear combinations of the Mittag-Leffler functions and which are characterized by different effective growth rates. Examples of intersectoral dynamics with power-law memory are suggested for two sectoral cases. We formulate two principles of intersectoral dynamics with memory: the principle of changing of technological growth rates and the principle of domination change. It has been shown that in the input-output economic dynamics the effects of fading memory can change the economic growth rate and dominant behavior of economic sectors.

  16. A Bayesian Model of the Memory Colour Effect.

    Science.gov (United States)

    Witzel, Christoph; Olkkonen, Maria; Gegenfurtner, Karl R

    2018-01-01

    According to the memory colour effect, the colour of a colour-diagnostic object is not perceived independently of the object itself. Instead, it has been shown through an achromatic adjustment method that colour-diagnostic objects still appear slightly in their typical colour, even when they are colourimetrically grey. Bayesian models provide a promising approach to capture the effect of prior knowledge on colour perception and to link these effects to more general effects of cue integration. Here, we model memory colour effects using prior knowledge about typical colours as priors for the grey adjustments in a Bayesian model. This simple model does not involve any fitting of free parameters. The Bayesian model roughly captured the magnitude of the measured memory colour effect for photographs of objects. To some extent, the model predicted observed differences in memory colour effects across objects. The model could not account for the differences in memory colour effects across different levels of realism in the object images. The Bayesian model provides a particularly simple account of memory colour effects, capturing some of the multiple sources of variation of these effects.

  17. Memory

    Science.gov (United States)

    ... it has to decide what is worth remembering. Memory is the process of storing and then remembering this information. There are different types of memory. Short-term memory stores information for a few ...

  18. Toxin-Induced Experimental Models of Learning and Memory Impairment.

    Science.gov (United States)

    More, Sandeep Vasant; Kumar, Hemant; Cho, Duk-Yeon; Yun, Yo-Sep; Choi, Dong-Kug

    2016-09-01

    Animal models for learning and memory have significantly contributed to novel strategies for drug development and hence are an imperative part in the assessment of therapeutics. Learning and memory involve different stages including acquisition, consolidation, and retrieval and each stage can be characterized using specific toxin. Recent studies have postulated the molecular basis of these processes and have also demonstrated many signaling molecules that are involved in several stages of memory. Most insights into learning and memory impairment and to develop a novel compound stems from the investigations performed in experimental models, especially those produced by neurotoxins models. Several toxins have been utilized based on their mechanism of action for learning and memory impairment such as scopolamine, streptozotocin, quinolinic acid, and domoic acid. Further, some toxins like 6-hydroxy dopamine (6-OHDA), 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and amyloid-β are known to cause specific learning and memory impairment which imitate the disease pathology of Parkinson's disease dementia and Alzheimer's disease dementia. Apart from these toxins, several other toxins come under a miscellaneous category like an environmental pollutant, snake venoms, botulinum, and lipopolysaccharide. This review will focus on the various classes of neurotoxin models for learning and memory impairment with their specific mechanism of action that could assist the process of drug discovery and development for dementia and cognitive disorders.

  19. Aplikasi Bidirectional Assosiatif Memori (BAM) Network pada Pengenalan Model

    OpenAIRE

    Iskandar, Iskhaq

    2001-01-01

    Penelitian ini bertujuan untuk menyusun suatu simulasi komputer yang dapat dipergunakan untuk menguji kemampuan memori komputer dalam mengenali suatu model tertentu berdasarkan algoritma Bidirectional Assosiatif Memori Neural Network. Model yang digunakan dalam penelitian dalam penelitian ini adalah huruf-huruf abjad yang dinyatakan dalam kode polar –1 dan +1 dalam bentuk matrik [5x3]. Hasil yang didapat dalam penelitian ini menunjukkan bahwa rancangan network yang disusun mampu mengenali mod...

  20. Why Narrating Changes Memory: A Contribution to an Integrative Model of Memory and Narrative Processes.

    Science.gov (United States)

    Smorti, Andrea; Fioretti, Chiara

    2016-06-01

    This paper aims to reflect on the relation between autobiographical memory (ME) and autobiographical narrative (NA), examining studies on the effects of narrating on the narrator and showing how studying these relations can make more comprehensible both memory's and narrating's way of working. Studies that address explicitly on ME and NA are scarce and touch this issue indirectly. Authors consider different trends of studies of ME and NA: congruency vs incongruency hypotheses on retrieving, the way of organizing memories according to gist or verbatim format and their role in organizing positive and negative emotional experiences, the social roots of ME and NA, the rules of conversation based on narrating. Analysis of investigations leads the Authors to point out three basic results of their research. Firstly, NA transforms ME because it narrativizes memories according to a narrative format. This means that memories, when are narrated, are transformed in stories (verbal language) and socialised. Secondly, the narrativization process is determined by the act of telling something within a communicative situation. Thus, relational situation of narrating act, by modifying the story, modifies also memories. The Authors propose the RE.NA.ME model (RElation, NArration, MEmory) to understand and study ME and NA. Finally, this study claims that ME and NA refer to two different types of processes having a wide area of overlapping. This is due to common social, developmental and cultural roots that make NA to include part of ME (narrative of memory) and ME to include part of NA (memory of personal events that have been narrated).

  1. Improving the Communication Pattern in Matrix-Vector Operations for Large Scale-Free Graphs by Disaggregation

    Energy Technology Data Exchange (ETDEWEB)

    Kuhlemann, Verena [Emory Univ., Atlanta, GA (United States); Vassilevski, Panayot S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2013-10-28

    Matrix-vector multiplication is the key operation in any Krylov-subspace iteration method. We are interested in Krylov methods applied to problems associated with the graph Laplacian arising from large scale-free graphs. Furthermore, computations with graphs of this type on parallel distributed-memory computers are challenging. This is due to the fact that scale-free graphs have a degree distribution that follows a power law, and currently available graph partitioners are not efficient for such an irregular degree distribution. The lack of a good partitioning leads to excessive interprocessor communication requirements during every matrix-vector product. Here, we present an approach to alleviate this problem based on embedding the original irregular graph into a more regular one by disaggregating (splitting up) vertices in the original graph. The matrix-vector operations for the original graph are performed via a factored triple matrix-vector product involving the embedding graph. And even though the latter graph is larger, we are able to decrease the communication requirements considerably and improve the performance of the matrix-vector product.

  2. Coupling effects on turning points of infectious diseases epidemics in scale-free networks.

    Science.gov (United States)

    Kim, Kiseong; Lee, Sangyeon; Lee, Doheon; Lee, Kwang Hyung

    2017-05-31

    Pandemic is a typical spreading phenomenon that can be observed in the human society and is dependent on the structure of the social network. The Susceptible-Infective-Recovered (SIR) model describes spreading phenomena using two spreading factors; contagiousness (β) and recovery rate (γ). Some network models are trying to reflect the social network, but the real structure is difficult to uncover. We have developed a spreading phenomenon simulator that can input the epidemic parameters and network parameters and performed the experiment of disease propagation. The simulation result was analyzed to construct a new marker VRTP distribution. We also induced the VRTP formula for three of the network mathematical models. We suggest new marker VRTP (value of recovered on turning point) to describe the coupling between the SIR spreading and the Scale-free (SF) network and observe the aspects of the coupling effects with the various of spreading and network parameters. We also derive the analytic formulation of VRTP in the fully mixed model, the configuration model, and the degree-based model respectively in the mathematical function form for the insights on the relationship between experimental simulation and theoretical consideration. We discover the coupling effect between SIR spreading and SF network through devising novel marker VRTP which reflects the shifting effect and relates to entropy.

  3. A revised limbic system model for memory, emotion and behaviour.

    Science.gov (United States)

    Catani, Marco; Dell'acqua, Flavio; Thiebaut de Schotten, Michel

    2013-09-01

    Emotion, memories and behaviour emerge from the coordinated activities of regions connected by the limbic system. Here, we propose an update of the limbic model based on the seminal work of Papez, Yakovlev and MacLean. In the revised model we identify three distinct but partially overlapping networks: (i) the Hippocampal-diencephalic and parahippocampal-retrosplenial network dedicated to memory and spatial orientation; (ii) The temporo-amygdala-orbitofrontal network for the integration of visceral sensation and emotion with semantic memory and behaviour; (iii) the default-mode network involved in autobiographical memories and introspective self-directed thinking. The three networks share cortical nodes that are emerging as principal hubs in connectomic analysis. This revised network model of the limbic system reconciles recent functional imaging findings with anatomical accounts of clinical disorders commonly associated with limbic pathology. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. The Development of Working Memory: Further Note on the Comparability of Two Models of Working Memory.

    Science.gov (United States)

    de Ribaupierre, Anik; Bailleux, Christine

    2000-01-01

    Summarizes similarities and differences between the working memory models of Pascual-Leone and Baddeley. Debates whether each model makes a specific contribution to explanation of Kemps, De Rammelaere, and Desmet's results. Argues for necessity of theoretical task analyses. Compares a study similar to that of Kemps et al. in which different…

  5. Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models

    Directory of Open Access Journals (Sweden)

    Shelton Peiris

    2017-12-01

    Full Text Available This paper considers a flexible class of time series models generated by Gegenbauer polynomials incorporating the long memory in stochastic volatility (SV components in order to develop the General Long Memory SV (GLMSV model. We examine the corresponding statistical properties of this model, discuss the spectral likelihood estimation and investigate the finite sample properties via Monte Carlo experiments. We provide empirical evidence by applying the GLMSV model to three exchange rate return series and conjecture that the results of out-of-sample forecasts adequately confirm the use of GLMSV model in certain financial applications.

  6. Abnormal Fear Memory as a Model for Posttraumatic Stress Disorder.

    Science.gov (United States)

    Desmedt, Aline; Marighetto, Aline; Piazza, Pier-Vincenzo

    2015-09-01

    For over a century, clinicians have consistently described the paradoxical co-existence in posttraumatic stress disorder (PTSD) of sensory intrusive hypermnesia and declarative amnesia for the same traumatic event. Although this amnesia is considered as a critical etiological factor of the development and/or persistence of PTSD, most current animal models in basic neuroscience have focused exclusively on the hypermnesia, i.e., the persistence of a strong fear memory, neglecting the qualitative alteration of fear memory. The latest is characterized by an underrepresentation of the trauma in the context-based declarative memory system in favor of its overrepresentation in a cue-based sensory/emotional memory system. Combining psychological and neurobiological data as well as theoretical hypotheses, this review supports the idea that contextual amnesia is at the core of PTSD and its persistence and that altered hippocampal-amygdalar interaction may contribute to such pathologic memory. In a first attempt to unveil the neurobiological alterations underlying PTSD-related hypermnesia/amnesia, we describe a recent animal model mimicking in mice some critical aspects of such abnormal fear memory. Finally, this line of argument emphasizes the pressing need for a systematic comparison between normal/adaptive versus abnormal/maladaptive fear memory to identify biomarkers of PTSD while distinguishing them from general stress-related, potentially adaptive, neurobiological alterations. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  7. Short-term memory in Down syndrome: applying the working memory model.

    Science.gov (United States)

    Jarrold, C; Baddeley, A D

    2001-10-01

    This paper is divided into three sections. The first reviews the evidence for a verbal short-term memory deficit in Down syndrome. Existing research suggests that short-term memory for verbal information tends to be impaired in Down syndrome, in contrast to short-term memory for visual and spatial material. In addition, problems of hearing or speech do not appear to be a major cause of difficulties on tests of verbal short-term memory. This suggests that Down syndrome is associated with a specific memory problem, which we link to a potential deficit in the functioning of the 'phonological loop' of Baddeley's (1986) model of working memory. The second section considers the implications of a phonological loop problem. Because a reasonable amount is known about the normal functioning of the phonological loop, and of its role in language acquisition in typical development, we can make firm predictions as to the likely nature of the short-term memory problem in Down syndrome, and its consequences for language learning. However, we note that the existing evidence from studies with individuals with Down syndrome does not fit well with these predictions. This leads to the third section of the paper, in which we consider key questions to be addressed in future research. We suggest that there are two questions to be answered, which follow directly from the contradictory results outlined in the previous section. These are 'What is the precise nature of the verbal short-term memory deficit in Down syndrome', and 'What are the consequences of this deficit for learning'. We discuss ways in which these questions might be addressed in future work.

  8. On the Use of Memory Models in Audio Features

    DEFF Research Database (Denmark)

    Jensen, Karl Kristoffer

    2011-01-01

    Audio feature estimation is potentially improved by including higher- level models. One such model is the Short Term Memory (STM) model. A new paradigm of audio feature estimation is obtained by adding the influence of notes in the STM. These notes are identified when the perceptual spectral flux...

  9. Modeling Students' Memory for Application in Adaptive Educational Systems

    Science.gov (United States)

    Pelánek, Radek

    2015-01-01

    Human memory has been thoroughly studied and modeled in psychology, but mainly in laboratory setting under simplified conditions. For application in practical adaptive educational systems we need simple and robust models which can cope with aspects like varied prior knowledge or multiple-choice questions. We discuss and evaluate several models of…

  10. Computational modelling of memory retention from synapse to behaviour

    Science.gov (United States)

    van Rossum, Mark C. W.; Shippi, Maria

    2013-03-01

    One of our most intriguing mental abilities is the capacity to store information and recall it from memory. Computational neuroscience has been influential in developing models and concepts of learning and memory. In this tutorial review we focus on the interplay between learning and forgetting. We discuss recent advances in the computational description of the learning and forgetting processes on synaptic, neuronal, and systems levels, as well as recent data that open up new challenges for statistical physicists.

  11. Computational modelling of memory retention from synapse to behaviour

    International Nuclear Information System (INIS)

    Van Rossum, Mark C W; Shippi, Maria

    2013-01-01

    One of our most intriguing mental abilities is the capacity to store information and recall it from memory. Computational neuroscience has been influential in developing models and concepts of learning and memory. In this tutorial review we focus on the interplay between learning and forgetting. We discuss recent advances in the computational description of the learning and forgetting processes on synaptic, neuronal, and systems levels, as well as recent data that open up new challenges for statistical physicists. (paper)

  12. Music Genre Classification using an Auditory Memory Model

    DEFF Research Database (Denmark)

    Jensen, Kristoffer

    2011-01-01

    Audio feature estimation is potentially improved by including higher- level models. One such model is the Auditory Short Term Memory (STM) model. A new paradigm of audio feature estimation is obtained by adding the influence of notes in the STM. These notes are identified when the perceptual...... results, and an initial experiment with sensory dissonance has been undertaken with good results. The parameters obtained form the auditory memory model, along with the dissonance measure, are shown here to be of interest in genre classification....

  13. PageRank in scale-free random graphs

    NARCIS (Netherlands)

    Chen, Ningyuan; Litvak, Nelli; Olvera-Cravioto, Mariana; Bonata, Anthony; Chung, Fan; Pralat, Paweł

    2014-01-01

    We analyze the distribution of PageRank on a directed configuration model and show that as the size of the graph grows to infinity, the PageRank of a randomly chosen node can be closely approximated by the PageRank of the root node of an appropriately constructed tree. This tree approximation is in

  14. Discretized kinetic theory on scale-free networks

    Science.gov (United States)

    Bertotti, Maria Letizia; Modanese, Giovanni

    2016-10-01

    The network of interpersonal connections is one of the possible heterogeneous factors which affect the income distribution emerging from micro-to-macro economic models. In this paper we equip our model discussed in [1, 2] with a network structure. The model is based on a system of n differential equations of the kinetic discretized-Boltzmann kind. The network structure is incorporated in a probabilistic way, through the introduction of a link density P(α) and of correlation coefficients P(β|α), which give the conditioned probability that an individual with α links is connected to one with β links. We study the properties of the equations and give analytical results concerning the existence, normalization and positivity of the solutions. For a fixed network with P(α) = c/α q , we investigate numerically the dependence of the detailed and marginal equilibrium distributions on the initial conditions and on the exponent q. Our results are compatible with those obtained from the Bouchaud-Mezard model and from agent-based simulations, and provide additional information about the dependence of the individual income on the level of connectivity.

  15. Strategic Factor Markets Scale Free Resources and Economic Performance

    DEFF Research Database (Denmark)

    Geisler Asmussen, Christian

    2015-01-01

    -theoretic model, it shows how the impact of strategic factor markets on economic profits is influenced by product market rivalry, preexisting competitive (dis)advantages, and the interaction of acquired resources with those preexisting asymmetries. New insights include the result that resource suppliers will aim...

  16. A local adaptive algorithm for emerging scale-free hierarchical networks

    International Nuclear Information System (INIS)

    Gomez Portillo, I J; Gleiser, P M

    2010-01-01

    In this work we study a growing network model with chaotic dynamical units that evolves using a local adaptive rewiring algorithm. Using numerical simulations we show that the model allows for the emergence of hierarchical networks. First, we show that the networks that emerge with the algorithm present a wide degree distribution that can be fitted by a power law function, and thus are scale-free networks. Using the LaNet-vi visualization tool we present a graphical representation that reveals a central core formed only by hubs, and also show the presence of a preferential attachment mechanism. In order to present a quantitative analysis of the hierarchical structure we analyze the clustering coefficient. In particular, we show that as the network grows the clustering becomes independent of system size, and also presents a power law decay as a function of the degree. Finally, we compare our results with a similar version of the model that has continuous non-linear phase oscillators as dynamical units. The results show that local interactions play a fundamental role in the emergence of hierarchical networks.

  17. I. WORKING MEMORY CAPACITY IN CONTEXT: MODELING DYNAMIC PROCESSES OF BEHAVIOR, MEMORY, AND DEVELOPMENT.

    Science.gov (United States)

    Simmering, Vanessa R

    2016-09-01

    Working memory is a vital cognitive skill that underlies a broad range of behaviors. Higher cognitive functions are reliably predicted by working memory measures from two domains: children's performance on complex span tasks, and infants' performance in looking paradigms. Despite the similar predictive power across these research areas, theories of working memory development have not connected these different task types and developmental periods. The current project takes a first step toward bridging this gap by presenting a process-oriented theory, focusing on two tasks designed to assess visual working memory capacity in infants (the change-preference task) versus children and adults (the change detection task). Previous studies have shown inconsistent results, with capacity estimates increasing from one to four items during infancy, but only two to three items during early childhood. A probable source of this discrepancy is the different task structures used with each age group, but prior theories were not sufficiently specific to explain how performance relates across tasks. The current theory focuses on cognitive dynamics, that is, how memory representations are formed, maintained, and used within specific task contexts over development. This theory was formalized in a computational model to generate three predictions: 1) capacity estimates in the change-preference task should continue to increase beyond infancy; 2) capacity estimates should be higher in the change-preference versus change detection task when tested within individuals; and 3) performance should correlate across tasks because both rely on the same underlying memory system. I also tested a fourth prediction, that development across tasks could be explained through increasing real-time stability, realized computationally as strengthening connectivity within the model. Results confirmed these predictions, supporting the cognitive dynamics account of performance and developmental changes in real

  18. Long Memory Models to Generate Synthetic Hydrological Series

    Directory of Open Access Journals (Sweden)

    Guilherme Armando de Almeida Pereira

    2014-01-01

    Full Text Available In Brazil, much of the energy production comes from hydroelectric plants whose planning is not trivial due to the strong dependence on rainfall regimes. This planning is accomplished through optimization models that use inputs such as synthetic hydrologic series generated from the statistical model PAR(p (periodic autoregressive. Recently, Brazil began the search for alternative models able to capture the effects that the traditional model PAR(p does not incorporate, such as long memory effects. Long memory in a time series can be defined as a significant dependence between lags separated by a long period of time. Thus, this research develops a study of the effects of long dependence in the series of streamflow natural energy in the South subsystem, in order to estimate a long memory model capable of generating synthetic hydrologic series.

  19. Comparing single- and dual-process models of memory development.

    Science.gov (United States)

    Hayes, Brett K; Dunn, John C; Joubert, Amy; Taylor, Robert

    2017-11-01

    This experiment examined single-process and dual-process accounts of the development of visual recognition memory. The participants, 6-7-year-olds, 9-10-year-olds and adults, were presented with a list of pictures which they encoded under shallow or deep conditions. They then made recognition and confidence judgments about a list containing old and new items. We replicated the main trends reported by Ghetti and Angelini () in that recognition hit rates increased from 6 to 9 years of age, with larger age changes following deep than shallow encoding. Formal versions of the dual-process high threshold signal detection model and several single-process models (equal variance signal detection, unequal variance signal detection, mixture signal detection) were fit to the developmental data. The unequal variance and mixture signal detection models gave a better account of the data than either of the other models. A state-trace analysis found evidence for only one underlying memory process across the age range tested. These results suggest that single-process memory models based on memory strength are a viable alternative to dual-process models for explaining memory development. © 2016 John Wiley & Sons Ltd.

  20. EPS Mid-Career Award 2011. Are there multiple memory systems? Tests of models of implicit and explicit memory.

    Science.gov (United States)

    Shanks, David R; Berry, Christopher J

    2012-01-01

    This article reviews recent work aimed at developing a new framework, based on signal detection theory, for understanding the relationship between explicit (e.g., recognition) and implicit (e.g., priming) memory. Within this framework, different assumptions about sources of memorial evidence can be framed. Application to experimental results provides robust evidence for a single-system model in preference to multiple-systems models. This evidence comes from several sources including studies of the effects of amnesia and ageing on explicit and implicit memory. The framework allows a range of concepts in current memory research, such as familiarity, recollection, fluency, and source memory, to be linked to implicit memory. More generally, this work emphasizes the value of modern computational modelling techniques in the study of learning and memory.

  1. Comparing soil moisture memory in satellite observations and models

    Science.gov (United States)

    Stacke, Tobias; Hagemann, Stefan; Loew, Alexander

    2013-04-01

    A major obstacle to a correct parametrization of soil processes in large scale global land surface models is the lack of long term soil moisture observations for large parts of the globe. Currently, a compilation of soil moisture data derived from a range of satellites is released by the ESA Climate Change Initiative (ECV_SM). Comprising the period from 1978 until 2010, it provides the opportunity to compute climatological relevant statistics on a quasi-global scale and to compare these to the output of climate models. Our study is focused on the investigation of soil moisture memory in satellite observations and models. As a proxy for memory we compute the autocorrelation length (ACL) of the available satellite data and the uppermost soil layer of the models. Additional to the ECV_SM data, AMSR-E soil moisture is used as observational estimate. Simulated soil moisture fields are taken from ERA-Interim reanalysis and generated with the land surface model JSBACH, which was driven with quasi-observational meteorological forcing data. The satellite data show ACLs between one week and one month for the greater part of the land surface while the models simulate a longer memory of up to two months. Some pattern are similar in models and observations, e.g. a longer memory in the Sahel Zone and the Arabian Peninsula, but the models are not able to reproduce regions with a very short ACL of just a few days. If the long term seasonality is subtracted from the data the memory is strongly shortened, indicating the importance of seasonal variations for the memory in most regions. Furthermore, we analyze the change of soil moisture memory in the different soil layers of the models to investigate to which extent the surface soil moisture includes information about the whole soil column. A first analysis reveals that the ACL is increasing for deeper layers. However, its increase is stronger in the soil moisture anomaly than in its absolute values and the first even exceeds the

  2. Epidemic spreading on dynamical networks with temporary hubs and stable scale-free degree distribution

    International Nuclear Information System (INIS)

    Wu, An-Cai

    2014-01-01

    Recent empirical analyses of some realistic dynamical networks have demonstrated that their degree distributions are stable scale-free (SF), but the instantaneous well-connected hubs at one point of time can quickly become weakly connected. Motivated by these empirical results, we propose a simple toy dynamical agent-to-agent contact network model, in which each agent stays at one node of a static underlay network and the nearest neighbors swap their positions with each other. Although the degree distribution of the dynamical network model at any one time is equal to that in the static underlay network, the numbers and identities of each agent’s contacts will change over time. It is found that the dynamic interaction tends to suppress epidemic spreading in terms of larger epidemic threshold, smaller prevalence (the fraction of infected individuals) and smaller velocity of epidemic outbreak. Furthermore, the dynamic interaction results in the prevalence to undergo a phase transition at a finite threshold of the epidemic spread rate in the thermodynamic limit, which is in contradiction to the absence of an epidemic threshold in static SF networks. Some of these findings obtained from heterogeneous mean-field theory are in good agreement with numerical simulations. (paper)

  3. Overlapping Parietal Activity in Memory and Perception: Evidence for the Attention to Memory Model

    Science.gov (United States)

    Cabeza, Roberto; Mazuz, Yonatan S.; Stokes, Jared; Kragel, James E.; Woldorff, Marty G.; Ciaramelli, Elisa; Olson, Ingrid R.; Moscovitch, Morris

    2011-01-01

    The specific role of different parietal regions to episodic retrieval is a topic of intense debate. According to the Attention to Memory (AtoM) model, dorsal parietal cortex (DPC) mediates top-down attention processes guided by retrieval goals, whereas ventral parietal cortex (VPC) mediates bottom-up attention processes captured by the retrieval…

  4. Asymmetric cross-domain interference between two working memory tasks : Implications for models of working memory

    NARCIS (Netherlands)

    Morey, Candice C.; Morey, Richard D.; van der Reijden, Madeleine; Holweg, Margot

    2013-01-01

    Observations of higher dual-task costs for within-domain than cross-domain task combinations constitute classic evidence for multi-component models of working memory (e.g., Baddeley, 1986; Logie, 2011). However, we report an asymmetric pattern of interference between verbal and visual-spatial tasks,

  5. Lower Bounds in the Asymmetric External Memory Model

    DEFF Research Database (Denmark)

    Jacob, Riko; Sitchinava, Nodari

    2017-01-01

    Motivated by the asymmetric read and write costs of emerging non-volatile memory technologies, we study lower bounds for the problems of sorting, permuting and multiplying a sparse matrix by a dense vector in the asymmetric external memory model (AEM). Given an AEM with internal (symmetric) memory...... of size M, transfers between symmetric and asymmetric memory in blocks of size B and the ratio ω between write and read costs, we show Ω(min (N, ωN/B logω M/B N/B) lower bound for the cost of permuting N input elements. This lower bound also applies to the problem of sorting N elements. This proves...

  6. Multi-Type Directed Scale-Free Percolation

    International Nuclear Information System (INIS)

    Shang Yilun

    2012-01-01

    In this paper, we study a long-range percolation model on the lattice ℤ d with multi-type vertices and directed edges. Each vertex x in ℤ d is independently assigned a non-negative weight W x and a type ψ x , where (W x ) xinℤ d are i.i.d. random variables, and (ψ x ) xinℤ d are also i.i.d. Conditionally on weights and types, and given λ, α > 0, the edges are independent and the probability that there is a directed edge from x to y is given by p xy = 1 - exp(-λφ ψ x ψ y W x W y /|x-y| α ), where φ ij 's are entries from a type matrix Φ. We show that, when the tail of the distribution of W x is regularly varying with exponent τ - 1, the tails of the out/in-degree distributions are both regularly varying with exponent γ = α(τ - 1)/d. We formulate conditions under which there exist critical values λ c WCC in (0, ∞) and λ c SCC in (0, ∞) such that an infinite weak component and an infinite strong component emerge, respectively, when λ exceeds them. A phase transition is established for the shortest path lengths of directed and undirected edges in the infinite component at the point γ = 2, where the out/in-degrees switch from having finite to infinite variances. The random graph model studied here features some structures of multi-type vertices and directed edges which appear naturally in many real-world networks, such as the SNS networks and computer communication networks. (condensed matter: structural, mechanical, and thermal properties)

  7. Mechanisms of memory storage in a model perirhinal network.

    Science.gov (United States)

    Samarth, Pranit; Ball, John M; Unal, Gunes; Paré, Denis; Nair, Satish S

    2017-01-01

    The perirhinal cortex supports recognition and associative memory. Prior unit recording studies revealed that recognition memory involves a reduced responsiveness of perirhinal cells to familiar stimuli whereas associative memory formation is linked to increasing perirhinal responses to paired stimuli. Both effects are thought to depend on perirhinal plasticity but it is unclear how the same network could support these opposite forms of plasticity. However, a recent study showed that when neocortical inputs are repeatedly activated, depression or potentiation could develop, depending on the extent to which the stimulated neocortical activity recruited intrinsic longitudinal connections. We developed a biophysically realistic perirhinal model that reproduced these phenomena and used it to investigate perirhinal mechanisms of associative memory. These analyzes revealed that associative plasticity is critically dependent on a specific subset of neurons, termed conjunctive cells (CCs). When the model network was trained with spatially distributed but coincident neocortical inputs, CCs acquired excitatory responses to the paired inputs and conveyed them to distributed perirhinal sites via longitudinal projections. CC ablation during recall abolished expression of the associative memory. However, CC ablation during training did not prevent memory formation because new CCs emerged, revealing that competitive synaptic interactions governs the formation of CC assemblies.

  8. A phenomenological memristor model for synaptic memory and learning behaviors

    Institute of Scientific and Technical Information of China (English)

    Nan Shao; Sheng-Bing Zhang; Shu-Yuan Shao

    2017-01-01

    Properties that are similar to the memory and learning functions in biological systems have been observed and reported in the experimental studies of memristors fabricated by different materials.These properties include the forgetting effect,the transition from short-term memory (STM) to long-term memory (LTM),learning-experience behavior,etc.The mathematical model of this kind of memristor would be very important for its theoretical analysis and application design.In our analysis of the existing memristor model with these properties,we find that some behaviors of the model are inconsistent with the reported experimental observations.A phenomenological memristor model is proposed for this kind of memristor.The model design is based on the forgetting effect and STM-to-LTM transition since these behaviors are two typical properties of these memristors.Further analyses of this model show that this model can also be used directly or modified to describe other experimentally observed behaviors.Simulations show that the proposed model can give a better description of the reported memory and learning behaviors of this kind of memristor than the existing model.

  9. Likelihood ratio sequential sampling models of recognition memory.

    Science.gov (United States)

    Osth, Adam F; Dennis, Simon; Heathcote, Andrew

    2017-02-01

    The mirror effect - a phenomenon whereby a manipulation produces opposite effects on hit and false alarm rates - is benchmark regularity of recognition memory. A likelihood ratio decision process, basing recognition on the relative likelihood that a stimulus is a target or a lure, naturally predicts the mirror effect, and so has been widely adopted in quantitative models of recognition memory. Glanzer, Hilford, and Maloney (2009) demonstrated that likelihood ratio models, assuming Gaussian memory strength, are also capable of explaining regularities observed in receiver-operating characteristics (ROCs), such as greater target than lure variance. Despite its central place in theorising about recognition memory, however, this class of models has not been tested using response time (RT) distributions. In this article, we develop a linear approximation to the likelihood ratio transformation, which we show predicts the same regularities as the exact transformation. This development enabled us to develop a tractable model of recognition-memory RT based on the diffusion decision model (DDM), with inputs (drift rates) provided by an approximate likelihood ratio transformation. We compared this "LR-DDM" to a standard DDM where all targets and lures receive their own drift rate parameters. Both were implemented as hierarchical Bayesian models and applied to four datasets. Model selection taking into account parsimony favored the LR-DDM, which requires fewer parameters than the standard DDM but still fits the data well. These results support log-likelihood based models as providing an elegant explanation of the regularities of recognition memory, not only in terms of choices made but also in terms of the times it takes to make them. Copyright © 2016 Elsevier Inc. All rights reserved.

  10. Neurofeedback Tunes Scale-Free Dynamics in Spontaneous Brain Activity.

    Science.gov (United States)

    Ros, T; Frewen, P; Théberge, J; Michela, A; Kluetsch, R; Mueller, A; Candrian, G; Jetly, R; Vuilleumier, P; Lanius, R A

    2017-10-01

    Brain oscillations exhibit long-range temporal correlations (LRTCs), which reflect the regularity of their fluctuations: low values representing more random (decorrelated) while high values more persistent (correlated) dynamics. LRTCs constitute supporting evidence that the brain operates near criticality, a state where neuronal activities are balanced between order and randomness. Here, healthy adults used closed-loop brain training (neurofeedback, NFB) to reduce the amplitude of alpha oscillations, producing a significant increase in spontaneous LRTCs post-training. This effect was reproduced in patients with post-traumatic stress disorder, where abnormally random dynamics were reversed by NFB, correlating with significant improvements in hyperarousal. Notably, regions manifesting abnormally low LRTCs (i.e., excessive randomness) normalized toward healthy population levels, consistent with theoretical predictions about self-organized criticality. Hence, when exposed to appropriate training, spontaneous cortical activity reveals a residual capacity for "self-tuning" its own temporal complexity, despite manifesting the abnormal dynamics seen in individuals with psychiatric disorder. Lastly, we observed an inverse-U relationship between strength of LRTC and oscillation amplitude, suggesting a breakdown of long-range dependence at high/low synchronization extremes, in line with recent computational models. Together, our findings offer a broader mechanistic framework for motivating research and clinical applications of NFB, encompassing disorders with perturbed LRTCs. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  11. Scale-free correlations in the geographical spreading of obesity

    Science.gov (United States)

    Gallos, Lazaros; Barttfeld, Pablo; Havlin, Shlomo; Sigman, Mariano; Makse, Hernan

    2012-02-01

    Obesity levels have been universally increasing. A crucial problem is to determine the influence of global and local drivers behind the obesity epidemic, to properly guide effective policies. Despite the numerous factors that affect the obesity evolution, we show a remarkable regularity expressed in a predictable pattern of spatial long-range correlations in the geographical spreading of obesity. We study the spatial clustering of obesity and a number of related health and economic indicators, and we use statistical physics methods to characterize the growth of the resulting clusters. The resulting scaling exponents allow us to broadly classify these indicators into two separate universality classes, weakly or strongly correlated. Weak correlations are found in generic human activity such as population distribution and the growth of the whole economy. Strong correlations are recovered, among others, for obesity, diabetes, and the food industry sectors associated with food consumption. Obesity turns out to be a global problem where local details are of little importance. The long-range correlations suggest influence that extends to large scales, hinting that the physical model of obesity clustering can be mapped to a long-range correlated percolation process.

  12. Dynamic State Space Partitioning for External Memory Model Checking

    DEFF Research Database (Denmark)

    Evangelista, Sami; Kristensen, Lars Michael

    2009-01-01

    We describe a dynamic partitioning scheme usable by model checking techniques that divide the state space into partitions, such as most external memory and distributed model checking algorithms. The goal of the scheme is to reduce the number of transitions that link states belonging to different...

  13. Birth of scale-free molecular networks and the number of distinct DNA and protein domains per genome.

    Science.gov (United States)

    Rzhetsky, A; Gomez, S M

    2001-10-01

    Current growth in the field of genomics has provided a number of exciting approaches to the modeling of evolutionary mechanisms within the genome. Separately, dynamical and statistical analyses of networks such as the World Wide Web and the social interactions existing between humans have shown that these networks can exhibit common fractal properties-including the property of being scale-free. This work attempts to bridge these two fields and demonstrate that the fractal properties of molecular networks are linked to the fractal properties of their underlying genomes. We suggest a stochastic model capable of describing the evolutionary growth of metabolic or signal-transduction networks. This model generates networks that share important statistical properties (so-called scale-free behavior) with real molecular networks. In particular, the frequency of vertices connected to exactly k other vertices follows a power-law distribution. The shape of this distribution remains invariant to changes in network scale: a small subgraph has the same distribution as the complete graph from which it is derived. Furthermore, the model correctly predicts that the frequencies of distinct DNA and protein domains also follow a power-law distribution. Finally, the model leads to a simple equation linking the total number of different DNA and protein domains in a genome with both the total number of genes and the overall network topology. MatLab (MathWorks, Inc.) programs described in this manuscript are available on request from the authors. ar345@columbia.edu.

  14. Why does brain damage impair memory? A connectionist model of object recognition memory in perirhinal cortex.

    Science.gov (United States)

    Cowell, Rosemary A; Bussey, Timothy J; Saksida, Lisa M

    2006-11-22

    Object recognition is the canonical test of declarative memory, the type of memory putatively impaired after damage to the temporal lobes. Studies of object recognition memory have helped elucidate the anatomical structures involved in declarative memory, indicating a critical role for perirhinal cortex. We offer a mechanistic account of the effects of perirhinal cortex damage on object recognition memory, based on the assumption that perirhinal cortex stores representations of the conjunctions of visual features possessed by complex objects. Such representations are proposed to play an important role in memory when it is difficult to solve a task using representations of only individual visual features of stimuli, thought to be stored in regions of the ventral visual stream caudal to perirhinal cortex. The account is instantiated in a connectionist model, in which development of object representations with visual experience provides a mechanism for judgment of previous occurrence. We present simulations addressing the following empirical findings: (1) that impairments after damage to perirhinal cortex (modeled by removing the "perirhinal cortex" layer of the network) are exacerbated by lengthening the delay between presentation of to-be-remembered items and test, (2) that such impairments are also exacerbated by lengthening the list of to-be-remembered items, and (3) that impairments are revealed only when stimuli are trial unique rather than repeatedly presented. This study shows that it may be possible to account for object recognition impairments after damage to perirhinal cortex within a hierarchical, representational framework, in which complex conjunctive representations in perirhinal cortex play a critical role.

  15. Single Canonical Model of Reflexive Memory and Spatial Attention

    Science.gov (United States)

    Patel, Saumil S.; Red, Stuart; Lin, Eric; Sereno, Anne B.

    2015-01-01

    Many neurons in the dorsal and ventral visual stream have the property that after a brief visual stimulus presentation in their receptive field, the spiking activity in these neurons persists above their baseline levels for several seconds. This maintained activity is not always correlated with the monkey’s task and its origin is unknown. We have previously proposed a simple neural network model, based on shape selective neurons in monkey lateral intraparietal cortex, which predicts the valence and time course of reflexive (bottom-up) spatial attention. In the same simple model, we demonstrate here that passive maintained activity or short-term memory of specific visual events can result without need for an external or top-down modulatory signal. Mutual inhibition and neuronal adaptation play distinct roles in reflexive attention and memory. This modest 4-cell model provides the first simple and unified physiologically plausible mechanism of reflexive spatial attention and passive short-term memory processes. PMID:26493949

  16. Single Canonical Model of Reflexive Memory and Spatial Attention.

    Science.gov (United States)

    Patel, Saumil S; Red, Stuart; Lin, Eric; Sereno, Anne B

    2015-10-23

    Many neurons in the dorsal and ventral visual stream have the property that after a brief visual stimulus presentation in their receptive field, the spiking activity in these neurons persists above their baseline levels for several seconds. This maintained activity is not always correlated with the monkey's task and its origin is unknown. We have previously proposed a simple neural network model, based on shape selective neurons in monkey lateral intraparietal cortex, which predicts the valence and time course of reflexive (bottom-up) spatial attention. In the same simple model, we demonstrate here that passive maintained activity or short-term memory of specific visual events can result without need for an external or top-down modulatory signal. Mutual inhibition and neuronal adaptation play distinct roles in reflexive attention and memory. This modest 4-cell model provides the first simple and unified physiologically plausible mechanism of reflexive spatial attention and passive short-term memory processes.

  17. Memory Effects in the Two-Level Model for Glasses

    Science.gov (United States)

    Aquino, Gerardo; Allahverdyan, Armen; Nieuwenhuizen, Theo M.

    2008-07-01

    We study an ensemble of two-level systems interacting with a thermal bath. This is a well-known model for glasses. The origin of memory effects in this model is a quasistationary but nonequilibrium state of a single two-level system, which is realized due to a finite-rate cooling and slow thermally activated relaxation. We show that single-particle memory effects, such as negativity of the specific heat under reheating, vanish for a sufficiently disordered ensemble. In contrast, a disordered ensemble displays a collective memory effect [similar to the Kovacs effect], where nonequilibrium features of the ensemble are monitored via a macroscopic observable. An experimental realization of the effect can be used to further assess the consistency of the model.

  18. Development of Next Generation Heating System for Scale Free Steel Reheating

    Energy Technology Data Exchange (ETDEWEB)

    Dr. Arvind C. Thekdi

    2011-01-27

    The work carried out under this project includes development and design of components, controls, and economic modeling tools that would enable the steel industry to reduce energy intensity through reduction of scale formation during the steel reheating process. Application of scale free reheating offers savings in energy used for production of steel that is lost as scale, and increase in product yield for the global steel industry. The technology can be applied to a new furnace application as well as retrofit design for conversion of existing steel reheating furnaces. The development work has resulted in the knowledge base that will enable the steel industry and steel forging industry us to reheat steel with 75% to 95% reduction in scale formation and associated energy savings during the reheating process. Scale reduction also results in additional energy savings associated with higher yield from reheat furnaces. Energy used for steel production ranges from 9 MM Btu/ton to 16.6 MM Btu/ton or the industry average of approximately 13 MM Btu/ton. Hence, reduction in scale at reheating stage would represent a substantial energy reduction for the steel industry. Potential energy savings for the US steel industry could be in excess of 25 Trillion Btu/year when the technology is applied to all reheating processes. The development work has resulted in new design of reheating process and the required burners and control systems that would allow use of this technology for steel reheating in steel as well as steel forging industries.

  19. Effects of packet retransmission with finite packet lifetime on traffic capacity in scale-free networks

    Science.gov (United States)

    Jiang, Zhong-Yuan; Ma, Jian-Feng

    Existing routing strategies such as the global dynamic routing [X. Ling, M. B. Hu, R. Jiang and Q. S. Wu, Phys. Rev. E 81, 016113 (2010)] can achieve very high traffic capacity at the cost of extremely long packet traveling delay. In many real complex networks, especially for real-time applications such as the instant communication software, extremely long packet traveling time is unacceptable. In this work, we propose to assign a finite Time-to-Live (TTL) parameter for each packet. To guarantee every packet to arrive at its destination within its TTL, we assume that a packet is retransmitted by its source once its TTL expires. We employ source routing mechanisms in the traffic model to avoid the routing-flaps induced by the global dynamic routing. We compose extensive simulations to verify our proposed mechanisms. With small TTL, the effects of packet retransmission on network traffic capacity are obvious, and the phase transition from flow free state to congested state occurs. For the purpose of reducing the computation frequency of the routing table, we employ a computing cycle Tc within which the routing table is recomputed once. The simulation results show that the traffic capacity decreases with increasing Tc. Our work provides a good insight into the understanding of effects of packet retransmission with finite packet lifetime on traffic capacity in scale-free networks.

  20. Colored noise and memory effects on formal spiking neuron models

    Science.gov (United States)

    da Silva, L. A.; Vilela, R. D.

    2015-06-01

    Simplified neuronal models capture the essence of the electrical activity of a generic neuron, besides being more interesting from the computational point of view when compared to higher-dimensional models such as the Hodgkin-Huxley one. In this work, we propose a generalized resonate-and-fire model described by a generalized Langevin equation that takes into account memory effects and colored noise. We perform a comprehensive numerical analysis to study the dynamics and the point process statistics of the proposed model, highlighting interesting new features such as (i) nonmonotonic behavior (emergence of peak structures, enhanced by the choice of colored noise characteristic time scale) of the coefficient of variation (CV) as a function of memory characteristic time scale, (ii) colored noise-induced shift in the CV, and (iii) emergence and suppression of multimodality in the interspike interval (ISI) distribution due to memory-induced subthreshold oscillations. Moreover, in the noise-induced spike regime, we study how memory and colored noise affect the coherence resonance (CR) phenomenon. We found that for sufficiently long memory, not only is CR suppressed but also the minimum of the CV-versus-noise intensity curve that characterizes the presence of CR may be replaced by a maximum. The aforementioned features allow to interpret the interplay between memory and colored noise as an effective control mechanism to neuronal variability. Since both variability and nontrivial temporal patterns in the ISI distribution are ubiquitous in biological cells, we hope the present model can be useful in modeling real aspects of neurons.

  1. Scale-free behavior of networks with the copresence of preferential and uniform attachment rules

    Science.gov (United States)

    Pachon, Angelica; Sacerdote, Laura; Yang, Shuyi

    2018-05-01

    Complex networks in different areas exhibit degree distributions with a heavy upper tail. A preferential attachment mechanism in a growth process produces a graph with this feature. We herein investigate a variant of the simple preferential attachment model, whose modifications are interesting for two main reasons: to analyze more realistic models and to study the robustness of the scale-free behavior of the degree distribution. We introduce and study a model which takes into account two different attachment rules: a preferential attachment mechanism (with probability 1 - p) that stresses the rich get richer system, and a uniform choice (with probability p) for the most recent nodes, i.e. the nodes belonging to a window of size w to the left of the last born node. The latter highlights a trend to select one of the last added nodes when no information is available. The recent nodes can be either a given fixed number or a proportion (αn) of the total number of existing nodes. In the first case, we prove that this model exhibits an asymptotically power-law degree distribution. The same result is then illustrated through simulations in the second case. When the window of recent nodes has a constant size, we herein prove that the presence of the uniform rule delays the starting time from which the asymptotic regime starts to hold. The mean number of nodes of degree k and the asymptotic degree distribution are also determined analytically. Finally, a sensitivity analysis on the parameters of the model is performed.

  2. Short-Term Memory and Its Biophysical Model

    Science.gov (United States)

    Wang, Wei; Zhang, Kai; Tang, Xiao-wei

    1996-12-01

    The capacity of short-term memory has been studied using an integrate-and-fire neuronal network model. It is found that the storage of events depend on the manner of the correlation between the events, and the capacity is dominated by the value of after-depolarization potential. There is a monotonic increasing relationship between the value of after-depolarization potential and the memory numbers. The biophysics relevance of the network model is discussed and different kinds of the information processes are studied too.

  3. Convergence speed of consensus problems over undirected scale-free networks

    International Nuclear Information System (INIS)

    Sun Wei; Dou Li-Hua

    2010-01-01

    Scale-free networks and consensus behaviour among multiple agents have both attracted much attention. To investigate the consensus speed over scale-free networks is the major topic of the present work. A novel method is developed to construct scale-free networks due to their remarkable power-law degree distributions, while preserving the diversity of network topologies. The time cost or iterations for networks to reach a certain level of consensus is discussed, considering the influence from power-law parameters. They are both demonstrated to be reversed power-law functions of the algebraic connectivity, which is viewed as a measurement on convergence speed of the consensus behaviour. The attempts of tuning power-law parameters may speed up the consensus procedure, but it could also make the network less robust over time delay at the same time. Large scale of simulations are supportive to the conclusions. (general)

  4. Latent change models of adult cognition: are changes in processing speed and working memory associated with changes in episodic memory?

    Science.gov (United States)

    Hertzog, Christopher; Dixon, Roger A; Hultsch, David F; MacDonald, Stuart W S

    2003-12-01

    The authors used 6-year longitudinal data from the Victoria Longitudinal Study (VLS) to investigate individual differences in amount of episodic memory change. Latent change models revealed reliable individual differences in cognitive change. Changes in episodic memory were significantly correlated with changes in other cognitive variables, including speed and working memory. A structural equation model for the latent change scores showed that changes in speed and working memory predicted changes in episodic memory, as expected by processing resource theory. However, these effects were best modeled as being mediated by changes in induction and fact retrieval. Dissociations were detected between cross-sectional ability correlations and longitudinal changes. Shuffling the tasks used to define the Working Memory latent variable altered patterns of change correlations.

  5. Effect of trap position on the efficiency of trapping in treelike scale-free networks

    International Nuclear Information System (INIS)

    Zhang Zhongzhi; Lin Yuan; Ma Youjun

    2011-01-01

    The conventional wisdom is that the role and impact of nodes on dynamical processes in scale-free networks are not homogenous, because of the presence of highly connected nodes at the tail of their power-law degree distribution. In this paper, we explore the influence of different nodes as traps on the trapping efficiency of the trapping problem taking place on scale-free networks. To this end, we study in detail the trapping problem in two families of deterministically growing scale-free networks with treelike structure: one family is non-fractal, the other is fractal. In the first part of this work, we attack a special case of random walks on the two network families with a perfect trap located at a hub, i.e. node with the highest degree. The second study addresses the case with trap distributed uniformly over all nodes in the networks. For these two cases, we compute analytically the mean trapping time (MTT), a quantitative indicator characterizing the trapping efficiency of the trapping process. We show that in the non-fractal scale-free networks the MTT for both cases follows different scalings with the network order (number of network nodes), implying that trap's position has a significant effect on the trapping efficiency. In contrast, it is presented that for both cases in the fractal scale-free networks, the two leading scalings exhibit the same dependence on the network order, suggesting that the location of trap has no essential impact on the trapping efficiency. We also show that for both cases of the trapping problem, the trapping efficiency is more efficient in the non-fractal scale-free networks than in their fractal counterparts.

  6. Modeling Active Aging and Explicit Memory: An Empirical Study.

    Science.gov (United States)

    Ponce de León, Laura Ponce; Lévy, Jean Pierre; Fernández, Tomás; Ballesteros, Soledad

    2015-08-01

    The rapid growth of the population of older adults and their concomitant psychological status and health needs have captured the attention of researchers and health professionals. To help fill the void of literature available to social workers interested in mental health promotion and aging, the authors provide a model for active aging that uses psychosocial variables. Structural equation modeling was used to examine the relationships among the latent variables of the state of explicit memory, the perception of social resources, depression, and the perception of quality of life in a sample of 184 older adults. The results suggest that explicit memory is not a direct indicator of the perception of quality of life, but it could be considered an indirect indicator as it is positively correlated with perception of social resources and negatively correlated with depression. These last two variables influenced the perception of quality of life directly, the former positively and the latter negatively. The main outcome suggests that the perception of social support improves explicit memory and quality of life and reduces depression in active older adults. The findings also suggest that gerontological professionals should design memory training programs, improve available social resources, and offer environments with opportunities to exercise memory.

  7. The Neuroanatomical, Neurophysiological and Psychological Basis of Memory: Current Models and Their Origins.

    Science.gov (United States)

    Camina, Eduardo; Güell, Francisco

    2017-01-01

    This review aims to classify and clarify, from a neuroanatomical, neurophysiological, and psychological perspective, different memory models that are currently widespread in the literature as well as to describe their origins. We believe it is important to consider previous developments without which one cannot adequately understand the kinds of models that are now current in the scientific literature. This article intends to provide a comprehensive and rigorous overview for understanding and ordering the latest scientific advances related to this subject. The main forms of memory presented include sensory memory, short-term memory, and long-term memory. Information from the world around us is first stored by sensory memory, thus enabling the storage and future use of such information. Short-term memory (or memory) refers to information processed in a short period of time. Long-term memory allows us to store information for long periods of time, including information that can be retrieved consciously (explicit memory) or unconsciously (implicit memory).

  8. Heterogeneous Agent Model with Memory and Asset Price Behaviour

    Czech Academy of Sciences Publication Activity Database

    Vošvrda, Miloslav; Vácha, Lukáš

    2003-01-01

    Roč. 12, č. 2 (2003), s. 155-168 ISSN 1210-0455 R&D Projects: GA ČR GA402/00/0439; GA ČR GA402/01/0034 Institutional research plan: CEZ:AV0Z1075907 Keywords : efficient markets hypothesis * technical trading rules * heterogeneous agent model with memory and learning Subject RIV: AH - Economics

  9. Modeling single versus multiple systems in implicit and explicit memory.

    Science.gov (United States)

    Starns, Jeffrey J; Ratcliff, Roger; McKoon, Gail

    2012-04-01

    It is currently controversial whether priming on implicit tasks and discrimination on explicit recognition tests are supported by a single memory system or by multiple, independent systems. In a Psychological Review article, Berry and colleagues used mathematical modeling to address this question and provide compelling evidence against the independent-systems approach. Copyright © 2012 Elsevier Ltd. All rights reserved.

  10. A three-dimensional constitutive model for shape memory alloy

    International Nuclear Information System (INIS)

    Zhou, Bo; Yoon, Sung-Ho; Leng, Jin-Song

    2009-01-01

    Shape memory alloy (SMA) has a wide variety of practical applications due to its unique super-elasticity and shape memory effect. It is of practical interest to establish a constitutive model which predicts its phase transformation and mechanical behaviors. In this paper, a new three-dimensional phase transformation equation, which predicts the phase transformation behaviors of SMA, is developed based on the results of a differential scanning calorimetry (DSC) test. It overcomes both limitations: that Zhou's phase transformation equations fail to describe the phase transformation from twinned martensite to detwinned martensite of SMA and Brinson's phase transformation equation fails to express the influences of phase transformation peak temperatures on the phase transformation behaviors of SMA. A new three-dimensional constitutive equation, which predicts the mechanical behaviors associated with the super-elasticity and shape memory effect of SMA, is developed on the basis of thermodynamics and solid mechanics. Results of numerical simulations show that the new constitutive model, which includes the new phase transformation equation and constitutive equation, can predict the phase transformation and mechanical behaviors associated with the super-elasticity and shape memory effect of SMA precisely and comprehensively. It is proved that Brinson's constitutive model of SMA can be considered as one special case of the new constitutive model

  11. Polynomial constitutive model for shape memory and pseudo elasticity

    International Nuclear Information System (INIS)

    Savi, M.A.; Kouzak, Z.

    1995-01-01

    This paper reports an one-dimensional phenomenological constitutive model for shape memory and pseudo elasticity using a polynomial expression for the free energy which is based on the classical Devonshire theory. This study identifies the main characteristics of the classical theory and introduces a simple modification to obtain better results. (author). 9 refs., 6 figs

  12. A thermodynamically consistent model of shape-memory alloys

    Czech Academy of Sciences Publication Activity Database

    Benešová, Barbora

    2011-01-01

    Roč. 11, č. 1 (2011), s. 355-356 ISSN 1617-7061 R&D Projects: GA ČR GAP201/10/0357 Institutional research plan: CEZ:AV0Z20760514 Keywords : slape memory alloys * model based on relaxation * thermomechanic coupling Subject RIV: BA - General Mathematics http://onlinelibrary.wiley.com/doi/10.1002/pamm.201110169/abstract

  13. Modelling Long Memory Volatility in Agricultural Commodity Futures Returns

    NARCIS (Netherlands)

    R. Tansuchat (Roengchai); C-L. Chang (Chia-Lin); M.J. McAleer (Michael)

    2009-01-01

    textabstractThis paper estimates the long memory volatility model for 16 agricultural commodity futures returns from different futures markets, namely corn, oats, soybeans, soybean meal, soybean oil, wheat, live cattle, cattle feeder, pork, cocoa, coffee, cotton, orange juice, Kansas City wheat,

  14. Modelling Long Memory Volatility in Agricultural Commodity Futures Returns

    NARCIS (Netherlands)

    C-L. Chang (Chia-Lin); M.J. McAleer (Michael); R. Tansuchat (Roengchai)

    2012-01-01

    textabstractThis paper estimates a long memory volatility model for 16 agricultural commodity futures returns from different futures markets, namely corn, oats, soybeans, soybean meal, soybean oil, wheat, live cattle, cattle feeder, pork, cocoa, coffee, cotton, orange juice, Kansas City wheat,

  15. Thermomechanical model for NiTi shape memory wires

    International Nuclear Information System (INIS)

    Frost, M; Sedlák, P; Sippola, M; Šittner, P

    2010-01-01

    A simple one-dimensional rate-independent model is proposed. It is able to capture responses of a NiTi shape memory alloy wire element to mechanical and thermal loadings. Since the model takes into account martensitic phase transformation as well as deformation processes in the martensite, both shape memory effects and pseudoelasticity can be simulated. The model introduces non-hysteretic transformation strain. Particular attention was paid to description of partial loading cycles. By changing the input parameters the model can be adapted to various types of NiTi-based materials. The model was implemented in the finite element code Abaqus as a User routine and several simulations were performed to validate the implementation

  16. The Lévy flight foraging hypothesis: forgetting about memory may lead to false verification of Brownian motion.

    Science.gov (United States)

    Gautestad, Arild O; Mysterud, Atle

    2013-01-01

    The Lévy flight foraging hypothesis predicts a transition from scale-free Lévy walk (LW) to scale-specific Brownian motion (BM) as an animal moves from resource-poor towards resource-rich environment. However, the LW-BM continuum implies a premise of memory-less search, which contradicts the cognitive capacity of vertebrates. We describe methods to test if apparent support for LW-BM transitions may rather be a statistical artifact from movement under varying intensity of site fidelity. A higher frequency of returns to previously visited patches (stronger site fidelity) may erroneously be interpreted as a switch from LW towards BM. Simulations of scale-free, memory-enhanced space use illustrate how the ratio between return events and scale-free exploratory movement translates to varying strength of site fidelity. An expanded analysis of GPS data of 18 female red deer, Cervus elaphus, strengthens previous empirical support of memory-enhanced and scale-free space use in a northern forest ecosystem. A statistical mechanical model architecture that describes foraging under environment-dependent variation of site fidelity may allow for higher realism of optimal search models and movement ecology in general, in particular for vertebrates with high cognitive capacity.

  17. Thermodynamic modelling of shape memory behaviour: some examples

    International Nuclear Information System (INIS)

    Stalmans, R.; Humbeeck, J. van; Delaey, L.

    1995-01-01

    This paper gives a general view of a recently developed thermodynamic model of the thermoelastic martensitic transformation. Unlike existing empirical, mathematical or thermodynamic models, this generalised thermodynamic model can be used to understand and describe quantitatively the overall thermomechanical behaviour of polycrystalline shape memory alloys. Important points of difference between this and previous thermodynamic models are that the contributions of the stored elastic energy and of the crystal defects are also included. In addition, the mathematical approach and the assumptions in this model are selected in such a way that the calculations yield close approximations of the real behaviour and that the final mathematical equations are relatively simple. Several illustrations indicate that this model, in contrast to other models, can be used to understand the shape memory behaviour of complex cases. As an example of quantitative calculations, it is shown that this modelling can be an effective tool in the ''design'' of multifunctional materials consisting of shape memory elements embedded in matrix materials. (orig.)

  18. A Neuroanatomical Model of Prefrontal Inhibitory Modulation of Memory Retrieval

    Science.gov (United States)

    Depue, Brendan E.

    2012-01-01

    Memory of past experience is essential for guiding goal-related behavior. Being able to control accessibility of memory through modulation of retrieval enables humans to flexibly adapt to their environment. Understanding the specific neural pathways of how this control is achieved has largely eluded cognitive neuroscience. Accordingly, in the current paper I review literature that examines the overt control over retrieval in order to reduce accessibility. I first introduce three hypotheses of inhibition of retrieval. These hypotheses involve: i) attending to other stimuli as a form of diversionary attention, ii) inhibiting the specific individual neural representation of the memory, and iii) inhibiting the hippocampus and retrieval process more generally to prevent reactivation of the representation. I then analyze literature taken from the White Bear Suppression, Directed Forgetting and Think/No-Think tasks to provide evidence for these hypotheses. Finally, a neuroanatomical model is developed to indicate three pathways from PFC to the hippocampal complex that support inhibition of memory retrieval. Describing these neural pathways increases our understanding of control over memory in general. PMID:22374224

  19. Modeling the behaviour of shape memory materials under large deformations

    Science.gov (United States)

    Rogovoy, A. A.; Stolbova, O. S.

    2017-06-01

    In this study, the models describing the behavior of shape memory alloys, ferromagnetic materials and polymers have been constructed, using a formalized approach to develop the constitutive equations for complex media under large deformations. The kinematic and constitutive equations, satisfying the principles of thermodynamics and objectivity, have been derived. The application of the Galerkin procedure to the systems of equations of solid mechanics allowed us to obtain the Lagrange variational equation and variational formulation of the magnetostatics problems. These relations have been tested in the context of the problems of finite deformation in shape memory alloys and ferromagnetic materials during forward and reverse martensitic transformations and in shape memory polymers during forward and reverse relaxation transitions from a highly elastic to a glassy state.

  20. First Principles Modelling of Shape Memory Alloys Molecular Dynamics Simulations

    CERN Document Server

    Kastner, Oliver

    2012-01-01

    Materials sciences relate the macroscopic properties of materials to their microscopic structure and postulate the need for holistic multiscale research. The investigation of shape memory alloys is a prime example in this regard. This particular class of materials exhibits strong coupling of temperature, strain and stress, determined by solid state phase transformations of their metallic lattices. The present book presents a collection of simulation studies of this behaviour. Employing conceptually simple but comprehensive models, the fundamental material properties of shape memory alloys are qualitatively explained from first principles. Using contemporary methods of molecular dynamics simulation experiments, it is shown how microscale dynamics may produce characteristic macroscopic material properties. The work is rooted in the materials sciences of shape memory alloys and  covers  thermodynamical, micro-mechanical  and crystallographical aspects. It addresses scientists in these research fields and thei...

  1. Development of an engineering model for ferromagnetic shape memory alloys

    International Nuclear Information System (INIS)

    Tani, Yoshiaki; Todaka, Takashi; Enokizono, Masato

    2008-01-01

    This paper presents a relationship among stress, temperature and magnetic properties of a ferromagnetic shape memory alloy. In order to derive an engineering model of ferromagnetic shape memory alloys, we have developed a measuring system of the relationship among stress, temperature and magnetic properties. The samples used in this measurement are Fe68-Ni10-Cr9-Mn7-Si6 wt% ferromagnetic shape memory alloy. They are thin ribbons made by rapid cooling in air. In the measurement, the ribbon sample is inserted into a sample holder winding consisting of the B-coil and compensation coils, and magnetized in an open solenoid coil. The ribbon is stressed with attachment weights and heated with a heating wire. The specific susceptibility was increased by applying tension, and slightly increased by heating below the Curie temperature

  2. Towards Modeling False Memory With Computational Knowledge Bases.

    Science.gov (United States)

    Li, Justin; Kohanyi, Emma

    2017-01-01

    One challenge to creating realistic cognitive models of memory is the inability to account for the vast common-sense knowledge of human participants. Large computational knowledge bases such as WordNet and DBpedia may offer a solution to this problem but may pose other challenges. This paper explores some of these difficulties through a semantic network spreading activation model of the Deese-Roediger-McDermott false memory task. In three experiments, we show that these knowledge bases only capture a subset of human associations, while irrelevant information introduces noise and makes efficient modeling difficult. We conclude that the contents of these knowledge bases must be augmented and, more important, that the algorithms must be refined and optimized, before large knowledge bases can be widely used for cognitive modeling. Copyright © 2016 Cognitive Science Society, Inc.

  3. Calibration of Chaboche Model with a Memory Surface

    Directory of Open Access Journals (Sweden)

    Radim HALAMA

    2013-06-01

    Full Text Available This paper points out a sufficient description of the stress-strain behaviour of the Chaboche nonlinear kinematic hardening model only for materials with the Masing's behaviour, regardless of the number of backstress parts. Subsequently, there are presented two concepts of most widely used memory surfaces: Jiang-Sehitoglu concept (deviatoric plane and Chaboche concept (strain-space. On the base of experimental data of steel ST52 is then shown the possibility of capturing hysteresis loops and cyclic strain curve simultaneously in the usual range for low cycle fatigue calculations. A new model for cyclic hardening/softening behaviour modeling has been also developed based on the Jiang-Sehitoglu memory surface concept. Finally, there are formulated some recommendations for the use of individual models and the direction of further research in conclusions.

  4. Parameters affecting the resilience of scale-free networks to random failures.

    Energy Technology Data Exchange (ETDEWEB)

    Link, Hamilton E.; LaViolette, Randall A.; Lane, Terran (University of New Mexico, Albuquerque, NM); Saia, Jared (University of New Mexico, Albuquerque, NM)

    2005-09-01

    It is commonly believed that scale-free networks are robust to massive numbers of random node deletions. For example, Cohen et al. in (1) study scale-free networks including some which approximate the measured degree distribution of the Internet. Their results suggest that if each node in this network failed independently with probability 0.99, most of the remaining nodes would still be connected in a giant component. In this paper, we show that a large and important subclass of scale-free networks are not robust to massive numbers of random node deletions. In particular, we study scale-free networks which have minimum node degree of 1 and a power-law degree distribution beginning with nodes of degree 1 (power-law networks). We show that, in a power-law network approximating the Internet's reported distribution, when the probability of deletion of each node is 0.5 only about 25% of the surviving nodes in the network remain connected in a giant component, and the giant component does not persist beyond a critical failure rate of 0.9. The new result is partially due to improved analytical accommodation of the large number of degree-0 nodes that result after node deletions. Our results apply to power-law networks with a wide range of power-law exponents, including Internet-like networks. We give both analytical and empirical evidence that such networks are not generally robust to massive random node deletions.

  5. Some scale-free networks could be robust under selective node attacks

    Science.gov (United States)

    Zheng, Bojin; Huang, Dan; Li, Deyi; Chen, Guisheng; Lan, Wenfei

    2011-04-01

    It is a mainstream idea that scale-free network would be fragile under the selective attacks. Internet is a typical scale-free network in the real world, but it never collapses under the selective attacks of computer viruses and hackers. This phenomenon is different from the deduction of the idea above because this idea assumes the same cost to delete an arbitrary node. Hence this paper discusses the behaviors of the scale-free network under the selective node attack with different cost. Through the experiments on five complex networks, we show that the scale-free network is possibly robust under the selective node attacks; furthermore, the more compact the network is, and the larger the average degree is, then the more robust the network is; with the same average degrees, the more compact the network is, the more robust the network is. This result would enrich the theory of the invulnerability of the network, and can be used to build robust social, technological and biological networks, and also has the potential to find the target of drugs.

  6. Emergence of super cooperation of prisoner's dilemma games on scale-free networks.

    Directory of Open Access Journals (Sweden)

    Angsheng Li

    Full Text Available Recently, the authors proposed a quantum prisoner's dilemma game based on the spatial game of Nowak and May, and showed that the game can be played classically. By using this idea, we proposed three generalized prisoner's dilemma (GPD, for short games based on the weak Prisoner's dilemma game, the full prisoner's dilemma game and the normalized Prisoner's dilemma game, written by GPDW, GPDF and GPDN respectively. Our games consist of two players, each of which has three strategies: cooperator (C, defector (D and super cooperator (denoted by Q, and have a parameter γ to measure the entangled relationship between the two players. We found that our generalised prisoner's dilemma games have new Nash equilibrium principles, that entanglement is the principle of emergence and convergence (i.e., guaranteed emergence of super cooperation in evolutions of our generalised prisoner's dilemma games on scale-free networks, that entanglement provides a threshold for a phase transition of super cooperation in evolutions of our generalised prisoner's dilemma games on scale-free networks, that the role of heterogeneity of the scale-free networks in cooperations and super cooperations is very limited, and that well-defined structures of scale-free networks allow coexistence of cooperators and super cooperators in the evolutions of the weak version of our generalised prisoner's dilemma games.

  7. The Mathematics of Networks Science: Scale-Free, Power-Law Graphs and Continuum Theoretical Analysis

    Science.gov (United States)

    Padula, Janice

    2012-01-01

    When hoping to initiate or sustain students' interest in mathematics teachers should always consider relevance, relevance to students' lives and in the middle and later years of instruction in high school and university, accessibility. A topic such as the mathematics behind networks science, more specifically scale-free graphs, is up-to-date,…

  8. Betweenness-based algorithm for a partition scale-free graph

    International Nuclear Information System (INIS)

    Zhang Bai-Da; Wu Jun-Jie; Zhou Jing; Tang Yu-Hua

    2011-01-01

    Many real-world networks are found to be scale-free. However, graph partition technology, as a technology capable of parallel computing, performs poorly when scale-free graphs are provided. The reason for this is that traditional partitioning algorithms are designed for random networks and regular networks, rather than for scale-free networks. Multilevel graph-partitioning algorithms are currently considered to be the state of the art and are used extensively. In this paper, we analyse the reasons why traditional multilevel graph-partitioning algorithms perform poorly and present a new multilevel graph-partitioning paradigm, top down partitioning, which derives its name from the comparison with the traditional bottom—up partitioning. A new multilevel partitioning algorithm, named betweenness-based partitioning algorithm, is also presented as an implementation of top—down partitioning paradigm. An experimental evaluation of seven different real-world scale-free networks shows that the betweenness-based partitioning algorithm significantly outperforms the existing state-of-the-art approaches. (interdisciplinary physics and related areas of science and technology)

  9. Orthodontic applications of a superelastic shape-memory alloy model

    International Nuclear Information System (INIS)

    Glendenning, R.W.; Enlow, R.L.

    2000-01-01

    During orthodontic treatment, dental appliances (braces) made of shape memory alloys have the potential to provide nearly uniform low level stresses to dentitions during tooth movement over a large range of tooth displacement. In this paper we model superelastic behaviour of dental appliances using the finite element method and constitutive equations developed by F. Auricchio et al. Results of the mathematical model for 3-point bending and several promising 'closing loop' designs are compared with laboratory results for the same configurations. (orig.)

  10. Global forward-predicting dynamic routing for traffic concurrency space stereo multi-layer scale-free network

    International Nuclear Information System (INIS)

    Xie Wei-Hao; Zhou Bin; Liu En-Xiao; Lu Wei-Dang; Zhou Ting

    2015-01-01

    Many real communication networks, such as oceanic monitoring network and land environment observation network, can be described as space stereo multi-layer structure, and the traffic in these networks is concurrent. Understanding how traffic dynamics depend on these real communication networks and finding an effective routing strategy that can fit the circumstance of traffic concurrency and enhance the network performance are necessary. In this light, we propose a traffic model for space stereo multi-layer complex network and introduce two kinds of global forward-predicting dynamic routing strategies, global forward-predicting hybrid minimum queue (HMQ) routing strategy and global forward-predicting hybrid minimum degree and queue (HMDQ) routing strategy, for traffic concurrency space stereo multi-layer scale-free networks. By applying forward-predicting strategy, the proposed routing strategies achieve better performances in traffic concurrency space stereo multi-layer scale-free networks. Compared with the efficient routing strategy and global dynamic routing strategy, HMDQ and HMQ routing strategies can optimize the traffic distribution, alleviate the number of congested packets effectively and reach much higher network capacity. (paper)

  11. Memory and learning in a class of neural network models

    International Nuclear Information System (INIS)

    Wallace, D.J.

    1986-01-01

    The author discusses memory and learning properties of the neural network model now identified with Hopfield's work. The model, how it attempts to abstract some key features of the nervous system, and the sense in which learning and memory are identified in the model are described. A brief report is presented on the important role of phase transitions in the model and their implications for memory capacity. The results of numerical simulations obtained using the ICL Distributed Array Processors at Edinburgh are presented. A summary is presented on how the fraction of images which are perfectly stored, depends on the number of nodes and the number of nominal images which one attempts to store using the prescription in Hopfield's paper. Results are presented on the second phase transition in the model, which corresponds to almost total loss of storage capacity as the number of nominal images is increased. Results are given on the performance of a new iterative algorithm for exact storage of up to N images in an N node model

  12. Cosmological Simulations with Scale-Free Initial Conditions. I. Adiabatic Hydrodynamics

    International Nuclear Information System (INIS)

    Owen, J.M.; Weinberg, D.H.; Evrard, A.E.; Hernquist, L.; Katz, N.

    1998-01-01

    We analyze hierarchical structure formation based on scale-free initial conditions in an Einstein endash de Sitter universe, including a baryonic component with Ω bary = 0.05. We present three independent, smoothed particle hydrodynamics (SPH) simulations, performed at two resolutions (32 3 and 64 3 dark matter and baryonic particles) and with two different SPH codes (TreeSPH and P3MSPH). Each simulation is based on identical initial conditions, which consist of Gaussian-distributed initial density fluctuations that have a power spectrum P(k) ∝ k -1 . The baryonic material is modeled as an ideal gas subject only to shock heating and adiabatic heating and cooling; radiative cooling and photoionization heating are not included. The evolution is expected to be self-similar in time, and under certain restrictions we identify the expected scalings for many properties of the distribution of collapsed objects in all three realizations. The distributions of dark matter masses, baryon masses, and mass- and emission-weighted temperatures scale quite reliably. However, the density estimates in the central regions of these structures are determined by the degree of numerical resolution. As a result, mean gas densities and Bremsstrahlung luminosities obey the expected scalings only when calculated within a limited dynamic range in density contrast. The temperatures and luminosities of the groups show tight correlations with the baryon masses, which we find can be well represented by power laws. The Press-Schechter (PS) approximation predicts the distribution of group dark matter and baryon masses fairly well, though it tends to overestimate the baryon masses. Combining the PS mass distribution with the measured relations for T(M) and L(M) predicts the temperature and luminosity distributions fairly accurately, though there are some discrepancies at high temperatures/luminosities. In general the three simulations agree well for the properties of resolved groups, where a group

  13. Characterization of scale-free properties of human electrocorticography in awake and slow wave sleep states

    Directory of Open Access Journals (Sweden)

    John M Zempel

    2012-06-01

    Full Text Available Like many complex dynamic systems, the brain exhibits scale-free dynamics that follow power law scaling. Broadband power spectral density (PSD of brain electrical activity exhibits state-dependent power law scaling with a log frequency exponent that varies across frequency ranges. Widely divergent naturally occurring neural states, awake and slow wave sleep (SWS periods, were used evaluate the nature of changes in scale-free indices. We demonstrate two analytic approaches to characterizing electrocorticographic (ECoG data obtained during Awake and SWS states. A data driven approach was used, characterizing all available frequency ranges. Using an Equal Error State Discriminator (EESD, a single frequency range did not best characterize state across data from all six subjects, though the ability to distinguish awake and SWS states in individual subjects was excellent. Multisegment piecewise linear fits were used to characterize scale-free slopes across the entire frequency range (0.2-200 Hz. These scale-free slopes differed between Awake and SWS states across subjects, particularly at frequencies below 10 Hz and showed little difference at frequencies above 70 Hz. A Multivariate Maximum Likelihood Analysis (MMLA method using the multisegment slope indices successfully categorized ECoG data in most subjects, though individual variation was seen. The ECoG spectrum is not well characterized by a single linear fit across a defined set of frequencies, but is best described by a set of discrete linear fits across the full range of available frequencies. With increasing computational tractability, the use of scale-free slope values to characterize EEG data will have practical value in clinical and research EEG studies.

  14. Interference in memory for tonal pitch: implications for a working-memory model.

    Science.gov (United States)

    Pechmann, T; Mohr, G

    1992-05-01

    The degree of interference caused by different kinds of stimuli on memory for tonal pitch was studied. Musically trained and untrained subjects heard a sequence of two tones separated by an interval of 5 sec. The tones were either identical in pitch or differed by a semitone. Subjects had to decide whether the tones were identical or not. The interval was filled with tonal, verbal, or visual material under attended and unattended conditions. The results revealed clear group differences. Musically trained subjects' retention of the first test tone was only affected by the interposition of other tones. In contrast, the performance of musically untrained subjects was also affected by verbal and visual items. The findings are discussed in the framework of Baddeley's (1986) working-memory model.

  15. Physicochemical analog for modeling superimposed and coded memories

    Science.gov (United States)

    Ensanian, Minas

    1992-07-01

    The mammalian brain is distinguished by a life-time of memories being stored within the same general region of physicochemical space, and having two extraordinary features. First, memories to varying degrees are superimposed, as well as coded. Second, instantaneous recall of past events can often be affected by relatively simple, and seemingly unrelated sensory clues. For the purposes of attempting to mathematically model such complex behavior, and for gaining additional insights, it would be highly advantageous to be able to simulate or mimic similar behavior in a nonbiological entity where some analogical parameters of interest can reasonably be controlled. It has recently been discovered that in nonlinear accumulative metal fatigue memories (related to mechanical deformation) can be superimposed and coded in the crystal lattice, and that memory, that is, the total number of stress cycles can be recalled (determined) by scanning not the surfaces but the `edges' of the objects. The new scanning technique known as electrotopography (ETG) now makes the state space modeling of metallic networks possible. The author provides an overview of the new field and outlines the areas that are of immediate interest to the science of artificial neural networks.

  16. Computational Model-Based Prediction of Human Episodic Memory Performance Based on Eye Movements

    Science.gov (United States)

    Sato, Naoyuki; Yamaguchi, Yoko

    Subjects' episodic memory performance is not simply reflected by eye movements. We use a ‘theta phase coding’ model of the hippocampus to predict subjects' memory performance from their eye movements. Results demonstrate the ability of the model to predict subjects' memory performance. These studies provide a novel approach to computational modeling in the human-machine interface.

  17. Effect of quantum learning model in improving creativity and memory

    Science.gov (United States)

    Sujatmika, S.; Hasanah, D.; Hakim, L. L.

    2018-04-01

    Quantum learning is a combination of many interactions that exist during learning. This model can be applied by current interesting topic, contextual, repetitive, and give opportunities to students to demonstrate their abilities. The basis of the quantum learning model are left brain theory, right brain theory, triune, visual, auditorial, kinesthetic, game, symbol, holistic, and experiential learning theory. Creativity plays an important role to be success in the working world. Creativity shows alternatives way to problem-solving or creates something. Good memory plays a role in the success of learning. Through quantum learning, students will use all of their abilities, interested in learning and create their own ways of memorizing concepts of the material being studied. From this idea, researchers assume that quantum learning models can improve creativity and memory of the students.

  18. Generalized transport model for phase transition with memory

    International Nuclear Information System (INIS)

    Chen, Chi; Ciucci, Francesco

    2013-01-01

    A general model for phenomenological transport in phase transition is derived, which extends Jäckle and Frisch model of phase transition with memory and the Cahn–Hilliard model. In addition to including interfacial energy to account for the presence of interfaces, we introduce viscosity and relaxation contributions, which result from incorporating memory effect into the driving potential. Our simulation results show that even without interfacial energy term, the viscous term can lead to transient diffuse interfaces. From the phase transition induced hysteresis, we discover different energy dissipation mechanism for the interfacial energy and the viscosity effect. In addition, by combining viscosity and interfacial energy, we find that if the former dominates, then the concentration difference across the phase boundary is reduced; conversely, if the interfacial energy is greater then this difference is enlarged.

  19. On a Model of Associative Memory with Huge Storage Capacity

    Science.gov (United States)

    Demircigil, Mete; Heusel, Judith; Löwe, Matthias; Upgang, Sven; Vermet, Franck

    2017-07-01

    In Krotov et al. (in: Lee (eds) Advances in Neural Information Processing Systems, Curran Associates, Inc., Red Hook, 2016) Krotov and Hopfield suggest a generalized version of the well-known Hopfield model of associative memory. In their version they consider a polynomial interaction function and claim that this increases the storage capacity of the model. We prove this claim and take the "limit" as the degree of the polynomial becomes infinite, i.e. an exponential interaction function. With this interaction we prove that model has an exponential storage capacity in the number of neurons, yet the basins of attraction are almost as large as in the standard Hopfield model.

  20. Irrelevant sensory stimuli interfere with working memory storage: evidence from a computational model of prefrontal neurons.

    Science.gov (United States)

    Bancroft, Tyler D; Hockley, William E; Servos, Philip

    2013-03-01

    The encoding of irrelevant stimuli into the memory store has previously been suggested as a mechanism of interference in working memory (e.g., Lange & Oberauer, Memory, 13, 333-339, 2005; Nairne, Memory & Cognition, 18, 251-269, 1990). Recently, Bancroft and Servos (Experimental Brain Research, 208, 529-532, 2011) used a tactile working memory task to provide experimental evidence that irrelevant stimuli were, in fact, encoded into working memory. In the present study, we replicated Bancroft and Servos's experimental findings using a biologically based computational model of prefrontal neurons, providing a neurocomputational model of overwriting in working memory. Furthermore, our modeling results show that inhibition acts to protect the contents of working memory, and they suggest a need for further experimental research into the capacity of vibrotactile working memory.

  1. Thermoregulatory model of sleep control: losing the heat memory.

    Science.gov (United States)

    Nakao, M; McGinty, D; Szymusiak, R; Yamamoto, M

    1999-12-01

    Thermoregulatory mechanisms were hypothesized to provide primary control of non-rapid-eye-movement sleep (NREM). On the basis of this hypothesis, we incorporated the thermoregulatory feedback loops mediated by the "heat memory," heat load, and loss processes associated with sleep-wake cycles, which were modulated by two circadian oscillators. In addition, hypnogenic warm-sensitive neurons (HWSNs) were assumed to integrate thermoregulation and NREM control. The heat memory described above could be mediated by some sleep-promoting substances. In this paper, considering the possible carrier of the heat memory, its losing process is newly included in the model. The newly developed model can generate the appropriate features of human sleep-wake patterns. One of the special features of the model is to generate the bimodal distribution of the sleepiness. This bimodality becomes distinct, as the losing rate of the heat memory decreases or the amplitude of the Y oscillator increases. The theoretical analysis shows the losing rate of the heat memory control's rapidity of model response to a thermal perturbation, which is confirmed by simulating the responses with various losing rates to transient heat loads ("heat load pulse"). The sleepiness exhibits large responses to the heat load pulses applied in the early and late phases of wake period, while the response is significantly reduced to the pulse applied in the supposed wake-maintenance zone. This bimodality of the response appears to reflect the sensitivity of the HWSNs. In addition, the early pulse raises the immediate sleepiness rather than the nocturnal sleepiness, while the heat load pulse applied in the later phase of waking period significantly raises the sleepiness during a nocturnal sleep. In simulations of sleep deprivation, the discontinuous relationship between recovery sleep length and deprivation time is reproduced, where the critical sleep deprivation time at which the recovery sleep length jumps is extended

  2. Multiple Memory Systems Are Unnecessary to Account for Infant Memory Development: An Ecological Model

    Science.gov (United States)

    Rovee-Collier, Carolyn; Cuevas, Kimberly

    2009-01-01

    How the memory of adults evolves from the memory abilities of infants is a central problem in cognitive development. The popular solution holds that the multiple memory systems of adults mature at different rates during infancy. The "early-maturing system" (implicit or nondeclarative memory) functions automatically from birth, whereas the…

  3. Memory

    OpenAIRE

    Wager, Nadia

    2017-01-01

    This chapter will explore a response to traumatic victimisation which has divided the opinions of psychologists at an exponential rate. We will be examining amnesia for memories of childhood sexual abuse and the potential to recover these memories in adulthood. Whilst this phenomenon is generally accepted in clinical circles, it is seen as highly contentious amongst research psychologists, particularly experimental cognitive psychologists. The chapter will begin with a real case study of a wo...

  4. The storage capacity of Potts models for semantic memory retrieval

    Science.gov (United States)

    Kropff, Emilio; Treves, Alessandro

    2005-08-01

    We introduce and analyse a minimal network model of semantic memory in the human brain. The model is a global associative memory structured as a collection of N local modules, each coding a feature, which can take S possible values, with a global sparseness a (the average fraction of features describing a concept). We show that, under optimal conditions, the number cM of modules connected on average to a module can range widely between very sparse connectivity (high dilution, c_{M}/N\\to 0 ) and full connectivity (c_{M}\\to N ), maintaining a global network storage capacity (the maximum number pc of stored and retrievable concepts) that scales like pc~cMS2/a, with logarithmic corrections consistent with the constraint that each synapse may store up to a fraction of a bit.

  5. Alternative conceptions, memory, & mental models in physics education

    Science.gov (United States)

    Lee, Gyoungho; Shin, Jongho; Park, Jiyeon; Song, Sangho; Kim, Yeounsoo; Bao, Lei

    2005-09-01

    There are two somewhat independent research traditions, which converge to suggest a form of students' knowledge: alternative conceptions and mental models. However we have little literature that explains what they are different from each other and from memory. This study tried to describe these issues with some thoughts about how cognitive psychology and science education approaches can be best synthesized in order to approach these questions.

  6. A macroscopic model for magnetic shape-memory single crystals

    Czech Academy of Sciences Publication Activity Database

    Bessoud, A. L.; Kružík, Martin; Stefanelli, U.

    2013-01-01

    Roč. 64, č. 2 (2013), s. 343-359 ISSN 0044-2275 R&D Projects: GA AV ČR IAA100750802; GA ČR GAP201/10/0357 Institutional support: RVO:67985556 Keywords : magnetostriction * evolution Subject RIV: BA - General Mathematics Impact factor: 1.214, year: 2013 http://library.utia.cas.cz/separaty/2012/MTR/kruzik-a macroscopic model for magnetic shape- memory single crystals.pdf

  7. A Bayesian Model of the Memory Colour Effect

    OpenAIRE

    Witzel, Christoph; Olkkonen, Maria; Gegenfurtner, Karl R.

    2018-01-01

    According to the memory colour effect, the colour of a colour-diagnostic object is not perceived independently of the object itself. Instead, it has been shown through an achromatic adjustment method that colour-diagnostic objects still appear slightly in their typical colour, even when they are colourimetrically grey. Bayesian models provide a promising approach to capture the effect of prior knowledge on colour perception and to link these effects to more general effects of cue integration....

  8. A Bayesian model of the memory colour effect.

    OpenAIRE

    Witzel, Christoph; Olkkonen, Maria; Gegenfurtner, Karl R.

    2018-01-01

    According to the memory colour effect, the colour of a colour-diagnostic object is not perceived independently of the object itself. Instead, it has been shown through an achromatic adjustment method that colour-diagnostic objects still appear slightly in their typical colour, even when they are colourimetrically grey. Bayesian models provide a promising approach to capture the effect of prior knowledge on colour perception and to link these effects to more general effects of cue integration....

  9. Acute effects of alcohol on intrusive memory development and viewpoint dependence in spatial memory support a dual representation model.

    Science.gov (United States)

    Bisby, James A; King, John A; Brewin, Chris R; Burgess, Neil; Curran, H Valerie

    2010-08-01

    A dual representation model of intrusive memory proposes that personally experienced events give rise to two types of representation: an image-based, egocentric representation based on sensory-perceptual features; and a more abstract, allocentric representation that incorporates spatiotemporal context. The model proposes that intrusions reflect involuntary reactivation of egocentric representations in the absence of a corresponding allocentric representation. We tested the model by investigating the effect of alcohol on intrusive memories and, concurrently, on egocentric and allocentric spatial memory. With a double-blind independent group design participants were administered alcohol (.4 or .8 g/kg) or placebo. A virtual environment was used to present objects and test recognition memory from the same viewpoint as presentation (tapping egocentric memory) or a shifted viewpoint (tapping allocentric memory). Participants were also exposed to a trauma video and required to detail intrusive memories for 7 days, after which explicit memory was assessed. There was a selective impairment of shifted-view recognition after the low dose of alcohol, whereas the high dose induced a global impairment in same-view and shifted-view conditions. Alcohol showed a dose-dependent inverted "U"-shaped effect on intrusions, with only the low dose increasing the number of intrusions, replicating previous work. When same-view recognition was intact, decrements in shifted-view recognition were associated with increases in intrusions. The differential effect of alcohol on intrusive memories and on same/shifted-view recognition support a dual representation model in which intrusions might reflect an imbalance between two types of memory representation. These findings highlight important clinical implications, given alcohol's involvement in real-life trauma. Copyright 2010 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  10. A memory-based model of posttraumatic stress disorder

    DEFF Research Database (Denmark)

    Rubin, David C.; Berntsen, Dorthe; Johansen, Marlene Klindt

    2008-01-01

    In the mnemonic model of posttraumatic stress disorder (PTSD), the current memory of a negative event, not the event itself, determines symptoms. The model is an alternative to the current event-based etiology of PTSD represented in the Diagnostic and Statistical Manual of Mental Disorders (4th ed......., text rev.; American Psychiatric Association, 2000). The model accounts for important and reliable findings that are often inconsistent with the current diagnostic view and that have been neglected by theoretical accounts of the disorder, including the following observations. The diagnosis needs...

  11. Modeling recall memory for emotional objects in Alzheimer's disease.

    Science.gov (United States)

    Sundstrøm, Martin

    2011-07-01

    To examine whether emotional memory (EM) of objects with self-reference in Alzheimer's disease (AD) can be modeled with binomial logistic regression in a free recall and an object recognition test to predict EM enhancement. Twenty patients with AD and twenty healthy controls were studied. Six objects (three presented as gifts) were shown to each participant. Ten minutes later, a free recall and a recognition test were applied. The recognition test had target-objects mixed with six similar distracter objects. Participants were asked to name any object in the recall test and identify each object in the recognition test as known or unknown. The total of gift objects recalled in AD patients (41.6%) was larger than neutral objects (13.3%) and a significant EM recall effect for gifts was found (Wilcoxon: p recall and recognition but showed no EM enhancement due to a ceiling effect. A logistic regression showed that likelihood of emotional recall memory can be modeled as a function of MMSE score (p Recall memory was enhanced in AD patients for emotional objects indicating that EM in mild to moderate AD although impaired can be provoked with strong emotional load. The logistic regression model suggests that EM declines with the progression of AD rather than disrupts and may be a useful tool for evaluating magnitude of emotional load.

  12. A Probabilistic Palimpsest Model of Visual Short-term Memory

    Science.gov (United States)

    Matthey, Loic; Bays, Paul M.; Dayan, Peter

    2015-01-01

    Working memory plays a key role in cognition, and yet its mechanisms remain much debated. Human performance on memory tasks is severely limited; however, the two major classes of theory explaining the limits leave open questions about key issues such as how multiple simultaneously-represented items can be distinguished. We propose a palimpsest model, with the occurrent activity of a single population of neurons coding for several multi-featured items. Using a probabilistic approach to storage and recall, we show how this model can account for many qualitative aspects of existing experimental data. In our account, the underlying nature of a memory item depends entirely on the characteristics of the population representation, and we provide analytical and numerical insights into critical issues such as multiplicity and binding. We consider representations in which information about individual feature values is partially separate from the information about binding that creates single items out of multiple features. An appropriate balance between these two types of information is required to capture fully the different types of error seen in human experimental data. Our model provides the first principled account of misbinding errors. We also suggest a specific set of stimuli designed to elucidate the representations that subjects actually employ. PMID:25611204

  13. A heuristic model for working memory deficit in schizophrenia.

    Science.gov (United States)

    Qi, Zhen; Yu, Gina P; Tretter, Felix; Pogarell, Oliver; Grace, Anthony A; Voit, Eberhard O

    2016-11-01

    The life of schizophrenia patients is severely affected by deficits in working memory. In various brain regions, the reciprocal interactions between excitatory glutamatergic neurons and inhibitory GABAergic neurons are crucial. Other neurotransmitters, in particular dopamine, serotonin, acetylcholine, and norepinephrine, modulate the local balance between glutamate and GABA and therefore regulate the function of brain regions. Persistent alterations in the balances between the neurotransmitters can result in working memory deficits. Here we present a heuristic computational model that accounts for interactions among neurotransmitters across various brain regions. The model is based on the concept of a neurochemical interaction matrix at the biochemical level and combines this matrix with a mobile model representing physiological dynamic balances among neurotransmitter systems associated with working memory. The comparison of clinical and simulation results demonstrates that the model output is qualitatively very consistent with the available data. In addition, the model captured how perturbations migrated through different neurotransmitters and brain regions. Results showed that chronic administration of ketamine can cause a variety of imbalances, and application of an antagonist of the D2 receptor in PFC can also induce imbalances but in a very different manner. The heuristic computational model permits a variety of assessments of genetic, biochemical, and pharmacological perturbations and serves as an intuitive tool for explaining clinical and biological observations. The heuristic model is more intuitive than biophysically detailed models. It can serve as an important tool for interdisciplinary communication and even for psychiatric education of patients and relatives. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. The Development of Working Memory: Exploring the Complementarity of Two Models.

    Science.gov (United States)

    Kemps, Eva; De Rammelaere, Stijn; Desmet, Timothy

    2000-01-01

    Assessed 5-, 6-, 8- and 9-year-olds on two working memory tasks to explore the complementarity of working memory models postulated by Pascual-Leone and Baddeley. Pascual-Leone's theory offered a clear explanation of the results concerning central aspects of working memory. Baddeley's model provided a convincing account of findings regarding the…

  15. Inhibiting corticosterone synthesis during fear memory formation exacerbates cued fear extinction memory deficits within the single prolonged stress model.

    Science.gov (United States)

    Keller, Samantha M; Schreiber, William B; Stanfield, Briana R; Knox, Dayan

    2015-01-01

    Using the single prolonged stress (SPS) animal model of post-traumatic stress disorder (PTSD), previous studies suggest that enhanced glucocorticoid receptor (GR) expression leads to cued fear extinction retention deficits. However, it is unknown how the endogenous ligand of GRs, corticosterone (CORT), may contribute to extinction retention deficits in the SPS model. Given that CORT synthesis during fear learning is critical for fear memory consolidation and SPS enhances GR expression, CORT synthesis during fear memory formation could strengthen fear memory in SPS rats by enhancing GR activation during fear learning. In turn, this could lead to cued fear extinction retention deficits. We tested the hypothesis that CORT synthesis during fear learning leads to cued fear extinction retention deficits in SPS rats by administering the CORT synthesis inhibitor metyrapone to SPS and control rats prior to fear conditioning, and observed the effect this had on extinction memory. Inhibiting CORT synthesis during fear memory formation in control rats tended to decrease cued freezing, though this effect never reached statistical significance. Contrary to our hypothesis, inhibiting CORT synthesis during fear memory formation disrupted extinction retention in SPS rats. This finding suggests that even though SPS exposure leads to cued fear extinction memory deficits, CORT synthesis during fear memory formation enhances extinction retention in SPS rats. This suggests that stress-induced CORT synthesis in previously stressed rats can be beneficial. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. Tumour model with intrusive morphology, progressive phenotypical heterogeneity and memory

    Science.gov (United States)

    Atangana, Abdon; Alqahtani, Rubayyi T.

    2018-03-01

    The model of a tumour, taking into account invasive morphology, progressive phenotypical heterogeneity and also memory, is developed and analyzed in this paper. Three models are investigated: first we consider the model describing the proliferation concentrates in proximity of tumour boundaries, in which the oxygen levels are pronounced. Then we consider the model where the oxygen around the tumour is considered to be unchanged by the vascular system. Finally, we investigate the model of growth of tumours using the concept of non-local operators with the Mittag-Leffler kernel. We provide the numerical solution using the extended 3/8 Simpson method for the new trends of fractional integration for the proliferation concentrates in the proximity of the tumour model. Then we provide the exact solutions of the Gompertz model with three different fractional differentiations involving power law, exponential decay law and the Mittag-Leffler law.

  17. Simulating the wealth distribution with a Richest-Following strategy on scale-free network

    Science.gov (United States)

    Hu, Mao-Bin; Jiang, Rui; Wu, Qing-Song; Wu, Yong-Hong

    2007-07-01

    In this paper, we investigate the wealth distribution with agents playing evolutionary games on a scale-free social network adopting the Richest-Following strategy. Pareto's power-law distribution (1897) of wealth is demonstrated with power factor in agreement with that of US or Japan. Moreover, the agent's personal wealth is proportional to its number of contacts (connectivity), and this leads to the phenomenon that the rich gets richer and the poor gets relatively poorer, which agrees with the Matthew Effect.

  18. Trajectory Control of Scale-Free Dynamical Networks with Exogenous Disturbances

    International Nuclear Information System (INIS)

    Yang Hongyong; Zhang Shun; Zong Guangdeng

    2011-01-01

    In this paper, the trajectory control of multi-agent dynamical systems with exogenous disturbances is studied. Suppose multiple agents composing of a scale-free network topology, the performance of rejecting disturbances for the low degree node and high degree node is analyzed. Firstly, the consensus of multi-agent systems without disturbances is studied by designing a pinning control strategy on a part of agents, where this pinning control can bring multiple agents' states to an expected consensus track. Then, the influence of the disturbances is considered by developing disturbance observers, and disturbance observers based control (DOBC) are developed for disturbances generated by an exogenous system to estimate the disturbances. Asymptotical consensus of the multi-agent systems with disturbances under the composite controller can be achieved for scale-free network topology. Finally, by analyzing examples of multi-agent systems with scale-free network topology and exogenous disturbances, the verities of the results are proved. Under the DOBC with the designed parameters, the trajectory convergence of multi-agent systems is researched by pinning two class of the nodes. We have found that it has more stronger robustness to exogenous disturbances for the high degree node pinned than that of the low degree node pinned. (interdisciplinary physics and related areas of science and technology)

  19. Multiple synchronization transitions in scale-free neuronal networks with electrical and chemical hybrid synapses

    International Nuclear Information System (INIS)

    Liu, Chen; Wang, Jiang; Wang, Lin; Yu, Haitao; Deng, Bin; Wei, Xile; Tsang, Kaiming; Chan, Wailok

    2014-01-01

    Highlights: • Synchronization transitions in hybrid scale-free neuronal networks are investigated. • Multiple synchronization transitions can be induced by the time delay. • Effect of synchronization transitions depends on the ratio of the electrical and chemical synapses. • Coupling strength and the density of inter-neuronal links can enhance the synchronization. -- Abstract: The impacts of information transmission delay on the synchronization transitions in scale-free neuronal networks with electrical and chemical hybrid synapses are investigated. Numerical results show that multiple appearances of synchronization regions transitions can be induced by different information transmission delays. With the time delay increasing, the synchronization of neuronal activities can be enhanced or destroyed, irrespective of the probability of chemical synapses in the whole hybrid neuronal network. In particular, for larger probability of electrical synapses, the regions of synchronous activities appear broader with stronger synchronization ability of electrical synapses compared with chemical ones. Moreover, it can be found that increasing the coupling strength can promote synchronization monotonously, playing the similar role of the increasing the probability of the electrical synapses. Interestingly, the structures and parameters of the scale-free neuronal networks, especially the structural evolvement plays a more subtle role in the synchronization transitions. In the network formation process, it is found that every new vertex is attached to the more old vertices already present in the network, the more synchronous activities will be emerge

  20. Modeling aspects of human memory for scientific study.

    Energy Technology Data Exchange (ETDEWEB)

    Caudell, Thomas P. (University of New Mexico); Watson, Patrick (University of Illinois - Champaign-Urbana Beckman Institute); McDaniel, Mark A. (Washington University); Eichenbaum, Howard B. (Boston University); Cohen, Neal J. (University of Illinois - Champaign-Urbana Beckman Institute); Vineyard, Craig Michael; Taylor, Shawn Ellis; Bernard, Michael Lewis; Morrow, James Dan; Verzi, Stephen J.

    2009-10-01

    Working with leading experts in the field of cognitive neuroscience and computational intelligence, SNL has developed a computational architecture that represents neurocognitive mechanisms associated with how humans remember experiences in their past. The architecture represents how knowledge is organized and updated through information from individual experiences (episodes) via the cortical-hippocampal declarative memory system. We compared the simulated behavioral characteristics with those of humans measured under well established experimental standards, controlling for unmodeled aspects of human processing, such as perception. We used this knowledge to create robust simulations of & human memory behaviors that should help move the scientific community closer to understanding how humans remember information. These behaviors were experimentally validated against actual human subjects, which was published. An important outcome of the validation process will be the joining of specific experimental testing procedures from the field of neuroscience with computational representations from the field of cognitive modeling and simulation.

  1. Modeling and Simulation of Elementary Robot Behaviors using Associative Memories

    Directory of Open Access Journals (Sweden)

    Claude F. Touzet

    2006-06-01

    Full Text Available Today, there are several drawbacks that impede the necessary and much needed use of robot learning techniques in real applications. First, the time needed to achieve the synthesis of any behavior is prohibitive. Second, the robot behavior during the learning phase is – by definition – bad, it may even be dangerous. Third, except within the lazy learning approach, a new behavior implies a new learning phase. We propose in this paper to use associative memories (self-organizing maps to encode the non explicit model of the robot-world interaction sampled by the lazy memory, and then generate a robot behavior by means of situations to be achieved, i.e., points on the self-organizing maps. Any behavior can instantaneously be synthesized by the definition of a goal situation. Its performance will be minimal (not necessarily bad and will improve by the mere repetition of the behavior.

  2. Pandemics and immune memory in the noisy Penna model

    Science.gov (United States)

    Cebrat, Stanisław; Bonkowska, Katarzyna; Biecek, Przemysław

    2007-06-01

    In the noisy Penna model of ageing, instead of counting the number of defective loci which eventually kill an individual, the noise describing the health status of individuals is introduced. This white noise is composed of two components: the environmental one and the personal one. If the sum of both trespasses the limit set for the individuals homeodynamics the individual dies. The energy of personal fluctuations depends on the number of defective loci expressed in the individuals genome. Environmental fluctuations, the same for all individuals can include some signals, corresponding to the exposition to pathogens which could be dangerous for a fraction of the organisms. Personal noise and the component of random environmental fluctuations, when superimposed on the signal can be life threatening if they are stronger than the limit set for individuals homeodynamics. Nevertheless, some organisms survive the period of dangerous signal and they may remember the signal in the future, like antigens are remembered by our immune systems. Unfortunately, this memory weakens with time and, even worse, some additional defective genes are switched on during the ageing. If the same pathogens (signals) emerge during the lifespan of the population, a fraction of the population could remember it and could respond by increasing the resistance to it. Again, unfortunately for some individuals, their memory could be too weak and their own health status has worsened due to the accumulated mutations, they have to die. Though, a fraction of individuals can survive the pandemics due to the immune memory, but a fraction of population has no such a memory because they were born after the last pandemic or they didnt notice this pandemic. Our simple model, by implementing the noise instead of deterministic threshold of genetic defects, describes how the impact of pandemics on populations depends on the time which elapsed between the two incidents and how the different age groups of

  3. MULTI: a shared memory approach to cooperative molecular modeling.

    Science.gov (United States)

    Darden, T; Johnson, P; Smith, H

    1991-03-01

    A general purpose molecular modeling system, MULTI, based on the UNIX shared memory and semaphore facilities for interprocess communication is described. In addition to the normal querying or monitoring of geometric data, MULTI also provides processes for manipulating conformations, and for displaying peptide or nucleic acid ribbons, Connolly surfaces, close nonbonded contacts, crystal-symmetry related images, least-squares superpositions, and so forth. This paper outlines the basic techniques used in MULTI to ensure cooperation among these specialized processes, and then describes how they can work together to provide a flexible modeling environment.

  4. Hidden long evolutionary memory in a model biochemical network

    Science.gov (United States)

    Ali, Md. Zulfikar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

    2018-04-01

    We introduce a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational algorithm, and apply the model to study neutral drift in networks that yield oscillatory dynamics. Starting with a functional core module, random evolutionary drift increases network complexity even in the absence of specific selective pressures. Surprisingly, we uncover a hidden order in sequence space that gives rise to long-term evolutionary memory, implying strong constraints on network evolution due to the topology of accessible sequence space.

  5. Orthodontic applications of a superelastic shape-memory alloy model

    Energy Technology Data Exchange (ETDEWEB)

    Glendenning, R.W.; Enlow, R.L. [Otago Univ., Dunedin (New Zealand). Dept. of Math. and Stat.; Hood, J.A.A. [Dept. of Oral Sciences and Orthodontics, Univ. of Otago, Dunedin (New Zealand)

    2000-07-01

    During orthodontic treatment, dental appliances (braces) made of shape memory alloys have the potential to provide nearly uniform low level stresses to dentitions during tooth movement over a large range of tooth displacement. In this paper we model superelastic behaviour of dental appliances using the finite element method and constitutive equations developed by F. Auricchio et al. Results of the mathematical model for 3-point bending and several promising 'closing loop' designs are compared with laboratory results for the same configurations. (orig.)

  6. Fast sparsely synchronized brain rhythms in a scale-free neural network.

    Science.gov (United States)

    Kim, Sang-Yoon; Lim, Woochang

    2015-08-01

    We consider a directed version of the Barabási-Albert scale-free network model with symmetric preferential attachment with the same in- and out-degrees and study the emergence of sparsely synchronized rhythms for a fixed attachment degree in an inhibitory population of fast-spiking Izhikevich interneurons. Fast sparsely synchronized rhythms with stochastic and intermittent neuronal discharges are found to appear for large values of J (synaptic inhibition strength) and D (noise intensity). For an intensive study we fix J at a sufficiently large value and investigate the population states by increasing D. For small D, full synchronization with the same population-rhythm frequency fp and mean firing rate (MFR) fi of individual neurons occurs, while for large D partial synchronization with fp>〈fi〉 (〈fi〉: ensemble-averaged MFR) appears due to intermittent discharge of individual neurons; in particular, the case of fp>4〈fi〉 is referred to as sparse synchronization. For the case of partial and sparse synchronization, MFRs of individual neurons vary depending on their degrees. As D passes a critical value D* (which is determined by employing an order parameter), a transition to unsynchronization occurs due to the destructive role of noise to spoil the pacing between sparse spikes. For D

  7. Fast sparsely synchronized brain rhythms in a scale-free neural network

    Science.gov (United States)

    Kim, Sang-Yoon; Lim, Woochang

    2015-08-01

    We consider a directed version of the Barabási-Albert scale-free network model with symmetric preferential attachment with the same in- and out-degrees and study the emergence of sparsely synchronized rhythms for a fixed attachment degree in an inhibitory population of fast-spiking Izhikevich interneurons. Fast sparsely synchronized rhythms with stochastic and intermittent neuronal discharges are found to appear for large values of J (synaptic inhibition strength) and D (noise intensity). For an intensive study we fix J at a sufficiently large value and investigate the population states by increasing D . For small D , full synchronization with the same population-rhythm frequency fp and mean firing rate (MFR) fi of individual neurons occurs, while for large D partial synchronization with fp> ( : ensemble-averaged MFR) appears due to intermittent discharge of individual neurons; in particular, the case of fp>4 is referred to as sparse synchronization. For the case of partial and sparse synchronization, MFRs of individual neurons vary depending on their degrees. As D passes a critical value D* (which is determined by employing an order parameter), a transition to unsynchronization occurs due to the destructive role of noise to spoil the pacing between sparse spikes. For D

  8. Memories.

    Science.gov (United States)

    Brand, Judith, Ed.

    1998-01-01

    This theme issue of the journal "Exploring" covers the topic of "memories" and describes an exhibition at San Francisco's Exploratorium that ran from May 22, 1998 through January 1999 and that contained over 40 hands-on exhibits, demonstrations, artworks, images, sounds, smells, and tastes that demonstrated and depicted the biological,…

  9. DESTINY: A Comprehensive Tool with 3D and Multi-Level Cell Memory Modeling Capability

    Directory of Open Access Journals (Sweden)

    Sparsh Mittal

    2017-09-01

    Full Text Available To enable the design of large capacity memory structures, novel memory technologies such as non-volatile memory (NVM and novel fabrication approaches, e.g., 3D stacking and multi-level cell (MLC design have been explored. The existing modeling tools, however, cover only a few memory technologies, technology nodes and fabrication approaches. We present DESTINY, a tool for modeling 2D/3D memories designed using SRAM, resistive RAM (ReRAM, spin transfer torque RAM (STT-RAM, phase change RAM (PCM and embedded DRAM (eDRAM and 2D memories designed using spin orbit torque RAM (SOT-RAM, domain wall memory (DWM and Flash memory. In addition to single-level cell (SLC designs for all of these memories, DESTINY also supports modeling MLC designs for NVMs. We have extensively validated DESTINY against commercial and research prototypes of these memories. DESTINY is very useful for performing design-space exploration across several dimensions, such as optimizing for a target (e.g., latency, area or energy-delay product for a given memory technology, choosing the suitable memory technology or fabrication method (i.e., 2D v/s 3D for a given optimization target, etc. We believe that DESTINY will boost studies of next-generation memory architectures used in systems ranging from mobile devices to extreme-scale supercomputers. The latest source-code of DESTINY is available from the following git repository: https://bitbucket.org/sparshmittal/destinyv2.

  10. What Can the Diffusion Model Tell Us About Prospective Memory?

    Science.gov (United States)

    Horn, Sebastian S.; Bayen, Ute J.; Smith, Rebekah E.

    2011-01-01

    Cognitive process models, such as Ratcliff’s (1978) diffusion model, are useful tools for examining cost- or interference effects in event-based prospective memory (PM). The diffusion model includes several parameters that provide insight into how and why ongoing-task performance may be affected by a PM task and is ideally suited to analyze performance because both reaction time and accuracy are taken into account. Separate analyses of these measures can easily yield misleading interpretations in cases of speed-accuracy tradeoffs. The diffusion model allows us to measure possible criterion shifts and is thus an important methodological improvement over standard analyses. Performance in an ongoing lexical decision task (Smith, 2003) was analyzed with the diffusion model. The results suggest that criterion shifts play an important role when a PM task is added, but do not fully explain the cost effect on RT. PMID:21443332

  11. Evolutive Masing model, cycling plasticity, ageing and memory effects

    International Nuclear Information System (INIS)

    Sidoroff, F.

    1987-01-01

    Many models are proposed for the mechanical description of the cyclic behaviour of metals and used for structure analysis under cyclic loading. The evolutive Masing model has been proposed (Fougeres, Sidoroff, Vincent and Waille 1985) to combine - the accuracy of hereditary models for the description of hysteresis on each cycle, - the versatility of internal variables for the state description and evolution, - a sufficient microstructural basis to make the interaction easier with microstructural investigations. The purpose of the present work is to discuss this model and to compare different evolution assumptions with respect to some memory effects (cyclic hardening and softening, multilevel tests, ageing). Attention is limited to uniaxial, rate independent elasto-plastic behaviour. (orig./GL)

  12. Knowledge Loss: A Defensive Model In Nuclear Research Organization Memory

    International Nuclear Information System (INIS)

    Mohamad Safuan Bin Sulaiman; Muhd Noor Muhd Yunus

    2013-01-01

    Knowledge is an essential part of research based organization. It should be properly managed to ensure that any pitfalls of knowledge retention due to knowledge loss of both tacit and explicit is mitigated. Audit of the knowledge entities exist in the organization is important to identify the size of critical knowledge. It is very much related to how much know-what, know-how and know-why experts exist in the organization. This study conceptually proposed a defensive model for Nuclear Malaysia's organization memory and application of Knowledge Loss Risk Assessment (KLRA) as an important tool for critical knowledge identification. (author)

  13. Evaluating Multicore Algorithms on the Unified Memory Model

    Directory of Open Access Journals (Sweden)

    John E. Savage

    2009-01-01

    Full Text Available One of the challenges to achieving good performance on multicore architectures is the effective utilization of the underlying memory hierarchy. While this is an issue for single-core architectures, it is a critical problem for multicore chips. In this paper, we formulate the unified multicore model (UMM to help understand the fundamental limits on cache performance on these architectures. The UMM seamlessly handles different types of multiple-core processors with varying degrees of cache sharing at different levels. We demonstrate that our model can be used to study a variety of multicore architectures on a variety of applications. In particular, we use it to analyze an option pricing problem using the trinomial model and develop an algorithm for it that has near-optimal memory traffic between cache levels. We have implemented the algorithm on a two Quad-Core Intel Xeon 5310 1.6 GHz processors (8 cores. It achieves a peak performance of 19.5 GFLOPs, which is 38% of the theoretical peak of the multicore system. We demonstrate that our algorithm outperforms compiler-optimized and auto-parallelized code by a factor of up to 7.5.

  14. Memory effects in the relaxation of the Gaussian trap model

    Science.gov (United States)

    Diezemann, Gregor; Heuer, Andreas

    2011-03-01

    We investigate the memory effect in a simple model for glassy relaxation, a trap model with a Gaussian density of states. In this model, thermal equilibrium is reached at all finite temperatures and we therefore can consider jumps from low to high temperatures in addition to the quenches usually considered in aging studies. We show that the evolution of the energy following the Kovacs protocol can approximately be expressed as a difference of two monotonously decaying functions and thus show the existence of a so-called Kovacs hump whenever these functions are not single exponentials. It is well established that the Kovacs effect also occurs in the linear response regime, and we show that most of the gross features do not change dramatically when large temperature jumps are considered. However, there is one distinguishing feature that only exists beyond the linear regime, which we discuss in detail. For the memory experiment with inverted temperatures, i.e., jumping up and then down again, we find a very similar behavior apart from an opposite sign of the hump.

  15. Scale-Free Relationships between Social and Landscape Factors in Urban Systems

    Directory of Open Access Journals (Sweden)

    Chunzhu Wei

    2017-01-01

    Full Text Available Urban planners and ecologists have long debated the relationship between the structure of urban landscapes and social activities. There have, however, been very few discussions as to whether any such relationships might depend on the scales of observation. This work applies a hierarchical zoning technique to data from the city of Quito, Ecuador, to examine how relationships between typical spatial landscape metrics and social indicators depend on zoning scales. Our results showed that the estimates of both landscape heterogeneity features and social indicators significantly depend on the zoning scale. The mean values of the typical landscape metrics and the social indicators all exhibited predictable responses to a changing zoning scale, suggesting a consistent and significant scaling relationship within the multiple zoning scales. Yet relationships between these pairs of variables remain notably invariant to scale. This quantitative demonstration of the scale-free nature of the relationship between landscape characteristics and social indicators furthers our understanding of the relationships between landscape structures and social aspects of urban spaces, including deprivation and public service accessibility. The relationships between social indicators and one typical landscape aggregation metric (represented as the percentage of like adjacencies were nevertheless significantly dependent on scale, suggesting the importance of zoning scale decisions for analyzing the relationships between the social indicators and the landscape characteristics related with landscape adjacency. Aside from this typical landscape aggregation metric, the general invariance to the zoning scale of relationships between landscape structures and socioeconomic indicators in Quito suggests the importance of applying these scale-free relationships in understanding complex socio-ecological systems in other cities, which are shaped by the conflated influences of both

  16. Models for Total-Dose Radiation Effects in Non-Volatile Memory

    Energy Technology Data Exchange (ETDEWEB)

    Campbell, Philip Montgomery; Wix, Steven D.

    2017-04-01

    The objective of this work is to develop models to predict radiation effects in non- volatile memory: flash memory and ferroelectric RAM. In flash memory experiments have found that the internal high-voltage generators (charge pumps) are the most sensitive to radiation damage. Models are presented for radiation effects in charge pumps that demonstrate the experimental results. Floating gate models are developed for the memory cell in two types of flash memory devices by Intel and Samsung. These models utilize Fowler-Nordheim tunneling and hot electron injection to charge and erase the floating gate. Erase times are calculated from the models and compared with experimental results for different radiation doses. FRAM is less sensitive to radiation than flash memory, but measurements show that above 100 Krad FRAM suffers from a large increase in leakage current. A model for this effect is developed which compares closely with the measurements.

  17. Entanglement percolation on a quantum internet with scale-free and clustering characters

    International Nuclear Information System (INIS)

    Wu Liang; Zhu Shiqun

    2011-01-01

    The applicability of entanglement percolation protocol to real Internet structure is investigated. If the current Internet can be used directly in the quantum regime, the protocol can provide a way to establish long-distance entanglement when the links are pure nonmaximally entangled states. This applicability is primarily due to the combination of scale-free degree distribution and a high level of clustering, both of which are widely observed in many natural and artificial networks including the current Internet. It suggests that the topology of real Internet may play an important role in entanglement establishment.

  18. Entanglement percolation on a quantum internet with scale-free and clustering characters

    Energy Technology Data Exchange (ETDEWEB)

    Wu Liang; Zhu Shiqun [School of Physical Science and Technology, Soochow University, Suzhou, Jiangsu 215006 (China)

    2011-11-15

    The applicability of entanglement percolation protocol to real Internet structure is investigated. If the current Internet can be used directly in the quantum regime, the protocol can provide a way to establish long-distance entanglement when the links are pure nonmaximally entangled states. This applicability is primarily due to the combination of scale-free degree distribution and a high level of clustering, both of which are widely observed in many natural and artificial networks including the current Internet. It suggests that the topology of real Internet may play an important role in entanglement establishment.

  19. An efficient strategy for enhancing traffic capacity by removing links in scale-free networks

    International Nuclear Information System (INIS)

    Huang, Wei; Chow, Tommy W S

    2010-01-01

    An efficient link-removal strategy, called the variance-of-neighbor-degree-reduction (VNDR) strategy, for enhancing the traffic capacity of scale-free networks is proposed in this paper. The VNDR strategy, which considers the important role of hub nodes, balances the amounts of packets routed from each node to the node's neighbors. Compared against the outcomes of strategies that remove links among hub nodes, our results show that the traffic capacity can be greatly enhanced, especially under the shortest path routing strategy. It is also found that the average transport time is effectively reduced by using the VNDR strategy only under the shortest path routing strategy

  20. An extended continuum model considering optimal velocity change with memory and numerical tests

    Science.gov (United States)

    Qingtao, Zhai; Hongxia, Ge; Rongjun, Cheng

    2018-01-01

    In this paper, an extended continuum model of traffic flow is proposed with the consideration of optimal velocity changes with memory. The new model's stability condition and KdV-Burgers equation considering the optimal velocities change with memory are deduced through linear stability theory and nonlinear analysis, respectively. Numerical simulation is carried out to study the extended continuum model, which explores how optimal velocity changes with memory affected velocity, density and energy consumption. Numerical results show that when considering the effects of optimal velocity changes with memory, the traffic jams can be suppressed efficiently. Both the memory step and sensitivity parameters of optimal velocity changes with memory will enhance the stability of traffic flow efficiently. Furthermore, numerical results demonstrates that the effect of optimal velocity changes with memory can avoid the disadvantage of historical information, which increases the stability of traffic flow on road, and so it improve the traffic flow stability and minimize cars' energy consumptions.

  1. Memory of irrigation effects on hydroclimate and its modeling challenge

    Science.gov (United States)

    Chen, Fei; Xu, Xiaoyu; Barlage, Michael; Rasmussen, Roy; Shen, Shuanghe; Miao, Shiguang; Zhou, Guangsheng

    2018-06-01

    Irrigation modifies land-surface water and energy budgets, and also influences weather and climate. However, current earth-system models, used for weather prediction and climate projection, are still in their infancy stage to consider irrigation effects. This study used long-term data collected from two contrasting (irrigated and rainfed) nearby maize-soybean rotation fields, to study the effects of irrigation memory on local hydroclimate. For a 12 year average, irrigation decreases summer surface-air temperature by less than 1 °C and increases surface humidity by 0.52 g kg‑1. The irrigation cooling effect is more pronounced and longer lasting for maize than for soybean. Irrigation reduces maximum, minimum, and averaged temperature over maize by more than 0.5 °C for the first six days after irrigation, but its temperature effect over soybean is mixed and negligible two or three days after irrigation. Irrigation increases near-surface humidity over maize by about 1 g kg‑1 up to ten days and increases surface humidity over soybean (~ 0.8 g kg‑1) with a similar memory. These differing effects of irrigation memory on temperature and humidity are associated with respective changes in the surface sensible and latent heat fluxes for maize and soybean. These findings highlight great need and challenges for earth-system models to realistically simulate how irrigation effects vary with crop species and with crop growth stages, and to capture complex interactions between agricultural management and water-system components (crop transpiration, precipitation, river, reservoirs, lakes, groundwater, etc.) at various spatial and temporal scales.

  2. Neural field model of memory-guided search.

    Science.gov (United States)

    Kilpatrick, Zachary P; Poll, Daniel B

    2017-12-01

    Many organisms can remember locations they have previously visited during a search. Visual search experiments have shown exploration is guided away from these locations, reducing redundancies in the search path before finding a hidden target. We develop and analyze a two-layer neural field model that encodes positional information during a search task. A position-encoding layer sustains a bump attractor corresponding to the searching agent's current location, and search is modeled by velocity input that propagates the bump. A memory layer sustains persistent activity bounded by a wave front, whose edges expand in response to excitatory input from the position layer. Search can then be biased in response to remembered locations, influencing velocity inputs to the position layer. Asymptotic techniques are used to reduce the dynamics of our model to a low-dimensional system of equations that track the bump position and front boundary. Performance is compared for different target-finding tasks.

  3. Neural field model of memory-guided search

    Science.gov (United States)

    Kilpatrick, Zachary P.; Poll, Daniel B.

    2017-12-01

    Many organisms can remember locations they have previously visited during a search. Visual search experiments have shown exploration is guided away from these locations, reducing redundancies in the search path before finding a hidden target. We develop and analyze a two-layer neural field model that encodes positional information during a search task. A position-encoding layer sustains a bump attractor corresponding to the searching agent's current location, and search is modeled by velocity input that propagates the bump. A memory layer sustains persistent activity bounded by a wave front, whose edges expand in response to excitatory input from the position layer. Search can then be biased in response to remembered locations, influencing velocity inputs to the position layer. Asymptotic techniques are used to reduce the dynamics of our model to a low-dimensional system of equations that track the bump position and front boundary. Performance is compared for different target-finding tasks.

  4. Modeling the Role of Working Memory and Episodic Memory in Behavioral Tasks

    OpenAIRE

    Zilli, Eric A.; Hasselmo, Michael E.

    2008-01-01

    The mechanisms of goal-directed behavior have been studied using reinforcement learning theory, but these theoretical techniques have not often been used to address the role of memory systems in performing behavioral tasks. The present work addresses this shortcoming by providing a way in which working memory and episodic memory may be included in the reinforcement learning framework, then simulating the successful acquisition and performance of six behavioral tasks, drawn from or inspired by...

  5. Ordering chaos and synchronization transitions by chemical delay and coupling on scale-free neuronal networks

    International Nuclear Information System (INIS)

    Gong Yubing; Xie Yanhang; Lin Xiu; Hao Yinghang; Ma Xiaoguang

    2010-01-01

    Research highlights: → Chemical delay and chemical coupling can tame chaotic bursting. → Chemical delay-induced transitions from bursting synchronization to intermittent multiple spiking synchronizations. → Chemical coupling-induced different types of delay-dependent firing transitions. - Abstract: Chemical synaptic connections are more common than electric ones in neurons, and information transmission delay is especially significant for the synapses of chemical type. In this paper, we report a phenomenon of ordering spatiotemporal chaos and synchronization transitions by the delays and coupling through chemical synapses of modified Hodgkin-Huxley (MHH) neurons on scale-free networks. As the delay τ is increased, the neurons exhibit transitions from bursting synchronization (BS) to intermittent multiple spiking synchronizations (SS). As the coupling g syn is increased, the neurons exhibit different types of firing transitions, depending on the values of τ. For a smaller τ, there are transitions from spatiotemporal chaotic bursting (SCB) to BS or SS; while for a larger τ, there are transitions from SCB to intermittent multiple SS. These findings show that the delays and coupling through chemical synapses can tame the chaotic firings and repeatedly enhance the firing synchronization of neurons, and hence could play important roles in the firing activity of the neurons on scale-free networks.

  6. Impacts of hybrid synapses on the noise-delayed decay in scale-free neural networks

    International Nuclear Information System (INIS)

    Yilmaz, Ergin

    2014-01-01

    Highlights: • We investigate the NDD phenomenon in a hybrid scale-free network. • Electrical synapses are more impressive on the emergence of NDD. • Electrical synapses are more efficient in suppressing of the NDD. • Average degree has two opposite effects on the appearance time of the first spike. - Abstract: We study the phenomenon of noise-delayed decay in a scale-free neural network consisting of excitable FitzHugh–Nagumo neurons. In contrast to earlier works, where only electrical synapses are considered among neurons, we primarily examine the effects of hybrid synapses on the noise-delayed decay in this study. We show that the electrical synaptic coupling is more impressive than the chemical coupling in determining the appearance time of the first-spike and more efficient on the mitigation of the delay time in the detection of a suprathreshold input signal. We obtain that hybrid networks including inhibitory chemical synapses have higher signal detection capabilities than those of including excitatory ones. We also find that average degree exhibits two different effects, which are strengthening and weakening the noise-delayed decay effect depending on the noise intensity

  7. Scale-Free Brain-Wave Music from Simultaneously EEG and fMRI Recordings

    Science.gov (United States)

    Lu, Jing; Wu, Dan; Yang, Hua; Luo, Cheng; Li, Chaoyi; Yao, Dezhong

    2012-01-01

    In the past years, a few methods have been developed to translate human EEG to music. In 2009, PloS One 4 e5915, we developed a method to generate scale-free brainwave music where the amplitude of EEG was translated to music pitch according to the power law followed by both of them, the period of an EEG waveform is translated directly to the duration of a note, and the logarithm of the average power change of EEG is translated to music intensity according to the Fechner's law. In this work, we proposed to adopt simultaneously-recorded fMRI signal to control the intensity of the EEG music, thus an EEG-fMRI music is generated by combining two different and simultaneous brain signals. And most importantly, this approach further realized power law for music intensity as fMRI signal follows it. Thus the EEG-fMRI music makes a step ahead in reflecting the physiological process of the scale-free brain. PMID:23166768

  8. Effect of clustering on attack vulnerability of interdependent scale-free networks

    International Nuclear Information System (INIS)

    Li, Rui-qi; Sun, Shi-wen; Ma, Yi-lin; Wang, Li; Xia, Cheng-yi

    2015-01-01

    In order to deeply understand the complex interdependent systems, it is of great concern to take clustering coefficient, which is an important feature of many real-world systems, into account. Previous study mainly focused on the impact of clustering on interdependent networks under random attacks, while we extend the study to the case of the more realistic attacking strategy, targeted attack. A system composed of two interdependent scale-free networks with tunable clustering is provided. The effects of coupling strength and coupling preference on attack vulnerability are explored. Numerical simulation results demonstrate that interdependent links between two networks make the entire system much more fragile to attacks. Also, it is found that clustering significantly increases the vulnerability of interdependent scale-free networks. Moreover, for fully coupled network, disassortative coupling is found to be most vulnerable to random attacks, while the random and assortative coupling have little difference. Additionally, enhancing coupling strength can greatly enhance the fragility of interdependent networks against targeted attacks. These results can not only improve the deep understanding of structural complexity of complex systems, but also provide insights into the guidance of designing resilient infrastructures.

  9. Increased signaling entropy in cancer requires the scale-free property of protein interaction networks

    Science.gov (United States)

    Teschendorff, Andrew E.; Banerji, Christopher R. S.; Severini, Simone; Kuehn, Reimer; Sollich, Peter

    2015-01-01

    One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is unclear how these perturbations give rise to the observed increased plasticity. Elucidating such systems-level principles is key for an improved understanding of cancer. Recently, it has been shown that signaling entropy, an overall measure of signaling pathway promiscuity, and computable from integrating a sample's gene expression profile with a protein interaction network, correlates with phenotypic plasticity and is increased in cancer compared to normal tissue. Here we develop a computational framework for studying the effects of network perturbations on signaling entropy. We demonstrate that the increased signaling entropy of cancer is driven by two factors: (i) the scale-free (or near scale-free) topology of the interaction network, and (ii) a subtle positive correlation between differential gene expression and node connectivity. Indeed, we show that if protein interaction networks were random graphs, described by Poisson degree distributions, that cancer would generally not exhibit an increased signaling entropy. In summary, this work exposes a deep connection between cancer, signaling entropy and interaction network topology. PMID:25919796

  10. Utilizing Maximal Independent Sets as Dominating Sets in Scale-Free Networks

    Science.gov (United States)

    Derzsy, N.; Molnar, F., Jr.; Szymanski, B. K.; Korniss, G.

    Dominating sets provide key solution to various critical problems in networked systems, such as detecting, monitoring, or controlling the behavior of nodes. Motivated by graph theory literature [Erdos, Israel J. Math. 4, 233 (1966)], we studied maximal independent sets (MIS) as dominating sets in scale-free networks. We investigated the scaling behavior of the size of MIS in artificial scale-free networks with respect to multiple topological properties (size, average degree, power-law exponent, assortativity), evaluated its resilience to network damage resulting from random failure or targeted attack [Molnar et al., Sci. Rep. 5, 8321 (2015)], and compared its efficiency to previously proposed dominating set selection strategies. We showed that, despite its small set size, MIS provides very high resilience against network damage. Using extensive numerical analysis on both synthetic and real-world (social, biological, technological) network samples, we demonstrate that our method effectively satisfies four essential requirements of dominating sets for their practical applicability on large-scale real-world systems: 1.) small set size, 2.) minimal network information required for their construction scheme, 3.) fast and easy computational implementation, and 4.) resiliency to network damage. Supported by DARPA, DTRA, and NSF.

  11. Scale-free brain-wave music from simultaneously EEG and fMRI recordings.

    Science.gov (United States)

    Lu, Jing; Wu, Dan; Yang, Hua; Luo, Cheng; Li, Chaoyi; Yao, Dezhong

    2012-01-01

    In the past years, a few methods have been developed to translate human EEG to music. In 2009, PloS One 4 e5915, we developed a method to generate scale-free brainwave music where the amplitude of EEG was translated to music pitch according to the power law followed by both of them, the period of an EEG waveform is translated directly to the duration of a note, and the logarithm of the average power change of EEG is translated to music intensity according to the Fechner's law. In this work, we proposed to adopt simultaneously-recorded fMRI signal to control the intensity of the EEG music, thus an EEG-fMRI music is generated by combining two different and simultaneous brain signals. And most importantly, this approach further realized power law for music intensity as fMRI signal follows it. Thus the EEG-fMRI music makes a step ahead in reflecting the physiological process of the scale-free brain.

  12. Single or multiple synchronization transitions in scale-free neuronal networks with electrical or chemical coupling

    International Nuclear Information System (INIS)

    Hao Yinghang; Gong, Yubing; Wang Li; Ma Xiaoguang; Yang Chuanlu

    2011-01-01

    Research highlights: → Single synchronization transition for gap-junctional coupling. → Multiple synchronization transitions for chemical synaptic coupling. → Gap junctions and chemical synapses have different impacts on synchronization transition. → Chemical synapses may play a dominant role in neurons' information processing. - Abstract: In this paper, we have studied time delay- and coupling strength-induced synchronization transitions in scale-free modified Hodgkin-Huxley (MHH) neuron networks with gap-junctions and chemical synaptic coupling. It is shown that the synchronization transitions are much different for these two coupling types. For gap-junctions, the neurons exhibit a single synchronization transition with time delay and coupling strength, while for chemical synapses, there are multiple synchronization transitions with time delay, and the synchronization transition with coupling strength is dependent on the time delay lengths. For short delays we observe a single synchronization transition, whereas for long delays the neurons exhibit multiple synchronization transitions as the coupling strength is varied. These results show that gap junctions and chemical synapses have different impacts on the pattern formation and synchronization transitions of the scale-free MHH neuronal networks, and chemical synapses, compared to gap junctions, may play a dominant and more active function in the firing activity of the networks. These findings would be helpful for further understanding the roles of gap junctions and chemical synapses in the firing dynamics of neuronal networks.

  13. Single or multiple synchronization transitions in scale-free neuronal networks with electrical or chemical coupling

    Energy Technology Data Exchange (ETDEWEB)

    Hao Yinghang [School of Physics, Ludong University, Yantai 264025 (China); Gong, Yubing, E-mail: gongyubing09@hotmail.co [School of Physics, Ludong University, Yantai 264025 (China); Wang Li; Ma Xiaoguang; Yang Chuanlu [School of Physics, Ludong University, Yantai 264025 (China)

    2011-04-15

    Research highlights: Single synchronization transition for gap-junctional coupling. Multiple synchronization transitions for chemical synaptic coupling. Gap junctions and chemical synapses have different impacts on synchronization transition. Chemical synapses may play a dominant role in neurons' information processing. - Abstract: In this paper, we have studied time delay- and coupling strength-induced synchronization transitions in scale-free modified Hodgkin-Huxley (MHH) neuron networks with gap-junctions and chemical synaptic coupling. It is shown that the synchronization transitions are much different for these two coupling types. For gap-junctions, the neurons exhibit a single synchronization transition with time delay and coupling strength, while for chemical synapses, there are multiple synchronization transitions with time delay, and the synchronization transition with coupling strength is dependent on the time delay lengths. For short delays we observe a single synchronization transition, whereas for long delays the neurons exhibit multiple synchronization transitions as the coupling strength is varied. These results show that gap junctions and chemical synapses have different impacts on the pattern formation and synchronization transitions of the scale-free MHH neuronal networks, and chemical synapses, compared to gap junctions, may play a dominant and more active function in the firing activity of the networks. These findings would be helpful for further understanding the roles of gap junctions and chemical synapses in the firing dynamics of neuronal networks.

  14. Synchronous bursts on scale-free neuronal networks with attractive and repulsive coupling.

    Directory of Open Access Journals (Sweden)

    Qingyun Wang

    Full Text Available This paper investigates the dependence of synchronization transitions of bursting oscillations on the information transmission delay over scale-free neuronal networks with attractive and repulsive coupling. It is shown that for both types of coupling, the delay always plays a subtle role in either promoting or impairing synchronization. In particular, depending on the inherent oscillation period of individual neurons, regions of irregular and regular propagating excitatory fronts appear intermittently as the delay increases. These delay-induced synchronization transitions are manifested as well-expressed minima in the measure for spatiotemporal synchrony. For attractive coupling, the minima appear at every integer multiple of the average oscillation period, while for the repulsive coupling, they appear at every odd multiple of the half of the average oscillation period. The obtained results are robust to the variations of the dynamics of individual neurons, the system size, and the neuronal firing type. Hence, they can be used to characterize attractively or repulsively coupled scale-free neuronal networks with delays.

  15. Influence of different initial distributions on robust cooperation in scale-free networks: A comparative study

    International Nuclear Information System (INIS)

    Chen Xiaojie; Fu Feng; Wang Long

    2008-01-01

    We study the evolutionary Prisoner's dilemma game on scale-free networks, focusing on the influence of different initial distributions for cooperators and defectors on the evolution of cooperation. To address this issue, we consider three types of initial distributions for defectors: uniform distribution at random, occupying the most connected nodes, and occupying the lowest-degree nodes, respectively. It is shown that initial configurations for defectors can crucially influence the cooperation level and the evolution speed of cooperation. Interestingly, the situation where defectors initially occupy the lowest-degree vertices can exhibit the most robust cooperation, compared with two other distributions. That is, the cooperation level is least affected by the initial percentage of defectors. Moreover, in this situation, the whole system evolves fastest to the prevalent cooperation. Besides, we obtain the critical values of initial frequency of defectors above which the extinction of cooperators occurs for the respective initial distributions. Our results might be helpful in explaining the maintenance of high cooperation in scale-free networks

  16. A Mathematical Model for the Hippocampus: Towards the Understanding of Episodic Memory and Imagination

    Science.gov (United States)

    Tsuda, I.; Yamaguti, Y.; Kuroda, S.; Fukushima, Y.; Tsukada, M.

    How does the brain encode episode? Based on the fact that the hippocampus is responsible for the formation of episodic memory, we have proposed a mathematical model for the hippocampus. Because episodic memory includes a time series of events, an underlying dynamics for the formation of episodic memory is considered to employ an association of memories. David Marr correctly pointed out in his theory of archecortex for a simple memory that the hippocampal CA3 is responsible for the formation of associative memories. However, a conventional mathematical model of associative memory simply guarantees a single association of memory unless a rule for an order of successive association of memories is given. The recent clinical studies in Maguire's group for the patients with the hippocampal lesion show that the patients cannot make a new story, because of the lack of ability of imagining new things. Both episodic memory and imagining things include various common characteristics: imagery, the sense of now, retrieval of semantic information, and narrative structures. Taking into account these findings, we propose a mathematical model of the hippocampus in order to understand the common mechanism of episodic memory and imagination.

  17. Evolutionary games played by multi-agent system with different memory capacity

    Science.gov (United States)

    Zhang, Jianlei; Zhang, Chunyan

    2015-06-01

    The evolution of cooperation is still an enigma. Resolution of cooperative dilemma is a hot topic as a perplexing interdisciplinary project, and has captured wide attention of researchers from many disciplines as a multidisciplinary field. Our main concern is the design of a networked evolutionary game model in which players show difference in memory capability. The idea of different memory capacities has its origin on the pervasive individual heterogeneity of real agents in nature. It is concluded that this proposed multiple memory capacity stimulates cooperation in lattice-structured populations. The networking effect is also investigated via a scale free network which is associated with the heterogeneous populations structure. Interestingly, results suggest that the effectiveness of a heterogeneous network at fostering cooperation is reduced in the presence of individual memory here. A thorough inquiry in the coevolutionary dynamics of individual memory and spatial structure in evolutionary games is planned for the immediate future.

  18. Hysteresis behaviour of thermoelastic alloys: some shape memory alloys models

    International Nuclear Information System (INIS)

    Lexcellent, C.; Torra, V.; Raniecki, B.

    1993-01-01

    The hysteretic behaviour of shape memory alloys (SMA) needs a more and more thin analysis because of its importance for technological applications. The comparison between different approaches allows to explicite the specifity of every model (macroscopic approach, micro-macro level, local description, phenomenological approach) and their points of convergence. On one hand, a thermodynamic treatment with a free energy expression as a mixing rule of each phase (parent or austenite phase and martensite) by adding a coupling term: the configurational energy, allowes modelling of material hysteresis loops. On the other hand, a phenomenological treatment based on a local investigation of two single crystals with a visualisation of microscopic parameters allows to perceive the phase transition mechanisms (nucleation, growth). All the obtained results show the importance of entropy production (or of the definition of the configurational energy term) for the correct description of hysteresis loops (subloops or external). (orig.)

  19. Modeling Brain Responses in an Arithmetic Working Memory Task

    Science.gov (United States)

    Hamid, Aini Ismafairus Abd; Yusoff, Ahmad Nazlim; Mukari, Siti Zamratol-Mai Sarah; Mohamad, Mazlyfarina; Manan, Hanani Abdul; Hamid, Khairiah Abdul

    2010-07-01

    Functional magnetic resonance imaging (fMRI) was used to investigate brain responses due to arithmetic working memory. Nine healthy young male subjects were given simple addition and subtraction instructions in noise and in quiet. The general linear model (GLM) and random field theory (RFT) were implemented in modelling the activation. The results showed that addition and subtraction evoked bilateral activation in Heschl's gyrus (HG), superior temporal gyrus (STG), inferior frontal gyrus (IFG), supramarginal gyrus (SG) and precentral gyrus (PCG). The HG, STG, SG and PCG activate higher number of voxels in noise as compared to in quiet for addition and subtraction except for IFG that showed otherwise. The percentage of signal change (PSC) in all areas is higher in quiet as compared to in noise. Surprisingly addition (not subtraction) exhibits stronger activation.

  20. Evolutive masing model, cyclic plasticity, ageing and memory effects

    International Nuclear Information System (INIS)

    Sidoroff, F.

    1987-01-01

    Many models are proposed for the mechanical description of the cyclic behaviour of metals and used for structure analysis under cyclic loading. Such a model must include two basic features: Dissipative behaviour on each cycle (hysteresis loop); evolution of this behaviour during the material's life (cyclic hardening or softening, aging,...). However, if both aspects are present in most existing models, the balance between them may be quite different. Many metallurgical investigations have been performed about the microstructure and its evolution during cyclic loading, and it is desirable to introduce these informations in phenomenological models. The evolutive Masing model has been proposed to combine: the accuracy of hereditary models for the description of hysteresis on each cycle, the versatility of internal variables for the state description and evolution, a sufficient microstructural basis to make the interaction easier with microstructural investigations. The purpose of the present work is to discuss this model and to compare different evolution assumptions with respect to some memory effects (cyclic hardening and softening, multilevel tests, aging). Attention is limited to uniaxial, rate independent elasto-plastic behaviour

  1. Higher order moments of the matter distribution in scale-free cosmological simulations with large dynamic range

    Science.gov (United States)

    Lucchin, Francesco; Matarrese, Sabino; Melott, Adrian L.; Moscardini, Lauro

    1994-01-01

    We calculate reduced moments (xi bar)(sub q) of the matter density fluctuations, up to order q = 5, from counts in cells produced by particle-mesh numerical simulations with scale-free Gaussian initial conditions. We use power-law spectra P(k) proportional to k(exp n) with indices n = -3, -2, -1, 0, 1. Due to the supposed absence of characteristic times or scales in our models, all quantities are expected to depend on a single scaling variable. For each model, the moments at all times can be expressed in terms of the variance (xi bar)(sub 2), alone. We look for agreement with the hierarchical scaling ansatz, according to which ((xi bar)(sub q)) proportional to ((xi bar)(sub 2))(exp (q - 1)). For n less than or equal to -2 models, we find strong deviations from the hierarchy, which are mostly due to the presence of boundary problems in the simulations. A small, residual signal of deviation from the hierarchical scaling is however also found in n greater than or equal to -1 models. The wide range of spectra considered and the large dynamic range, with careful checks of scaling and shot-noise effects, allows us to reliably detect evolution away from the perturbation theory result.

  2. A Developmental Psychopathology Model of Overgeneral Autobiographical Memory

    Science.gov (United States)

    Valentino, Kristin

    2011-01-01

    Overgeneral memory (OGM) is a phenomenon that refers to difficulty retrieving specific autobiographical memories. The tendency to be overgeneral in autobiographical memory recall has been commonly observed among individuals with emotional disorders compared to those without emotional disorders. Despite significant advances in identifying…

  3. Reflections on Working Memory: Are the Two Models Complementary?

    Science.gov (United States)

    Pascual-Leone, Juan

    2000-01-01

    Compares and contrasts working memory theory of Baddeley and theory of constructive operators of Pascual- Leone. Concludes that although the theory of constructive operators is complementary with working memory theory (explains developmental and individual differences that working memory theory cannot), the converse is not true; theory of…

  4. Empirical study of the metal-nitride-oxide-semiconductor device characteristics deduced from a microscopic model of memory traps

    International Nuclear Information System (INIS)

    Ngai, K.L.; Hsia, Y.

    1982-01-01

    A graded-nitride gate dielectric metal-nitride-oxide-semiconductor (MNOS) memory transistor exhibiting superior device characteristics is presented and analyzed based on a qualitative microscopic model of the memory traps. The model is further reviewed to interpret some generic properties of the MNOS memory transistors including memory window, erase-write speed, and the retention-endurance characteristic features

  5. Implications of the Declarative/Procedural Model for Improving Second Language Learning: The Role of Memory Enhancement Techniques

    Science.gov (United States)

    Ullman, Michael T.; Lovelett, Jarrett T.

    2018-01-01

    The declarative/procedural (DP) model posits that the learning, storage, and use of language critically depend on two learning and memory systems in the brain: declarative memory and procedural memory. Thus, on the basis of independent research on the memory systems, the model can generate specific and often novel predictions for language. Till…

  6. Through the Immune Looking Glass: A Model for Brain Memory Strategies.

    Science.gov (United States)

    Sánchez-Ramón, Silvia; Faure, Florence

    2016-01-01

    The immune system (IS) and the central nervous system (CNS) are complex cognitive networks involved in defining the identity (self) of the individual through recognition and memory processes that enable one to anticipate responses to stimuli. Brain memory has traditionally been classified as either implicit or explicit on psychological and anatomical grounds, with reminiscences of the evolutionarily-based innate-adaptive IS responses. Beyond the multineuronal networks of the CNS, we propose a theoretical model of brain memory integrating the CNS as a whole. This is achieved by analogical reasoning between the operational rules of recognition and memory processes in both systems, coupled to an evolutionary analysis. In this new model, the hippocampus is no longer specifically ascribed to explicit memory but rather it both becomes part of the innate (implicit) memory system and tightly controls the explicit memory system. Alike the antigen presenting cells for the IS, the hippocampus would integrate transient and pseudo-specific (i.e., danger-fear) memories and would drive the formation of long-term and highly specific or explicit memories (i.e., the taste of the Proust's madeleine cake) by the more complex and recent, evolutionarily speaking, neocortex. Experimental and clinical evidence is provided to support the model. We believe that the singularity of this model's approximation could help to gain a better understanding of the mechanisms operating in brain memory strategies from a large-scale network perspective.

  7. A Hamiltonian driven quantum-like model for overdistribution in episodic memory recollection.

    Science.gov (United States)

    Broekaert, Jan B.; Busemeyer, Jerome R.

    2017-06-01

    While people famously forget genuine memories over time, they also tend to mistakenly over-recall equivalent memories concerning a given event. The memory phenomenon is known by the name of episodic overdistribution and occurs both in memories of disjunctions and partitions of mutually exclusive events and has been tested, modeled and documented in the literature. The total classical probability of recalling exclusive sub-events most often exceeds the probability of recalling the composed event, i.e. a subadditive total. We present a Hamiltonian driven propagation for the Quantum Episodic Memory model developed by Brainerd (et al., 2015) for the episodic memory overdistribution in the experimental immediate item false memory paradigm (Brainerd and Reyna, 2008, 2010, 2015). Following the Hamiltonian method of Busemeyer and Bruza (2012) our model adds time-evolution of the perceived memory state through the stages of the experimental process based on psychologically interpretable parameters - γ_c for recollection capability of cues, κ_p for bias or description-dependence by probes and β for the average gist component in the memory state at start. With seven parameters the Hamiltonian model shows good accuracy of predictions both in the EOD-disjunction and in the EOD-subadditivity paradigm. We noticed either an outspoken preponderance of the gist over verbatim trace, or the opposite, in the initial memory state when β is real. Only for complex β a mix of both traces is present in the initial state for the EOD-subadditivity paradigm.

  8. The Neuroanatomical, Neurophysiological and Psychological Basis of Memory: Current Models and Their Origins

    Directory of Open Access Journals (Sweden)

    Eduardo Camina

    2017-06-01

    Full Text Available This review aims to classify and clarify, from a neuroanatomical, neurophysiological, and psychological perspective, different memory models that are currently widespread in the literature as well as to describe their origins. We believe it is important to consider previous developments without which one cannot adequately understand the kinds of models that are now current in the scientific literature. This article intends to provide a comprehensive and rigorous overview for understanding and ordering the latest scientific advances related to this subject. The main forms of memory presented include sensory memory, short-term memory, and long-term memory. Information from the world around us is first stored by sensory memory, thus enabling the storage and future use of such information. Short-term memory (or memory refers to information processed in a short period of time. Long-term memory allows us to store information for long periods of time, including information that can be retrieved consciously (explicit memory or unconsciously (implicit memory.

  9. The Neuroanatomical, Neurophysiological and Psychological Basis of Memory: Current Models and Their Origins

    Science.gov (United States)

    Camina, Eduardo; Güell, Francisco

    2017-01-01

    This review aims to classify and clarify, from a neuroanatomical, neurophysiological, and psychological perspective, different memory models that are currently widespread in the literature as well as to describe their origins. We believe it is important to consider previous developments without which one cannot adequately understand the kinds of models that are now current in the scientific literature. This article intends to provide a comprehensive and rigorous overview for understanding and ordering the latest scientific advances related to this subject. The main forms of memory presented include sensory memory, short-term memory, and long-term memory. Information from the world around us is first stored by sensory memory, thus enabling the storage and future use of such information. Short-term memory (or memory) refers to information processed in a short period of time. Long-term memory allows us to store information for long periods of time, including information that can be retrieved consciously (explicit memory) or unconsciously (implicit memory). PMID:28713278

  10. Scale-free crystallization of two-dimensional complex plasmas: Domain analysis using Minkowski tensors

    Science.gov (United States)

    Böbel, A.; Knapek, C. A.; Räth, C.

    2018-05-01

    Experiments of the recrystallization processes in two-dimensional complex plasmas are analyzed to rigorously test a recently developed scale-free phase transition theory. The "fractal-domain-structure" (FDS) theory is based on the kinetic theory of Frenkel. It assumes the formation of homogeneous domains, separated by defect lines, during crystallization and a fractal relationship between domain area and boundary length. For the defect number fraction and system energy a scale-free power-law relation is predicted. The long-range scaling behavior of the bond-order correlation function shows clearly that the complex plasma phase transitions are not of the Kosterlitz, Thouless, Halperin, Nelson, and Young type. Previous preliminary results obtained by counting the number of dislocations and applying a bond-order metric for structural analysis are reproduced. These findings are supplemented by extending the use of the bond-order metric to measure the defect number fraction and furthermore applying state-of-the-art analysis methods, allowing a systematic testing of the FDS theory with unprecedented scrutiny: A morphological analysis of lattice structure is performed via Minkowski tensor methods. Minkowski tensors form a complete family of additive, motion covariant and continuous morphological measures that are sensitive to nonlinear properties. The FDS theory is rigorously confirmed and predictions of the theory are reproduced extremely well. The predicted scale-free power-law relation between defect fraction number and system energy is verified for one more order of magnitude at high energies compared to the inherently discontinuous bond-order metric. It is found that the fractal relation between crystalline domain area and circumference is independent of the experiment, the particular Minkowski tensor method, and the particular choice of parameters. Thus, the fractal relationship seems to be inherent to two-dimensional phase transitions in complex plasmas. Minkowski

  11. Short-ranged memory model with preferential growth

    Science.gov (United States)

    Schaigorodsky, Ana L.; Perotti, Juan I.; Almeira, Nahuel; Billoni, Orlando V.

    2018-02-01

    In this work we introduce a variant of the Yule-Simon model for preferential growth by incorporating a finite kernel to model the effects of bounded memory. We characterize the properties of the model combining analytical arguments with extensive numerical simulations. In particular, we analyze the lifetime and popularity distributions by mapping the model dynamics to corresponding Markov chains and branching processes, respectively. These distributions follow power laws with well-defined exponents that are within the range of the empirical data reported in ecologies. Interestingly, by varying the innovation rate, this simple out-of-equilibrium model exhibits many of the characteristics of a continuous phase transition and, around the critical point, it generates time series with power-law popularity, lifetime and interevent time distributions, and nontrivial temporal correlations, such as a bursty dynamics in analogy with the activity of solar flares. Our results suggest that an appropriate balance between innovation and oblivion rates could provide an explanatory framework for many of the properties commonly observed in many complex systems.

  12. The impact of working memory and the "process of process modelling" on model quality: Investigating experienced versus inexperienced modellers

    DEFF Research Database (Denmark)

    Martini, Markus; Pinggera, Jakob; Neurauter, Manuel

    2016-01-01

    of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling....... the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension...

  13. Thermomechanical model for NiTi shape memory wires

    Czech Academy of Sciences Publication Activity Database

    Frost, Miroslav; Sedlák, Petr; Sippola, M.; Šittner, Petr

    2010-01-01

    Roč. 19, č. 9 (2010), s. 1-10 ISSN 0964-1726 R&D Projects: GA MŠk(CZ) 1M06031; GA ČR(CZ) GA106/09/1573; GA ČR(CZ) GP106/09/P302; GA ČR GAP108/10/1296 Institutional research plan: CEZ:AV0Z20760514; CEZ:AV0Z10100520 Keywords : shape memory alloys * modeling * proportional loading Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 2.094, year: 2010 http://apps.isiknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=3&SID=U2fe5mHN9p3gHClCdF1&page=1&doc=1

  14. Bessel functions in mass action modeling of memories and remembrances

    Energy Technology Data Exchange (ETDEWEB)

    Freeman, Walter J. [Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720-3206 (United States); Capolupo, Antonio [Dipartimento di Fisica, E.R. Caianiello Universitá di Salerno, and INFN Gruppo collegato di Salerno, Fisciano 84084 (Italy); Kozma, Robert [Department of Mathematics, Memphis University, Memphis, TN 38152 (United States); Olivares del Campo, Andrés [The Blackett Laboratory, Imperial College London, Prince Consort Road, London SW7 2BZ (United Kingdom); Vitiello, Giuseppe, E-mail: vitiello@sa.infn.it [Dipartimento di Fisica, E.R. Caianiello Universitá di Salerno, and INFN Gruppo collegato di Salerno, Fisciano 84084 (Italy)

    2015-10-02

    Data from experimental observations of a class of neurological processes (Freeman K-sets) present functional distribution reproducing Bessel function behavior. We model such processes with couples of damped/amplified oscillators which provide time dependent representation of Bessel equation. The root loci of poles and zeros conform to solutions of K-sets. Some light is shed on the problem of filling the gap between the cellular level dynamics and the brain functional activity. Breakdown of time-reversal symmetry is related with the cortex thermodynamic features. This provides a possible mechanism to deduce lifetime of recorded memory. - Highlights: • We consider data from observations of impulse responses of cortex to electric shocks. • These data are fitted by Bessel functions which may be represented by couples of damped/amplified oscillators. • We study the data by using couples of damped/amplified oscillators. • We discuss lifetime and other properties of the considered brain processes.

  15. Through the Immune Looking Glass: A Model for Brain Memory Strategies.

    Directory of Open Access Journals (Sweden)

    Silvia eSánchez-Ramón

    2016-02-01

    Full Text Available The immune system (IS and the central nervous system (CNS are complex cognitive networks involved in defining the identity (self of the individual through recognition and memory processes that enable one to anticipate responses to stimuli. Brain memory has traditionally been classified as either implicit or explicit on psychological and anatomical grounds, with reminiscences of the evolutionarily-based innate-adaptive IS responses. Beyond the multineuronal networks of the CNS, we propose a theoretical model of brain memory integrating the CNS as a whole. This is achieved by analogical reasoning between the operational rules of recognition and memory processes in both systems, coupled to an evolutionary analysis. In this new model, the hippocampus is no longer specifically ascribed to explicit memory but rather it both becomes part of the innate (implicit memory system and tightly controls the explicit memory system. Alike the antigen presenting cells for the IS, the hippocampus would integrate transient and pseudo-specific (i.e. danger-fear memories and would drive the formation of long-term and highly specific or explicit memories (i.e. the taste of the Proust’s madeleine cake by the more complex and recent, evolutionarily speaking, neocortex. Experimental and clinical evidence is provided to support the model. We believe that the singularity of this model’s approximation could help to gain a better understanding of the mechanisms operating in brain memory strategies from a large-scale network perspective.

  16. Through the Immune Looking Glass: A Model for Brain Memory Strategies

    Science.gov (United States)

    Sánchez-Ramón, Silvia; Faure, Florence

    2016-01-01

    The immune system (IS) and the central nervous system (CNS) are complex cognitive networks involved in defining the identity (self) of the individual through recognition and memory processes that enable one to anticipate responses to stimuli. Brain memory has traditionally been classified as either implicit or explicit on psychological and anatomical grounds, with reminiscences of the evolutionarily-based innate-adaptive IS responses. Beyond the multineuronal networks of the CNS, we propose a theoretical model of brain memory integrating the CNS as a whole. This is achieved by analogical reasoning between the operational rules of recognition and memory processes in both systems, coupled to an evolutionary analysis. In this new model, the hippocampus is no longer specifically ascribed to explicit memory but rather it both becomes part of the innate (implicit) memory system and tightly controls the explicit memory system. Alike the antigen presenting cells for the IS, the hippocampus would integrate transient and pseudo-specific (i.e., danger-fear) memories and would drive the formation of long-term and highly specific or explicit memories (i.e., the taste of the Proust’s madeleine cake) by the more complex and recent, evolutionarily speaking, neocortex. Experimental and clinical evidence is provided to support the model. We believe that the singularity of this model’s approximation could help to gain a better understanding of the mechanisms operating in brain memory strategies from a large-scale network perspective. PMID:26869886

  17. Surface Soil Moisture Memory Estimated from Models and SMAP Observations

    Science.gov (United States)

    He, Q.; Mccoll, K. A.; Li, C.; Lu, H.; Akbar, R.; Pan, M.; Entekhabi, D.

    2017-12-01

    Soil moisture memory(SMM), which is loosely defined as the time taken by soil to forget an anomaly, has been proved to be important in land-atmosphere interaction. There are many metrics to calculate the SMM timescale, for example, the timescale based on the time-series autocorrelation, the timescale ignoring the soil moisture time series and the timescale which only considers soil moisture increment. Recently, a new timescale based on `Water Cycle Fraction' (Kaighin et al., 2017), in which the impact of precipitation on soil moisture memory is considered, has been put up but not been fully evaluated in global. In this study, we compared the surface SMM derived from SMAP observations with that from land surface model simulations (i.e., the SMAP Nature Run (NR) provided by the Goddard Earth Observing System, version 5) (Rolf et al., 2014). Three timescale metrics were used to quantify the surface SMM as: T0 based on the soil moisture time series autocorrelation, deT0 based on the detrending soil moisture time series autocorrelation, and tHalf based on the Water Cycle Fraction. The comparisons indicate that: (1) there are big gaps between the T0 derived from SMAP and that from NR (2) the gaps get small for deT0 case, in which the seasonality of surface soil moisture was removed with a moving average filter; (3) the tHalf estimated from SMAP is much closer to that from NR. The results demonstrate that surface SMM can vary dramatically among different metrics, while the memory derived from land surface model differs from the one from SMAP observation. tHalf, with considering the impact of precipitation, may be a good choice to quantify surface SMM and have high potential in studies related to land atmosphere interactions. References McColl. K.A., S.H. Alemohammad, R. Akbar, A.G. Konings, S. Yueh, D. Entekhabi. The Global Distribution and Dynamics of Surface Soil Moisture, Nature Geoscience, 2017 Reichle. R., L. Qing, D.L. Gabrielle, A. Joe. The "SMAP_Nature_v03" Data

  18. Episodic grammar: a computational model of the interaction between episodic and semantic memory in language processing

    NARCIS (Netherlands)

    Borensztajn, G.; Zuidema, W.; Carlson, L.; Hoelscher, C.; Shipley, T.F.

    2011-01-01

    We present a model of the interaction of semantic and episodic memory in language processing. Our work shows how language processing can be understood in terms of memory retrieval. We point out that the perceived dichotomy between rule-based versus exemplar-based language modelling can be

  19. A Buffer Model of Memory Encoding and Temporal Correlations in Retrieval

    Science.gov (United States)

    Lehman, Melissa; Malmberg, Kenneth J.

    2013-01-01

    Atkinson and Shiffrin's (1968) dual-store model of memory includes structural aspects of memory along with control processes. The rehearsal buffer is a process by which items are kept in mind and long-term episodic traces are formed. The model has been both influential and controversial. Here, we describe a novel variant of Atkinson and Shiffrin's…

  20. The retention characteristics of nonvolatile SNOS memory transistors in a radiation environment: Experiment and model

    International Nuclear Information System (INIS)

    McWhorter, P.J.; Miller, S.L.; Dellin, T.A.; Axness, C.L.

    1987-01-01

    Experimental data and a model to accurately and quantitatively predict the data are presented for retention of SNOS memory devices over a wide range of dose rates. A wide range of SNOS stack geometries are examined. The model is designed to aid in screening nonvolatile memories for use in a radiation environment

  1. Effects of adaptive degrees of trust on coevolution of quantum strategies on scale-free networks

    Science.gov (United States)

    Li, Qiang; Chen, Minyou; Perc, Matjaž; Iqbal, Azhar; Abbott, Derek

    2013-10-01

    We study the impact of adaptive degrees of trust on the evolution of cooperation in the quantum prisoner's dilemma game. In addition to the strategies, links between players are also subject to evolution. Starting with a scale-free interaction network, players adjust trust towards their neighbors based on received payoffs. The latter governs the strategy adoption process, while trust governs the rewiring of links. As soon as the degree of trust towards a neighbor drops to zero, the link is rewired to another randomly chosen player within the network. We find that for small temptations to defect cooperators always dominate, while for intermediate and strong temptations a single quantum strategy is able to outperform all other strategies. In general, reciprocal trust remains within close relationships and favors the dominance of a single strategy. Due to coevolution, the power-law degree distributions transform to Poisson distributions.

  2. The Medieval inquisition: scale-free networks and the suppression of heresy

    Science.gov (United States)

    Ormerod, Paul; Roach, Andrew P.

    2004-08-01

    Qualitative evidence suggests that heresy within the medieval Church had many of the characteristics of a scale-free network. From the perspective of the Church, heresy can be seen as an infectious disease. The disease persisted for long periods of time, breaking out again even when the Church believed it to have been eradicated. A principal mechanism of heresy was through a small number of individuals with very large numbers of social contacts. Initial attempts by the inquisition to suppress heresy by general persecution, or even mass slaughter, of populations thought to harbour the ‘disease’ failed. Gradually, however, inquisitors learned about the nature of the social networks by which heresy both spread and persisted. Eventually, a policy of targeting key individuals was implemented, which proved to be much more successful.

  3. Complex Quantum Network Manifolds in Dimension d > 2 are Scale-Free

    Science.gov (United States)

    Bianconi, Ginestra; Rahmede, Christoph

    2015-09-01

    In quantum gravity, several approaches have been proposed until now for the quantum description of discrete geometries. These theoretical frameworks include loop quantum gravity, causal dynamical triangulations, causal sets, quantum graphity, and energetic spin networks. Most of these approaches describe discrete spaces as homogeneous network manifolds. Here we define Complex Quantum Network Manifolds (CQNM) describing the evolution of quantum network states, and constructed from growing simplicial complexes of dimension . We show that in d = 2 CQNM are homogeneous networks while for d > 2 they are scale-free i.e. they are characterized by large inhomogeneities of degrees like most complex networks. From the self-organized evolution of CQNM quantum statistics emerge spontaneously. Here we define the generalized degrees associated with the -faces of the -dimensional CQNMs, and we show that the statistics of these generalized degrees can either follow Fermi-Dirac, Boltzmann or Bose-Einstein distributions depending on the dimension of the -faces.

  4. Improved routing strategies for data traffic in scale-free networks

    International Nuclear Information System (INIS)

    Wu, Zhi-Xi; Peng, Gang; Wong, Wing-Ming; Yeung, Kai-Hau

    2008-01-01

    We study the information packet routing process in scale-free networks by mimicking Internet traffic delivery. We incorporate both the global shortest paths information and local degree information of the network in the dynamic process, via two tunable parameters, α and β, to guide the packet routing. We measure the performance of the routing method by both the average transit times of packets and the critical packet generation rate (above which packet aggregation occurs in the network). We found that the routing strategies which integrate ingredients of both global and local topological information of the underlying networks perform much better than the traditional shortest path routing protocol taking into account the global topological information only. Moreover, by doing comparative studies with some related works, we found that the performance of our proposed method shows universal efficiency characteristic against the amount of traffic

  5. Efficiency of quarantine and self-protection processes in epidemic spreading control on scale-free networks

    Science.gov (United States)

    Esquivel-Gómez, Jose de Jesus; Barajas-Ramírez, Juan Gonzalo

    2018-01-01

    One of the most effective mechanisms to contain the spread of an infectious disease through a population is the implementation of quarantine policies. However, its efficiency is affected by different aspects, for example, the structure of the underlining social network where highly connected individuals are more likely to become infected; therefore, the speed of the transmission of the decease is directly determined by the degree distribution of the network. Another aspect that influences the effectiveness of the quarantine is the self-protection processes of the individuals in the population, that is, they try to avoid contact with potentially infected individuals. In this paper, we investigate the efficiency of quarantine and self-protection processes in preventing the spreading of infectious diseases over complex networks with a power-law degree distribution [ P ( k ) ˜ k - ν ] for different ν values. We propose two alternative scale-free models that result in power-law degree distributions above and below the exponent ν = 3 associated with the conventional Barabási-Albert model. Our results show that the exponent ν determines the effectiveness of these policies in controlling the spreading process. More precisely, we show that for the ν exponent below three, the quarantine mechanism loses effectiveness. However, the efficiency is improved if the quarantine is jointly implemented with a self-protection process driving the number of infected individuals significantly lower.

  6. Scale-free brain quartet: artistic filtering of multi-channel brainwave music.

    Science.gov (United States)

    Wu, Dan; Li, Chaoyi; Yao, Dezhong

    2013-01-01

    To listen to the brain activities as a piece of music, we proposed the scale-free brainwave music (SFBM) technology, which translated scalp EEGs into music notes according to the power law of both EEG and music. In the present study, the methodology was extended for deriving a quartet from multi-channel EEGs with artistic beat and tonality filtering. EEG data from multiple electrodes were first translated into MIDI sequences by SFBM, respectively. Then, these sequences were processed by a beat filter which adjusted the duration of notes in terms of the characteristic frequency. And the sequences were further filtered from atonal to tonal according to a key defined by the analysis of the original music pieces. Resting EEGs with eyes closed and open of 40 subjects were utilized for music generation. The results revealed that the scale-free exponents of the music before and after filtering were different: the filtered music showed larger variety between the eyes-closed (EC) and eyes-open (EO) conditions, and the pitch scale exponents of the filtered music were closer to 1 and thus it was more approximate to the classical music. Furthermore, the tempo of the filtered music with eyes closed was significantly slower than that with eyes open. With the original materials obtained from multi-channel EEGs, and a little creative filtering following the composition process of a potential artist, the resulted brainwave quartet opened a new window to look into the brain in an audible musical way. In fact, as the artistic beat and tonal filters were derived from the brainwaves, the filtered music maintained the essential properties of the brain activities in a more musical style. It might harmonically distinguish the different states of the brain activities, and therefore it provided a method to analyze EEGs from a relaxed audio perspective.

  7. Working memory contributes to the encoding of object location associations: Support for a 3-part model of object location memory.

    Science.gov (United States)

    Gillis, M Meredith; Garcia, Sarah; Hampstead, Benjamin M

    2016-09-15

    A recent model by Postma and colleagues posits that the encoding of object location associations (OLAs) requires the coordination of several cognitive processes mediated by ventral (object perception) and dorsal (spatial perception) visual pathways as well as the hippocampus (feature binding) [1]. Within this model, frontoparietal network recruitment is believed to contribute to both the spatial processing and working memory task demands. The current study used functional magnetic resonance imaging (fMRI) to test each step of this model in 15 participants who encoded OLAs and performed standard n-back tasks. As expected, object processing resulted in activation of the ventral visual stream. Object in location processing resulted in activation of both the ventral and dorsal visual streams as well as a lateral frontoparietal network. This condition was also the only one to result in medial temporal lobe activation, supporting its role in associative learning. A conjunction analysis revealed areas of shared activation between the working memory and object in location phase within the lateral frontoparietal network, anterior insula, and basal ganglia; consistent with prior working memory literature. Overall, findings support Postma and colleague's model and provide clear evidence for the role of working memory during OLA encoding. Published by Elsevier B.V.

  8. Quantitative metal magnetic memory reliability modeling for welded joints

    Science.gov (United States)

    Xing, Haiyan; Dang, Yongbin; Wang, Ben; Leng, Jiancheng

    2016-03-01

    Metal magnetic memory(MMM) testing has been widely used to detect welded joints. However, load levels, environmental magnetic field, and measurement noises make the MMM data dispersive and bring difficulty to quantitative evaluation. In order to promote the development of quantitative MMM reliability assessment, a new MMM model is presented for welded joints. Steel Q235 welded specimens are tested along the longitudinal and horizontal lines by TSC-2M-8 instrument in the tensile fatigue experiments. The X-ray testing is carried out synchronously to verify the MMM results. It is found that MMM testing can detect the hidden crack earlier than X-ray testing. Moreover, the MMM gradient vector sum K vs is sensitive to the damage degree, especially at early and hidden damage stages. Considering the dispersion of MMM data, the K vs statistical law is investigated, which shows that K vs obeys Gaussian distribution. So K vs is the suitable MMM parameter to establish reliability model of welded joints. At last, the original quantitative MMM reliability model is first presented based on the improved stress strength interference theory. It is shown that the reliability degree R gradually decreases with the decreasing of the residual life ratio T, and the maximal error between prediction reliability degree R 1 and verification reliability degree R 2 is 9.15%. This presented method provides a novel tool of reliability testing and evaluating in practical engineering for welded joints.

  9. Using visual lateralization to model learning and memory in zebrafish larvae.

    Science.gov (United States)

    Andersson, Madelene Åberg; Ek, Fredrik; Olsson, Roger

    2015-03-02

    Impaired learning and memory are common symptoms of neurodegenerative and neuropsychiatric diseases. Present, there are several behavioural test employed to assess cognitive functions in animal models, including the frequently used novel object recognition (NOR) test. However, although atypical functional brain lateralization has been associated with neuropsychiatric conditions, spanning from schizophrenia to autism, few animal models are available to study this phenomenon in learning and memory deficits. Here we present a visual lateralization NOR model (VLNOR) in zebrafish larvae as an assay that combines brain lateralization and NOR. In zebrafish larvae, learning and memory are generally assessed by habituation, sensitization, or conditioning paradigms, which are all representatives of nondeclarative memory. The VLNOR is the first model for zebrafish larvae that studies a memory similar to the declarative memory described for mammals. We demonstrate that VLNOR can be used to study memory formation, storage, and recall of novel objects, both short and long term, in 10-day-old zebrafish. Furthermore we show that the VLNOR model can be used to study chemical modulation of memory formation and maintenance using dizocilpine (MK-801), a frequently used non-competitive antagonist of the NMDA receptor, used to test putative antipsychotics in animal models.

  10. Scale-free animal movement patterns: Levy walks outperform fractional Brownian motions and fractional Levy motions in random search scenarios

    International Nuclear Information System (INIS)

    Reynolds, A M

    2009-01-01

    The movement patterns of a diverse range of animals have scale-free characteristics. These characteristics provide necessary but not sufficient conditions for the presence of movement patterns that can be approximated by Levy walks. Nevertheless, it has been widely assumed that the occurrence of scale-free animal movements can indeed be attributed to the presence of Levy walks. This is, in part, because it is known that the super-diffusive properties of Levy walks can be advantageous in random search scenarios when searchers have little or no prior knowledge of target locations. However, fractional Brownian motions (fBms) and fractional Levy motions (fLms) are both scale-free and super-diffusive, and so it is possible that these motions rather than Levy walks underlie some or all occurrences of scale-free animal movement patterns. Here this possibility is examined in numerical simulations through a determination of the searching efficiencies of fBm and fLm searches. It is shown that these searches are less efficient than Levy walk searches. This finding does not rule out the possibility that some animals with scale-free movement patterns are executing fBm and fLm searches, but it does make Levy walk searches the more likely possibility.

  11. The MNESIS model: Memory systems and processes, identity and future thinking.

    Science.gov (United States)

    Eustache, Francis; Viard, Armelle; Desgranges, Béatrice

    2016-07-01

    The Memory NEo-Structural Inter-Systemic model (MNESIS; Eustache and Desgranges, Neuropsychology Review, 2008) is a macromodel based on neuropsychological data which presents an interactive construction of memory systems and processes. Largely inspired by Tulving's SPI model, MNESIS puts the emphasis on the existence of different memory systems in humans and their reciprocal relations, adding new aspects, such as the episodic buffer proposed by Baddeley. The more integrative comprehension of brain dynamics offered by neuroimaging has contributed to rethinking the existence of memory systems. In the present article, we will argue that understanding the concept of memory by dividing it into systems at the functional level is still valid, but needs to be considered in the light of brain imaging. Here, we reinstate the importance of this division in different memory systems and illustrate, with neuroimaging findings, the links that operate between memory systems in response to task demands that constrain the brain dynamics. During a cognitive task, these memory systems interact transiently to rapidly assemble representations and mobilize functions to propose a flexible and adaptative response. We will concentrate on two memory systems, episodic and semantic memory, and their links with autobiographical memory. More precisely, we will focus on interactions between episodic and semantic memory systems in support of 1) self-identity in healthy aging and in brain pathologies and 2) the concept of the prospective brain during future projection. In conclusion, this MNESIS global framework may help to get a general representation of human memory and its brain implementation with its specific components which are in constant interaction during cognitive processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. A Multivariate Asymmetric Long Memory Conditional Volatility Model with X, Regularity and Asymptotics

    NARCIS (Netherlands)

    M. Asai (Manabu); M.J. McAleer (Michael)

    2016-01-01

    textabstractThe paper derives a Multivariate Asymmetric Long Memory conditional volatility model with Exogenous Variables (X), or the MALMX model, with dynamic conditional correlations, appropriate regularity conditions, and associated asymptotic theory. This enables checking of internal consistency

  13. Working Memory Capacity and Categorization: Individual Differences and Modeling

    Science.gov (United States)

    Lewandowsky, Stephan

    2011-01-01

    Working memory is crucial for many higher-level cognitive functions, ranging from mental arithmetic to reasoning and problem solving. Likewise, the ability to learn and categorize novel concepts forms an indispensable part of human cognition. However, very little is known about the relationship between working memory and categorization, and…

  14. Dynamic Memory Model for Non-Stationary Optimization

    DEFF Research Database (Denmark)

    Bendtsen, Claus Nørgaard; Krink, Thiemo

    2002-01-01

    Real-world problems are often nonstationary and can cause cyclic, repetitive patterns in the search landscape. For this class of problems, we introduce a new GA with dynamic explicit memory, which showed superior performance compared to a classic GA and a previously introduced memory-based GA for...

  15. Modeling and Predistortion of Envelope Tracking Power Amplifiers using a Memory Binomial Model

    DEFF Research Database (Denmark)

    Tafuri, Felice Francesco; Sira, Daniel; Larsen, Torben

    2013-01-01

    . The model definition is based on binomial series, hence the name of memory binomial model (MBM). The MBM is here applied to measured data-sets acquired from an ET measurement set-up. When used as a PA model the MBM showed an NMSE (Normalized Mean Squared Error) as low as −40dB and an ACEPR (Adjacent Channel...... Error Power Ratio) below −51 dB. The simulated predistortion results showed that the MBM can improve the compensation of distortion in the adjacent channel of 5.8 dB and 5.7 dB compared to a memory polynomial predistorter (MPPD). The predistortion performance in the time domain showed an NMSE...

  16. Working Memory Span Development: A Time-Based Resource-Sharing Model Account

    Science.gov (United States)

    Barrouillet, Pierre; Gavens, Nathalie; Vergauwe, Evie; Gaillard, Vinciane; Camos, Valerie

    2009-01-01

    The time-based resource-sharing model (P. Barrouillet, S. Bernardin, & V. Camos, 2004) assumes that during complex working memory span tasks, attention is frequently and surreptitiously switched from processing to reactivate decaying memory traces before their complete loss. Three experiments involving children from 5 to 14 years of age…

  17. Models of Verbal Working Memory Capacity: What Does It Take to Make Them Work?

    Science.gov (United States)

    Cowan, Nelson; Rouder, Jeffrey N.; Blume, Christopher L.; Saults, J. Scott

    2012-01-01

    Theories of working memory (WM) capacity limits will be more useful when we know what aspects of performance are governed by the limits and what aspects are governed by other memory mechanisms. Whereas considerable progress has been made on models of WM capacity limits for visual arrays of separate objects, less progress has been made in…

  18. Mental model construction, not just memory, is a central component of cognitive change in psychotherapy.

    Science.gov (United States)

    von Hecker, Ulrich; McIntosh, Daniel N; Sedek, Grzegorz

    2015-01-01

    We challenge the idea that a cognitive perspective on therapeutic change concerns only memory processes. We argue that inclusion of impairments in more generative cognitive processes is necessary for complete understanding of cases such as depression. In such cases what is identified in the target article as an "integrative memory structure" is crucially supported by processes of mental model construction.

  19. Recent Progress on Modeling Slip Deformation in Shape Memory Alloys

    Science.gov (United States)

    Sehitoglu, H.; Alkan, S.

    2018-03-01

    This paper presents an overview of slip deformation in shape memory alloys. The performance of shape memory alloys depends on their slip resistance often quantified through the Critical Resolved Shear Stress (CRSS) or the flow stress. We highlight previous studies that identify the active slip systems and then proceed to show how non- Schmid effects can be dominant in shape memory slip behavior. The work is mostly derived from our recent studies while we highlight key earlier works on slip deformation. We finally discuss the implications of understanding the role of slip on curtailing the transformation strains and also the temperature range over which superelasticity prevails.

  20. Recent Progress on Modeling Slip Deformation in Shape Memory Alloys

    Science.gov (United States)

    Sehitoglu, H.; Alkan, S.

    2018-03-01

    This paper presents an overview of slip deformation in shape memory alloys. The performance of shape memory alloys depends on their slip resistance often quantified through the Critical Resolved Shear Stress (CRSS) or the flow stress. We highlight previous studies that identify the active slip systems and then proceed to show how non-Schmid effects can be dominant in shape memory slip behavior. The work is mostly derived from our recent studies while we highlight key earlier works on slip deformation. We finally discuss the implications of understanding the role of slip on curtailing the transformation strains and also the temperature range over which superelasticity prevails.

  1. Memory sparing, fast scattering formalism for rigorous diffraction modeling

    Science.gov (United States)

    Iff, W.; Kämpfe, T.; Jourlin, Y.; Tishchenko, A. V.

    2017-07-01

    The basics and algorithmic steps of a novel scattering formalism suited for memory sparing and fast electromagnetic calculations are presented. The formalism, called ‘S-vector algorithm’ (by analogy with the known scattering-matrix algorithm), allows the calculation of the collective scattering spectra of individual layered micro-structured scattering objects. A rigorous method of linear complexity is applied to model the scattering at individual layers; here the generalized source method (GSM) resorting to Fourier harmonics as basis functions is used as one possible method of linear complexity. The concatenation of the individual scattering events can be achieved sequentially or in parallel, both having pros and cons. The present development will largely concentrate on a consecutive approach based on the multiple reflection series. The latter will be reformulated into an implicit formalism which will be associated with an iterative solver, resulting in improved convergence. The examples will first refer to 1D grating diffraction for the sake of simplicity and intelligibility, with a final 2D application example.

  2. Human processor modelling language (HPML): Estimate working memory load through interaction

    OpenAIRE

    Geisler, J.; Scheben, C.

    2007-01-01

    To operate machines over their user interface may cause high load on human's working memory. This load can decrease performance in the working task significantly if this task is a cognitive challenging one, e. g. diagnosis. With the »Human Processor Modelling Language« (HPML) the interaction activity can be modelled with a directed graph. From such models a condensed indicator value for working memory load can be estimated. Thus different user interface solutions can get compared with respect...

  3. A dynamic routing strategy with limited buffer on scale-free network

    Science.gov (United States)

    Wang, Yufei; Liu, Feng

    2016-04-01

    In this paper, we propose an integrated routing strategy based on global static topology information and local dynamic data packet queue lengths to improve the transmission efficiency of scale-free networks. The proposed routing strategy is a combination of a global static routing strategy (based on the shortest path algorithm) and local dynamic queue length management, in which, instead of using an infinite buffer, the queue length of each node i in the proposed routing strategy is limited by a critical queue length Qic. When the network traffic is lower and the queue length of each node i is shorter than its critical queue length Qic, it forwards packets according to the global routing table. With increasing network traffic, when the buffers of the nodes with higher degree are full, they do not receive packets due to their limited buffers and the packets have to be delivered to the nodes with lower degree. The global static routing strategy can shorten the transmission time that it takes a packet to reach its destination, and the local limited queue length can balance the network traffic. The optimal critical queue lengths of nodes have been analysed. Simulation results show that the proposed routing strategy can get better performance than that of the global static strategy based on topology, and almost the same performance as that of the global dynamic routing strategy with less complexity.

  4. Efficient routing on scale-free networks based on local information

    International Nuclear Information System (INIS)

    Yin Chuanyang; Wang Binghong; Wang Wenxu; Zhou Tao; Yang Huijie

    2006-01-01

    In this Letter, we propose a new routing strategy with a single tunable parameter α only based on local information of network topology. The probability that a given node i with degree k i receives packets from its neighbors is proportional to k i α . In order to maximize the packets handling capacity of underlying structure that can be measured by the critical point of continuous phase transition from free flow to congestion, the optimal value of α is sought out. Through investigating the distributions of queue length on each node in free state, we give an explanation why the delivering capacity of the network can be enhanced by choosing the optimal α. Furthermore, dynamic properties right after the critical point are also studied. Interestingly, it is found that although the system enters the congestion state, it still possesses partial delivering capability which does not depend on α. This phenomenon suggests that the capacity of the scale-free network can be enhanced by increasing the forwarding ability of small important nodes which bear severe congestion

  5. Fractional parentage analysis and a scale-free reproductive network of brown trout.

    Science.gov (United States)

    Koyano, Hitoshi; Serbezov, Dimitar; Kishino, Hirohisa; Schweder, Tore

    2013-11-07

    In this study, we developed a method of fractional parentage analysis using microsatellite markers. We propose a method for calculating parentage probability, which considers missing data and genotyping errors due to null alleles and other causes, by regarding observed alleles as realizations of random variables which take values in the set of alleles at the locus and developing a method for simultaneously estimating the true and null allele frequencies of all alleles at each locus. We then applied our proposed method to a large sample collected from a wild population of brown trout (Salmo trutta). On analyzing the data using our method, we found that the reproductive success of brown trout obeyed a power law, indicating that when the parent-offspring relationship is regarded as a link, the reproductive system of brown trout is a scale-free network. Characteristics of the reproductive network of brown trout include individuals with large bodies as hubs in the network and different power exponents of degree distributions between males and females. © 2013 Elsevier Ltd. All rights reserved.

  6. Cascading Dynamics of Heterogenous Scale-Free Networks with Recovery Mechanism

    Directory of Open Access Journals (Sweden)

    Shudong Li

    2013-01-01

    Full Text Available In network security, how to use efficient response methods against cascading failures of complex networks is very important. In this paper, concerned with the highest-load attack (HL and random attack (RA on one edge, we define five kinds of weighting strategies to assign the external resources for recovering the edges from cascading failures in heterogeneous scale-free (SF networks. The influence of external resources, the tolerance parameter, and the different weighting strategies on SF networks against cascading failures is investigated carefully. We find that, under HL attack, the fourth kind of weighting method can more effectively improve the integral robustness of SF networks, simultaneously control the spreading velocity, and control the outburst of cascading failures in SF networks than other methods. Moreover, the third method is optimal if we only knew the local structure of SF networks and the uniform assignment is the worst. The simulations of the real-world autonomous system in, Internet have also supported our findings. The results are useful for using efficient response strategy against the emergent accidents and controlling the cascading failures in the real-world networks.

  7. Formation of model-free motor memories during motor adaptation depends on perturbation schedule.

    Science.gov (United States)

    Orban de Xivry, Jean-Jacques; Lefèvre, Philippe

    2015-04-01

    Motor adaptation to an external perturbation relies on several mechanisms such as model-based, model-free, strategic, or repetition-dependent learning. Depending on the experimental conditions, each of these mechanisms has more or less weight in the final adaptation state. Here we focused on the conditions that lead to the formation of a model-free motor memory (Huang VS, Haith AM, Mazzoni P, Krakauer JW. Neuron 70: 787-801, 2011), i.e., a memory that does not depend on an internal model or on the size or direction of the errors experienced during the learning. The formation of such model-free motor memory was hypothesized to depend on the schedule of the perturbation (Orban de Xivry JJ, Ahmadi-Pajouh MA, Harran MD, Salimpour Y, Shadmehr R. J Neurophysiol 109: 124-136, 2013). Here we built on this observation by directly testing the nature of the motor memory after abrupt or gradual introduction of a visuomotor rotation, in an experimental paradigm where the presence of model-free motor memory can be identified (Huang VS, Haith AM, Mazzoni P, Krakauer JW. Neuron 70: 787-801, 2011). We found that relearning was faster after abrupt than gradual perturbation, which suggests that model-free learning is reduced during gradual adaptation to a visuomotor rotation. In addition, the presence of savings after abrupt introduction of the perturbation but gradual extinction of the motor memory suggests that unexpected errors are necessary to induce a model-free motor memory. Overall, these data support the hypothesis that different perturbation schedules do not lead to a more or less stabilized motor memory but to distinct motor memories with different attributes and neural representations. Copyright © 2015 the American Physiological Society.

  8. The multi-component model of working memory: explorations in experimental cognitive psychology.

    Science.gov (United States)

    Repovs, G; Baddeley, A

    2006-04-28

    There are a number of ways one can hope to describe and explain cognitive abilities, each of them contributing a unique and valuable perspective. Cognitive psychology tries to develop and test functional accounts of cognitive systems that explain the capacities and properties of cognitive abilities as revealed by empirical data gathered by a range of behavioral experimental paradigms. Much of the research in the cognitive psychology of working memory has been strongly influenced by the multi-component model of working memory [Baddeley AD, Hitch GJ (1974) Working memory. In: Recent advances in learning and motivation, Vol. 8 (Bower GA, ed), pp 47-90. New York: Academic Press; Baddeley AD (1986) Working memory. Oxford, UK: Clarendon Press; Baddeley A. Working memory: Thought and action. Oxford: Oxford University Press, in press]. By expanding the notion of a passive short-term memory to an active system that provides the basis for complex cognitive abilities, the model has opened up numerous questions and new lines of research. In this paper we present the current revision of the multi-component model that encompasses a central executive, two unimodal storage systems: a phonological loop and a visuospatial sketchpad, and a further component, a multimodal store capable of integrating information into unitary episodic representations, termed episodic buffer. We review recent empirical data within experimental cognitive psychology that has shaped the development of the multicomponent model and the understanding of the capacities and properties of working memory. Research based largely on dual-task experimental designs and on neuropsychological evidence has yielded valuable information about the fractionation of working memory into independent stores and processes, the nature of representations in individual stores, the mechanisms of their maintenance and manipulation, the way the components of working memory relate to each other, and the role they play in other

  9. A process-model based approach to prospective memory impairment in Parkinson's disease.

    Science.gov (United States)

    Kliegel, Matthias; Altgassen, Mareike; Hering, Alexandra; Rose, Nathan S

    2011-07-01

    The present review discusses the current state of research on the clinical neuropsychology of prospective memory in Parkinson's disease. To do so the paper is divided in two sections. In the first section, we briefly outline key features of the (partly implicit) rationale underlying the available literature on the clinical neuropsychology of prospective memory. Here, we present a conceptual model that guides our approach to the clinical neuropsychology of prospective memory in general and to the effects of Parkinson's disease on prospective memory in particular. In the second section, we use this model to guide our review of the available literature and suggest some open issues and future directions motivated by previous findings and the proposed conceptual model. The review suggests that certain phases of the prospective memory process (intention formation und initiation) are particularly impaired by Parkinson's disease. In addition, it is argued that prospective memory may be preserved when tasks involve specific features (e.g., focal cues) that reduce the need for strategic monitoring processes. In terms of suggestions for future directions, it is noted that intervention studies are needed which target the specific phases of the prospective memory process that are impaired in Parkinson's disease, such as planning interventions. Moreover, it is proposed that prospective memory deficits in Parkinson's disease should be explored in the context of a general impairment in the ability to form an intention and plan or coordinate an appropriate series of actions. Copyright © 2011 Elsevier Ltd. All rights reserved.

  10. A unitary signal-detection model of implicit and explicit memory.

    Science.gov (United States)

    Berry, Christopher J; Shanks, David R; Henson, Richard N A

    2008-10-01

    Do dissociations imply independent systems? In the memory field, the view that there are independent implicit and explicit memory systems has been predominantly supported by dissociation evidence. Here, we argue that many of these dissociations do not necessarily imply distinct memory systems. We review recent work with a single-system computational model that extends signal-detection theory (SDT) to implicit memory. SDT has had a major influence on research in a variety of domains. The current work shows that it can be broadened even further in its range of application. Indeed, the single-system model that we present does surprisingly well in accounting for some key dissociations that have been taken as evidence for independent implicit and explicit memory systems.

  11. Why are you telling me that? A conceptual model of the social function of autobiographical memory.

    Science.gov (United States)

    Alea, Nicole; Bluck, Susan

    2003-03-01

    In an effort to stimulate and guide empirical work within a functional framework, this paper provides a conceptual model of the social functions of autobiographical memory (AM) across the lifespan. The model delineates the processes and variables involved when AMs are shared to serve social functions. Components of the model include: lifespan contextual influences, the qualitative characteristics of memory (emotionality and level of detail recalled), the speaker's characteristics (age, gender, and personality), the familiarity and similarity of the listener to the speaker, the level of responsiveness during the memory-sharing process, and the nature of the social relationship in which the memory sharing occurs (valence and length of the relationship). These components are shown to influence the type of social function served and/or, the extent to which social functions are served. Directions for future empirical work to substantiate the model and hypotheses derived from the model are provided.

  12. Nonlinear Model of Pseudoelastic Shape Memory Alloy Damper Considering Residual Martensite Strain Effect

    Directory of Open Access Journals (Sweden)

    Y. M. Parulekar

    2012-01-01

    Full Text Available Recently, there has been increasing interest in using superelastic shape memory alloys for applications in seismic resistant-design. Shape memory alloys (SMAs have a unique property by which they can recover their original shape after experiencing large strains up to 8% either by heating (shape memory effect or removing stress (pseudoelastic effect. Many simplified shape memory alloy models are suggested in the past literature for capturing the pseudoelastic response of SMAs in passive vibration control of structures. Most of these models do not consider the cyclic effects of SMA's and resulting residual martensite deformation. Therefore, a suitable constitutive model of shape memory alloy damper which represents the nonlinear hysterical dynamic system appropriately is essential. In this paper a multilinear hysteretic model incorporating residual martensite strain effect of pseudoelastic shape memory alloy damper is developed and experimentally validated using SMA wire, based damper device. A sensitivity analysis is done using the proposed model along with three other simplified SMA models. The models are implemented on a steel frame representing an SDOF system and the comparison of seismic response of structure with all the models is made in the numerical study.

  13. Activation and Binding in Verbal Working Memory: A Dual-Process Model for the Recognition of Nonwords

    Science.gov (United States)

    Oberauer, Klauss; Lange, Elke B.

    2009-01-01

    The article presents a mathematical model of short-term recognition based on dual-process models and the three-component theory of working memory [Oberauer, K. (2002). Access to information in working memory: Exploring the focus of attention. "Journal of Experimental Psychology: Learning, Memory, and Cognition, 28", 411-421]. Familiarity arises…

  14. Method of computer generation and projection recording of microholograms for holographic memory systems: mathematical modelling and experimental implementation

    International Nuclear Information System (INIS)

    Betin, A Yu; Bobrinev, V I; Evtikhiev, N N; Zherdev, A Yu; Zlokazov, E Yu; Lushnikov, D S; Markin, V V; Odinokov, S B; Starikov, S N; Starikov, R S

    2013-01-01

    A method of computer generation and projection recording of microholograms for holographic memory systems is presented; the results of mathematical modelling and experimental implementation of the method are demonstrated. (holographic memory)

  15. A Preisach type model for temperature driven hysteresis memory erasure in shape memory materials

    Czech Academy of Sciences Publication Activity Database

    Kopfová, J.; Krejčí, Pavel

    2011-01-01

    Roč. 23, č. 2 (2011), s. 125-137 ISSN 0935-1175 R&D Projects: GA ČR GAP201/10/2315 Institutional research plan: CEZ:AV0Z10190503 Keywords : shape memory * hysteresis * thermodynamical consistency * uniform convergence Subject RIV: BA - General Mathematics Impact factor: 1.310, year: 2011 http://www.springerlink.com/content/6325635691ku0477/

  16. Statistical evaluation of waveform collapse reveals scale-free properties of neuronal avalanches

    Directory of Open Access Journals (Sweden)

    Aleena eShaukat

    2016-04-01

    Full Text Available Neural avalanches are a prominent form of brain activity characterized by network-wide bursts whose statistics follow a power-law distribution with a slope near 3/2. Recent work suggests that avalanches of different durations can be rescaled and thus collapsed together. This collapse mirrors work in statistical physics where it is proposed to form a signature of systems evolving in a critical state. However, no rigorous statistical test has been proposed to examine the degree to which neuronal avalanches collapse together. Here, we describe a statistical test based on functional data analysis, where raw avalanches are first smoothed with a Fourier basis, then rescaled using a time-warping function. Finally, an F ratio test combined with a bootstrap permutation is employed to determine if avalanches collapse together in a statistically reliable fashion. To illustrate this approach, we recorded avalanches from cortical cultures on multielectrode arrays as in previous work. Analyses show that avalanches of various durations can be collapsed together in a statistically robust fashion. However, a principal components analysis revealed that the offset of avalanches resulted in marked variance in the time-warping function, thus arguing for limitations to the strict fractal nature of avalanche dynamics. We compared these results with those obtained from cultures treated with an AMPA/NMDA receptor antagonist (APV/DNQX, which yield a power-law of avalanche durations with a slope greater than 3/2. When collapsed together, these avalanches showed marked misalignments both at onset and offset time-points. In sum, the proposed statistical evaluation suggests the presence of scale-free avalanche waveforms and constitutes an avenue for examining critical dynamics in neuronal systems.

  17. Modeling of mechanical properties for ferrous shape memory alloy

    International Nuclear Information System (INIS)

    Wada, Manabu; Ide, Yusuke; Mizote, Shinichiro; Naoi, Hisashi; Tsukimori, Kazuyuki

    2002-08-01

    In order to acquire technical data that are necessary for manufacture and design of the simulation test device for analyzing the core mechanics of Fast Breeder Reactor, ferrous shape memory alloy of Fe-28%Mn-6%Si-5%Cr is melted, forged and heat-treated. The microstructures are austenite. The specimens are deformed of up to 16% work-strain by tensile and compressive test, resulting in appearance of epsilon-martensite that is induced by stress. Then, heating at 673K for 10 minutes causes austenitic transformation from epsilon-martensite and shape memory strains are measured. We also investigate shape memory character of specimens, which are given, so called 'training treatment' of 5% pre-strain and recovery heat treatment. As a result, there is little difference between tensile and compressive test without training treatment and shape memory strain is 2% after being given 5% work-strain and recovery heat treatment. On the other hand, training treatment is remarkable and shape memory strain reaches to 3.7% after 5% work-strain. We analyze shape recovery character of this alloy specimen at three-point bending by using finite element method, and indicate possibility that its deformation behavior can be estimated from mechanical properties' data obtained at tensile and compressive test. (author)

  18. Modeling High Frequency Data with Long Memory and Structural Change: A-HYEGARCH Model

    Directory of Open Access Journals (Sweden)

    Yanlin Shi

    2018-03-01

    Full Text Available In this paper, we propose an Adaptive Hyperbolic EGARCH (A-HYEGARCH model to estimate the long memory of high frequency time series with potential structural breaks. Based on the original HYGARCH model, we use the logarithm transformation to ensure the positivity of conditional variance. The structural change is further allowed via a flexible time-dependent intercept in the conditional variance equation. To demonstrate its effectiveness, we perform a range of Monte Carlo studies considering various data generating processes with and without structural changes. Empirical testing of the A-HYEGARCH model is also conducted using high frequency returns of S&P 500, FTSE 100, ASX 200 and Nikkei 225. Our simulation and empirical evidence demonstrate that the proposed A-HYEGARCH model outperforms various competing specifications and can effectively control for structural breaks. Therefore, our model may provide more reliable estimates of long memory and could be a widely useful tool for modelling financial volatility in other contexts.

  19. Spatial But Not Oculomotor Information Biases Perceptual Memory: Evidence From Face Perception and Cognitive Modeling.

    Science.gov (United States)

    Wantz, Andrea L; Lobmaier, Janek S; Mast, Fred W; Senn, Walter

    2017-08-01

    Recent research put forward the hypothesis that eye movements are integrated in memory representations and are reactivated when later recalled. However, "looking back to nothing" during recall might be a consequence of spatial memory retrieval. Here, we aimed at distinguishing between the effect of spatial and oculomotor information on perceptual memory. Participants' task was to judge whether a morph looked rather like the first or second previously presented face. Crucially, faces and morphs were presented in a way that the morph reactivated oculomotor and/or spatial information associated with one of the previously encoded faces. Perceptual face memory was largely influenced by these manipulations. We considered a simple computational model with an excellent match (4.3% error) that expresses these biases as a linear combination of recency, saccade, and location. Surprisingly, saccades did not play a role. The results suggest that spatial and temporal rather than oculomotor information biases perceptual face memory. Copyright © 2016 Cognitive Science Society, Inc.

  20. Memory Effects and Coverage Dependence of Surface Diffusion in a Model Adsorption System

    DEFF Research Database (Denmark)

    Vattulainen, Ilpo Tapio; Ying, S. C.; Ala-Nissila, T.

    1999-01-01

    in tracer and collective diffusion. We show that memory effects can be very pronounced deep inside the ordered phases and in regions close to first and second order phase transition boundaries. Particular attention is paid to the details of the time dependence of memory effects. The memory effect in tracer......We study the coverage dependence of surface diffusion coefficients for a strongly interacting adsorption system O/W(110) via Monte Carlo simulations of a lattice-gas model. In particular, we consider the nature and emergence of memory effects as contained in the corresponding correlation factors...... diffusion is found to decay following a power law after an initial transient period. This behavior persists until the hydrodynamic regime is reached, after which the memory effect decays exponentially. The time required to reach the hydrodynamical regime and the related exponential decay is strongly...

  1. A single-system model predicts recognition memory and repetition priming in amnesia.

    Science.gov (United States)

    Berry, Christopher J; Kessels, Roy P C; Wester, Arie J; Shanks, David R

    2014-08-13

    We challenge the claim that there are distinct neural systems for explicit and implicit memory by demonstrating that a formal single-system model predicts the pattern of recognition memory (explicit) and repetition priming (implicit) in amnesia. In the current investigation, human participants with amnesia categorized pictures of objects at study and then, at test, identified fragmented versions of studied (old) and nonstudied (new) objects (providing a measure of priming), and made a recognition memory judgment (old vs new) for each object. Numerous results in the amnesic patients were predicted in advance by the single-system model, as follows: (1) deficits in recognition memory and priming were evident relative to a control group; (2) items judged as old were identified at greater levels of fragmentation than items judged new, regardless of whether the items were actually old or new; and (3) the magnitude of the priming effect (the identification advantage for old vs new items) overall was greater than that of items judged new. Model evidence measures also favored the single-system model over two formal multiple-systems models. The findings support the single-system model, which explains the pattern of recognition and priming in amnesia primarily as a reduction in the strength of a single dimension of memory strength, rather than a selective explicit memory system deficit. Copyright © 2014 the authors 0270-6474/14/3410963-12$15.00/0.

  2. Superdiffusion in a non-Markovian random walk model with a Gaussian memory profile

    Science.gov (United States)

    Borges, G. M.; Ferreira, A. S.; da Silva, M. A. A.; Cressoni, J. C.; Viswanathan, G. M.; Mariz, A. M.

    2012-09-01

    Most superdiffusive Non-Markovian random walk models assume that correlations are maintained at all time scales, e.g., fractional Brownian motion, Lévy walks, the Elephant walk and Alzheimer walk models. In the latter two models the random walker can always "remember" the initial times near t = 0. Assuming jump size distributions with finite variance, the question naturally arises: is superdiffusion possible if the walker is unable to recall the initial times? We give a conclusive answer to this general question, by studying a non-Markovian model in which the walker's memory of the past is weighted by a Gaussian centered at time t/2, at which time the walker had one half the present age, and with a standard deviation σt which grows linearly as the walker ages. For large widths we find that the model behaves similarly to the Elephant model, but for small widths this Gaussian memory profile model behaves like the Alzheimer walk model. We also report that the phenomenon of amnestically induced persistence, known to occur in the Alzheimer walk model, arises in the Gaussian memory profile model. We conclude that memory of the initial times is not a necessary condition for generating (log-periodic) superdiffusion. We show that the phenomenon of amnestically induced persistence extends to the case of a Gaussian memory profile.

  3. Deception and Cognitive Load: Expanding our Horizon with a Working Memory Model

    Directory of Open Access Journals (Sweden)

    Siegfried Ludwig Sporer

    2016-04-01

    Full Text Available Deception and Cognitive Load: Expanding our Horizon with a Working Memory ModelAbstractRecently, studies on deception and its detection have increased dramatically. Many of these studies rely on the cognitive load approach as the sole explanatory principle to understand deception. These studies have been exclusively on lies about negative actions (usually lies of suspects of [mock] crimes. Instead, we need to re-focus more generally on the cognitive processes involved in generating both lies and truths, not just on manipulations of cognitive load. Using Baddeley's (2000, 2007, 2012 working memory model, which integrates verbal and visual processes in working memory with retrieval from long-term memory and control of action, not only verbal content cues but also nonverbal, paraverbal and linguistic cues can be investigated within a single framework. The proposed model considers long-term semantic, episodic and autobiographical memory and their connections with working memory and action. It also incorporates ironic processes of mental control (Wegner, 1994, 2009, the role of scripts and schemata and retrieval cues and retrieval processes. Specific predictions of the model are outlined and support from selective studies is presented. The model is applicable to different types of reports, particularly about lies and truths about complex events, and to different modes of production (oral, hand-written, typed. Predictions regarding several moderator variables and methods to investigate them are proposed.

  4. Object selection costs in visual working memory: A diffusion model analysis of the focus of attention.

    Science.gov (United States)

    Sewell, David K; Lilburn, Simon D; Smith, Philip L

    2016-11-01

    A central question in working memory research concerns the degree to which information in working memory is accessible to other cognitive processes (e.g., decision-making). Theories assuming that the focus of attention can only store a single object at a time require the focus to orient to a target representation before further processing can occur. The need to orient the focus of attention implies that single-object accounts typically predict response time costs associated with object selection even when working memory is not full (i.e., memory load is less than 4 items). For other theories that assume storage of multiple items in the focus of attention, predictions depend on specific assumptions about the way resources are allocated among items held in the focus, and how this affects the time course of retrieval of items from the focus. These broad theoretical accounts have been difficult to distinguish because conventional analyses fail to separate components of empirical response times related to decision-making from components related to selection and retrieval processes associated with accessing information in working memory. To better distinguish these response time components from one another, we analyze data from a probed visual working memory task using extensions of the diffusion decision model. Analysis of model parameters revealed that increases in memory load resulted in (a) reductions in the quality of the underlying stimulus representations in a manner consistent with a sample size model of visual working memory capacity and (b) systematic increases in the time needed to selectively access a probed representation in memory. The results are consistent with single-object theories of the focus of attention. The results are also consistent with a subset of theories that assume a multiobject focus of attention in which resource allocation diminishes both the quality and accessibility of the underlying representations. (PsycINFO Database Record (c) 2016

  5. Memory in cultured cortical networks: experiment and modeling

    NARCIS (Netherlands)

    Witteveen, Tim; van Veenendaal, Tamar; le Feber, Jakob; Sergeev, A.

    The mechanism behind memory is one of the mysteries in neuroscience. Here we unravel part of the mechanism by showing that cultured neuronal networks develop an activity connectivity balance. External inputs disturb this balance and induce connectivity changes. The new connectivity is no longer

  6. Memory enhancement by Tamoxifen on amyloidosis mouse model.

    Science.gov (United States)

    Pandey, Deepika; Banerjee, Sugato; Basu, Mahua; Mishra, Nibha

    2016-03-01

    Tamoxifen (TMX) is a selective estrogen receptor modulator (SERM) used in the treatment of breast cancer. Earlier studies show its neuroprotection via regulating apoptosis, microglial functions, and synaptic plasticity. TMX also showed memory enhancement in ovariectomized mice, and protection from amyloid induced damage in hippocampal cell line. These reports encouraged us to explore the role of TMX in relevance to Alzheimer's disease (AD). We report here, the effect of TMX treatment a) on memory, and b) levels of neurotransmitters (acetylcholine (ACh) and dopamine (DA)) in breeding-retired-female mice injected with beta amyloid1-42 (Aβ1-42). Mice were treated with TMX (10mg/kg, i.p.) for 15 days. In Morris water maze test, the TMX treated mice escape latency decreased during training trials. They also spent longer time in the platform quadrant on probe trial, compared to controls. In Passive avoidance test, TMX treated mice avoided stepping on the shock chamber. This suggests that TMX protects memory from Aβ induced toxicity. In frontal cortex, ACh was moderately increased, with TMX treatment. In striatum, dopamine was significantly increased, 3,4-dihydroxyphenylacetic acid (DOPAC) level and DOPAC/DA ratio was decreased post TMX treatment. Therefore, TMX enhances spatial and contextual memory by reducing dopamine metabolism and increasing ACh level in Aβ1-42 injected-breeding-retired-female mice. Copyright © 2015. Published by Elsevier Inc.

  7. Dataflow models for shared memory access latency analysis

    NARCIS (Netherlands)

    Staschulat, Jan; Bekooij, Marco Jan Gerrit

    2009-01-01

    Performance analysis of applications in multi-core platforms is challenging because of temporal interference while accessing shared resources. Especially, memory arbiters introduce a non-constant delay which signicantly in uences the execution time of a task. In this paper, we selected a

  8. Electrophysiological Evidence for a Sensory Recruitment Model of Somatosensory Working Memory.

    Science.gov (United States)

    Katus, Tobias; Grubert, Anna; Eimer, Martin

    2015-12-01

    Sensory recruitment models of working memory assume that information storage is mediated by the same cortical areas that are responsible for the perceptual processing of sensory signals. To test this assumption, we measured somatosensory event-related brain potentials (ERPs) during a tactile delayed match-to-sample task. Participants memorized a tactile sample set at one task-relevant hand to compare it with a subsequent test set on the same hand. During the retention period, a sustained negativity (tactile contralateral delay activity, tCDA) was elicited over primary somatosensory cortex contralateral to the relevant hand. The amplitude of this component increased with memory load and was sensitive to individual limitations in memory capacity, suggesting that the tCDA reflects the maintenance of tactile information in somatosensory working memory. The tCDA was preceded by a transient negativity (N2cc component) with a similar contralateral scalp distribution, which is likely to reflect selection of task-relevant tactile stimuli at the encoding stage. The temporal sequence of N2cc and tCDA components mirrors previous observations from ERP studies of working memory in vision. The finding that the sustained somatosensory delay period activity varies as a function of memory load supports a sensory recruitment model for spatial working memory in touch. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  9. Modeling learning and memory using verbal learning tests: results from ACTIVE.

    Science.gov (United States)

    Gross, Alden L; Rebok, George W; Brandt, Jason; Tommet, Doug; Marsiske, Michael; Jones, Richard N

    2013-03-01

    To investigate the influence of memory training on initial recall and learning. The Advanced Cognitive Training for Independent and Vital Elderly study of community-dwelling adults older than age 65 (n = 1,401). We decomposed trial-level recall in the Auditory Verbal Learning Test (AVLT) and Hopkins Verbal Learning Test (HVLT) into initial recall and learning across trials using latent growth models. Trial-level increases in words recalled in the AVLT and HVLT at each follow-up visit followed an approximately logarithmic shape. Over the 5-year study period, memory training was associated with slower decline in Trial 1 AVLT recall (Cohen's d = 0.35, p = .03) and steep pre- and posttraining acceleration in learning (d = 1.56, p learning, d = 3.10, p memory-trained group had a higher level of recall than the control group through the end of the 5-year study period despite faster decline in learning. This study contributes to the understanding of the mechanisms by which training benefits memory and expands current knowledge by reporting long-term changes in initial recall and learning, as measured from growth models and by characterization of the impact of memory training on these components. Results reveal that memory training delays the worsening of memory span and boosts learning.

  10. Performance analysis and comparison of a minimum interconnections direct storage model with traditional neural bidirectional memories.

    Science.gov (United States)

    Bhatti, A Aziz

    2009-12-01

    This study proposes an efficient and improved model of a direct storage bidirectional memory, improved bidirectional associative memory (IBAM), and emphasises the use of nanotechnology for efficient implementation of such large-scale neural network structures at a considerable lower cost reduced complexity, and less area required for implementation. This memory model directly stores the X and Y associated sets of M bipolar binary vectors in the form of (MxN(x)) and (MxN(y)) memory matrices, requires O(N) or about 30% of interconnections with weight strength ranging between +/-1, and is computationally very efficient as compared to sequential, intraconnected and other bidirectional associative memory (BAM) models of outer-product type that require O(N(2)) complex interconnections with weight strength ranging between +/-M. It is shown that it is functionally equivalent to and possesses all attributes of a BAM of outer-product type, and yet it is simple and robust in structure, very large scale integration (VLSI), optical and nanotechnology realisable, modular and expandable neural network bidirectional associative memory model in which the addition or deletion of a pair of vectors does not require changes in the strength of interconnections of the entire memory matrix. The analysis of retrieval process, signal-to-noise ratio, storage capacity and stability of the proposed model as well as of the traditional BAM has been carried out. Constraints on and characteristics of unipolar and bipolar binaries for improved storage and retrieval are discussed. The simulation results show that it has log(e) N times higher storage capacity, superior performance, faster convergence and retrieval time, when compared to traditional sequential and intraconnected bidirectional memories.

  11. Bayesian Inference on the Memory Parameter for Gamma-Modulated Regression Models

    Directory of Open Access Journals (Sweden)

    Plinio Andrade

    2015-09-01

    Full Text Available In this work, we propose a Bayesian methodology to make inferences for the memory parameter and other characteristics under non-standard assumptions for a class of stochastic processes. This class generalizes the Gamma-modulated process, with trajectories that exhibit long memory behavior, as well as decreasing variability as time increases. Different values of the memory parameter influence the speed of this decrease, making this heteroscedastic model very flexible. Its properties are used to implement an approximate Bayesian computation and MCMC scheme to obtain posterior estimates. We test and validate our method through simulations and real data from the big earthquake that occurred in 2010 in Chile.

  12. Olfactory memory: a bridge between humans and animals in models of cognitive aging.

    Science.gov (United States)

    Eichenbaum, Howard; Robitsek, R Jonathan

    2009-07-01

    Odor-recognition memory in rodents may provide a valuable model of cognitive aging. In a recent study we used signal detection analyses to distinguish odor recognition based on recollection versus that based on familiarity. Aged rats were selectively impaired in recollection, with relative sparing of familiarity, and the deficits in recollection were correlated with spatial memory impairments. These results complement electrophysiological findings indicating age-associated deficits in the ability of hippocampal neurons to differentiate contextual information, and this information-processing impairment may underlie the common age-associated decline in olfactory and spatial memory.

  13. Effects on locomotion and memory in 2 models of cerebral hypoperfusion in male Wistar rats.

    Science.gov (United States)

    Martínez-Díaz, J A; García, L I; Hernández, M E; Aranda-Abreu, G E

    2015-09-01

    Cerebral ischaemia is one of the most common neurological diseases worldwide. Its many sequelae range from motor and sensory symptoms to cognitive decline and dementia. Animal models of cerebral ischaemia/hypoperfusion elicit effects on long term memory; however, the effects of these procedures on short term memory are not clearly understood and effects induced by alternative hypoperfusion models are completely unknown. We evaluated the effects of 2 cerebral hyperperfusion models on memory in 3-month-old male rats. Episodic memory and working memory were assessed using the new object recognition test and the spontaneous alteration test, respectively. Neurological assessment was also performed, along with an open field test to evaluate locomotor activity. Rats in both hyperperfusion models displayed no cognitive changes. Rats with unilateral left-sided ligation plus temporary ligation of the right carotid tended to show slightly impaired performance on the new object recognition test on the second day after the procedure. In contrast, the group with permanent unilateral ligation tended to display alterations in working and episodic memory 9 days after the procedure, but they subsequently recovered. Despite these differences, both hypoperfusion groups displayed clear signs of motor impairment 2 days after the procedure, as reflected by their decreased locomotor activity during the open field test. Copyright © 2014 Sociedad Española de Neurología. Published by Elsevier España, S.L.U. All rights reserved.

  14. Histone Deacetylase Inhibition Induces Odor Preference Memory Extension and Maintains Enhanced AMPA Receptor Expression in the Rat Pup Model

    Science.gov (United States)

    Bhattacharya, Sriya; Mukherjee, Bandhan; Doré, Jules J. E.; Yuan, Qi; Harley, Carolyn W.; McLean, John H.

    2017-01-01

    Histone deacetylase (HDAC) plays a role in synaptic plasticity and long-term memory formation. We hypothesized that trichostatin-A (TSA), an HDAC inhibitor, would promote long-term odor preference memory and maintain enhanced GluA1 receptor levels that have been hypothesized to support memory. We used an early odor preference learning model in…

  15. Modeling spatial-temporal operations with context-dependent associative memories.

    Science.gov (United States)

    Mizraji, Eduardo; Lin, Juan

    2015-10-01

    We organize our behavior and store structured information with many procedures that require the coding of spatial and temporal order in specific neural modules. In the simplest cases, spatial and temporal relations are condensed in prepositions like "below" and "above", "behind" and "in front of", or "before" and "after", etc. Neural operators lie beneath these words, sharing some similarities with logical gates that compute spatial and temporal asymmetric relations. We show how these operators can be modeled by means of neural matrix memories acting on Kronecker tensor products of vectors. The complexity of these memories is further enhanced by their ability to store episodes unfolding in space and time. How does the brain scale up from the raw plasticity of contingent episodic memories to the apparent stable connectivity of large neural networks? We clarify this transition by analyzing a model that flexibly codes episodic spatial and temporal structures into contextual markers capable of linking different memory modules.

  16. Memory consolidation from seconds to weeks: A three-stage neural network model with autonomous reinstatement dynamics

    Directory of Open Access Journals (Sweden)

    Florian eFiebig

    2014-07-01

    Full Text Available Declarative long-term memories are not created at an instant. Gradual stabilization and temporally shifting dependence of acquired declarative memories on different brain regions - called systems consolidation - can be tracked in time by lesion experiments. The observation of temporally graded retrograde amnesia following hippocampal lesions, points to a gradual transfer of memory from hippocampus to neocortical long-term memory. Spontaneous reactivations of hippocampal memories, as observed in place cell reactivations during slow-wave-sleep, are supposed to drive neocortical reinstatements and facilitate this process.We propose a functional neural network implementation of these ideas and furthermore suggest an extended three-stage framework that also includes the prefrontal cortex and bridges the temporal chasm between working memory percepts on the scale of seconds and consolidated long-term memory on the scale of weeks or months.We show that our three-stage model can autonomously produce the necessary stochastic reactivation dynamics for successful episodic memory consolidation. The resulting learning system is shown to exhibit classical memory effects seen in experimental studies, such as retrograde and anterograde amnesia after simulated hippocampal lesioning; furthermore the model reproduces peculiar biological findings on memory modulation, such as retrograde facilitation of memory after suppressed acquisition of new long-term memories - similar to the effects of benzodiazepines on memory.

  17. A model of cognitive and operational memory of organizations in changing worlds

    OpenAIRE

    Giovanni Dosi; Luigi Marengo; Evita Paraskevopoulou; Marco Valente

    2015-01-01

    This work analyzes and models the nature and dynamics of organizational memory, as such an essential ingredient of organizational capabilities. There are two sides to it, namely a cognitive side, involving the beliefs and interpretative frameworks by which the organization categorizes the states of the world and its own internal states, and an operational one, including routines and procedures that store the knowledge of how to do things. We formalize both types of memory by means of evolving...

  18. Beyond accessibility? Toward an on-line and memory-based model of framing effects

    OpenAIRE

    Matthes, Jörg

    2007-01-01

    This theoretical article investigates the effects of media frames on individuals' judgments. In contrast to previous theorizing, we suggest that framing scholars should embrace both, on-line and memory-based judgment formation processes. Based on that premise, we propose a model that distinguishes between two phases of framing effects. Along the first phase, the media's framing contributes to the formation of an on-line or a memory-based judgment. The second phase describes six hypothetical r...

  19. An approach to modeling tensile–compressive asymmetry for martensitic shape memory alloys

    International Nuclear Information System (INIS)

    Zaki, Wael

    2010-01-01

    In this paper, the asymmetric tensile–compressive behavior of shape memory alloys is modeled based on the mathematical framework of Raniecki and Mróz (2008 Acta Mech. 195 81–102). The framework allows the definition of smooth, non-symmetric, pressure-insensitive yield functions that are used here to incorporate tensile–compressive modeling capabilities into the Zaki–Moumni (ZM) model for shape memory materials. It is found that, despite some increased complexity, the generalized model is capable of producing satisfactory results that agree with uniaxial experimental data taken from the literature

  20. A new pattern associative memory model for image recognition based on Hebb rules and dot product

    Science.gov (United States)

    Gao, Mingyue; Deng, Limiao; Wang, Yanjiang

    2018-04-01

    A great number of associative memory models have been proposed to realize information storage and retrieval inspired by human brain in the last few years. However, there is still much room for improvement for those models. In this paper, we extend a binary pattern associative memory model to accomplish real-world image recognition. The learning process is based on the fundamental Hebb rules and the retrieval is implemented by a normalized dot product operation. Our proposed model can not only fulfill rapid memory storage and retrieval for visual information but also have the ability on incremental learning without destroying the previous learned information. Experimental results demonstrate that our model outperforms the existing Self-Organizing Incremental Neural Network (SOINN) and Back Propagation Neuron Network (BPNN) on recognition accuracy and time efficiency.

  1. Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model

    Science.gov (United States)

    Orth, Rene; Koster, Randal Dean; Seneviratne, Sonia I.

    2013-01-01

    Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.

  2. A cross-lagged model of the reciprocal associations of loneliness and memory functioning.

    Science.gov (United States)

    Ayalon, Liat; Shiovitz-Ezra, Sharon; Roziner, Ilan

    2016-05-01

    The study was designed to evaluate the reciprocal associations of loneliness and memory functioning using a cross-lagged model. The study was based on the psychosocial questionnaire of the Health and Retirement Study, which is a U.S. nationally representative survey of individuals over the age of 50 and their spouses of any age. A total of 1,225 respondents had complete data on the loneliness measure in 2004 and at least in 1 of the subsequent waves (e.g., 2008, 2012) and were maintained for analysis. A cross-lagged model was estimated to examine the reciprocal associations of loneliness and memory functioning, controlling for age, gender, education, depressive symptoms, number of medical conditions, and the number of close social relationships. The model had adequate fit indices: χ2(860, N = 1,225) = 1,401.54, p memory functioning was nonsignificant, B(SE) = -.11(.08), p = .15, whereas the lagged effect of memory functioning on loneliness was significant, B(SE) = -.06(.02), p = .01, indicating that lower levels of memory functioning precede higher levels of loneliness 4 years afterward. Further research is required to better understand the mechanisms responsible for the temporal association between reduced memory functioning and increased loneliness. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  3. Memory-induced resonancelike suppression of spike generation in a resonate-and-fire neuron model

    Science.gov (United States)

    Mankin, Romi; Paekivi, Sander

    2018-01-01

    The behavior of a stochastic resonate-and-fire neuron model based on a reduction of a fractional noise-driven generalized Langevin equation (GLE) with a power-law memory kernel is considered. The effect of temporally correlated random activity of synaptic inputs, which arise from other neurons forming local and distant networks, is modeled as an additive fractional Gaussian noise in the GLE. Using a first-passage-time formulation, in certain system parameter domains exact expressions for the output interspike interval (ISI) density and for the survival probability (the probability that a spike is not generated) are derived and their dependence on input parameters, especially on the memory exponent, is analyzed. In the case of external white noise, it is shown that at intermediate values of the memory exponent the survival probability is significantly enhanced in comparison with the cases of strong and weak memory, which causes a resonancelike suppression of the probability of spike generation as a function of the memory exponent. Moreover, an examination of the dependence of multimodality in the ISI distribution on input parameters shows that there exists a critical memory exponent αc≈0.402 , which marks a dynamical transition in the behavior of the system. That phenomenon is illustrated by a phase diagram describing the emergence of three qualitatively different structures of the ISI distribution. Similarities and differences between the behavior of the model at internal and external noises are also discussed.

  4. Meta-analysis of the research impact of Baddeley’s multicomponent working memory model and Cowan’s embedded-processes model of working memory : a bibliometric mapping approach

    OpenAIRE

    Gruszka-Gosiewska, Aleksandra; Orzechowski, Jarosław

    2016-01-01

    In this study bibliometric mapping method was employed to visualise the current research trends and the impact of the two most influential models of working memory, namely: A. D. Baddeley and G. J. Hitch’s (1974) multicomponent working memory model and N. Cowan’s (1988) embedded-processes model of working memory. Using VOSviewer software two maps were generated based on the index-term words extracted from the research papers citing Baddeley (2000) and Cowan (2001), respectively. The maps repr...

  5. Cellular Shape Memory Alloy Structures: Experiments & Modeling (Part 1)

    Science.gov (United States)

    2012-08-01

    High -­‐ temperature  SMAs 24 Braze  Joint  between  two  wrought  pieces  of  a  Ni24.5Pd25Ti50.5  HTSMA   (HTSMA  from...process  can  be  used   to  join  other  metal  alloys  and   high -­‐ temperature   SMAs 25 Cellular  Shape  Memory...20 30 40 50 60 910 3 4 8 5 2 T (°C) Shape memory & superelasticity 1 0 e (%) (GPa) 6 7 A NiTi wire

  6. The golden mean, scale free extension of real number system, fuzzy sets and 1/f spectrum in physics and biology

    CERN Document Server

    Datta, D P

    2003-01-01

    We show that the generic 1/f spectrum problem acquires a natural explanation in a class of scale free solutions to the ordinary differential equations. We prove the existence and uniqueness of this class of solutions and show how this leads to a nonstandard, fuzzy extension of the ordinary framework of calculus, and hence, that of the classical dynamics and quantum mechanics. The exceptional role of the golden mean irrational number is also explained.

  7. The golden mean, scale free extension of real number system, fuzzy sets and 1/f spectrum in physics and biology

    International Nuclear Information System (INIS)

    Datta, Dhurjati Prasad

    2003-01-01

    We show that the generic 1/f spectrum problem acquires a natural explanation in a class of scale free solutions to the ordinary differential equations. We prove the existence and uniqueness of this class of solutions and show how this leads to a nonstandard, fuzzy extension of the ordinary framework of calculus, and hence, that of the classical dynamics and quantum mechanics. The exceptional role of the golden mean irrational number is also explained

  8. Understanding, modeling, and improving main-memory database performance

    OpenAIRE

    Manegold, S.

    2002-01-01

    textabstractDuring the last two decades, computer hardware has experienced remarkable developments. Especially CPU (clock-)speed has been following Moore's Law, i.e., doubling every 18 months; and there is no indication that this trend will change in the foreseeable future. Recent research has revealed that database performance, even with main-memory based systems, can hardly benefit from the ever increasing CPU power. The reason for this is that the performance of other hardware components h...

  9. Modeling human color categorization: Color discrimination and color memory

    OpenAIRE

    Heskes, T.; van den Broek, Egon; Lucas, P.; Hendriks, Maria A.; Vuurpijl, L.G.; Puts, M.J.H.; Wiegerinck, W.

    2003-01-01

    Color matching in Content-Based Image Retrieval is done using a color space and measuring distances between colors. Such an approach yields non-intuitive results for the user. We introduce color categories (or focal colors), determine that they are valid, and use them in two experiments. The experiments conducted prove the difference between color categorization by the cognitive processes color discrimination and color memory. In addition, they yield a Color Look-Up Table, which can improve c...

  10. A sharp interface evolutionary model for shape memory alloys

    Czech Academy of Sciences Publication Activity Database

    Knüpfer, H.; Kružík, Martin

    2016-01-01

    Roč. 96, č. 11 (2016), s. 1347-1355 ISSN 0044-2267 R&D Projects: GA ČR GA14-15264S Institutional support: RVO:67985556 Keywords : Polyconvexity * shape memory materials * rate-independent problems Subject RIV: BA - General Mathematics Impact factor: 1.332, year: 2016 http://library.utia.cas.cz/separaty/2016/MTR/kruzik-0465809.pdf

  11. Magnetic shape-memory alloys: thermomechanical modelling and analysis

    Czech Academy of Sciences Publication Activity Database

    Roubíček, Tomáš; Stefanelli, U.

    2014-01-01

    Roč. 26, č. 6 (2014), s. 783-810 ISSN 0935-1175 R&D Projects: GA ČR GAP201/10/0357 Institutional support: RVO:61388998 Keywords : magnetic shape- memory alloys * martensitic phase transformation * ferro/paramagnetic phase transformation Subject RIV: BA - General Mathematics Impact factor: 1.779, year: 2014 http://link.springer.com/article/10.1007/s00161-014-0339-8#

  12. The memory state heuristic: A formal model based on repeated recognition judgments.

    Science.gov (United States)

    Castela, Marta; Erdfelder, Edgar

    2017-02-01

    The recognition heuristic (RH) theory predicts that, in comparative judgment tasks, if one object is recognized and the other is not, the recognized one is chosen. The memory-state heuristic (MSH) extends the RH by assuming that choices are not affected by recognition judgments per se, but by the memory states underlying these judgments (i.e., recognition certainty, uncertainty, or rejection certainty). Specifically, the larger the discrepancy between memory states, the larger the probability of choosing the object in the higher state. The typical RH paradigm does not allow estimation of the underlying memory states because it is unknown whether the objects were previously experienced or not. Therefore, we extended the paradigm by repeating the recognition task twice. In line with high threshold models of recognition, we assumed that inconsistent recognition judgments result from uncertainty whereas consistent judgments most likely result from memory certainty. In Experiment 1, we fitted 2 nested multinomial models to the data: an MSH model that formalizes the relation between memory states and binary choices explicitly and an approximate model that ignores the (unlikely) possibility of consistent guesses. Both models provided converging results. As predicted, reliance on recognition increased with the discrepancy in the underlying memory states. In Experiment 2, we replicated these results and found support for choice consistency predictions of the MSH. Additionally, recognition and choice latencies were in agreement with the MSH in both experiments. Finally, we validated critical parameters of our MSH model through a cross-validation method and a third experiment. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  13. Equilibrium and nonequilibrium properties of Boolean decision problems on scale-free graphs with competing interactions with external biases

    Science.gov (United States)

    Zhu, Zheng; Andresen, Juan Carlos; Janzen, Katharina; Katzgraber, Helmut G.

    2013-03-01

    We study the equilibrium and nonequilibrium properties of Boolean decision problems with competing interactions on scale-free graphs in a magnetic field. Previous studies at zero field have shown a remarkable equilibrium stability of Boolean variables (Ising spins) with competing interactions (spin glasses) on scale-free networks. When the exponent that describes the power-law decay of the connectivity of the network is strictly larger than 3, the system undergoes a spin-glass transition. However, when the exponent is equal to or less than 3, the glass phase is stable for all temperatures. First we perform finite-temperature Monte Carlo simulations in a field to test the robustness of the spin-glass phase and show, in agreement with analytical calculations, that the system exhibits a de Almeida-Thouless line. Furthermore, we study avalanches in the system at zero temperature to see if the system displays self-organized criticality. This would suggest that damage (avalanches) can spread across the whole system with nonzero probability, i.e., that Boolean decision problems on scale-free networks with competing interactions are fragile when not in thermal equilibrium.

  14. Boolean decision problems with competing interactions on scale-free networks: Equilibrium and nonequilibrium behavior in an external bias

    Science.gov (United States)

    Zhu, Zheng; Andresen, Juan Carlos; Moore, M. A.; Katzgraber, Helmut G.

    2014-02-01

    We study the equilibrium and nonequilibrium properties of Boolean decision problems with competing interactions on scale-free networks in an external bias (magnetic field). Previous studies at zero field have shown a remarkable equilibrium stability of Boolean variables (Ising spins) with competing interactions (spin glasses) on scale-free networks. When the exponent that describes the power-law decay of the connectivity of the network is strictly larger than 3, the system undergoes a spin-glass transition. However, when the exponent is equal to or less than 3, the glass phase is stable for all temperatures. First, we perform finite-temperature Monte Carlo simulations in a field to test the robustness of the spin-glass phase and show that the system has a spin-glass phase in a field, i.e., exhibits a de Almeida-Thouless line. Furthermore, we study avalanche distributions when the system is driven by a field at zero temperature to test if the system displays self-organized criticality. Numerical results suggest that avalanches (damage) can spread across the whole system with nonzero probability when the decay exponent of the interaction degree is less than or equal to 2, i.e., that Boolean decision problems on scale-free networks with competing interactions can be fragile when not in thermal equilibrium.

  15. Optimization and Implementation of Scaling-Free CORDIC-Based Direct Digital Frequency Synthesizer for Body Care Area Network Systems

    Directory of Open Access Journals (Sweden)

    Ying-Shen Juang

    2012-01-01

    Full Text Available Coordinate rotation digital computer (CORDIC is an efficient algorithm for computations of trigonometric functions. Scaling-free-CORDIC is one of the famous CORDIC implementations with advantages of speed and area. In this paper, a novel direct digital frequency synthesizer (DDFS based on scaling-free CORDIC is presented. The proposed multiplier-less architecture with small ROM and pipeline data path has advantages of high data rate, high precision, high performance, and less hardware cost. The design procedure with performance and hardware analysis for optimization has also been given. It is verified by Matlab simulations and then implemented with field programmable gate array (FPGA by Verilog. The spurious-free dynamic range (SFDR is over 86.85 dBc, and the signal-to-noise ratio (SNR is more than 81.12 dB. The scaling-free CORDIC-based architecture is suitable for VLSI implementations for the DDFS applications in terms of hardware cost, power consumption, SNR, and SFDR. The proposed DDFS is very suitable for medical instruments and body care area network systems.

  16. Memory as the "whole brain work": a large-scale model based on "oscillations in super-synergy".

    Science.gov (United States)

    Başar, Erol

    2005-01-01

    According to recent trends, memory depends on several brain structures working in concert across many levels of neural organization; "memory is a constant work-in progress." The proposition of a brain theory based on super-synergy in neural populations is most pertinent for the understanding of this constant work in progress. This report introduces a new model on memory basing on the processes of EEG oscillations and Brain Dynamics. This model is shaped by the following conceptual and experimental steps: 1. The machineries of super-synergy in the whole brain are responsible for formation of sensory-cognitive percepts. 2. The expression "dynamic memory" is used for memory processes that evoke relevant changes in alpha, gamma, theta and delta activities. The concerted action of distributed multiple oscillatory processes provides a major key for understanding of distributed memory. It comprehends also the phyletic memory and reflexes. 3. The evolving memory, which incorporates reciprocal actions or reverberations in the APLR alliance and during working memory processes, is especially emphasized. 4. A new model related to "hierarchy of memories as a continuum" is introduced. 5. The notions of "longer activated memory" and "persistent memory" are proposed instead of long-term memory. 6. The new analysis to recognize faces emphasizes the importance of EEG oscillations in neurophysiology and Gestalt analysis. 7. The proposed basic framework called "Memory in the Whole Brain Work" emphasizes that memory and all brain functions are inseparable and are acting as a "whole" in the whole brain. 8. The role of genetic factors is fundamental in living system settings and oscillations and accordingly in memory, according to recent publications. 9. A link from the "whole brain" to "whole body," and incorporation of vegetative and neurological system, is proposed, EEG oscillations and ultraslow oscillations being a control parameter.

  17. Capacity for patterns and sequences in Kanerva's SDM as compared to other associative memory models. [Sparse, Distributed Memory

    Science.gov (United States)

    Keeler, James D.

    1988-01-01

    The information capacity of Kanerva's Sparse Distributed Memory (SDM) and Hopfield-type neural networks is investigated. Under the approximations used here, it is shown that the total information stored in these systems is proportional to the number connections in the network. The proportionality constant is the same for the SDM and Hopfield-type models independent of the particular model, or the order of the model. The approximations are checked numerically. This same analysis can be used to show that the SDM can store sequences of spatiotemporal patterns, and the addition of time-delayed connections allows the retrieval of context dependent temporal patterns. A minor modification of the SDM can be used to store correlated patterns.

  18. Quantitative Analysis of Memristance Defined Exponential Model for Multi-bits Titanium Dioxide Memristor Memory Cell

    Directory of Open Access Journals (Sweden)

    DAOUD, A. A. D.

    2016-05-01

    Full Text Available The ability to store multiple bits in a single memristor based memory cell is a key feature for high-capacity memory packages. Studying multi-bit memristor circuits requires high accuracy in modelling the memristance change. A memristor model based on a novel definition of memristance is proposed. A design of a single memristor memory cell using the proposed model for the platinum electrodes titanium dioxide memristor is illustrated. A specific voltage pulse is used with varying its parameters (amplitude or pulse width to store different number of states in a single memristor. New state variation parameters associated with the utilized model are provided and their effects on write and read processes of memristive multi-states are analysed. PSPICE simulations are also held, and they show a good agreement with the data obtained from the analysis.

  19. Avalanches and generalized memory associativity in a network model for conscious and unconscious mental functioning

    Science.gov (United States)

    Siddiqui, Maheen; Wedemann, Roseli S.; Jensen, Henrik Jeldtoft

    2018-01-01

    We explore statistical characteristics of avalanches associated with the dynamics of a complex-network model, where two modules corresponding to sensorial and symbolic memories interact, representing unconscious and conscious mental processes. The model illustrates Freud's ideas regarding the neuroses and that consciousness is related with symbolic and linguistic memory activity in the brain. It incorporates the Stariolo-Tsallis generalization of the Boltzmann Machine in order to model memory retrieval and associativity. In the present work, we define and measure avalanche size distributions during memory retrieval, in order to gain insight regarding basic aspects of the functioning of these complex networks. The avalanche sizes defined for our model should be related to the time consumed and also to the size of the neuronal region which is activated, during memory retrieval. This allows the qualitative comparison of the behaviour of the distribution of cluster sizes, obtained during fMRI measurements of the propagation of signals in the brain, with the distribution of avalanche sizes obtained in our simulation experiments. This comparison corroborates the indication that the Nonextensive Statistical Mechanics formalism may indeed be more well suited to model the complex networks which constitute brain and mental structure.

  20. A Cognitive Attachment Model of prolonged grief: integrating attachments, memory, and identity.

    Science.gov (United States)

    Maccallum, Fiona; Bryant, Richard A

    2013-08-01

    Prolonged grief (PG), otherwise known as complicated grief, has attracted much attention in recent years as a potentially debilitating condition that affects approximately 10% of bereaved people. We propose a model of PG that integrates processes of attachment, self-identity, and autobiographical memory. The paper commences with a discussion of the PG construct and reviews current evidence regarding the distinctiveness of PG from other bereavement related-outcomes. We then review the evidence regarding the dysfunctional attachments, appraisals, and coping styles that people with PG display. Recent evidence pertaining to the patterns of autobiographical memory in PG is described in the context of the self-memory system. This system provides a unifying framework to understand the roles of personal memories, identity, attachments, and coping responses in PG. The proposed model places emphasis on how one's sense of identity influences yearning, memories of the deceased, appraisals, and coping strategies, to maintain a focus on the loss. The model is discussed in relation to existing models of PG. The potential for shaping treatment strategies to shift perceptions of the self is then outlined. Finally, we outline future directions to test propositions stemming from the model and enhance our understanding of the mechanisms underlying PG. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. Generalized nucleation and looping model for epigenetic memory of histone modifications

    Science.gov (United States)

    Erdel, Fabian; Greene, Eric C.

    2016-01-01

    Histone modifications can redistribute along the genome in a sequence-independent manner, giving rise to chromatin position effects and epigenetic memory. The underlying mechanisms shape the endogenous chromatin landscape and determine its response to ectopically targeted histone modifiers. Here, we simulate linear and looping-driven spreading of histone modifications and compare both models to recent experiments on histone methylation in fission yeast. We find that a generalized nucleation-and-looping mechanism describes key observations on engineered and endogenous methylation domains including intrinsic spatial confinement, independent regulation of domain size and memory, variegation in the absence of antagonists, and coexistence of short- and long-term memory at loci with weak and strong constitutive nucleation. These findings support a straightforward relationship between the biochemical properties of chromatin modifiers and the spatiotemporal modification pattern. The proposed mechanism gives rise to a phase diagram for cellular memory that may be generally applicable to explain epigenetic phenomena across different species. PMID:27382173

  2. An analytical study of physical models with inherited temporal and spatial memory

    Science.gov (United States)

    Jaradat, Imad; Alquran, Marwan; Al-Khaled, Kamel

    2018-04-01

    Du et al. (Sci. Reb. 3, 3431 (2013)) demonstrated that the fractional derivative order can be physically interpreted as a memory index by fitting the test data of memory phenomena. The aim of this work is to study analytically the joint effect of the memory index on time and space coordinates simultaneously. For this purpose, we introduce a novel bivariate fractional power series expansion that is accompanied by twofold fractional derivatives ordering α, β\\in(0,1]. Further, some convergence criteria concerning our expansion are presented and an analog of the well-known bivariate Taylor's formula in the sense of mixed fractional derivatives is obtained. Finally, in order to show the functionality and efficiency of this expansion, we employ the corresponding Taylor's series method to obtain closed-form solutions of various physical models with inherited time and space memory.

  3. [A neuropsychoanalytic freudian model of psychic trauma and memory. Theoretical and clinical applications].

    Science.gov (United States)

    Cohen, Diego; Basili, Rubén; Sharpin de Basili, Isabel

    2009-01-01

    The traumatic memory is conceptualized by means of an amplified Freudian neuropsychoanalytic model using a contemporary memory system based on its contents, conscious and unconscious recollection (explicit and implicit memories) highlighting the validity of the Freudian discoveries. This is then related to the psychoanalytical theories of consciousness, affects and thinking. Particular importance is given to Freud's seduction theory, its relation to memory and the clinical application of these concepts to the basic organization of the personality, together with the relation to Bowlby's concept of emotional deprivation. The development and working trough of trauma is postulated as a vector to make "real" or phantasized trauma unconscious through repression in neurosis, splitting in borderline personality organization, and primitive mechanisms of projection in psychosis.

  4. GABA from reactive astrocytes impairs memory in mouse models of Alzheimer's disease.

    Science.gov (United States)

    Jo, Seonmi; Yarishkin, Oleg; Hwang, Yu Jin; Chun, Ye Eun; Park, Mijeong; Woo, Dong Ho; Bae, Jin Young; Kim, Taekeun; Lee, Jaekwang; Chun, Heejung; Park, Hyun Jung; Lee, Da Yong; Hong, Jinpyo; Kim, Hye Yun; Oh, Soo-Jin; Park, Seung Ju; Lee, Hyo; Yoon, Bo-Eun; Kim, YoungSoo; Jeong, Yong; Shim, Insop; Bae, Yong Chul; Cho, Jeiwon; Kowall, Neil W; Ryu, Hoon; Hwang, Eunmi; Kim, Daesoo; Lee, C Justin

    2014-08-01

    In Alzheimer's disease (AD), memory impairment is the most prominent feature that afflicts patients and their families. Although reactive astrocytes have been observed around amyloid plaques since the disease was first described, their role in memory impairment has been poorly understood. Here, we show that reactive astrocytes aberrantly and abundantly produce the inhibitory gliotransmitter GABA by monoamine oxidase-B (Maob) and abnormally release GABA through the bestrophin 1 channel. In the dentate gyrus of mouse models of AD, the released GABA reduces spike probability of granule cells by acting on presynaptic GABA receptors. Suppressing GABA production or release from reactive astrocytes fully restores the impaired spike probability, synaptic plasticity, and learning and memory in the mice. In the postmortem brain of individuals with AD, astrocytic GABA and MAOB are significantly upregulated. We propose that selective inhibition of astrocytic GABA synthesis or release may serve as an effective therapeutic strategy for treating memory impairment in AD.

  5. Modeling of strain effects on the device behaviors of ferroelectric memory field-effect transistors

    International Nuclear Information System (INIS)

    Yang, Feng; Hu, Guangda; Wu, Weibing; Yang, Changhong; Wu, Haitao; Tang, Minghua

    2013-01-01

    The influence of strains on the channel current–gate voltage behaviors and memory windows of ferroelectric memory field-effect transistors (FeMFETs) were studied using an improved model based on the Landau–Devonshire theory. ‘Channel potential–gate voltage’ ferroelectric polarization and silicon surface potential diagrams were constructed for strained single-domain BaTiO 3 FeMFETs. The compressive strains can increase (or decrease) the amplitude of transistor currents and enlarge memory windows. However, tensile strains only decrease the maximum value of transistor currents and compress memory windows. Mismatch strains were found to have a significant influence on the electrical behaviors of the devices, therefore, they must be considered in FeMFET device designing. (fast track communication)

  6. Design, fabrication, testing and delivery of a feasibility model laminated ferrite memory

    Science.gov (United States)

    Heckler, H. C.

    1973-01-01

    The effect of using multiword addressing with laminated ferrite arrays was made. Both a reduction in the number of components, and a reduction in power consumption was obtained for memory capacities between one million bits and one million words. An investigation into the effect of variations in the processing steps resulted in a number of process modifications that improved the quality of the arrays. A feasibility model laminated ferrite memory system was constructed by modifying a commercial plated wire memory system to operate with laminated ferrite arrays. To provide flexibility for the testing of the laminated ferrite memory, an exerciser has been constructed to automatically control the loading and recirculation of arbitrary size checkerboard patterns of one's and zero's and to display the patterns of stored information on a CRT screen.

  7. Frozen Fractals all Around: Solar flares, Ampere’s Law, and the Search for Units in Scale-Free Processes.

    Science.gov (United States)

    McAteer, R. T. James

    2015-08-01

    My soul is spiraling in frozen fractals all around, And one thought crystallizes like an icy blast, I'm never going back, the past is in the past.Elsa, from Disney’s Frozen, characterizes two fundamental aspects of scale-free processes in Nature: fractals are everywhere in space; fractals can be used to probe changes in time. Self-Organized Criticality provides a powerful set of tools to study scale-free processes. It connects spatial fractals (more generically, multifractals) to temporal evolution. The drawback is that this usually results in scale-free, unit-less, indices, which can be difficult to connect to everyday physics. Here, I show a novel method that connects one of the most powerful SOC tools - the wavelet transform modulus maxima approach to calculating multifractality - to one of the most powerful equations in all of physics - Ampere’s law. In doing so I show how the multifractal spectra can be expressed in terms of current density, and how current density can then be used for the prediction of future energy release from such a system.Our physical understanding of the solar magnetic field structure, and hence our ability to predict solar activity, is limited by the type of data currently available. I show that the multifractal spectrum provides a powerful physical connection between the details of photospheric magnetic gradients of current data and the coronal magnetic structure. By decomposing Ampere’s law and comparing it to the wavelet transform modulus maximum method, I show how the scale-free Holder exponent provides a direct measure of current density across all relevant sizes. The prevalence of this current density across various scales is connected to its stability in time, and hence to the ability of the magnetic structure to store and then release energy. Hence (spatial) multifractals inform us of (future) solar activity.Finally I discuss how such an approach can be used in any study of scale-free processes, and highlight the necessary

  8. Subtle alterations in memory systems and normal visual attention in the GAERS model of absence epilepsy.

    Science.gov (United States)

    Marques-Carneiro, J E; Faure, J-B; Barbelivien, A; Nehlig, A; Cassel, J-C

    2016-03-01

    Even if considered benign, absence epilepsy may alter memory and attention, sometimes subtly. Very little is known on behavior and cognitive functions in the Genetic Absence Epilepsy Rats from Strasbourg (GAERS) model of absence epilepsy. We focused on different memory systems and sustained visual attention, using Non Epileptic Controls (NECs) and Wistars as controls. A battery of cognitive/behavioral tests was used. The functionality of reference, working, and procedural memory was assessed in the Morris water maze (MWM), 8-arm radial maze, T-maze and/or double-H maze. Sustained visual attention was evaluated in the 5-choice serial reaction time task. In the MWM, GAERS showed delayed learning and less efficient working memory. In the 8-arm radial maze and T-maze tests, working memory performance was normal in GAERS, although most GAERS preferred an egocentric strategy (based on proprioceptive/kinesthetic information) to solve the task, but could efficiently shift to an allocentric strategy (based on spatial cues) after protocol alteration. Procedural memory and visual attention were mostly unimpaired. Absence epilepsy has been associated with some learning problems in children. In GAERS, the differences in water maze performance (slower learning of the reference memory task and weak impairment of working memory) and in radial arm maze strategies suggest that cognitive alterations may be subtle, task-specific, and that normal performance can be a matter of strategy adaptation. Altogether, these results strengthen the "face validity" of the GAERS model: in humans with absence epilepsy, cognitive alterations are not easily detectable, which is compatible with subtle deficits. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

  9. Constitutive model for a stress- and thermal-induced phase transition in a shape memory polymer

    International Nuclear Information System (INIS)

    Guo, Xiaogang; Liu, Liwu; Liu, Yanju; Zhou, Bo; Leng, Jinsong

    2014-01-01

    Recently, increasing applications of shape memory polymers have pushed forward the development of appropriate constitutive models for smart materials such as the shape memory polymer. During the heating process, the phase transition, which is a continuous time-dependent process, happens in the shape memory polymer, and various individual phases will form at different configuration temperatures. In addition, these phases can generally be divided into two parts: the frozen and active phase (Liu Y et al 2006 Int. J. Plast. 22 279–313). During the heating or cooling process, the strain will be stored or released with the occurring phase transition between these two parts. Therefore, a shape memory effect emerges. In this paper, a new type of model was developed to characterize the variation of the volume fraction in a shape memory polymer during the phase transition. In addition to the temperature variation, the applied stress was also taken as a significant influence factor on the phase transition. Based on the experimental results, an exponential equation was proposed to describe the relationship between the stress and phase transition temperature. For the sake of describing the mechanical behaviors of the shape memory polymer, a three-dimensional constitutive model was established. Also, the storage strain, which was the key factor of the shape memory effect, was also discussed in detail. Similar to previous works, we first explored the effect of applied stress on storage strain. Through comparisons with the DMA and the creep experimental results, the rationality and accuracy of the new phase transition and constitutive model were finally verified. (paper)

  10. Relating Memory To Functional Performance In Normal Aging to Dementia Using Hierarchical Bayesian Cognitive Processing Models

    Science.gov (United States)

    Shankle, William R.; Pooley, James P.; Steyvers, Mark; Hara, Junko; Mangrola, Tushar; Reisberg, Barry; Lee, Michael D.

    2012-01-01

    Determining how cognition affects functional abilities is important in Alzheimer’s disease and related disorders (ADRD). 280 patients (normal or ADRD) received a total of 1,514 assessments using the Functional Assessment Staging Test (FAST) procedure and the MCI Screen (MCIS). A hierarchical Bayesian cognitive processing (HBCP) model was created by embedding a signal detection theory (SDT) model of the MCIS delayed recognition memory task into a hierarchical Bayesian framework. The SDT model used latent parameters of discriminability (memory process) and response bias (executive function) to predict, simultaneously, recognition memory performance for each patient and each FAST severity group. The observed recognition memory data did not distinguish the six FAST severity stages, but the latent parameters completely separated them. The latent parameters were also used successfully to transform the ordinal FAST measure into a continuous measure reflecting the underlying continuum of functional severity. HBCP models applied to recognition memory data from clinical practice settings accurately translated a latent measure of cognition to a continuous measure of functional severity for both individuals and FAST groups. Such a translation links two levels of brain information processing, and may enable more accurate correlations with other levels, such as those characterized by biomarkers. PMID:22407225

  11. Deception and Cognitive Load: Expanding Our Horizon with a Working Memory Model.

    Science.gov (United States)

    Sporer, Siegfried L

    2016-01-01

    Recently, studies on deception and its detection have increased dramatically. Many of these studies rely on the "cognitive load approach" as the sole explanatory principle to understand deception. These studies have been exclusively on lies about negative actions (usually lies of suspects of [mock] crimes). Instead, we need to re-focus more generally on the cognitive processes involved in generating both lies and truths, not just on manipulations of cognitive load. Using Baddeley's (2000, 2007, 2012) working memory model, which integrates verbal and visual processes in working memory with retrieval from long-term memory and control of action, not only verbal content cues but also nonverbal, paraverbal, and linguistic cues can be investigated within a single framework. The proposed model considers long-term semantic, episodic and autobiographical memory and their connections with working memory and action. It also incorporates ironic processes of mental control (Wegner, 1994, 2009), the role of scripts and schemata and retrieval cues and retrieval processes. Specific predictions of the model are outlined and support from selective studies is presented. The model is applicable to different types of reports, particularly about lies and truths about complex events, and to different modes of production (oral, hand-written, typed). Predictions regarding several moderator variables and methods to investigate them are proposed.

  12. A Dynamic Model for Decision Making During Memory Retrieval

    Science.gov (United States)

    2015-10-26

    a  knowledge  task  (pseudo-­‐ lexical  decision),  a  perceptual  task  (perceptual  identification),  and  an  episodic... lexical decision), a perceptual task (perceptual identification), and an episodic recognition task (recognition memory for occurrence of a test item...Topics in Cognitive Science, 4(1), 135-150. Cox, G. E., Kachergis, G., and Shiffrin, R. M. (2012). Gaussian process regression for trajectory analysis . In

  13. A Neural Network Model of the Visual Short-Term Memory

    DEFF Research Database (Denmark)

    Petersen, Anders; Kyllingsbæk, Søren; Hansen, Lars Kai

    2009-01-01

    In this paper a neural network model of Visual Short-Term Memory (VSTM) is presented. The model links closely with Bundesen’s (1990) well-established mathematical theory of visual attention. We evaluate the model’s ability to fit experimental data from a classical whole and partial report study...

  14. A Memory-Based Model of Posttraumatic Stress Disorder: Evaluating Basic Assumptions Underlying the PTSD Diagnosis

    Science.gov (United States)

    Rubin, David C.; Berntsen, Dorthe; Bohni, Malene Klindt

    2008-01-01

    In the mnemonic model of posttraumatic stress disorder (PTSD), the current memory of a negative event, not the event itself, determines symptoms. The model is an alternative to the current event-based etiology of PTSD represented in the "Diagnostic and Statistical Manual of Mental Disorders" (4th ed., text rev.; American Psychiatric Association,…

  15. Folk music style modelling by recurrent neural networks with long short term memory units

    OpenAIRE

    Sturm, Bob; Santos, João Felipe; Korshunova, Iryna

    2015-01-01

    We demonstrate two generative models created by training a recurrent neural network (RNN) with three hidden layers of long short-term memory (LSTM) units. This extends past work in numerous directions, including training deeper models with nearly 24,000 high-level transcriptions of folk tunes. We discuss our on-going work.

  16. Postscript: More Problems with Botvinick and Plaut's (2006) PDP Model of Short-Term Memory

    Science.gov (United States)

    Bowers, Jeffrey S.; Damian, Markus F.; Davis, Colin J.

    2009-01-01

    Presents a postscript to the current authors' comment on the original article, "Short-term memory for serial order: A recurrent neural network model," by M. M. Botvinick and D. C. Plaut. In their commentary, the current authors demonstrated that Botvinick and Plaut's (2006) model of immediate serial recall catastrophically fails when familiar…

  17. Short-Term Memory for Serial Order: A Recurrent Neural Network Model

    Science.gov (United States)

    Botvinick, Matthew M.; Plaut, David C.

    2006-01-01

    Despite a century of research, the mechanisms underlying short-term or working memory for serial order remain uncertain. Recent theoretical models have converged on a particular account, based on transient associations between independent item and context representations. In the present article, the authors present an alternative model, according…

  18. Discrete-State and Continuous Models of Recognition Memory: Testing Core Properties under Minimal Assumptions

    Science.gov (United States)

    Kellen, David; Klauer, Karl Christoph

    2014-01-01

    A classic discussion in the recognition-memory literature concerns the question of whether recognition judgments are better described by continuous or discrete processes. These two hypotheses are instantiated by the signal detection theory model (SDT) and the 2-high-threshold model, respectively. Their comparison has almost invariably relied on…

  19. Animal Model of Methylphenidate's Longterm Memory-Enhancing Effects

    Science.gov (United States)

    Carmack, Stephanie A.; Howell, Kristin K.; Rasaei, Kleou; Reas, Emilie T.; Anagnostaras, Stephan G.

    2014-01-01

    Methylphenidate (MPH), introduced more than 60 years ago, accounts for two-thirds of current prescriptions for attention deficit hyperactivity disorder (ADHD). Although many studies have modeled MPH's effect on executive function, almost none have directly modeled its effect on long-term memory (LTM), even though improvement in LTM is a…

  20. Distinct effects of perceptual quality on auditory word recognition, memory formation and recall in a neural model of sequential memory

    Directory of Open Access Journals (Sweden)

    Paul Miller

    2010-06-01

    Full Text Available Adults with sensory impairment, such as reduced hearing acuity, have impaired ability to recall identifiable words, even when their memory is otherwise normal. We hypothesize that poorer stimulus quality causes weaker activity in neurons responsive to the stimulus and more time to elapse between stimulus onset and identification. The weaker activity and increased delay to stimulus identification reduce the necessary strengthening of connections between neurons active before stimulus presentation and neurons active at the time of stimulus identification. We test our hypothesis through a biologically motivated computational model, which performs item recognition, memory formation and memory retrieval. In our simulations, spiking neurons are distributed into pools representing either items or context, in two separate, but connected winner-takes-all (WTA networks. We include associative, Hebbian learning, by comparing multiple forms of spike-timing dependent plasticity (STDP, which strengthen synapses between coactive neurons during stimulus identification. Synaptic strengthening by STDP can be sufficient to reactivate neurons during recall if their activity during a prior stimulus rose strongly and rapidly. We find that a single poor quality stimulus impairs recall of neighboring stimuli as well as the weak stimulus itself. We demonstrate that within the WTA paradigm of word recognition, reactivation of separate, connected sets of non-word, context cells permits reverse recall. Also, only with such coactive context cells, does slowing the rate of stimulus presentation increase recall probability. We conclude that significant temporal overlap of neural activity patterns, absent from individual WTA networks, is necessary to match behavioral data for word recall.

  1. Working Memory Capacity: Attention Control, Secondary Memory, or Both? A Direct Test of the Dual-Component Model

    Science.gov (United States)

    Unsworth, Nash; Spillers, Gregory J.

    2010-01-01

    The current study examined the extent to which attention control abilities, secondary memory abilities, or both accounted for variation in working memory capacity (WMC) and its relation to fluid intelligence. Participants performed various attention control, secondary memory, WMC, and fluid intelligence measures. Confirmatory factor analyses…

  2. A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation

    Science.gov (United States)

    Fiebig, Florian

    2017-01-01

    A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. SIGNIFICANCE STATEMENT Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and

  3. A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation.

    Science.gov (United States)

    Fiebig, Florian; Lansner, Anders

    2017-01-04

    A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and neurophysiology of the underlying

  4. Plausible carrier transport model in organic-inorganic hybrid perovskite resistive memory devices

    Science.gov (United States)

    Park, Nayoung; Kwon, Yongwoo; Choi, Jaeho; Jang, Ho Won; Cha, Pil-Ryung

    2018-04-01

    We demonstrate thermally assisted hopping (TAH) as an appropriate carrier transport model for CH3NH3PbI3 resistive memories. Organic semiconductors, including organic-inorganic hybrid perovskites, have been previously speculated to follow the space-charge-limited conduction (SCLC) model. However, the SCLC model cannot reproduce the temperature dependence of experimental current-voltage curves. Instead, the TAH model with temperature-dependent trap densities and a constant trap level are demonstrated to well reproduce the experimental results.

  5. Reactivation in working memory: an attractor network model of free recall.

    Science.gov (United States)

    Lansner, Anders; Marklund, Petter; Sikström, Sverker; Nilsson, Lars-Göran

    2013-01-01

    The dynamic nature of human working memory, the general-purpose system for processing continuous input, while keeping no longer externally available information active in the background, is well captured in immediate free recall of supraspan word-lists. Free recall tasks produce several benchmark memory phenomena, like the U-shaped serial position curve, reflecting enhanced memory for early and late list items. To account for empirical data, including primacy and recency as well as contiguity effects, we propose here a neurobiologically based neural network model that unifies short- and long-term forms of memory and challenges both the standard view of working memory as persistent activity and dual-store accounts of free recall. Rapidly expressed and volatile synaptic plasticity, modulated intrinsic excitability, and spike-frequency adaptation are suggested as key cellular mechanisms underlying working memory encoding, reactivation and recall. Recent findings on the synaptic and molecular mechanisms behind early LTP and on spiking activity during delayed-match-to-sample tasks support this view.

  6. Reactivation in working memory: an attractor network model of free recall.

    Directory of Open Access Journals (Sweden)

    Anders Lansner

    Full Text Available The dynamic nature of human working memory, the general-purpose system for processing continuous input, while keeping no longer externally available information active in the background, is well captured in immediate free recall of supraspan word-lists. Free recall tasks produce several benchmark memory phenomena, like the U-shaped serial position curve, reflecting enhanced memory for early and late list items. To account for empirical data, including primacy and recency as well as contiguity effects, we propose here a neurobiologically based neural network model that unifies short- and long-term forms of memory and challenges both the standard view of working memory as persistent activity and dual-store accounts of free recall. Rapidly expressed and volatile synaptic plasticity, modulated intrinsic excitability, and spike-frequency adaptation are suggested as key cellular mechanisms underlying working memory encoding, reactivation and recall. Recent findings on the synaptic and molecular mechanisms behind early LTP and on spiking activity during delayed-match-to-sample tasks support this view.

  7. Oligonol improves memory and cognition under an amyloid β(25-35)-induced Alzheimer's mouse model.

    Science.gov (United States)

    Choi, Yoon Young; Maeda, Takahiro; Fujii, Hajime; Yokozawa, Takako; Kim, Hyun Young; Cho, Eun Ju; Shibamoto, Takayuki

    2014-07-01

    Alzheimer's disease is an age-dependent progressive neurodegenerative disorder that results in impairments of memory and cognitive function. It is hypothesized that oligonol has ameliorative effects on memory impairment and reduced cognitive functions in mice with Alzheimer's disease induced by amyloid β(25-35) (Aβ(25-35)) injection. The protective effect of an oligonol against Aβ(25-35)-induced memory impairment was investigated in an in vivo Alzheimer's mouse model. The aggregation of Aβ25-35 was induced by incubation at 37°C for 3 days before injection into mice brains (5 nmol/mouse), and then oligonol was orally administered at 100 and 200 mg/kg of body weight for 2 weeks. Memory and cognition were observed in T-maze, object recognition, and Morris water maze tests. The group injected with Aβ(25-35) showed impairments in both recognition and memory. However, novel object recognition and new route awareness abilities were dose dependently improved by the oral administration of oligonol. In addition, the results of the Morris water maze test indicated that oligonol exerted protective activity against cognitive impairment induced by Aβ(25-35). Furthermore, nitric oxide formation and lipid peroxidation were significantly elevated by Aβ(25-35), whereas oligonol treatment significantly decreased nitric oxide formation and lipid peroxidation in the brain, liver, and kidneys. The present results suggest that oligonol improves Aβ(25-35)-induced memory deficit and cognition impairment. Copyright © 2014 Elsevier Inc. All rights reserved.

  8. Reactivation in Working Memory: An Attractor Network Model of Free Recall

    Science.gov (United States)

    Lansner, Anders; Marklund, Petter; Sikström, Sverker; Nilsson, Lars-Göran

    2013-01-01

    The dynamic nature of human working memory, the general-purpose system for processing continuous input, while keeping no longer externally available information active in the background, is well captured in immediate free recall of supraspan word-lists. Free recall tasks produce several benchmark memory phenomena, like the U-shaped serial position curve, reflecting enhanced memory for early and late list items. To account for empirical data, including primacy and recency as well as contiguity effects, we propose here a neurobiologically based neural network model that unifies short- and long-term forms of memory and challenges both the standard view of working memory as persistent activity and dual-store accounts of free recall. Rapidly expressed and volatile synaptic plasticity, modulated intrinsic excitability, and spike-frequency adaptation are suggested as key cellular mechanisms underlying working memory encoding, reactivation and recall. Recent findings on the synaptic and molecular mechanisms behind early LTP and on spiking activity during delayed-match-to-sample tasks support this view. PMID:24023690

  9. Fear memory in a neurodevelopmental model of schizophrenia based on the postnatal blockade of NMDA receptors.

    Science.gov (United States)

    Latusz, Joachim; Radaszkiewicz, Aleksandra; Bator, Ewelina; Wędzony, Krzysztof; Maćkowiak, Marzena

    2017-02-01

    Epidemiological data have indicated that memory impairment is observed during adolescence in groups at high risk for schizophrenia and might precede the appearance of schizophrenia symptoms in adulthood. In the present study, we used a neurodevelopmental model of schizophrenia based on the postnatal blockade of N-methyl-d-aspartate (NMDA) receptors in rats to investigate fear memory in adolescence and adulthood. The rats were treated with increasing doses of CGP 37849 (CGP), a competitive antagonist of the NMDA receptor (1.25mg/kg on days 1, 3, 6, 9; 2.5mg/kg on days 12, 15, 18 and 5mg/kg on day 21). Fear memory was analysed in delay and trace fear conditioning. Sensorimotor gating deficit, which is another cognitive symptom of schizophrenia, was also determined in adolescent and adult CGP-treated rats. Postnatal CGP administration disrupted cue- and context-dependent fear memory in adolescent rats in both delay and trace conditioning. In contrast, CGP administration evoked impairment only in cue-dependent fear memory in rats exposed to trace but not delay fear conditioning. The postnatal blockade of NMDA receptors induced sensorimotor gating deficits in adult rats but not in adolescent rats. The postnatal blockade of NMDA receptors induced fear memory impairment in adolescent rats before the onset of neurobehavioral deficits associated with schizophrenia. Copyright © 2016. Published by Elsevier Urban & Partner Sp. z o.o.

  10. Working memory load and the retro-cue effect: A diffusion model account.

    Science.gov (United States)

    Shepherdson, Peter; Oberauer, Klaus; Souza, Alessandra S

    2018-02-01

    Retro-cues (i.e., cues presented between the offset of a memory array and the onset of a probe) have consistently been found to enhance performance in working memory tasks, sometimes ameliorating the deleterious effects of increased memory load. However, the mechanism by which retro-cues exert their influence remains a matter of debate. To inform this debate, we applied a hierarchical diffusion model to data from 4 change detection experiments using single item, location-specific probes (i.e., a local recognition task) with either visual or verbal memory stimuli. Results showed that retro-cues enhanced the quality of information entering the decision process-especially for visual stimuli-and decreased the time spent on nondecisional processes. Further, cues interacted with memory load primarily on nondecision time, decreasing or abolishing load effects. To explain these findings, we propose an account whereby retro-cues act primarily to reduce the time taken to access the relevant representation in memory upon probe presentation, and in addition protect cued representations from visual interference. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  11. Structural Breaks and Long Memory Property in Korean Won Exchange Rates: Adaptive FIGARCH Model

    Directory of Open Access Journals (Sweden)

    Young Wook Han

    2011-06-01

    Full Text Available This paper explores the issue of structural breaks and long memory property in the conditional variance process of the Korean exchange rates. To analyze the above in detail, this paper examines the dynamics of the structural breaks and the long memory in the conditional variance process of the Korean exchange returns by using the daily KRW-USD and KRW-JPY exchange rates for the period from 2000 through 2007. In particular, this paper employs the Adaptive FIGARCH model of Baillie and Morana (2009 which account for the structural breaks and the long memory property together. This paper also finds that the new Adaptive FIGARCH model outperforms the usual FIGARCH model of Baillie et al. (1996 when the structural breaks are present and that the long memory property in the conditional variance process of the Korean exchange returns is significantly reduced after the structural breaks are accounted for. Thus, these results suggest that the upward biased long memory property observed in the conditional variance process of the Korean exchange returns could partially have been imparted as a result of neglecting the structural breaks.

  12. Spatial Impairment and Memory in Genetic Disorders: Insights from Mouse Models

    Directory of Open Access Journals (Sweden)

    Sang Ah Lee

    2017-02-01

    Full Text Available Research across the cognitive and brain sciences has begun to elucidate some of the processes that guide navigation and spatial memory. Boundary geometry and featural landmarks are two distinct classes of environmental cues that have dissociable neural correlates in spatial representation and follow different patterns of learning. Consequently, spatial navigation depends both on the type of cue available and on the type of learning provided. We investigated this interaction between spatial representation and memory by administering two different tasks (working memory, reference memory using two different environmental cues (rectangular geometry, striped landmark in mouse models of human genetic disorders: Prader-Willi syndrome (PWScrm+/p− mice, n = 12 and Beta-catenin mutation (Thr653Lys-substituted mice, n = 12. This exploratory study provides suggestive evidence that these models exhibit different abilities and impairments in navigating by boundary geometry and featural landmarks, depending on the type of memory task administered. We discuss these data in light of the specific deficits in cognitive and brain function in these human syndromes and their animal model counterparts.

  13. Caveats on psychological models of sleep and memory: a compass in an overgrown scenario.

    Science.gov (United States)

    Conte, Francesca; Ficca, Gianluca

    2013-04-01

    The search for a unitary model of sleep-memory relationships seems still far from accomplished, despite the huge body of data produced in the latest twenty years. So far, inconsistent results have been mainly addressed by parcelling out memory through a continuous refinement of its classification systems, with a major focus on dichotomic distinctions such as the one concerning the declarative vs. procedural memory systems, or the implicit vs. explicit nature of learning. Although this approach has provided a remarkable contribution, it has somehow resulted in an extreme fragmentation of the scenario, where it is even more complex to get a clear picture of the way sleep and memory are connected. This article, starting from a review of the most recent literature on sleep-memory relationships, is intended to provide a compass in this frantically moving landscape. By sorting out the most promising research lines, we highlight some crucial "ongoing" theoretical developments, such as: the rediscovery of the classical notion in psychology of memory that learning has a reconstructive rather than a reproductive nature, with the need of addressing phenomena such as the delicate balance between remembering and forgetting and the integration of different items of knowledge; the growing interest in the role of additional factors influencing memory processes, such as intentionality and learning strategies; the possibility that organizational rather than structural features of sleep are essential to sleep-dependent memory consolidation. We will also discuss how these recent perspectives disclose a number of relevant methodological caveats to be carefully taken into account when conceiving experimental designs. Copyright © 2012 Elsevier Ltd. All rights reserved.

  14. Dorsoventral and Proximodistal Hippocampal Processing Account for the Influences of Sleep and Context on Memory (Reconsolidation: A Connectionist Model

    Directory of Open Access Journals (Sweden)

    Justin Lines

    2017-01-01

    Full Text Available The context in which learning occurs is sufficient to reconsolidate stored memories and neuronal reactivation may be crucial to memory consolidation during sleep. The mechanisms of context-dependent and sleep-dependent memory (reconsolidation are unknown but involve the hippocampus. We simulated memory (reconsolidation using a connectionist model of the hippocampus that explicitly accounted for its dorsoventral organization and for CA1 proximodistal processing. Replicating human and rodent (reconsolidation studies yielded the following results. (1 Semantic overlap between memory items and extraneous learning was necessary to explain experimental data and depended crucially on the recurrent networks of dorsal but not ventral CA3. (2 Stimulus-free, sleep-induced internal reactivations of memory patterns produced heterogeneous recruitment of memory items and protected memories from subsequent interference. These simulations further suggested that the decrease in memory resilience when subjects were not allowed to sleep following learning was primarily due to extraneous learning. (3 Partial exposure to the learning context during simulated sleep (i.e., targeted memory reactivation uniformly increased memory item reactivation and enhanced subsequent recall. Altogether, these results show that the dorsoventral and proximodistal organization of the hippocampus may be important components of the neural mechanisms for context-based and sleep-based memory (reconsolidations.

  15. Can We Efficiently Check Concurrent Programs Under Relaxed Memory Models in Maude?

    DEFF Research Database (Denmark)

    Arrahman, Yehia Abd; Andric, Marina; Beggiato, Alessandro

    2014-01-01

    to the state space explosion. Several techniques have been proposed to mitigate those problems so to make verification under relaxed memory models feasible. We discuss how to adopt some of those techniques in a Maude-based approach to language prototyping, and suggest the use of other techniques that have been......Relaxed memory models offer suitable abstractions of the actual optimizations offered by multi-core architectures and by compilers of concurrent programming languages. Using such abstractions for verification purposes is challenging in part due to their inherent non-determinism which contributes...

  16. Analysis and modeling of resistive switching mechanism oriented to fault tolerance of resistive memory based on memristor

    International Nuclear Information System (INIS)

    Huang Da; Wu Jun-Jie; Tang Yu-Hua

    2014-01-01

    With the progress of the semiconductor industry, resistive memories, especially the memristor, have drawn increasing attention. The resistive memory based on memrsitor has not been commercialized mainly because of data error. Currently, there are more studies focused on fault tolerance of resistive memory. This paper studies the resistive switching mechanism which may have time-varying characteristics. Resistive switching mechanism is analyzed and its respective circuit model is established based on the memristor Spice model

  17. A Comparison of Dimensional Models of Emotion: Evidence from Emotions, Prototypical Events, Autobiographical Memories, and Words

    Science.gov (United States)

    Rubin, David C.; Talarico, Jennifer M.

    2009-01-01

    The intensity and valence of 30 emotion terms, 30 events typical of those emotions, and 30 autobiographical memories cued by those emotions were each rated by different groups of 40 undergraduates. A vector model gave a consistently better account of the data than a circumplex model, both overall and in the absence of high intensity, neutral valence stimuli. The Positive Activation - Negative Activation (PANA) model could be tested at high levels of activation, where it is identical to the vector model. The results replicated when ratings of arousal were used instead of ratings of intensity for the events and autobiographical memories. A reanalysis of word norms gave further support for the vector and PANA models by demonstrating that neutral valence, high arousal ratings resulted from the averaging of individual positive and negative valence ratings. Thus, compared to a circumplex model, vector and PANA models provided overall better fits. PMID:19691001

  18. Impact of interaction style and degree on the evolution of cooperation on Barabási-Albert scale-free network.

    Directory of Open Access Journals (Sweden)

    Fengjie Xie

    Full Text Available In this work, we study an evolutionary prisoner's dilemma game (PDG on Barabási-Albert scale-free networks with limited player interactions, and explore the effect of interaction style and degree on cooperation. The results show that high-degree preference interaction, namely the most applicable interaction in the real world, is less beneficial for emergence of cooperation on scale-free networks than random interaction. Besides, cooperation on scale-free networks is enhanced with the increase of interaction degree regardless whether the interaction is high-degree preference or random. If the interaction degree is very low, the cooperation level on scale-free networks is much lower than that on regular ring networks, which is against the common belief that scale-free networks must be more beneficial for cooperation. Our analysis indicates that the interaction relations, the strategy and the game payoff of high-connectivity players play important roles in the evolution of cooperation on scale-free networks. A certain number of interactions are necessary for scale-free networks to exhibit strong capability of facilitating cooperation. Our work provides important insight for members on how to interact with others in a social organization.

  19. A cognitive psychometric model for the psychodiagnostic assessment of memory-related deficits.

    Science.gov (United States)

    Alexander, Gregory E; Satalich, Timothy A; Shankle, W Rodman; Batchelder, William H

    2016-03-01

    Clinical tests used for psychodiagnostic purposes, such as the well-known Alzheimer's Disease Assessment Scale: Cognitive subscale (ADAS-Cog), include a free-recall task. The free-recall task taps into latent cognitive processes associated with learning and memory components of human cognition, any of which might be impaired with the progression of Alzheimer's disease (AD). A Hidden Markov model of free recall is developed to measure latent cognitive processes used during the free-recall task. In return, these cognitive measurements give us insight into the degree to which normal cognitive functions are differentially impaired by medical conditions, such as AD and related disorders. The model is used to analyze the free-recall data obtained from healthy elderly participants, participants diagnosed as having mild cognitive impairment, and participants diagnosed with early AD. The model is specified hierarchically to handle item differences because of the serial position curve in free recall, as well as within-group individual differences in participants' recall abilities. Bayesian hierarchical inference is used to estimate the model. The model analysis suggests that the impaired patients have the following: (1) long-term memory encoding deficits, (2) short-term memory (STM) retrieval deficits for all but very short time intervals, (3) poorer transfer into long-term memory for items successfully retrieved from STM, and (4) poorer retention of items encoded into long-term memory after longer delays. Yet, impaired patients appear to have no deficit in immediate recall of encoded words in long-term memory or for very short time intervals in STM. (c) 2016 APA, all rights reserved).

  20. Hysteresis modeling of magnetic shape memory alloy actuator based on Krasnosel'skii-Pokrovskii model.

    Science.gov (United States)

    Zhou, Miaolei; Wang, Shoubin; Gao, Wei

    2013-01-01

    As a new type of intelligent material, magnetically shape memory alloy (MSMA) has a good performance in its applications in the actuator manufacturing. Compared with traditional actuators, MSMA actuator has the advantages as fast response and large deformation; however, the hysteresis nonlinearity of the MSMA actuator restricts its further improving of control precision. In this paper, an improved Krasnosel'skii-Pokrovskii (KP) model is used to establish the hysteresis model of MSMA actuator. To identify the weighting parameters of the KP operators, an improved gradient correction algorithm and a variable step-size recursive least square estimation algorithm are proposed in this paper. In order to demonstrate the validity of the proposed modeling approach, simulation experiments are performed, simulations with improved gradient correction algorithm and variable step-size recursive least square estimation algorithm are studied, respectively. Simulation results of both identification algorithms demonstrate that the proposed modeling approach in this paper can establish an effective and accurate hysteresis model for MSMA actuator, and it provides a foundation for improving the control precision of MSMA actuator.

  1. Hysteresis Modeling of Magnetic Shape Memory Alloy Actuator Based on Krasnosel'skii-Pokrovskii Model

    Directory of Open Access Journals (Sweden)

    Miaolei Zhou

    2013-01-01

    Full Text Available As a new type of intelligent material, magnetically shape memory alloy (MSMA has a good performance in its applications in the actuator manufacturing. Compared with traditional actuators, MSMA actuator has the advantages as fast response and large deformation; however, the hysteresis nonlinearity of the MSMA actuator restricts its further improving of control precision. In this paper, an improved Krasnosel'skii-Pokrovskii (KP model is used to establish the hysteresis model of MSMA actuator. To identify the weighting parameters of the KP operators, an improved gradient correction algorithm and a variable step-size recursive least square estimation algorithm are proposed in this paper. In order to demonstrate the validity of the proposed modeling approach, simulation experiments are performed, simulations with improved gradient correction algorithm and variable step-size recursive least square estimation algorithm are studied, respectively. Simulation results of both identification algorithms demonstrate that the proposed modeling approach in this paper can establish an effective and accurate hysteresis model for MSMA actuator, and it provides a foundation for improving the control precision of MSMA actuator.

  2. Translation techniques for distributed-shared memory programming models

    Energy Technology Data Exchange (ETDEWEB)

    Fuller, Douglas James [Iowa State Univ., Ames, IA (United States)

    2005-01-01

    The high performance computing community has experienced an explosive improvement in distributed-shared memory hardware. Driven by increasing real-world problem complexity, this explosion has ushered in vast numbers of new systems. Each new system presents new challenges to programmers and application developers. Part of the challenge is adapting to new architectures with new performance characteristics. Different vendors release systems with widely varying architectures that perform differently in different situations. Furthermore, since vendors need only provide a single performance number (total MFLOPS, typically for a single benchmark), they only have strong incentive initially to optimize the API of their choice. Consequently, only a fraction of the available APIs are well optimized on most systems. This causes issues porting and writing maintainable software, let alone issues for programmers burdened with mastering each new API as it is released. Also, programmers wishing to use a certain machine must choose their API based on the underlying hardware instead of the application. This thesis argues that a flexible, extensible translator for distributed-shared memory APIs can help address some of these issues. For example, a translator might take as input code in one API and output an equivalent program in another. Such a translator could provide instant porting for applications to new systems that do not support the application's library or language natively. While open-source APIs are abundant, they do not perform optimally everywhere. A translator would also allow performance testing using a single base code translated to a number of different APIs. Most significantly, this type of translator frees programmers to select the most appropriate API for a given application based on the application (and developer) itself instead of the underlying hardware.

  3. Combining thermodynamic principles with Preisach models for superelastic shape memory alloy wires

    International Nuclear Information System (INIS)

    Doraiswamy, S; Rao, A; Srinivasa, A R

    2011-01-01

    We present a simple model for simulating the response of a superelastic shape memory alloy wire based on the thermodynamics of irreversible processes, which can simulate the full thermomechanical response including internal hysteresis loops, at different temperatures, with minimal data input. The key idea is to separate the dissipative response and the elastic response of shape memory alloys using a Gibbs potential based formulation, and then use a Preisach model for the dissipative part of the response. This enables better handling of the features observed in the superelastic response such as those due to changes in temperature and internal hysteresis loops. We compare the predicted response with experiments performed on 0.75 mm NiTi shape memory alloy wires at three different temperatures

  4. High Performance Programming Using Explicit Shared Memory Model on Cray T3D1

    Science.gov (United States)

    Simon, Horst D.; Saini, Subhash; Grassi, Charles

    1994-01-01

    The Cray T3D system is the first-phase system in Cray Research, Inc.'s (CRI) three-phase massively parallel processing (MPP) program. This system features a heterogeneous architecture that closely couples DEC's Alpha microprocessors and CRI's parallel-vector technology, i.e., the Cray Y-MP and Cray C90. An overview of the Cray T3D hardware and available programming models is presented. Under Cray Research adaptive Fortran (CRAFT) model four programming methods (data parallel, work sharing, message-passing using PVM, and explicit shared memory model) are available to the users. However, at this time data parallel and work sharing programming models are not available to the user community. The differences between standard PVM and CRI's PVM are highlighted with performance measurements such as latencies and communication bandwidths. We have found that the performance of neither standard PVM nor CRI s PVM exploits the hardware capabilities of the T3D. The reasons for the bad performance of PVM as a native message-passing library are presented. This is illustrated by the performance of NAS Parallel Benchmarks (NPB) programmed in explicit shared memory model on Cray T3D. In general, the performance of standard PVM is about 4 to 5 times less than obtained by using explicit shared memory model. This degradation in performance is also seen on CM-5 where the performance of applications using native message-passing library CMMD on CM-5 is also about 4 to 5 times less than using data parallel methods. The issues involved (such as barriers, synchronization, invalidating data cache, aligning data cache etc.) while programming in explicit shared memory model are discussed. Comparative performance of NPB using explicit shared memory programming model on the Cray T3D and other highly parallel systems such as the TMC CM-5, Intel Paragon, Cray C90, IBM-SP1, etc. is presented.

  5. Free-flight odor tracking in Drosophila is consistent with an optimal intermittent scale-free search.

    Directory of Open Access Journals (Sweden)

    Andy M Reynolds

    2007-04-01

    Full Text Available During their trajectories in still air, fruit flies (Drosophila melanogaster explore their landscape using a series of straight flight paths punctuated by rapid 90 degrees body-saccades [1]. Some saccades are triggered by visual expansion associated with collision avoidance. Yet many saccades are not triggered by visual cues, but rather appear spontaneously. Our analysis reveals that the control of these visually independent saccades and the flight intervals between them constitute an optimal scale-free active searching strategy. Two characteristics of mathematical optimality that are apparent during free-flight in Drosophila are inter-saccade interval lengths distributed according to an inverse square law, which does not vary across landscape scale, and 90 degrees saccade angles, which increase the likelihood that territory will be revisited and thereby reduce the likelihood that near-by targets will be missed. We also show that searching is intermittent, such that active searching phases randomly alternate with relocation phases. Behaviorally, this intermittency is reflected in frequently occurring short, slow speed inter-saccade intervals randomly alternating with rarer, longer, faster inter-saccade intervals. Searching patterns that scale similarly across orders of magnitude of length (i.e., scale-free have been revealed in animals as diverse as microzooplankton, bumblebees, albatrosses, and spider monkeys, but these do not appear to be optimised with respect to turning angle, whereas Drosophila free-flight search does. Also, intermittent searching patterns, such as those reported here for Drosophila, have been observed in foragers such as planktivorous fish and ground foraging birds. Our results with freely flying Drosophila may constitute the first reported example of searching behaviour that is both scale-free and intermittent.

  6. Methods for reducing interference in the Complementary Learning Systems model: oscillating inhibition and autonomous memory rehearsal.

    Science.gov (United States)

    Norman, Kenneth A; Newman, Ehren L; Perotte, Adler J

    2005-11-01

    The stability-plasticity problem (i.e. how the brain incorporates new information into its model of the world, while at the same time preserving existing knowledge) has been at the forefront of computational memory research for several decades. In this paper, we critically evaluate how well the Complementary Learning Systems theory of hippocampo-cortical interactions addresses the stability-plasticity problem. We identify two major challenges for the model: Finding a learning algorithm for cortex and hippocampus that enacts selective strengthening of weak memories, and selective punishment of competing memories; and preventing catastrophic forgetting in the case of non-stationary environments (i.e. when items are temporarily removed from the training set). We then discuss potential solutions to these problems: First, we describe a recently developed learning algorithm that leverages neural oscillations to find weak parts of memories (so they can be strengthened) and strong competitors (so they can be punished), and we show how this algorithm outperforms other learning algorithms (CPCA Hebbian learning and Leabra at memorizing overlapping patterns. Second, we describe how autonomous re-activation of memories (separately in cortex and hippocampus) during REM sleep, coupled with the oscillating learning algorithm, can reduce the rate of forgetting of input patterns that are no longer present in the environment. We then present a simple demonstration of how this process can prevent catastrophic interference in an AB-AC learning paradigm.

  7. Spaced training rescues memory and ERK1/2 signaling in fragile X syndrome model mice.

    Science.gov (United States)

    Seese, Ronald R; Wang, Kathleen; Yao, Yue Qin; Lynch, Gary; Gall, Christine M

    2014-11-25

    Recent studies have shown that short, spaced trains of afferent stimulation produce much greater long-term potentiation (LTP) than that obtained with a single, prolonged stimulation episode. The present studies demonstrate that spaced training regimens, based on these LTP timing rules, facilitate learning in wild-type (WT) mice and can offset learning and synaptic signaling impairments in the fragile X mental retardation 1 (Fmr1) knockout (KO) model of fragile X syndrome. We determined that 5 min of continuous training supports object location memory (OLM) in WT but not Fmr1 KO mice. However, the same amount of training distributed across three short trials, spaced by one hour, produced robust long-term memory in the KOs. At least three training trials were needed to realize the benefit of spacing, and intertrial intervals shorter or longer than 60 min were ineffective. Multiple short training trials also rescued novel object recognition in Fmr1 KOs. The spacing effect was surprisingly potent: just 1 min of OLM training, distributed across three trials, supported robust memory in both genotypes. Spacing also rescued training-induced activation of synaptic ERK1/2 in dorsal hippocampus of Fmr1 KO mice. These results show that a spaced training regimen designed to maximize synaptic potentiation facilitates recognition memory in WT mice and can offset synaptic signaling and memory impairments in a model of congenital intellectual disability.

  8. A phenomenological memristor model for short-term/long-term memory

    International Nuclear Information System (INIS)

    Chen, Ling; Li, Chuandong; Huang, Tingwen; Ahmad, Hafiz Gulfam; Chen, Yiran

    2014-01-01

    Memristor is considered to be a natural electrical synapse because of its distinct memory property and nanoscale. In recent years, more and more similar behaviors are observed between memristors and biological synapse, e.g., short-term memory (STM) and long-term memory (LTM). The traditional mathematical models are unable to capture the new emerging behaviors. In this article, an updated phenomenological model based on the model of the Hewlett–Packard (HP) Labs has been proposed to capture such new behaviors. The new dynamical memristor model with an improved ion diffusion term can emulate the synapse behavior with forgetting effect, and exhibit the transformation between the STM and the LTM. Further, this model can be used in building new type of neural networks with forgetting ability like biological systems, and it is verified by our experiment with Hopfield neural network. - Highlights: • We take the Fick diffusion and the Soret diffusion into account in the ion drift theory. • We develop a new model based on the old HP model. • The new model can describe the forgetting effect and the spike-rate-dependent property of memristor. • The new model can solve the boundary effect of all window functions discussed in [13]. • A new Hopfield neural network with the forgetting ability is built by the new memristor model

  9. The role of detachment of in-links in scale-free networks

    International Nuclear Information System (INIS)

    Lansky, P; Polito, F; Sacerdote, L

    2014-01-01

    Real-world networks may exhibit a detachment phenomenon determined by the canceling of previously existing connections. We discuss a tractable extension of the Yule model to account for this feature. Analytical results are derived and discussed both asymptotically and for a finite number of links. Comparison with the original model is performed in the supercritical case. The first-order asymptotic tail behavior of the two models is similar but differences arise in the second-order term. We explicitly refer to world wide web modeling and we show the agreement of the proposed model on very recent data. However, other possible network applications are also mentioned. (paper)

  10. Retrieval-induced NMDA receptor-dependent Arc expression in two models of cocaine-cue memory.

    Science.gov (United States)

    Alaghband, Yasaman; O'Dell, Steven J; Azarnia, Siavash; Khalaj, Anna J; Guzowski, John F; Marshall, John F

    2014-12-01

    The association of environmental cues with drugs of abuse results in persistent drug-cue memories. These memories contribute significantly to relapse among addicts. While conditioned place preference (CPP) is a well-established paradigm frequently used to examine the modulation of drug-cue memories, very few studies have used the non-preference-based model conditioned activity (CA) for this purpose. Here, we used both experimental approaches to investigate the neural substrates of cocaine-cue memories. First, we directly compared, in a consistent setting, the involvement of cortical and subcortical brain regions in cocaine-cue memory retrieval by quantifying activity-regulated cytoskeletal-associated (Arc) protein expression in both the CPP and CA models. Second, because NMDA receptor activation is required for Arc expression, we investigated the NMDA receptor dependency of memory persistence using the CA model. In both the CPP and CA models, drug-paired animals showed significant increases in Arc immunoreactivity in regions of the frontal cortex and amygdala compared to unpaired controls. Additionally, administration of a NMDA receptor antagonist (MK-801 or memantine) immediately after cocaine-CA memory reactivation impaired the subsequent conditioned locomotion associated with the cocaine-paired environment. The enhanced Arc expression evident in a subset of corticolimbic regions after retrieval of a cocaine-context memory, observed in both the CPP and CA paradigms, likely signifies that these regions: (i) are activated during retrieval of these memories irrespective of preference-based decisions, and (ii) undergo neuroplasticity in order to update information about cues previously associated with cocaine. This study also establishes the involvement of NMDA receptors in maintaining memories established using the CA model, a characteristic previously demonstrated using CPP. Overall, these results demonstrate the utility of the CA model for studies of cocaine

  11. Fechner’s law in metacognition: a quantitative model of visual working memory confidence

    Science.gov (United States)

    van den Berg, Ronald; Yoo, Aspen H.; Ma, Wei Ji

    2016-01-01

    Although visual working memory (VWM) has been studied extensively, it is unknown how people form confidence judgments about their memories. Peirce (1878) speculated that Fechner’s law – which states that sensation is proportional to the logarithm of stimulus intensity – might apply to confidence reports. Based on this idea, we hypothesize that humans map the precision of their VWM contents to a confidence rating through Fechner’s law. We incorporate this hypothesis into the best available model of VWM encoding and fit it to data from a delayed-estimation experiment. The model provides an excellent account of human confidence rating distributions as well as the relation between performance and confidence. Moreover, the best-fitting mapping in a model with a highly flexible mapping closely resembles the logarithmic mapping, suggesting that no alternative mapping exists that accounts better for the data than Fechner's law. We propose a neural implementation of the model and find that this model also fits the behavioral data well. Furthermore, we find that jointly fitting memory errors and confidence ratings boosts the power to distinguish previously proposed VWM encoding models by a factor of 5.99 compared to fitting only memory errors. Finally, we show that Fechner's law also accounts for metacognitive judgments in a word recognition memory task, which is a first indication that it may be a general law in metacognition. Our work presents the first model to jointly account for errors and confidence ratings in VWM and could lay the groundwork for understanding the computational mechanisms of metacognition. PMID:28221087

  12. Discrete-Slots Models of Visual Working-Memory Response Times

    Science.gov (United States)

    Donkin, Christopher; Nosofsky, Robert M.; Gold, Jason M.; Shiffrin, Richard M.

    2014-01-01

    Much recent research has aimed to establish whether visual working memory (WM) is better characterized by a limited number of discrete all-or-none slots or by a continuous sharing of memory resources. To date, however, researchers have not considered the response-time (RT) predictions of discrete-slots versus shared-resources models. To complement the past research in this field, we formalize a family of mixed-state, discrete-slots models for explaining choice and RTs in tasks of visual WM change detection. In the tasks under investigation, a small set of visual items is presented, followed by a test item in 1 of the studied positions for which a change judgment must be made. According to the models, if the studied item in that position is retained in 1 of the discrete slots, then a memory-based evidence-accumulation process determines the choice and the RT; if the studied item in that position is missing, then a guessing-based accumulation process operates. Observed RT distributions are therefore theorized to arise as probabilistic mixtures of the memory-based and guessing distributions. We formalize an analogous set of continuous shared-resources models. The model classes are tested on individual subjects with both qualitative contrasts and quantitative fits to RT-distribution data. The discrete-slots models provide much better qualitative and quantitative accounts of the RT and choice data than do the shared-resources models, although there is some evidence for “slots plus resources” when memory set size is very small. PMID:24015956

  13. Exploring Neural Network Models with Hierarchical Memories and Their Use in Modeling Biological Systems

    Science.gov (United States)

    Pusuluri, Sai Teja

    Energy landscapes are often used as metaphors for phenomena in biology, social sciences and finance. Different methods have been implemented in the past for the construction of energy landscapes. Neural network models based on spin glass physics provide an excellent mathematical framework for the construction of energy landscapes. This framework uses a minimal number of parameters and constructs the landscape using data from the actual phenomena. In the past neural network models were used to mimic the storage and retrieval process of memories (patterns) in the brain. With advances in the field now, these models are being used in machine learning, deep learning and modeling of complex phenomena. Most of the past literature focuses on increasing the storage capacity and stability of stored patterns in the network but does not study these models from a modeling perspective or an energy landscape perspective. This dissertation focuses on neural network models both from a modeling perspective and from an energy landscape perspective. I firstly show how the cellular interconversion phenomenon can be modeled as a transition between attractor states on an epigenetic landscape constructed using neural network models. The model allows the identification of a reaction coordinate of cellular interconversion by analyzing experimental and simulation time course data. Monte Carlo simulations of the model show that the initial phase of cellular interconversion is a Poisson process and the later phase of cellular interconversion is a deterministic process. Secondly, I explore the static features of landscapes generated using neural network models, such as sizes of basins of attraction and densities of metastable states. The simulation results show that the static landscape features are strongly dependent on the correlation strength and correlation structure between patterns. Using different hierarchical structures of the correlation between patterns affects the landscape features

  14. Cognitive memory.

    Science.gov (United States)

    Widrow, Bernard; Aragon, Juan Carlos

    2013-05-01

    Regarding the workings of the human mind, memory and pattern recognition seem to be intertwined. You generally do not have one without the other. Taking inspiration from life experience, a new form of computer memory has been devised. Certain conjectures about human memory are keys to the central idea. The design of a practical and useful "cognitive" memory system is contemplated, a memory system that may also serve as a model for many aspects of human memory. The new memory does not function like a computer memory where specific data is stored in specific numbered registers and retrieval is done by reading the contents of the specified memory register, or done by matching key words as with a document search. Incoming sensory data would be stored at the next available empty memory location, and indeed could be stored redundantly at several empty locations. The stored sensory data would neither have key words nor would it be located in known or specified memory locations. Sensory inputs concerning a single object or subject are stored together as patterns in a single "file folder" or "memory folder". When the contents of the folder are retrieved, sights, sounds, tactile feel, smell, etc., are obtained all at the same time. Retrieval would be initiated by a query or a prompt signal from a current set of sensory inputs or patterns. A search through the memory would be made to locate stored data that correlates with or relates to the prompt input. The search would be done by a retrieval system whose first stage makes use of autoassociative artificial neural networks and whose second stage relies on exhaustive search. Applications of cognitive memory systems have been made to visual aircraft identification, aircraft navigation, and human facial recognition. Concerning human memory, reasons are given why it is unlikely that long-term memory is stored in the synapses of the brain's neural networks. Reasons are given suggesting that long-term memory is stored in DNA or RNA

  15. What Models of Verbal Working Memory Can Learn from Phonological Theory: Decomposing the Phonological Similarity Effect

    Science.gov (United States)

    Schweppe, Judith; Grice, Martine; Rummer, Ralf

    2011-01-01

    Despite developments in phonology over the last few decades, models of verbal working memory make reference to phoneme-sized phonological units, rather than to the features of which they are composed. This study investigates the influence on short-term retention of such features by comparing the serial recall of lists of syllables with varying…

  16. MeSAP: a fast analytic power model for DRAM memories

    NARCIS (Netherlands)

    Poddar, S.; Jongerius, R.; Fiorin, L.; Mariani, G.; Dittmann, G.; Anghel, A.; Corporaal, H.

    2017-01-01

    The design of an energy-efficient memory subsystem is one of the key issues that system architects face today. To achieve this goal, architects usually rely on system simulators and trace-based DRAM power models. However, their long execution time makes the approach infeasible for the design-space

  17. Pricing European option with transaction costs under the fractional long memory stochastic volatility model

    Science.gov (United States)

    Wang, Xiao-Tian; Wu, Min; Zhou, Ze-Min; Jing, Wei-Shu

    2012-02-01

    This paper deals with the problem of discrete time option pricing using the fractional long memory stochastic volatility model with transaction costs. Through the 'anchoring and adjustment' argument in a discrete time setting, a European call option pricing formula is obtained.

  18. On dynamic selection of households for direct marketing based on Markov chain models with memory

    NARCIS (Netherlands)

    Otter, Pieter W.

    A simple, dynamic selection procedure is proposed, based on conditional, expected profits using Markov chain models with memory. The method is easy to apply, only frequencies and mean values have to be calculated or estimated. The method is empirically illustrated using a data set from a charitable

  19. Working Memory in Written Composition: An Evaluation of the 1996 Model

    Directory of Open Access Journals (Sweden)

    Ronald T. Kellogg, , , &

    2013-10-01

    Full Text Available A model of how working memory, as conceived by Baddeley (1986, supports the planning of ideas, translating ideas into written sentences, and reviewing the ideas and text already produced was proposed by Kellogg (1996. A progress report based on research from the past 17 years shows strong support for the core assumption that planning, translating, and reviewing are all dependent on the central executive. Similarly, the translation of ideas into a sentence does in fact require also verbal working memory, but the claim that editing makes no demands on the phonological loop is tenuous. As predicted by the model, planning also engages the visuo-spatial sketchpad. However, it turns out to do so only in planning with concrete concepts that elicit mental imagery. Abstract concepts do not require visuo-spatial resources, a point not anticipated by the original model. Moreover, it is unclear the extent to which planning involves spatial as opposed to visual working memory. Contrary to Baddeley’s original model, these are now known to be independent stores of working memory; the specific role of the spatial store in writing is uncertain based on the existing literature. The implications of this body of research for the instruction of writing are considered in the final section of the paper.

  20. Comparison of Three Models Dealing with Working Memory and Its Dimensions in Second Language Acquisition

    Directory of Open Access Journals (Sweden)

    Abdulaziz Alshahrani

    2017-12-01

    Full Text Available The current status of research on working memory (WM and its components in second language acquisition (SLA was examined in this review. Literature search was done on four aspects using search terms in Google Scholar. Hence, the review results are given and introduced. 1. In the definition of WM, some confusion exists on whether short term memory (STM or recent memory is the same as WM or different. 2. In this review, three main models have been discussed elaborately, as they are the only ones discussed in literature. They are: multicomponent model of Baddeley (2000, embedded process model of Cowan (2005 and attention control model of Engle and Kane (2003. 3. The phonological and executive components of WM were examined in more detail, as these determine the two basic aspects of language acquisition: language characteristics and acquisition methods (Wen, 2012. Overall, the variables related to phonological and executive working memories are evident from published research, but their interactive relationships and affecting factors are not entirely clear. 4. Admittedly, several diverse internal and external factors affect WM in relation to SLA. Some practically useful interventions are indicated by certain findings.

  1. Allergen immunotherapy induces a suppressive memory response mediated by IL-10 in a mouse asthma model

    NARCIS (Netherlands)

    Vissers, Joost L. M.; van Esch, Betty C. A. M.; Hofman, Gerard A.; Kapsenberg, Martien L.; Weller, Frank R.; van Oosterhout, Antoon J. M.

    2004-01-01

    Background: Human studies have demonstrated that allergen immunotherapy induces memory suppressive responses and IL-10 production by allergen-specific T cells. Previously, we established a mouse model in which allergen immunotherapy was effective in the suppression of allergen-induced asthma

  2. Generalization through the Recurrent Interaction of Episodic Memories: A Model of the Hippocampal System

    Science.gov (United States)

    Kumaran, Dharshan; McClelland, James L.

    2012-01-01

    In this article, we present a perspective on the role of the hippocampal system in generalization, instantiated in a computational model called REMERGE (recurrency and episodic memory results in generalization). We expose a fundamental, but neglected, tension between prevailing computational theories that emphasize the function of the hippocampus…

  3. Statistical mechanics of neocortical interactions: Constraints on 40-Hz models of short-term memory

    Science.gov (United States)

    Ingber, Lester

    1995-10-01

    Calculations presented in L. Ingber and P.L. Nunez, Phys. Rev. E 51, 5074 (1995) detailed the evolution of short-term memory in the neocortex, supporting the empirical 7+/-2 rule of constraints on the capacity of neocortical processing. These results are given further support when other recent models of 40-Hz subcycles of low-frequency oscillations are considered.

  4. Effects of Model Performances on Music Skill Acquisition and Overnight Memory Consolidation

    Science.gov (United States)

    Cash, Carla D.; Allen, Sarah E.; Simmons, Amy L.; Duke, Robert A.

    2014-01-01

    This study was designed to investigate the extent to which the presentation of an auditory model prior to learning a novel melody affects performance during active practice and the overnight consolidation of procedural memory. During evening training sessions, 32 nonpianist musicians practiced a 13-note keyboard melody with their left…

  5. Models Provide Specificity: Testing a Proposed Mechanism of Visual Working Memory Capacity Development

    Science.gov (United States)

    Simmering, Vanessa R.; Patterson, Rebecca

    2012-01-01

    Numerous studies have established that visual working memory has a limited capacity that increases during childhood. However, debate continues over the source of capacity limits and its developmental increase. Simmering (2008) adapted a computational model of spatial cognitive development, the Dynamic Field Theory, to explain not only the source…

  6. A Neural Network Model of the Effects of Entrenchment and Memory Development on Grammatical Gender Learning

    Science.gov (United States)

    Monner, Derek; Vatz, Karen; Morini, Giovanna; Hwang, So-One; DeKeyser, Robert

    2013-01-01

    To investigate potential causes of L2 performance deficits that correlate with age of onset, we use a computational model to explore the individual contributions of L1 entrenchment and aspects of memory development. Since development and L1 entrenchment almost invariably coincide, studying them independently is seldom possible in humans. To avoid…

  7. PMCAP: A Threat Model of Process Memory Data on the Windows Operating System

    Directory of Open Access Journals (Sweden)

    Jiaye Pan

    2017-01-01

    Full Text Available Research on endpoint security involves both traditional PC platform and prevalent mobile platform, among which the analysis of software vulnerability and malware is one of the important contents. For researchers, it is necessary to carry out nonstop exploration of the insecure factors in order to better protect the endpoints. Driven by this motivation, we propose a new threat model named Process Memory Captor (PMCAP on the Windows operating system which threatens the live process volatile memory data. Compared with other threats, PMCAP aims at dynamic data in the process memory and uses a noninvasive approach for data extraction. In this paper we describe and analyze the model and then give a detailed implementation taking four popular web browsers IE, Edge, Chrome, and Firefox as examples. Finally, the model is verified through real experiments and case studies. Compared with existing technologies, PMCAP can extract valuable data at a lower cost; some techniques in the model are also suitable for memory forensics and malware analysis.

  8. A comparative study of the working memory multicomponent model in psychosis and healthy controls.

    Science.gov (United States)

    Sánchez-Torres, Ana M; Elosúa, M Rosa; Lorente-Omeñaca, Ruth; Moreno-Izco, Lucía; Cuesta, Manuel J

    2015-08-01

    Working memory deficits are considered nuclear deficits in psychotic disorders. However, research has not found a generalized impairment in all of the components of working memory. We aimed to assess the components of the Baddeley and Hitch working memory model: the temporary systems-the phonological loop, the visuospatial sketchpad and the episodic buffer (introduced later by Baddeley)-and the central executive system, which includes four executive functions: divided attention, updating, shifting and inhibition. We assessed working memory performance in a sample of 21 patients with a psychotic disorder and 21 healthy controls. Patients also underwent a clinical assessment. Both univariate and repeated measures ANOVAs were applied to analyze performance in the working memory components between groups. Patients with a psychotic disorder underperformed compared to the controls in all of the working memory tasks, but after controlling for age and premorbid IQ, we only found a difference in performance in the N-Back task. Repeated measures ANCOVAs showed that patients also underperformed compared to the controls in the Digit span test and the TMT task. Not all of the components of working memory were impaired in the patients. Specifically, patients' performance was impaired in the tasks selected to assess the phonological loop and the shifting executive function. Patients' also showed worse performance than controls in the N-Back task, representative of the updating executive function. However, we did not find higher impairment in the patients' performance respect to controls when increasing the loading of the task. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. Estimating Memory Deterioration Rates Following Neurodegeneration and Traumatic Brain Injuries in a Hopfield Network Model

    Directory of Open Access Journals (Sweden)

    Melanie Weber

    2017-11-01

    Full Text Available Neurodegenerative diseases and traumatic brain injuries (TBI are among the main causes of cognitive dysfunction in humans. At a neuronal network level, they both extensively exhibit focal axonal swellings (FAS, which in turn, compromise the information encoded in spike trains and lead to potentially severe functional deficits. There are currently no satisfactory quantitative predictors of decline in memory-encoding neuronal networks based on the impact and statistics of FAS. Some of the challenges of this translational approach include our inability to access small scale injuries with non-invasive methods, the overall complexity of neuronal pathologies, and our limited knowledge of how networks process biological signals. The purpose of this computational study is three-fold: (i to extend Hopfield's model for associative memory to account for the effects of FAS, (ii to calibrate FAS parameters from biophysical observations of their statistical distribution and size, and (iii to systematically evaluate deterioration rates for different memory-recall tasks as a function of FAS injury. We calculate deterioration rates for a face-recognition task to account for highly correlated memories and also for a discrimination task of random, uncorrelated memories with a size at the capacity limit of the Hopfield network. While it is expected that the performance of any injured network should decrease with injury, our results link, for the first time, the memory recall ability to observed FAS statistics. This allows for plausible estimates of cognitive decline for different stages of brain disorders within neuronal networks, bridging experimental observations following neurodegeneration and TBI with compromised memory recall. The work lends new insights to help close the gap between theory and experiment on how biological signals are processed in damaged, high-dimensional functional networks, and towards positing new diagnostic tools to measure cognitive

  10. Estimating Memory Deterioration Rates Following Neurodegeneration and Traumatic Brain Injuries in a Hopfield Network Model

    Science.gov (United States)

    Weber, Melanie; Maia, Pedro D.; Kutz, J. Nathan

    2017-01-01

    Neurodegenerative diseases and traumatic brain injuries (TBI) are among the main causes of cognitive dysfunction in humans. At a neuronal network level, they both extensively exhibit focal axonal swellings (FAS), which in turn, compromise the information encoded in spike trains and lead to potentially severe functional deficits. There are currently no satisfactory quantitative predictors of decline in memory-encoding neuronal networks based on the impact and statistics of FAS. Some of the challenges of this translational approach include our inability to access small scale injuries with non-invasive methods, the overall complexity of neuronal pathologies, and our limited knowledge of how networks process biological signals. The purpose of this computational study is three-fold: (i) to extend Hopfield's model for associative memory to account for the effects of FAS, (ii) to calibrate FAS parameters from biophysical observations of their statistical distribution and size, and (iii) to systematically evaluate deterioration rates for different memory-recall tasks as a function of FAS injury. We calculate deterioration rates for a face-recognition task to account for highly correlated memories and also for a discrimination task of random, uncorrelated memories with a size at the capacity limit of the Hopfield network. While it is expected that the performance of any injured network should decrease with injury, our results link, for the first time, the memory recall ability to observed FAS statistics. This allows for plausible estimates of cognitive decline for different stages of brain disorders within neuronal networks, bridging experimental observations following neurodegeneration and TBI with compromised memory recall. The work lends new insights to help close the gap between theory and experiment on how biological signals are processed in damaged, high-dimensional functional networks, and towards positing new diagnostic tools to measure cognitive deficits. PMID

  11. Retrieval and organizational strategies in conceptual memory a computer model

    CERN Document Server

    Kolodner, Janet L

    2014-01-01

    'Someday we expect that computers will be able to keep us informed about the news. People have imagined being able to ask their home computers questions such as "What's going on in the world?"…'. Originally published in 1984, this book is a fascinating look at the world of memory and computers before the internet became the mainstream phenomenon it is today. It looks at the early development of a computer system that could keep us informed in a way that we now take for granted. Presenting a theory of remembering, based on human information processing, it begins to address many of the hard problems implicated in the quest to make computers remember. The book had two purposes in presenting this theory of remembering. First, to be used in implementing intelligent computer systems, including fact retrieval systems and intelligent systems in general. Any intelligent program needs to use and store and use a great deal of knowledge. The strategies and structures in the book were designed to be used for that purpos...

  12. Uncertainty analysis of a one-dimensional constitutive model for shape memory alloy thermomechanical description

    DEFF Research Database (Denmark)

    Oliveira, Sergio A.; Savi, Marcelo A.; Santos, Ilmar F.

    2014-01-01

    The use of shape memory alloys (SMAs) in engineering applications has increased the interest of the accuracy analysis of their thermomechanical description. This work presents an uncertainty analysis related to experimental tensile tests conducted with shape memory alloy wires. Experimental data...... are compared with numerical simulations obtained from a constitutive model with internal constraints employed to describe the thermomechanical behavior of SMAs. The idea is to evaluate if the numerical simulations are within the uncertainty range of the experimental data. Parametric analysis is also developed...

  13. The impact of working memory and the "process of process modelling" on model quality: Investigating experienced versus inexperienced modellers.

    Science.gov (United States)

    Martini, Markus; Pinggera, Jakob; Neurauter, Manuel; Sachse, Pierre; Furtner, Marco R; Weber, Barbara

    2016-05-09

    A process model (PM) represents the graphical depiction of a business process, for instance, the entire process from online ordering a book until the parcel is delivered to the customer. Knowledge about relevant factors for creating PMs of high quality is lacking. The present study investigated the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension, modelling, and reconciliation) were related to PM quality. Our results show that the WM function of relational integration was positively related to PM quality in both modelling groups. The ratio of comprehension phases was negatively related to PM quality in inexperienced modellers and the ratio of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling.

  14. ON THE ISSUE OF "MEMORY" MARKOV MODEL OF DAMAGE ACCUMULATION

    Directory of Open Access Journals (Sweden)

    A. I. Lantuh-Lyaschenko

    2010-04-01

    Full Text Available This paper presents the application of a probabilistic approach for the modeling of service life of highway bridge elements. The focus of this paper is on the Markov stochastic deterioration models. These models can be used as effective tool for technical state assessments and prediction of residual resource of a structure. For the bridge maintenance purpose these models can give quantitative criteria of a reliability level, risk and prediction algorithms of the residual resource.

  15. A Memory Hierarchy Model Based on Data Reuse for Full-Search Motion Estimation on High-Definition Digital Videos

    Directory of Open Access Journals (Sweden)

    Alba Sandyra Bezerra Lopes

    2012-01-01

    Full Text Available The motion estimation is the most complex module in a video encoder requiring a high processing throughput and high memory bandwidth, mainly when the focus is high-definition videos. The throughput problem can be solved increasing the parallelism in the internal operations. The external memory bandwidth may be reduced using a memory hierarchy. This work presents a memory hierarchy model for a full-search motion estimation core. The proposed memory hierarchy model is based on a data reuse scheme considering the full search algorithm features. The proposed memory hierarchy expressively reduces the external memory bandwidth required for the motion estimation process, and it provides a very high data throughput for the ME core. This throughput is necessary to achieve real time when processing high-definition videos. When considering the worst bandwidth scenario, this memory hierarchy is able to reduce the external memory bandwidth in 578 times. A case study for the proposed hierarchy, using 32×32 search window and 8×8 block size, was implemented and prototyped on a Virtex 4 FPGA. The results show that it is possible to reach 38 frames per second when processing full HD frames (1920×1080 pixels using nearly 299 Mbytes per second of external memory bandwidth.

  16. Constitutive modeling of SMA SMP multifunctional high performance smart adaptive shape memory composite

    International Nuclear Information System (INIS)

    Jarali, Chetan S; Raja, S; Upadhya, A R

    2010-01-01

    Materials design involving the thermomechanical constitutive modeling of shape memory alloy (SMA) and shape memory polymer (SMP) composites is a key topic in the development of smart adaptive shape memory composites (SASMC). In this work, a constitutive model for SASMC is developed. First, a one-dimensional SMA model, which can simulate the pseudoelastic (PE) and shape memory effects (SME) is presented. Subsequently, a one-dimensional SMP model able to reproduce the SME is addressed. Both SMA and SMP models are based on a single internal state variable, namely the martensite fraction and the frozen fraction, which can be expressed as a function of temperature. A consistent form of the analytical solution for the SMP model is obtained using the fourth-order Runge–Kutta method. Finally, the SASMC constitutive model is proposed, following two analytical homogenization approaches. One approach is based on an equivalent inclusion method and the other approach is the rule of mixtures. The SMA and SMP constitutive models are validated independently with experimental results. However, the validation of the composite model is performed using the two homogenization approaches and a close agreement in results is observed. Results regarding the isothermal and thermomechanical stress–strain responses are analyzed as a function of SMA volume fraction. Further, it is concluded that the proposed composite model is able to reproduce consistently the overall composite response by taking into consideration not only the phase transformations, variable modulus and transformation stresses in SMA but also the variable modulus, the evolution of stored strain and thermal strain in the SMP

  17. "Shape function + memory mechanism"-based hysteresis modeling of magnetorheological fluid actuators

    Science.gov (United States)

    Qian, Li-Jun; Chen, Peng; Cai, Fei-Long; Bai, Xian-Xu

    2018-03-01

    A hysteresis model based on "shape function + memory mechanism" is presented and its feasibility is verified through modeling the hysteresis behavior of a magnetorheological (MR) damper. A hysteresis phenomenon in resistor-capacitor (RC) circuit is first presented and analyzed. In the hysteresis model, the "memory mechanism" originating from the charging and discharging processes of the RC circuit is constructed by adopting a virtual displacement variable and updating laws for the reference points. The "shape function" is achieved and generalized from analytical solutions of the simple semi-linear Duhem model. Using the approach, the memory mechanism reveals the essence of specific Duhem model and the general shape function provides a direct and clear means to fit the hysteresis loop. In the frame of the structure of a "Restructured phenomenological model", the original hysteresis operator, i.e., the Bouc-Wen operator, is replaced with the new hysteresis operator. The comparative work with the Bouc-Wen operator based model demonstrates superior performances of high computational efficiency and comparable accuracy of the new hysteresis operator-based model.

  18. Introducing memory and association mechanism into a biologically inspired visual model.

    Science.gov (United States)

    Qiao, Hong; Li, Yinlin; Tang, Tang; Wang, Peng

    2014-09-01

    A famous biologically inspired hierarchical model (HMAX model), which was proposed recently and corresponds to V1 to V4 of the ventral pathway in primate visual cortex, has been successfully applied to multiple visual recognition tasks. The model is able to achieve a set of position- and scale-tolerant recognition, which is a central problem in pattern recognition. In this paper, based on some other biological experimental evidence, we introduce the memory and association mechanism into the HMAX model. The main contributions of the work are: 1) mimicking the active memory and association mechanism and adding the top down adjustment to the HMAX model, which is the first try to add the active adjustment to this famous model and 2) from the perspective of information, algorithms based on the new model can reduce the computation storage and have a good recognition performance. The new model is also applied to object recognition processes. The primary experimental results show that our method is efficient with a much lower memory requirement.

  19. A stress-induced phase transition model for semi-crystallize shape memory polymer

    Science.gov (United States)

    Guo, Xiaogang; Zhou, Bo; Liu, Liwu; Liu, Yanju; Leng, Jinsong

    2014-03-01

    The developments of constitutive models for shape memory polymer (SMP) have been motivated by its increasing applications. During cooling or heating process, the phase transition which is a continuous time-dependent process happens in semi-crystallize SMP and the various individual phases form at different temperature and in different configuration. Then, the transformation between these phases occurred and shape memory effect will emerge. In addition, stress applied on SMP is an important factor for crystal melting during phase transition. In this theory, an ideal phase transition model considering stress or pre-strain is the key to describe the behaviors of shape memory effect. So a normal distributed model was established in this research to characterize the volume fraction of each phase in SMP during phase transition. Generally, the experiment results are partly backward (in heating process) or forward (in cooling process) compared with the ideal situation considering delay effect during phase transition. So, a correction on the normal distributed model is needed. Furthermore, a nonlinear relationship between stress and phase transition temperature Tg is also taken into account for establishing an accurately normal distributed phase transition model. Finally, the constitutive model which taking the stress as an influence factor on phase transition was also established. Compared with the other expressions, this new-type model possesses less parameter and is more accurate. For the sake of verifying the rationality and accuracy of new phase transition and constitutive model, the comparisons between the simulated and experimental results were carried out.

  20. Modeling Longitudinal Changes in Older Adults’ Memory for Spoken Discourse: Findings from the ACTIVE Cohort

    Science.gov (United States)

    Payne, Brennan R.; Gross, Alden L.; Parisi, Jeanine M.; Sisco, Shannon M.; Stine-Morrow, Elizabeth A. L.; Marsiske, Michael; Rebok, George W.

    2014-01-01

    Episodic memory shows substantial declines with advancing age, but research on longitudinal trajectories of spoken discourse memory (SDM) in older adulthood is limited. Using parallel process latent growth curve models, we examined 10 years of longitudinal data from the no-contact control group (N = 698) of the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) randomized controlled trial in order to test (a) the degree to which SDM declines with advancing age, (b) predictors of these age-related declines, and (c) the within-person relationship between longitudinal changes in SDM and longitudinal changes in fluid reasoning and verbal ability over 10 years, independent of age. Individuals who were younger, White, had more years of formal education, were male, and had better global cognitive function and episodic memory performance at baseline demonstrated greater levels of SDM on average. However, only age at baseline uniquely predicted longitudinal changes in SDM, such that declines accelerated with greater age. Independent of age, within-person decline in reasoning ability over the 10-year study period was substantially correlated with decline in SDM (r = .87). An analogous association with SDM did not hold for verbal ability. The findings suggest that longitudinal declines in fluid cognition are associated with reduced spoken language comprehension. Unlike findings from memory for written prose, preserved verbal ability may not protect against developmental declines in memory for speech. PMID:24304364