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. Modeling interactome: scale-free or geometric?

    Science.gov (United States)

    Przulj, N; Corneil, D G; Jurisica, I

    2004-12-12

    Networks have been used to model many real-world phenomena to better understand the phenomena and to guide experiments in order to predict their behavior. Since incorrect models lead to incorrect predictions, it is vital to have as accurate a model as possible. As a result, new techniques and models for analyzing and modeling real-world networks have recently been introduced. One example of large and complex networks involves protein-protein interaction (PPI) networks. We analyze PPI networks of yeast Saccharomyces cerevisiae and fruitfly Drosophila melanogaster using a newly introduced measure of local network structure as well as the standardly used measures of global network structure. We examine the fit of four different network models, including Erdos-Renyi, scale-free and geometric random network models, to these PPI networks with respect to the measures of local and global network structure. We demonstrate that the currently accepted scale-free model of PPI networks fails to fit the data in several respects and show that a random geometric model provides a much more accurate model of the PPI data. We hypothesize that only the noise in these networks is scale-free. We systematically evaluate how well-different network models fit the PPI networks. We show that the structure of PPI networks is better modeled by a geometric random graph than by a scale-free model. Supplementary information is available at http://www.cs.utoronto.ca/~juris/data/data/ppiGRG04/

  3. A scale-free neural network for modelling neurogenesis

    Science.gov (United States)

    Perotti, Juan I.; Tamarit, Francisco A.; Cannas, Sergio A.

    2006-11-01

    In this work we introduce a neural network model for associative memory based on a diluted Hopfield model, which grows through a neurogenesis algorithm that guarantees that the final network is a small-world and scale-free one. We also analyze the storage capacity of the network and prove that its performance is larger than that measured in a randomly dilute network with the same connectivity.

  4. 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.

  5. Scale-free random graphs and Potts model

    Indian Academy of Sciences (India)

    We introduce a simple algorithm that constructs scale-free random graphs efficiently: each vertex has a prescribed weight − (0 < < 1) and an edge can connect vertices and with rate . Corresponding equilibrium ensemble is identified and the problem is solved by the → 1 limit of the -state Potts ...

  6. Canonical fitness model for simple scale-free graphs

    OpenAIRE

    Flegel, F.; Sokolov, I. M.

    2012-01-01

    We consider a fitness model assumed to generate simple graphs with power-law heavy-tailed degree sequence: P(k) \\propto k^{-1-\\alpha} with 0 < \\alpha < 1, in which the corresponding distributions do not posses a mean. We discuss the situations in which the model is used to produce a multigraph and examine what happens if the multiple edges are merged to a single one and thus a simple graph is built. We give the relation between the (normalized) fitness parameter r and the expected degree \

  7. Scale-free random graphs and Potts model

    Indian Academy of Sciences (India)

    real-world networks such as the world-wide web, the Internet, the coauthorship, the protein interaction networks and so on display power-law behaviors in the degree ... in this paper, we study the evolution of SF random graphs from the perspective of equilibrium statistical physics. The formulation in terms of the spin model ...

  8. Modeling Peer-to-Peer Botnet on Scale-Free Network

    Directory of Open Access Journals (Sweden)

    Liping Feng

    2014-01-01

    Full Text Available Peer-to-peer (P2P botnets have emerged as one of the serious threats to Internet security. To prevent effectively P2P botnet, in this paper, a mathematical model which combines the scale-free trait of Internet with the formation of P2P botnet is presented. Explicit mathematical analysis demonstrates that the model has a globally stable endemic equilibrium when infection rate is greater than a critical value. Meanwhile, we find that, in scale-free network, the critical value is very little. Hence, it is unrealistic to completely dispel the P2P botnet. Numerical simulations show that one can take effective countermeasures to reduce the scale of P2P botnet or delay its outbreak. Our findings can provide meaningful instruction to network security management.

  9. On thermodynamic states of the Ising model on scale-free graphs

    Directory of Open Access Journals (Sweden)

    Yu. Kozitsky

    2013-06-01

    Full Text Available There is proposed a model of scale-free random graphs which are locally close to the uncorrelated complex random networks with divergent 2> studied in, e.g., S. N. Dorogovtsev et al, Rev. Mod. Phys., 80, 1275 (2008. It is shown that the Ising model on the proposed graphs with interaction intensities of arbitrary signs with probability one is in a paramagnetic state at sufficiently high finite values of the temperature. For the same graphs, the bond percolation model with probability one is in a nonpercolative state for positive values of the percolation probability. These results and their possible extensions are also discussed.

  10. Theoretical model for mesoscopic-level scale-free self-organization of functional brain networks.

    Science.gov (United States)

    Piersa, Jaroslaw; Piekniewski, Filip; Schreiber, Tomasz

    2010-11-01

    In this paper, we provide theoretical and numerical analysis of a geometric activity flow network model which is aimed at explaining mathematically the scale-free functional graph self-organization phenomena emerging in complex nervous systems at a mesoscale level. In our model, each unit corresponds to a large number of neurons and may be roughly seen as abstracting the functional behavior exhibited by a single voxel under functional magnetic resonance imaging (fMRI). In the course of the dynamics, the units exchange portions of formal charge, which correspond to waves of activity in the underlying microscale neuronal circuit. The geometric model abstracts away the neuronal complexity and is mathematically tractable, which allows us to establish explicit results on its ground states and the resulting charge transfer graph modeling functional graph of the network. We show that, for a wide choice of parameters and geometrical setups, our model yields a scale-free functional connectivity with the exponent approaching 2, which is in agreement with previous empirical studies based on fMRI. The level of universality of the presented theory allows us to claim that the model does shed light on mesoscale functional self-organization phenomena of the nervous system, even without resorting to closer details of brain connectivity geometry which often remain unknown. The material presented here significantly extends our previous work where a simplified mean-field model in a similar spirit was constructed, ignoring the underlying network geometry.

  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 distribution of Dead Sea sinkholes: Observations and modeling

    Science.gov (United States)

    Yizhaq, H.; Ish-Shalom, C.; Raz, E.; Ashkenazy, Y.

    2017-05-01

    There are currently more than 5500 sinkholes along the Dead Sea in Israel. These were formed due to the dissolution of subsurface salt layers as a result of the replacement of hypersaline groundwater by fresh brackish groundwater. This process has been associated with a sharp decline in the Dead Sea water level, currently more than 1 m/yr, resulting in a lower water table that has allowed the intrusion of fresher brackish water. We studied the distribution of the sinkhole sizes and found that it is scale free with a power law exponent close to 2. We constructed a stochastic cellular automata model to understand the observed scale-free behavior and the growth of the sinkhole area in time. The model consists of a lower salt layer and an upper soil layer in which cavities that develop in the lower layer lead to collapses in the upper layer. The model reproduces the observed power law distribution without involving the threshold behavior commonly associated with criticality.

  13. Scale-free distribution of Dead Sea sinkholes--observations and modeling

    CERN Document Server

    Yizhaq, Hezi; Raz, Eli; Ashkenazy, Yosef

    2016-01-01

    There are currently more than 5500 sinkholes along the Dead Sea in Israel. These were formed due to dissolution of subsurface salt layers as a result of the replacement of hypersaline groundwater by fresh brackish groundwater. This process was associated with a sharp decline in the Dead Sea level, currently more than one meter per year, resulting in a lower water table that has allowed the intrusion of fresher brackish water. We studied the distribution of the sinkholes sizes and found that it is scale-free with a power-law exponent close to 2. We constructed a stochastic cellular automata model to understand the observed scale-free behavior and the growth of the sinkholes area in time. The model consists of a lower salt layer and an upper soil layer in which cavities that develop in the lower layer lead to collapses in the upper layer. The model reproduces the observed power-law distribution without entailing the threshold behavior commonly associated with criticality.

  14. 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.

  15. Optimal control strategy for a novel computer virus propagation model on scale-free networks

    Science.gov (United States)

    Zhang, Chunming; Huang, Haitao

    2016-06-01

    This paper aims to study the combined impact of reinstalling system and network topology on the spread of computer viruses over the Internet. Based on scale-free network, this paper proposes a novel computer viruses propagation model-SLBOSmodel. A systematic analysis of this new model shows that the virus-free equilibrium is globally asymptotically stable when its spreading threshold is less than one; nevertheless, it is proved that the viral equilibrium is permanent if the spreading threshold is greater than one. Then, the impacts of different model parameters on spreading threshold are analyzed. Next, an optimally controlled SLBOS epidemic model on complex networks is also studied. We prove that there is an optimal control existing for the control problem. Some numerical simulations are finally given to illustrate the main results.

  16. Statistical properties of Olami-Feder-Christensen model on Barabasi-Albert scale-free network

    Science.gov (United States)

    Tanaka, Hiroki; Hatano, Takahiro

    2017-12-01

    The Olami-Feder-Christensen model on the Barabasi-Albert type scale-free network is investigated in the context of statistical seismology. This simple model may be regarded as the interacting faults obeying power-law size distribution under two assumptions: (i) each node represents a distinct fault; (ii) the degree of a node is proportional to the fault size and the energy accumulated around it. Depending on the strength of an interaction, the toppling events exhibit temporal clustering as is ubiquitously observed for natural earthquakes. Defining a geometrical parameter that characterizes the heterogeneity of the energy stored in the nodes, we show that aftershocks are characterized as a process of regaining the heterogeneity that is lost by the main shock. The heterogeneity is not significantly altered during the loading process and foreshocks.

  17. 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.

  18. 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.

  19. Modeling the spread of virus in packets on scale free network

    Science.gov (United States)

    Lamzabi, S.; Lazfi, S.; Rachadi, A.; Ez-Zahraouy, H.; Benyoussef, A.

    2016-01-01

    In this paper, we propose a new model for computer virus attacks and recovery at the level of information packets. The model we propose is based on one hand on the susceptible-infected (SI) and susceptible-infected-recovered (SIR) stochastic epidemic models for computer virus propagation and on the other hand on the time-discrete Markov chain of the minimal traffic routing protocol. We have applied this model to the scale free Barabasi-Albert network to determine how the dynamics of virus propagation is affected by the traffic flow in both the free-flow and the congested phases. The numerical results show essentially that the proportion of infected and recovered packets increases when the rate of infection λ and the recovery rate β increase in the free-flow phase while in the congested phase, the number of infected (recovered) packets presents a maximum (minimum) at certain critical value of β characterizing a certain competition between the infection and the recovery rates.

  20. 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.

  1. 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.

  2. Modified Penna bit-string network evolution model for scale-free networks with assortative mixing

    Science.gov (United States)

    Kim, Yup; Choi, Woosik; Yook, Soon-Hyung

    2012-02-01

    Motivated by biological aging dynamics, we introduce a network evolution model for social interaction networks. In order to study the effect of social interactions originating from biological and sociological reasons on the topological properties of networks, we introduce the activitydependent rewiring process. From the numerical simulations, we show that the degree distribution of the obtained networks follows a power-law distribution with an exponentially decaying tail, P( k) ˜ ( k + c)- γ exp(- k/k 0). The obtained value of γ is in the range 2 networks. Moreover, we also show that the degree-degree correlation of the network is positive, which is a characteristic of social interaction networks. The possible applications of our model to real systems are also discussed.

  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. Excitable scale free networks

    Science.gov (United States)

    Copelli, M.; Campos, P. R. A.

    2007-04-01

    When a simple excitable system is continuously stimulated by a Poissonian external source, the response function (mean activity versus stimulus rate) generally shows a linear saturating shape. This is experimentally verified in some classes of sensory neurons, which accordingly present a small dynamic range (defined as the interval of stimulus intensity which can be appropriately coded by the mean activity of the excitable element), usually about one or two decades only. The brain, on the other hand, can handle a significantly broader range of stimulus intensity, and a collective phenomenon involving the interaction among excitable neurons has been suggested to account for the enhancement of the dynamic range. Since the role of the pattern of such interactions is still unclear, here we investigate the performance of a scale-free (SF) network topology in this dynamic range problem. Specifically, we study the transfer function of disordered SF networks of excitable Greenberg-Hastings cellular automata. We observe that the dynamic range is maximum when the coupling among the elements is critical, corroborating a general reasoning recently proposed. Although the maximum dynamic range yielded by general SF networks is slightly worse than that of random networks, for special SF networks which lack loops the enhancement of the dynamic range can be dramatic, reaching nearly five decades. In order to understand the role of loops on the transfer function we propose a simple model in which the density of loops in the network can be gradually increased, and show that this is accompanied by a gradual decrease of dynamic range.

  5. 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.

  6. Scale-free dynamics of somatic adaptability in immune system

    CERN Document Server

    Saito, Shiro

    2009-01-01

    The long-time dynamics of somatic adaptability in immune system is simulated by a simple physical model. The immune system described by the model exhibits a scale free behavior as is observed in living systems. The balance between the positive and negative feedbacks of the model leads to a robust immune system where the positive one corresponds to the formation of memory cells and the negative one to immunosuppression. Also the immunosenescence of the system is discussed based on the time-dependence of the epigenetic landscape of the adaptive immune cells in the shape space.

  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. 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).

  9. Enhanced storage capacity with errors in scale-free Hopfield neural networks: An analytical study.

    Science.gov (United States)

    Kim, Do-Hyun; Park, Jinha; Kahng, Byungnam

    2017-01-01

    The Hopfield model is a pioneering neural network model with associative memory retrieval. The analytical solution of the model in mean field limit revealed that memories can be retrieved without any error up to a finite storage capacity of O(N), where N is the system size. Beyond the threshold, they are completely lost. Since the introduction of the Hopfield model, the theory of neural networks has been further developed toward realistic neural networks using analog neurons, spiking neurons, etc. Nevertheless, those advances are based on fully connected networks, which are inconsistent with recent experimental discovery that the number of connections of each neuron seems to be heterogeneous, following a heavy-tailed distribution. Motivated by this observation, we consider the Hopfield model on scale-free networks and obtain a different pattern of associative memory retrieval from that obtained on the fully connected network: the storage capacity becomes tremendously enhanced but with some error in the memory retrieval, which appears as the heterogeneity of the connections is increased. Moreover, the error rates are also obtained on several real neural networks and are indeed similar to that on scale-free model networks.

  10. 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.

  11. Analysis of Average Shortest-Path Length of Scale-Free Network

    Directory of Open Access Journals (Sweden)

    Guoyong Mao

    2013-01-01

    Full Text Available Computing the average shortest-path length of a large scale-free network needs much memory space and computation time. Hence, parallel computing must be applied. In order to solve the load-balancing problem for coarse-grained parallelization, the relationship between the computing time of a single-source shortest-path length of node and the features of node is studied. We present a dynamic programming model using the average outdegree of neighboring nodes of different levels as the variable and the minimum time difference as the target. The coefficients are determined on time measurable networks. A native array and multimap representation of network are presented to reduce the memory consumption of the network such that large networks can still be loaded into the memory of each computing core. The simplified load-balancing model is applied on a network of tens of millions of nodes. Our experiment shows that this model can solve the load-imbalance problem of large scale-free network very well. Also, the characteristic of this model can meet the requirements of networks with ever-increasing complexity and scale.

  12. 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.

  13. 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

  14. Scale-free transport in fusion plasmas: theory and applications

    Energy Technology Data Exchange (ETDEWEB)

    Sanchez, Raul [ORNL; Mier, Jose Angel [Universidad Carlos III, Madrid, Spain; Newman, David E [University of Alaska; Carreras, Benjamin A [BACV Solutions, Inc., Oak Ridge; Garcia, Luis [Universidad Carlos III, Madrid, Spain; Leboeuf, Jean-Noel [JNL Scientific, Inc., Casa Grande, AZ; Decyk, Viktor [University of California, Los Angeles

    2008-01-01

    A novel approach to detect the existence of scale-free transport in turbulent flows, based on the characterization of its Lagrangian characteristics, is presented and applied to two situations relevant for tokamak plasmas. The first one, radial transport in the presence of near-critical turbulence, has been known for quite some time to yield scale-free, superdiffusive transport. We use it to test the method and illustrate its robustness with respect to other approaches. The second situation, radial transport across radially-sheared poloidal zonal flows driven by turbulence via the Reynold stresses, is examined for the first time in this manner. The result is rather surprising and different from the traditionally assumed diffusive behavior. Instead, radial transport behaves instead in a scale-free, subdiffusive manner, which may have implications for the modeling of transport across transport barriers.

  15. 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.

  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. 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 a memory model. This approach is validated here by the comparison of the sensory dissonance using memory model to data obtained using human subjects....

  18. 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 elements.

  19. 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...

  20. Models of memory: information processing.

    Science.gov (United States)

    Eysenck, M W

    1988-01-01

    A complete understanding of human memory will necessarily involve consideration of the active processes involved at the time of learning and of the organization and nature of representation of information in long-term memory. In addition to process and structure, it is important for theory to indicate the ways in which stimulus-driven and conceptually driven processes interact with each other in the learning situation. Not surprisingly, no existent theory provides a detailed specification of all of these factors. However, there are a number of more specific theories which are successful in illuminating some of the component structures and processes. The working memory model proposed by Baddeley and Hitch (1974) and modified subsequently has shown how the earlier theoretical construct of the short-term store should be replaced with the notion of working memory. In essence, working memory is a system which is used both to process information and to permit the transient storage of information. It comprises a number of conceptually distinct, but functionally interdependent components. So far as long-term memory is concerned, there is evidence of a number of different kinds of representation. Of particular importance is the distinction between declarative knowledge and procedural knowledge, a distinction which has received support from the study of amnesic patients. Kosslyn has argued for a distinction between literal representation and propositional representation, whereas Tulving has distinguished between episodic and semantic memories. While Tulving's distinction is perhaps the best known, there is increasing evidence that episodic and semantic memory differ primarily in content rather than in process, and so the distinction may be of less theoretical value than was originally believed.(ABSTRACT TRUNCATED AT 250 WORDS)

  1. 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

  2. Characterizing the intrinsic correlations of scale-free networks

    CERN Document Server

    de Brito, J B; Moreira, A A; Andrade, J S

    2015-01-01

    Very often, when studying topological or dynamical properties of random scale-free networks, it is tacitly assumed that degree-degree correlations are not present. However, simple constraints, such as the absence of multiple edges and self-loops, can give rise to intrinsic correlations in these structures. In the same way that Fermionic correlations in thermodynamic systems are relevant only in the limit of low temperature, the intrinsic correlations in scale-free networks are relevant only when the extreme values for the degrees grow faster than the square-root of the network size. In this situation, these correlations can significantly affect the dependence of the average degree of the nearest neighbors of a given vertice on this vertices's degree. Here, we introduce an analytical approach that is capable to predict the functional form of this property. Moreover, our results indicate that random scale-free networks models are not self-averaging, that is, the second moment of their degree distribution may va...

  3. 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.

  4. 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.

  5. Scale-free music of the brain.

    Science.gov (United States)

    Wu, Dan; Li, Chao-Yi; Yao, De-Zhong

    2009-06-15

    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. 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, Pbrain, which provide a real-time strategy for monitoring brain activities and are potentially useful to neurofeedback therapy.

  6. 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.

  7. Exact Solutions of a Generalized Weighted Scale Free Network

    Directory of Open Access Journals (Sweden)

    Li Tan

    2013-01-01

    Full Text Available We investigate a class of generalized weighted scale-free networks, where the new vertex connects to m pairs of vertices selected preferentially. The key contribution of this paper is that, from the standpoint of random processes, we provide rigorous analytic solutions for the steady state distributions, including the vertex degree distribution, the vertex strength distribution and the edge weight distribution. Numerical simulations indicate that this network model yields three power law distributions for the vertex degrees, vertex strengths and edge weights, respectively.

  8. Statistical mechanics of scale-free gene expression networks

    Science.gov (United States)

    Gross, Eitan

    2012-12-01

    The gene co-expression networks of many organisms including bacteria, mice and man exhibit scale-free distribution. This heterogeneous distribution of connections decreases the vulnerability of the network to random attacks and thus may confer the genetic replication machinery an intrinsic resilience to such attacks, triggered by changing environmental conditions that the organism may be subject to during evolution. This resilience to random attacks comes at an energetic cost, however, reflected by the lower entropy of the scale-free distribution compared to the more homogenous, random network. In this study we found that the cell cycle-regulated gene expression pattern of the yeast Saccharomyces cerevisiae obeys a power-law distribution with an exponent α = 2.1 and an entropy of 1.58. The latter is very close to the maximal value of 1.65 obtained from linear optimization of the entropy function under the constraint of a constant cost function, determined by the average degree connectivity . We further show that the yeast's gene expression network can achieve scale-free distribution in a process that does not involve growth but rather via re-wiring of the connections between nodes of an ordered network. Our results support the idea of an evolutionary selection, which acts at the level of the protein sequence, and is compatible with the notion of greater biological importance of highly connected nodes in the protein interaction network. Our constrained re-wiring model provides a theoretical framework for a putative thermodynamically driven evolutionary selection process.

  9. The emergence of overlapping scale-free genetic architecture in digital organisms.

    Science.gov (United States)

    Gerlee, P; Lundh, T

    2008-01-01

    We have studied the evolution of genetic architecture in digital organisms and found that the gene overlap follows a scale-free distribution, which is commonly found in metabolic networks of many organisms. Our results show that the slope of the scale-free distribution depends on the mutation rate and that the gene development is driven by expansion of already existing genes, which is in direct correspondence to the preferential growth algorithm that gives rise to scale-free networks. To further validate our results we have constructed a simple model of gene development, which recapitulates the results from the evolutionary process and shows that the mutation rate affects the tendency of genes to cluster. In addition we could relate the slope of the scale-free distribution to the genetic complexity of the organisms and show that a high mutation rate gives rise to a more complex genetic architecture.

  10. Innovation diffusion equations on correlated scale-free networks

    Science.gov (United States)

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

    2016-07-01

    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.

  11. A memory model for autonomous virtual humans

    OpenAIRE

    Peters, Christopher; O'SULLIVAN, CAROL ANN

    2002-01-01

    PUBLISHED A memory model based on ?stage theory?, the dominant view of memory from the field of cognitive psychology, is presented for application to autonomous virtual humans. The virtual human senses external stimuli through a synthetic vision system. The vision system incorporates multiple modes of vision in order to accommodate a perceptual attention approach. The memory model is used to store perceived and attended object data at different stages in a filtering process....

  12. Modeling Power Amplifiers using Memory Polynomials

    NARCIS (Netherlands)

    Kokkeler, Andre B.J.

    2005-01-01

    In this paper we present measured in- and output data of a power amplifier (PA). We compare this data with an AM-AM and AM-PM model. We conclude that a more sophisticated PA model is needed to cope with severe memory effects. We suggest to use memory polynomials and introduce two approaches to

  13. 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.

  14. The spread of computer viruses over a reduced scale-free network

    Science.gov (United States)

    Yang, Lu-Xing; Yang, Xiaofan

    2014-02-01

    Due to the high dimensionality of an epidemic model of computer viruses over a general scale-free network, it is difficult to make a close study of its dynamics. In particular, it is extremely difficult, if not impossible, to prove the global stability of its viral equilibrium, if any. To overcome this difficulty, we suggest to simplify a general scale-free network by partitioning all of its nodes into two classes: higher-degree nodes and lower-degree nodes, and then equating the degrees of all higher-degree nodes and all lower-degree nodes, respectively, yielding a reduced scale-free network. We then propose an epidemic model of computer viruses over a reduced scale-free network. A theoretical analysis reveals that the proposed model is bound to have a globally stable viral equilibrium, implying that any attempt to eradicate network viruses would prove unavailing. As a result, the next best thing we can do is to restrain virus prevalence. Based on an analysis of the impact of different model parameters on virus prevalence, some practicable measures are recommended to contain virus spreading. The work in this paper adequately justifies the idea of reduced scale-free networks.

  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...... optimization algorithms that are specially designed for this problem....

  16. Neural Network Model of memory retrieval

    Directory of Open Access Journals (Sweden)

    Stefano eRecanatesi

    2015-12-01

    Full Text Available Human memory can store large amount of information. Nevertheless, recalling is often achallenging task. In a classical free recall paradigm, where participants are asked to repeat abriefly presented list of words, people make mistakes for lists as short as 5 words. We present amodel for memory retrieval based on a Hopfield neural network where transition between itemsare determined by similarities in their long-term memory representations. Meanfield analysis ofthe model reveals stable states of the network corresponding (1 to single memory representationsand (2 intersection between memory representations. We show that oscillating feedback inhibitionin the presence of noise induces transitions between these states triggering the retrieval ofdifferent memories. The network dynamics qualitatively predicts the distribution of time intervalsrequired to recall new memory items observed in experiments. It shows that items having largernumber of neurons in their representation are statistically easier to recall and reveals possiblebottlenecks in our ability of retrieving memories. Overall, we propose a neural network model ofinformation retrieval broadly compatible with experimental observations and is consistent with ourrecent graphical model (Romani et al., 2013.

  17. A model of memory for incidental learning

    Science.gov (United States)

    Browse, Roger A.; Drewell, Lisa Y.

    2009-02-01

    This paper describes a radial basis memory system that is used to model the performance of human participants in a task of learning to traverse mazes in a virtual environment. The memory model is a multiple-trace system, in which each event is stored as a separate memory trace. In the modeling of the maze traversal task, the events that are stored as memories are the perceptions and decisions taken at the intersections of the maze. As the virtual agent traverses the maze, it makes decisions based upon all of its memories, but those that match best to the current perceptual situation, and which were successful in the past, have the greatest influence. As the agent carries out repeated attempts to traverse the same maze, memories of successful decisions accumulate, and performance gradually improves. The system uses only three free parameters, which most importantly includes adjustments to the standard deviation of the underlying Gaussian used as the radial basis function. It is demonstrated that adjustments of these parameters can easily result in exact modeling of the average human performance in the same task, and that variation of the parameters matches the variation in human performance. We conclude that human memory interaction that does not involve conscious memorization, as in learning navigation routes, may be much more primitive and simply explained than has been previously thought.

  18. 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).

  19. Working memory, situation models, and synesthesia.

    Science.gov (United States)

    Radvansky, Gabriel A; Gibson, Bradley S; McNerney, M Windy

    2014-01-01

    Research on language comprehension suggests a strong relationship between working memory span measures and language comprehension. However, there is also evidence that this relationship weakens at higher levels of comprehension, such as the situation model level. The current study explored this relationship by comparing 10 grapheme-color synesthetes who have additional color experiences when they read words that begin with different letters and 48 normal controls on a number of tests of complex working memory capacity and processing at the situation model level. On all tests of working memory capacity, the synesthetes outperformed the controls. Importantly, there was no carryover benefit for the synesthetes for processing at the situation model level. This reinforces the idea that although some aspects of language comprehension are related to working memory span scores, this applies less directly to situation model levels. This suggests that theories of working memory must take into account this limitation, and the working memory processes that are involved in situation model construction and processing must be derived.

  20. Bio-Inspired Computation: Clock-Free, Grid-Free, Scale-Free and Symbol Free

    Science.gov (United States)

    2015-06-11

    AFRL-AFOSR-JP-TR-2015-0002 Bio -inspired computation: clock-free, grid-free, scale-free, and symbol free Janet Wiles THE UNIVERSITY OF QUEENSLAND...SUBTITLE Bio -inspired computation: clock-free, grid-free, scale-free, and symbol free 5a. CONTRACT NUMBER FA2386-12-1-4050 5b. GRANT NUMBER 5c...SUPPLEMENTARY NOTES 14. ABSTRACT The project developed a new fundamental component for bio -inspired computing, based on a new way of modelling

  1. Modeling floating body memory devices

    Science.gov (United States)

    Hindupur, Ramya

    TCAD simulations have been performed using SILVACO ATLAS 2D device simulator for a Zero-Capacitor Random Access Memory (ZRAM), a new generation memory cell which is being researched as an alternative for DRAM memory cells in order to get rid of the bulky storage capacitor. In our study we have taken into consideration a Dual Gate-ZRAM (DGZRAM) as it helps reduce drain-induced barrier lowering and hence leakage, while having better control of the charge in the substrate. The states are written into the device using impact ionization to generate a large number of holes in the substrate, which alter the threshold voltage of the device. The effect of the gate oxide thickness and substrate body thickness are being taken into consideration to increase the change in the threshold voltage and thereby the noise margin. A DGZRAM structure with a Quantum well introduced into the substrate via a SiGe layer was also simulated. The quantum well introduces a hole storage pocket in the substrate. Comparisons in terms of noise margin have been made for both the devices, which show that the structure with the quantum well in the substrate performs better than the bulk structure. Simulations have been performed taking into consideration gate electrodes with different work functions and it has been observed that while n-polysilicon has a detrimental impact in conventional MOSFETs due to high off-state leakage current, it can be used to obtain low power memory cells. Parameters such as the quantum well doping density, composition of Ge in the quantum well, channel length of the device, SiGe layer thickness and its position with respect to the top gate have been varied to obtain the optimum noise margin for the device.

  2. Quartic chameleons: Safely scale-free in the early Universe

    Science.gov (United States)

    Miller, Carisa; Erickcek, Adrienne L.

    2016-11-01

    In chameleon gravity, there exists a light scalar field that couples to the trace of the stress-energy tensor in such a way that its mass depends on the ambient matter density, and the field is screened in local, high-density environments. Recently it was shown that, for the runaway potentials commonly considered in chameleon theories, the field's coupling to matter and the hierarchy of scales between Standard Model particles and the energy scale of such potentials result in catastrophic effects in the early Universe when these particles become nonrelativistic. Perturbations with trans-Planckian energies are excited, and the theory suffers a breakdown in calculability at the relatively low temperatures of big bang nucleosynthesis. We consider a chameleon field in a quartic potential and show that the scale-free nature of this potential allows the chameleon to avoid many of the problems encountered by runaway potentials. Following inflation, the chameleon field oscillates around the minimum of its effective potential, and rapid changes in its effective mass excite perturbations via quantum particle production. The quartic model, however, only generates high-energy perturbations at comparably high temperatures and is able remain a well-behaved effective field theory at nucleosynthesis.

  3. The effects of working memory resource availability on prospective memory: a formal modeling approach.

    Science.gov (United States)

    Smith, Rebekah E; Bayen, Ute J

    2005-01-01

    The PAM theory of event-based prospective memory (Smith, 2003; Smith & Bayen, 2004a) proposes that successful prospective memory performance demands upon the interaction of preparatory attentional processes and retrospective memory processes. The two experiments in the current study represent the first application of a formal model to investigate the sensitivity of these underlying processes to variations in working memory resource availability. Multinomial modeling of data from prospective-memory tasks showed that working memory span influenced preparatory attentional processes and retrospective-memory processes.

  4. 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.

  5. 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.

  6. Traffic properties for stochastic routings on scale-free networks

    CERN Document Server

    Hayashi, Yukio

    2011-01-01

    For realistic scale-free networks, we investigate the traffic properties of stochastic routing inspired by a zero-range process known in statistical physics. By parameters $\\alpha$ and $\\delta$, this model controls degree-dependent hopping of packets and forwarding of packets with higher performance at more busy nodes. Through a theoretical analysis and numerical simulations, we derive the condition for the concentration of packets at a few hubs. In particular, we show that the optimal $\\alpha$ and $\\delta$ are involved in the trade-off between a detour path for $\\alpha 0$; In the low-performance regime at a small $\\delta$, the wandering path for $\\alpha 0$ and $\\alpha < 0$ is small, neither the wandering long path with short wait trapped at nodes ($\\alpha = -1$), nor the short hopping path with long wait trapped at hubs ($\\alpha = 1$) is advisable. A uniformly random walk ($\\alpha = 0$) yields slightly better performance. We also discuss the congestion phenomena in a more complicated situation with pack...

  7. 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.

  8. Evolution of vocabulary on scale-free and random networks

    Science.gov (United States)

    Kalampokis, Alkiviadis; Kosmidis, Kosmas; Argyrakis, Panos

    2007-06-01

    We examine the evolution of the vocabulary of a group of individuals (linguistic agents) on a scale-free network, using Monte Carlo simulations and assumptions from evolutionary game theory. It is known that when the agents are arranged in a two-dimensional lattice structure and interact by diffusion and encounter, then their final vocabulary size is the maximum possible. Knowing all available words is essential in order to increase the probability to “survive” by effective reproduction. On scale-free networks we find a different result. It is not necessary to learn the entire vocabulary available. Survival chances are increased by using the vocabulary of the “hubs” (nodes with high degree). The existence of the “hubs” in a scale-free network is the source of an additional important fitness generating mechanism.

  9. 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%

  10. 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

  11. An optimal routing strategy on scale-free networks

    Science.gov (United States)

    Yang, Yibo; Zhao, Honglin; Ma, Jinlong; Qi, Zhaohui; Zhao, Yongbin

    Traffic is one of the most fundamental dynamical processes in networked systems. With the traditional shortest path routing (SPR) protocol, traffic congestion is likely to occur on the hub nodes on scale-free networks. In this paper, we propose an improved optimal routing (IOR) strategy which is based on the betweenness centrality and the degree centrality of nodes in the scale-free networks. With the proposed strategy, the routing paths can accurately bypass hub nodes in the network to enhance the transport efficiency. Simulation results show that the traffic capacity as well as some other indexes reflecting transportation efficiency are further improved with the IOR strategy. Owing to the significantly improved traffic performance, this study is helpful to design more efficient routing strategies in communication or transportation systems.

  12. Metric clusters in evolutionary games on scale-free networks.

    Science.gov (United States)

    Kleineberg, Kaj-Kolja

    2017-12-01

    The evolution of cooperation in social dilemmas in structured populations has been studied extensively in recent years. Whereas many theoretical studies have found that a heterogeneous network of contacts favors cooperation, the impact of spatial effects in scale-free networks is still not well understood. In addition to being heterogeneous, real contact networks exhibit a high mean local clustering coefficient, which implies the existence of an underlying metric space. Here we show that evolutionary dynamics in scale-free networks self-organize into spatial patterns in the underlying metric space. The resulting metric clusters of cooperators are able to survive in social dilemmas as their spatial organization shields them from surrounding defectors, similar to spatial selection in Euclidean space. We show that under certain conditions these metric clusters are more efficient than the most connected nodes at sustaining cooperation and that heterogeneity does not always favor-but can even hinder-cooperation in social dilemmas.

  13. 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...... at (and largely succeed in) setting resource prices so that the acquiring firms earn negative strategic factor market profits—sacrificing some of their preexisting market power rents—by acquiring resources that they know to be overpriced....

  14. Evolution of Scale-Free Wireless Sensor Networks with Feature of Small-World Networks

    Directory of Open Access Journals (Sweden)

    Ying Duan

    2017-01-01

    Full Text Available Scale-free network and small-world network are the most impacting discoveries in the complex networks theories and have already been successfully proved to be highly effective in improving topology structures of wireless sensor networks. However, currently both theories are not jointly applied to have further improvements in the generation of WSN topologies. Therefore, this paper proposes a cluster-structured evolution model of WSNs considering the characteristics of both networks. With introduction of energy sensitivity and maximum limitation of degrees that a cluster head could have, the performance of our model can be ensured. In order to give an overall assessment of lifting effects of shortcuts, four placement schemes of shortcuts are analyzed. The characteristics of small-world network and scale-free network of our model are proved via theoretical derivation and simulations. Besides, we find that, by introducing shortcuts into scale-free wireless sensor network, the performance of the network can be improved concerning energy-saving and invulnerability, and we discover that the schemes constructing shortcuts between cluster heads and the sink node have better promoted effects than the scheme building shortcuts between pairs of cluster heads, and the schemes based on the preferential principle are superior to the schemes based on the random principle.

  15. 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).

  16. 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

  17. Robustness of scale-free networks to cascading failures induced by fluctuating loads.

    Science.gov (United States)

    Mizutaka, Shogo; Yakubo, Kousuke

    2015-07-01

    Taking into account the fact that overload failures in real-world functional networks are usually caused by extreme values of temporally fluctuating loads that exceed the allowable range, we study the robustness of scale-free networks against cascading overload failures induced by fluctuating loads. In our model, loads are described by random walkers moving on a network and a node fails when the number of walkers on the node is beyond the node capacity. Our results obtained by using the generating function method show that scale-free networks are more robust against cascading overload failures than Erdős-Rényi random graphs with homogeneous degree distributions. This conclusion is contrary to that predicted by previous works, which neglect the effect of fluctuations of loads.

  18. Wikipedia information flow analysis reveals the scale-free architecture of the semantic space.

    Directory of Open Access Journals (Sweden)

    Adolfo Paolo Masucci

    Full Text Available In this paper we extract the topology of the semantic space in its encyclopedic acception, measuring the semantic flow between the different entries of the largest modern encyclopedia, Wikipedia, and thus creating a directed complex network of semantic flows. Notably at the percolation threshold the semantic space is characterised by scale-free behaviour at different levels of complexity and this relates the semantic space to a wide range of biological, social and linguistics phenomena. In particular we find that the cluster size distribution, representing the size of different semantic areas, is scale-free. Moreover the topology of the resulting semantic space is scale-free in the connectivity distribution and displays small-world properties. However its statistical properties do not allow a classical interpretation via a generative model based on a simple multiplicative process. After giving a detailed description and interpretation of the topological properties of the semantic space, we introduce a stochastic model of content-based network, based on a copy and mutation algorithm and on the Heaps' law, that is able to capture the main statistical properties of the analysed semantic space, including the Zipf's law for the word frequency distribution.

  19. Wikipedia information flow analysis reveals the scale-free architecture of the semantic space.

    Science.gov (United States)

    Masucci, Adolfo Paolo; Kalampokis, Alkiviadis; Eguíluz, Victor Martínez; Hernández-García, Emilio

    2011-02-28

    In this paper we extract the topology of the semantic space in its encyclopedic acception, measuring the semantic flow between the different entries of the largest modern encyclopedia, Wikipedia, and thus creating a directed complex network of semantic flows. Notably at the percolation threshold the semantic space is characterised by scale-free behaviour at different levels of complexity and this relates the semantic space to a wide range of biological, social and linguistics phenomena. In particular we find that the cluster size distribution, representing the size of different semantic areas, is scale-free. Moreover the topology of the resulting semantic space is scale-free in the connectivity distribution and displays small-world properties. However its statistical properties do not allow a classical interpretation via a generative model based on a simple multiplicative process. After giving a detailed description and interpretation of the topological properties of the semantic space, we introduce a stochastic model of content-based network, based on a copy and mutation algorithm and on the Heaps' law, that is able to capture the main statistical properties of the analysed semantic space, including the Zipf's law for the word frequency distribution.

  20. EEG microstate sequences in healthy humans at rest reveal scale-free dynamics

    Science.gov (United States)

    Van De Ville, Dimitri; Britz, Juliane; Michel, Christoph M.

    2010-01-01

    Recent findings identified electroencephalography (EEG) microstates as the electrophysiological correlates of fMRI resting-state networks. Microstates are defined as short periods (100 ms) during which the EEG scalp topography remains quasi-stable; that is, the global topography is fixed but strength might vary and polarity invert. Microstates represent the subsecond coherent activation within global functional brain networks. Surprisingly, these rapidly changing EEG microstates correlate significantly with activity in fMRI resting-state networks after convolution with the hemodynamic response function that constitutes a strong temporal smoothing filter. We postulate here that microstate sequences should reveal scale-free, self-similar dynamics to explain this remarkable effect and thus that microstate time series show dependencies over long time ranges. To that aim, we deploy wavelet-based fractal analysis that allows determining scale-free behavior. We find strong statistical evidence that microstate sequences are scale free over six dyadic scales covering the 256-ms to 16-s range. The degree of long-range dependency is maintained when shuffling the local microstate labels but becomes indistinguishable from white noise when equalizing microstate durations, which indicates that temporal dynamics are their key characteristic. These results advance the understanding of temporal dynamics of brain-scale neuronal network models such as the global workspace model. Whereas microstates can be considered the “atoms of thoughts,” the shortest constituting elements of cognition, they carry a dynamic signature that is reminiscent at characteristic timescales up to multiple seconds. The scale-free dynamics of the microstates might be the basis for the rapid reorganization and adaptation of the functional networks of the brain. PMID:20921381

  1. 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.

  2. Scale-free texture of the fast solar wind

    Science.gov (United States)

    Hnat, B.; Chapman, S. C.; Gogoberidze, G.; Wicks, R. T.

    2011-12-01

    The higher-order statistics of magnetic field magnitude fluctuations in the fast quiet solar wind are quantified systematically, scale by scale. We find a single global non-Gaussian scale-free behavior from minutes to over 5 h. This spans the signature of an inertial range of magnetohydrodynamic turbulence and a ˜1/f range in magnetic field components. This global scaling in field magnitude fluctuations is an intrinsic component of the underlying texture of the solar wind and puts a strong constraint on any theory of solar corona and the heliosphere. Intriguingly, the magnetic field and velocity components show scale-dependent dynamic alignment outside of the inertial range.

  3. Forecasting temperature indices with timevarying long-memory models

    OpenAIRE

    Massimiliano Caporin; Juliusz Pres

    2008-01-01

    The hedging of weather risks has become extremely relevant in recent years, promoting the diffusion of weather derivative contracts. The pricing of such contracts require the development of appropriate models for the prediction of the underlying weather variables. Within this framework, we present a modification of the double long memory ARFIMA-FIGARCH model introducing time-varying memory coefficients for both mean and variance. The model satisfies the empirical evidence of changing memory o...

  4. 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.

  5. The Geometry of Memory: A Physical Model

    Science.gov (United States)

    Maier, Willard; Miller, Bruce

    2008-10-01

    In recent history physicists have become interested in viewing processes in the brain in terms of the nonlinear dynamics of interacting neurons. To achieve this they have explored different levels of fidelity in modeling the interacting neurons. An open question is whether there is a connection between specific firing patterns and the representation of memory. Izhikevich has proposed a possible connection that he has named polychoronous groups and explored it within the context of a specific dynamical model. Here a minimal model of polychronous groups in neural networks is presented. The model is computationally efficient and allows the study of polychronous groups independent of specific neuron models prevalent in the literature. Computational experiments were performed with the model in one- and two-dimensional neural architectures to determine the dependence of the number of polychronous groups on various connectivity options. Our results (arXiv:0806.1070v1 [cond-mat.dis-nn]) suggest that the concept is robust and may therefore play an important role in more realistic systems. The possibility of using polychronous groups as computational elements is also discussed.

  6. Lower bound of assortativity coefficient in scale-free networks

    Science.gov (United States)

    Yang, Dan; Pan, Liming; Zhou, Tao

    2017-03-01

    The degree-degree correlation is important in understanding the structural organization of a network and dynamics upon a network. Such correlation is usually measured by the assortativity coefficient r, with natural bounds r ∈ [ - 1 , 1 ] . For scale-free networks with power-law degree distribution p ( k ) ˜ k - γ , we analytically obtain the lower bound of assortativity coefficient in the limit of large network size, which is not -1 but dependent on the power-law exponent γ. This work challenges the validation of the assortativity coefficient in heterogeneous networks, suggesting that one cannot judge whether a network is positively or negatively correlated just by looking at its assortativity coefficient alone.

  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. 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.

  9. 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

  10. 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

  11. Modeling selective local interactions with memory.

    Science.gov (United States)

    Galante, Amanda; Levy, Doron

    2013-10-01

    Recently we developed a stochastic particle system describing local interactions between cyanobacteria. We focused on the common freshwater cyanobacteria Synechocystis sp., which are coccoidal bacteria that utilize group dynamics to move toward a light source, a motion referred to as phototaxis. We were particularly interested in the local interactions between cells that were located in low to medium density areas away from the front. The simulations of our stochastic particle system in 2D replicated many experimentally observed phenomena, such as the formation of aggregations and the quasi-random motion of cells. In this paper, we seek to develop a better understanding of group dynamics produced by this model. To facilitate this study, we replace the stochastic model with a system of ordinary differential equations describing the evolution of particles in 1D. Unlike many other models, our emphasis is on particles that selectively choose one of their neighbors as the preferred direction of motion. Furthermore, we incorporate memory by allowing persistence in the motion. We conduct numerical simulations which allow us to efficiently explore the space of parameters, in order to study the stability, size, and merging of aggregations.

  12. 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.

  13. Extraversion is encoded by scale-free dynamics of default mode network.

    Science.gov (United States)

    Lei, Xu; Zhao, Zhiying; Chen, Hong

    2013-07-01

    Resting-state functional Magnetic Resonance Imaging (rsfMRI) is a powerful tool to investigate neurological and psychiatric diseases. Recently, the evidences linking the scaling properties of resting-state activity and the personality have been accumulated. However, it remains unknown whether the personality is associated with the scale-free dynamics of default mode network (DMN) - the most widely studied network in the rsfMRI literatures. To investigate this question, we estimated the Hurst exponent, quantifying long memory of a time-series, in DMN of rsfMRI in 20 healthy individuals. The Hurst exponent in DMN, whether extracted by independent component analysis (ICA) or region of interest (ROI), was significantly associated with the extraversion score of the revised Eysenck Personality Questionnaire. Specifically, longer memory in DMN corresponded to lower extraversion. We provide evidences for an association between individual differences in personality and scaling dynamics in DMN, whose alteration has been previously linked with introspective cognition. This association might arise from the efficiency in online information processing. Our results suggest that personality trait may be reflected by the scaling property of resting-state networks. Copyright © 2012 Elsevier Inc. All rights reserved.

  14. 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…

  15. 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.

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

    Directory of Open Access Journals (Sweden)

    Tao Gong

    Full Text Available 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.

  17. Large fluctuations in anti-coordination games on scale-free graphs

    Science.gov (United States)

    Sabsovich, Daniel; Mobilia, Mauro; Assaf, Michael

    2017-05-01

    We study the influence of the complex topology of scale-free graphs on the dynamics of anti-coordination games (e.g. snowdrift games). These reference models are characterized by the coexistence (evolutionary stable mixed strategy) of two competing species, say ‘cooperators’ and ‘defectors’, and, in finite systems, by metastability and large-fluctuation-driven fixation. In this work, we use extensive computer simulations and an effective diffusion approximation (in the weak selection limit) to determine under which circumstances, depending on the individual-based update rules, the topology drastically affects the long-time behavior of anti-coordination games. In particular, we compute the variance of the number of cooperators in the metastable state and the mean fixation time when the dynamics is implemented according to the voter model (death-first/birth-second process) and the link dynamics (birth/death or death/birth at random). For the voter update rule, we show that the scale-free topology effectively renormalizes the population size and as a result the statistics of observables depend on the network’s degree distribution. In contrast, such a renormalization does not occur with the link dynamics update rule and we recover the same behavior as on complete graphs.

  18. 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.

  19. Mechanical failure in amorphous solids: Scale-free spinodal criticality

    Science.gov (United States)

    Procaccia, Itamar; Rainone, Corrado; Singh, Murari

    2017-09-01

    The mechanical failure of amorphous media is a ubiquitous phenomenon from material engineering to geology. It has been noticed for a long time that the phenomenon is "scale-free," indicating some type of criticality. In spite of attempts to invoke "Self-Organized Criticality," the physical origin of this criticality, and also its universal nature, being quite insensitive to the nature of microscopic interactions, remained elusive. Recently we proposed that the precise nature of this critical behavior is manifested by a spinodal point of a thermodynamic phase transition. Demonstrating this requires the introduction of an "order parameter" that is suitable for distinguishing between disordered amorphous systems. At the spinodal point there exists a divergent correlation length which is associated with the system-spanning instabilities (known also as shear bands) which are typical to the mechanical yield. The theory, the order parameter used and the correlation functions which exhibit the divergent correlation length are universal in nature and can be applied to any amorphous solid that undergoes mechanical yield. The phenomenon is seen at its sharpest in athermal systems, as is explained below; in this paper we extend the discussion also to thermal systems, showing that at sufficiently high temperatures the spinodal phenomenon is destroyed by thermal fluctuations.

  20. 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

  1. 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.

  2. Formal Specification of the OpenMP Memory Model

    Energy Technology Data Exchange (ETDEWEB)

    Bronevetsky, G; de Supinski, B

    2006-12-19

    OpenMP [2] is an important API for shared memory programming, combining shared memory's potential for performance with a simple programming interface. Unfortunately, OpenMP lacks a critical tool for demonstrating whether programs are correct: a formal memory model. Instead, the current official definition of the OpenMP memory model (the OpenMP 2.5 specification [2]) is in terms of informal prose. As a result, it is impossible to verify OpenMP applications formally since the prose does not provide a formal consistency model that precisely describes how reads and writes on different threads interact. We expand on our previous work that focused on the formal verification of OpenMP programs through a formal memory model [?]. As in that work, our formalization, which is derived from the existing prose model [2], provides a two-step process to verify whether an observed OpenMP execution is conformant. This paper extends the model to cover the entire specification. In addition to this formalization, our contributions include a discussion of ambiguities in the current prose-based memory model description. Although our formal model may not capture the current informal memory model perfectly, in part due to these ambiguities, our model reflects our understanding of the informal model's intent. We conclude with several examples that may indicate areas of the OpenMP memory model that need further refinement, however it is specified. Our goal is to motivate the OpenMP community to adopt those refinements eventually, ideally through a formal model, in later OpenMP specifications.

  3. 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 ...

  4. Synchronization in Scale Free networks: The role of finite size effects

    CERN Document Server

    Torres, Débora; La Rocca, Cristian E; Braunstein, Lidia A

    2015-01-01

    Synchronization problems in complex networks are very often studied by researchers due to its many applications to various fields such as neurobiology, e-commerce and completion of tasks. In particular, Scale Free networks with degree distribution $P(k)\\sim k^{-\\lambda}$, 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 $2.5< \\lambda <3$, 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 $\\lambda$: 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 $\\lambda$, which means that the synchroniza...

  5. 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.

  6. 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.

  7. Acute glucocorticoid effects on the multicomponent model of working memory.

    Science.gov (United States)

    Vaz, Leonardo José; Pradella-Hallinan, Márcia; Bueno, Orlando Francisco Amodeo; Pompéia, Sabine

    2011-10-01

    In comparison with basal physiological levels, acute, high levels of cortisol affect learning and memory. Despite reports of cortisol-induced episodic memory effects, no study has used a comprehensive battery of tests to evaluate glucocorticoid effects on the multicomponent model of working memory. Here, we report the results of a double-blind, placebo-controlled, between-subjects study. Twenty healthy young men were randomly assigned to either acute cortisol (30 mg hydrocortisone) or placebo administration. Participants were subjected to an extensive cognitive test battery that evaluated all systems of the multicomponent model of working memory, including various executive domains (shifting, updating, inhibition, planning and access to long-term memory). Compared with placebo, hydrocortisone administration increased cortisol blood levels and impaired working memory in storage of multimodal information in the episodic buffer and maintenance/reverberation of information in the phonological loop. Hydrocortisone also decreased performance in planning and inhibition tasks, the latter having been explained by changes in storage of information in working memory. Thus, hydrocortisone acutely impairs various components of working memory, including executive functioning. This effect must be considered when administering similar drugs, which are widely used for the treatment of many clinical disorders. Copyright © 2011 John Wiley & Sons, Ltd.

  8. 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.

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

    Directory of Open Access Journals (Sweden)

    Sandeep Vasant More

    2016-09-01

    Full Text Available 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.

  10. 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).

  11. 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.

  12. Community structure and scale-free collections of Erdős-Rényi graphs.

    Science.gov (United States)

    Seshadhri, C; Kolda, Tamara G; Pinar, Ali

    2012-05-01

    Community structure plays a significant role in the analysis of social networks and similar graphs, yet this structure is little understood and not well captured by most models. We formally define a community to be a subgraph that is internally highly connected and has no deeper substructure. We use tools of combinatorics to show that any such community must contain a dense Erdős-Rényi (ER) subgraph. Based on mathematical arguments, we hypothesize that any graph with a heavy-tailed degree distribution and community structure must contain a scale-free collection of dense ER subgraphs. These theoretical observations corroborate well with empirical evidence. From this, we propose the Block Two-Level Erdős-Rényi (BTER) model, and demonstrate that it accurately captures the observable properties of many real-world social networks.

  13. Scale-free systems organization as entropy competition

    Science.gov (United States)

    Sanchirico, A.; Fiorentino, M.

    2009-04-01

    networks, technological systems, as electronic circuits, geomorphological systems, as river networks, and so on. Here, based on statistical mechanics, we discuss how network systems organize themselves into an equilibrium scale-free structure. In particular, we show that the power-law is the most probable distribution that both nodes and edges, in a reciprocal competition, assume when the respective entropy functions reach their maxima, under mutual constraint. The proposed approach predicts scaling exponent values in agreement with those most frequently observed in nature.

  14. Evolution of Models of Working Memory and Cognitive Resources.

    Science.gov (United States)

    Wingfield, Arthur

    2016-01-01

    The goal of this article is to trace the evolution of models of working memory and cognitive resources from the early 20th century to today. Linear flow models of information processing common in the 1960s and 1970s centered on the transfer of verbal information from a limited-capacity short-term memory store to long-term memory through rehearsal. Current conceptions see working memory as a dynamic system that includes both maintaining and manipulating information through a series of interactive components that include executive control and attentional resources. These models also reflect the evolution from an almost exclusive concentration on working memory for verbal materials to inclusion of a visual working memory component. Although differing in postulated mechanisms and emphasis, these evolving viewpoints all share the recognition that human information processing is a limited-capacity system with limits on the amount of information that can be attended to, remain activated in memory, and utilized at one time. These limitations take on special importance in spoken language comprehension, especially when the stimuli have complex linguistic structures or listening effort is increased by poor acoustic quality or reduced hearing acuity.

  15. Research on Associative Memory Models of Emotional Robots

    Directory of Open Access Journals (Sweden)

    Wang Yi

    2014-02-01

    Full Text Available Associative memory is essential to realize man-machine cooperation in the natural interaction between humans and robots. The establishment of associative memory model is to solve the problem. First, based on the theory of emotional energy, mood spontaneous metastasis model and stimulate metastasis model are put forward. Then we can achieve affective computing on the external excitation combining with Markov chain model which is about emotions of spontaneous metastasis and HMM model which is about stimulating metastasis. Second, based on the neural network, the associative memory model which is applied in emotional robots is put forward by calculating the emotional state of the robot's dynamic change of mind and considering their own needs at the same time. Finally, the model was applied to the emotional robot platform which we developed. The effect is validated better.

  16. Model-Driven Study of Visual Memory

    Science.gov (United States)

    2004-12-01

    Kantner, 2005). In addition, following up the AFOSR Program Re- view, the PI launched a small scale effort to explore the online visuospatial memory...446. Brunswik, E., & Reiter, L. (1937). Eindruckscharaktere schematisierter gesichter. Zeitschrift ftir Psychologie , 142, 67-134. Bullock, D

  17. Hypergraph-Based Recognition Memory Model for Lifelong Experience

    Directory of Open Access Journals (Sweden)

    Hyoungnyoun Kim

    2014-01-01

    Full Text Available 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.

  18. Social Models Enhance Apes’ Memory for Novel Events

    Science.gov (United States)

    Howard, Lauren H.; Wagner, Katherine E.; Woodward, Amanda L.; Ross, Stephen R.; Hopper, Lydia M.

    2017-01-01

    Nonhuman primates are more likely to learn from the actions of a social model than a non-social “ghost display”, however the mechanism underlying this effect is still unknown. One possibility is that live models are more engaging, drawing increased attention to social stimuli. However, recent research with humans has suggested that live models fundamentally alter memory, not low-level attention. In the current study, we developed a novel eye-tracking paradigm to disentangle the influence of social context on attention and memory in apes. Tested in two conditions, zoo-housed apes (2 gorillas, 5 chimpanzees) were familiarized to videos of a human hand (social condition) and mechanical claw (non-social condition) constructing a three-block tower. During the memory test, subjects viewed side-by-side pictures of the previously-constructed block tower and a novel block tower. In accordance with looking-time paradigms, increased looking time to the novel block tower was used to measure event memory. Apes evidenced memory for the event featuring a social model, though not for the non-social condition. This effect was not dependent on attention differences to the videos. These findings provide the first evidence that, like humans, social stimuli increase nonhuman primates’ event memory, which may aid in information transmission via social learning. PMID:28106098

  19. Scale-free foraging by primates emerges from their interaction with a complex environment

    Science.gov (United States)

    Boyer, Denis; Ramos-Fernández, Gabriel; Miramontes, Octavio; Mateos, José L; Cocho, Germinal; Larralde, Hernán; Ramos, Humberto; Rojas, Fernando

    2006-01-01

    Scale-free foraging patterns are widespread among animals. These may be the outcome of an optimal searching strategy to find scarce, randomly distributed resources, but a less explored alternative is that this behaviour may result from the interaction of foraging animals with a particular distribution of resources. We introduce a simple foraging model where individual primates follow mental maps and choose their displacements according to a maximum efficiency criterion, in a spatially disordered environment containing many trees with a heterogeneous size distribution. We show that a particular tree-size frequency distribution induces non-Gaussian movement patterns with multiple spatial scales (Lévy walks). These results are consistent with field observations of tree-size variation and spider monkey (Ateles geoffroyi) foraging patterns. We discuss the consequences that our results may have for the patterns of seed dispersal by foraging primates. PMID:16790406

  20. Effects of maximum node degree on computer virus spreading in scale-free networks

    Science.gov (United States)

    Bamaarouf, O.; Ould Baba, A.; Lamzabi, S.; Rachadi, A.; Ez-Zahraouy, H.

    2017-10-01

    The increase of the use of the Internet networks favors the spread of viruses. In this paper, we studied the spread of viruses in the scale-free network with different topologies based on the Susceptible-Infected-External (SIE) model. It is found that the network structure influences the virus spreading. We have shown also that the nodes of high degree are more susceptible to infection than others. Furthermore, we have determined a critical maximum value of node degree (Kc), below which the network is more resistible and the computer virus cannot expand into the whole network. The influence of network size is also studied. We found that the network with low size is more effective to reduce the proportion of infected nodes.

  1. A hybrid queuing strategy for network traffic on scale-free networks

    Science.gov (United States)

    Cai, Kai-Quan; Yu, Lu; Zhu, Yan-Bo

    2017-02-01

    In this paper, a hybrid queuing strategy (HQS) is proposed in traffic dynamics model on scale-free networks, where the delivery priority of packets in the queue is related to their distance to destination and the queue length of next jump. We compare the performance of the proposed HQS with that of the traditional first-in-first-out (FIFO) queuing strategy and the shortest-remaining-path-first (SRPF) queuing strategy proposed by Du et al. It is observed that the network traffic efficiency utilizing HQS with suitable value of parameter h can be further improved in the congestion state. Our work provides new insights for the understanding of the networked-traffic systems.

  2. 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

  3. Deception and Cognitive Load: Expanding Our Horizon with a Working Memory Model

    National Research Council Canada - National Science Library

    Sporer, Siegfried L

    2016-01-01

    ...) 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...

  4. 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…

  5. 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...

  6. 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.

  7. 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.

  8. 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.

  9. 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,

  10. Everyday memory: towards a translationally effective method of modelling the encoding, forgetting and enhancement of memory.

    Science.gov (United States)

    Nonaka, Mio; Fitzpatrick, Richard; Lapira, Jennifer; Wheeler, Damian; Spooner, Patrick A; Corcoles-Parada, Marta; Muñoz-López, Mónica; Tully, Tim; Peters, Marco; Morris, Richard G M

    2017-08-01

    The testing of cognitive enhancers could benefit from the development of novel behavioural tasks that display better translational relevance for daily memory and permit the examination of potential targets in a within-subjects manner with less variability. We here outline an optimized spatial 'everyday memory' task. We calibrate it systematically by interrogating certain well-established determinants of memory and consider its potential for revealing novel features of encoding-related gene activation. Rats were trained in an event arena in which food was hidden in sandwells in a different location everyday. They found the food during an initial memory-encoding trial and were then required to remember the location in six alternative choice or probe trials at various time-points later. Training continued daily over a period of 4 months, realizing a stable high level of performance and characterized by delay-dependent forgetting over 24 h. Spaced but not massed access to multiple rewards enhanced the persistence of memory, as did post-encoding administration of the PDE4 inhibitor Rolipram. Quantitative PCR and then genome-wide analysis of gene expression led to a new observation - stronger gene-activation in hippocampus and retrosplenial cortex following spaced than massed training. In a subsidiary study, a separate group of animals replicated aspects of this training profile, going on to show enhanced memory when training was subject to post-encoding environmental novelty. Distinctive features of this protocol include its potential validity as a model of memory encoding used routinely by human subjects everyday, and the possibility of multiple within-subject comparisons to speed up assays of novel compounds. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  11. 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.

  12. An Agent Memory Model Enabling Rational and Biased Reasoning

    NARCIS (Netherlands)

    Heuvelink, A.; Klein, M.C.A.; Treur, J.

    2008-01-01

    This paper presents an architecture for a memory model that facilitates versatile reasoning mechanisms over the beliefs stored in an agent's belief base. Based on an approach for belief aggregation, a model is introduced for controlling both the formation of abstract and complex beliefs and the

  13. 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...

  14. 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.

  15. 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.

  16. The temporal structures and functional significance of scale-free brain activity.

    Science.gov (United States)

    He, Biyu J; Zempel, John M; Snyder, Abraham Z; Raichle, Marcus E

    2010-05-13

    Scale-free dynamics, with a power spectrum following P proportional to f(-beta), are an intrinsic feature of many complex processes in nature. In neural systems, scale-free activity is often neglected in electrophysiological research. Here, we investigate scale-free dynamics in human brain and show that it contains extensive nested frequencies, with the phase of lower frequencies modulating the amplitude of higher frequencies in an upward progression across the frequency spectrum. The functional significance of scale-free brain activity is indicated by task performance modulation and regional variation, with beta being larger in default network and visual cortex and smaller in hippocampus and cerebellum. The precise patterns of nested frequencies in the brain differ from other scale-free dynamics in nature, such as earth seismic waves and stock market fluctuations, suggesting system-specific generative mechanisms. Our findings reveal robust temporal structures and behavioral significance of scale-free brain activity and should motivate future study on its physiological mechanisms and cognitive implications. Copyright 2010 Elsevier Inc. All rights reserved.

  17. First principles modeling of magnetic random access memory devices (invited)

    Energy Technology Data Exchange (ETDEWEB)

    Butler, W.H.; Zhang, X.; Schulthess, T.C.; Nicholson, D.M.; Oparin, A.B. [Metals and Ceramics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); MacLaren, J.M. [Department of Physics, Tulane University, New Orleans, Louisiana 70018 (United States)

    1999-04-01

    Giant magnetoresistance (GMR) and spin-dependent tunneling may be used to make magnetic random access memory devices. We have applied first-principles based electronic structure techniques to understand these effects and in the case of GMR to model the transport properties of the devices. {copyright} {ital 1999 American Institute of Physics.}

  18. An adaptive routing scheme in scale-free networks

    Science.gov (United States)

    Ben Haddou, Nora; Ez-Zahraouy, Hamid; Benyoussef, Abdelilah

    2015-05-01

    We suggest an optimal form of traffic awareness already introduced as a routing protocol which combines structural and local dynamic properties of the network to determine the followed path between source and destination of the packet. Instead of using the shortest path, we incorporate the "efficient path" in the protocol and we propose a new parameter α that controls the contribution of the queue in the routing process. Compared to the original model, the capacity of the network can be improved more than twice when using the optimal conditions of our model. Moreover, the adjustment of the proposed parameter allows the minimization of the travel time.

  19. 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

  20. A semiclassical model for a memory dephasing channel

    Science.gov (United States)

    D'Arrigo, A.; Benenti, G.; Falci, G.

    2009-07-01

    We study a dephasing channel with memory, described by a Hamiltonian model in which the system-environment interaction is described by a stochastic process. We propose a useful way to describe the correlations of channel uses. Moreover, we give a general expression for the coherences decay factors as a function of the number of channel uses and of the stochastic process power spectrum. We also study the impact of memory on the three-qubit code, showing that correlations among channel uses hardly affect the code performance.

  1. 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...

  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. When is a Scale-Free Graph Ultra-Small?

    Science.gov (United States)

    van der Hofstad, Remco; Komjáthy, Júlia

    2017-10-01

    In this paper we study typical distances in the configuration model, when the degrees have asymptotically infinite variance. We assume that the empirical degree distribution follows a power law with exponent τ \\in (2,3), up to value n^{{β _n}} for some {β _n}≫ (log n)^{-γ } and γ \\in (0,1). This assumption is satisfied for power law i.i.d. degrees, and also includes truncated power-law empirical degree distributions where the (possibly exponential) truncation happens at n^{{β _n}}. These examples are commonly observed in many real-life networks. We show that the graph distance between two uniformly chosen vertices centers around 2 log log (n^{{β _n}}) / |log (τ -2)| + 1/({β _n}(3-τ )), with tight fluctuations. Thus, the graph is an ultrasmall world whenever 1/{β _n}=o(log log n). We determine the distribution of the fluctuations around this value, in particular we prove these form a sequence of tight random variables with distributions that show log log -periodicity, and as a result it is non-converging. We describe the topology and number of shortest paths: We show that the number of shortest paths is of order n^{f_n{β _n}}, where f_n \\in (0,1) is a random variable that oscillates with n. We decompose shortest paths into three segments, two `end-segments' starting at each of the two uniformly chosen vertices, and a middle segment. The two end-segments of any shortest path have length log log (n^{{β _n}}) / |log (τ -2)|+tight, and the total degree is increasing towards the middle of the path on these segments. The connecting middle segment has length 1/({β _n}(3-τ ))+tight, and it contains only vertices with degree at least of order n^{(1-f_n){β _n}}, thus all the degrees on this segment are comparable to the maximal degree. Our theorems also apply when instead of truncating the degrees, we start with a configuration model and we remove every vertex with degree at least n^{{β _n}}, and the edges attached to these vertices. This sheds light on

  4. A Dynamic Model for Decision Making During Memory Retrieval

    Science.gov (United States)

    2015-10-26

    extensively   a  dynamic   model  that  explains  the...Greg Cox titled: " Dynamic modeling of memory storage and retrieval". This research is now being prepared for submission to Psychological Review. The...Topics in Cognitive Science, 4(1), 135-150. Cox , G. E., Kachergis, G., and Shiffrin, R. M. (2012). Gaussian process regression for trajectory analysis.

  5. 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 ...... partitions, and thereby limit the amount of disk access and network communication. We report on several experiments made with our verification platform ASAP that implements the dynamic partitioning scheme proposed in this paper....

  6. 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.

  7. Modeling of shape memory alloys and application to porous materials

    Science.gov (United States)

    Panico, Michele

    In the last two decades the number of innovative applications for advanced materials has been rapidly increasing. Shape memory alloys (SMAs) are an exciting class of these materials which exhibit large reversible stresses and strains due to a thermoelastic phase transformation. SMAs have been employed in the biomedical field for producing cardiovascular stents, shape memory foams have been successfully tested as bone implant material, and SMAs are being used as deployable switches in aerospace applications. The behavior of shape memory alloys is intrinsically complex due to the coupling of phase transformation with thermomechanical loading, so it is critical for constitutive models to correctly simulate their response over a wide range of stress and temperature. In the first part of this dissertation, we propose a macroscopic phenomenological model for SMAs that is based on the classical framework of thermodynamics of irreversible processes and accounts for the effect of multiaxial stress states and non-proportional loading histories. The model is able to account for the evolution of both self-accommodated and oriented martensite. Moreover, reorientation of the product phase according to loading direction is specifically accounted for. Computational tests demonstrate the ability of the model to simulate the main aspects of the shape memory response in a one-dimensional setting and some of the features that have been experimentally found in the case of multi-axial non-proportional loading histories. In the second part of this dissertation, this constitutive model has been used to study the mesoscopic behavior of porous shape memory alloys with particular attention to the mechanical response under cyclic loading conditions. In order to perform numerical simulations, the model was implemented into the commercial finite element code ABAQUS. Due to stress concentrations in a porous microstructure, the constitutive law was enhanced to account for the development of

  8. The modeling and simulation of visuospatial working memory

    Science.gov (United States)

    Liang, Lina; Zhang, Zhikang

    2010-01-01

    Camperi and Wang (Comput Neurosci 5:383–405, 1998) presented a network model for working memory that combines intrinsic cellular bistability with the recurrent network architecture of the neocortex. While Fall and Rinzel (Comput Neurosci 20:97–107, 2006) replaced this intrinsic bistability with a biological mechanism-Ca2+ release subsystem. In this study, we aim to further expand the above work. We integrate the traditional firing-rate network with Ca2+ subsystem-induced bistability, amend the synaptic weights and suggest that Ca2+ concentration only increase the efficacy of synaptic input but has nothing to do with the external input for the transient cue. We found that our network model maintained the persistent activity in response to a brief transient stimulus like that of the previous two models and the working memory performance was resistant to noise and distraction stimulus if Ca2+ subsystem was tuned to be bistable. PMID:22132045

  9. 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.

  10. Analytical Expressions for the REM Model of Recognition Memory

    Science.gov (United States)

    Montenegro, Maximiliano; Myung, Jay I.; Pitt, Mark A.

    2014-01-01

    An inordinate amount of computation is required to evaluate predictions of simulation-based models. Following Myung et al (2007), we derived an analytic form expression of the REM model of recognition memory using a Fourier transform technique, which greatly reduces the time required to perform model simulations. The accuracy of the derivation is verified by showing a close correspondence between its predictions and those reported in Shiffrin and Steyvers (1997). The derivation also shows that REM’s predictions depend upon the vector length parameter, and that model parameters are not identifiable unless one of the parameters is fixed. PMID:25089060

  11. 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.

  12. A neural model of retrospective attention in visual working memory.

    Science.gov (United States)

    Bays, Paul M; Taylor, Robert

    2018-02-01

    An informative cue that directs attention to one of several items in working memory improves subsequent recall of that item. Here we examine the mechanism of this retro-cue effect using a model of short-term memory based on neural population coding. Our model describes recalled feature values as the output of an optimal decoding of spikes generated by a tuned population of neurons. This neural model provides a better account of human recall data than an influential model that assumes errors can be described as a mixture of normally distributed noise and random guesses. The retro-cue benefit is revealed to be consistent with a higher firing rate of the population encoding the cued versus uncued items, with no difference in tuning specificity. Additionally, a retro-cued item is less likely to be swapped with another item in memory, an effect that can also be explained by greater activity of the underlying population. These results provide a parsimonious account of the effects of retrospective attention on recall and demonstrate a principled method for investigating neural representations with behavioral tasks. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  13. Model Equations of Shape Memory Effect - Nitinol

    Directory of Open Access Journals (Sweden)

    Ion Vela

    2010-01-01

    Full Text Available Even it has been already confirmed that SMA’s have high potential for robotic actuators, actuators included in space robotics, underwater robotics, robotics for logistics, safety, as well as “green robotics” (robotics for the environment, energy conservation, sustainable development or agriculture, the number of applications of SMA-based actuators is still quite small, especially in applications in which their large strains, high specific work output and structural integration potential are useful,. The paper presents a formulated mathematical model calculated for binary SMA (Ni-Ti, helpful to estimate the stress distribution along with the transformation ratio of a SMA active element.

  14. 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.

  15. 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.

  16. A Zebrafish Model of Diabetes Mellitus and Metabolic Memory

    Science.gov (United States)

    Intine, Robert V.; Olsen, Ansgar S.; Sarras, Michael P.

    2013-01-01

    Diabetes mellitus currently affects 346 million individuals and this is projected to increase to 400 million by 2030. Evidence from both the laboratory and large scale clinical trials has revealed that diabetic complications progress unimpeded via the phenomenon of metabolic memory even when glycemic control is pharmaceutically achieved. Gene expression can be stably altered through epigenetic changes which not only allow cells and organisms to quickly respond to changing environmental stimuli but also confer the ability of the cell to "memorize" these encounters once the stimulus is removed. As such, the roles that these mechanisms play in the metabolic memory phenomenon are currently being examined. We have recently reported the development of a zebrafish model of type I diabetes mellitus and characterized this model to show that diabetic zebrafish not only display the known secondary complications including the changes associated with diabetic retinopathy, diabetic nephropathy and impaired wound healing but also exhibit impaired caudal fin regeneration. This model is unique in that the zebrafish is capable to regenerate its damaged pancreas and restore a euglycemic state similar to what would be expected in post-transplant human patients. Moreover, multiple rounds of caudal fin amputation allow for the separation and study of pure epigenetic effects in an in vivo system without potential complicating factors from the previous diabetic state. Although euglycemia is achieved following pancreatic regeneration, the diabetic secondary complication of fin regeneration and skin wound healing persists indefinitely. In the case of impaired fin regeneration, this pathology is retained even after multiple rounds of fin regeneration in the daughter fin tissues. These observations point to an underlying epigenetic process existing in the metabolic memory state. Here we present the methods needed to successfully generate the diabetic and metabolic memory groups of fish and

  17. 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 recognition in AD patients due to a ceiling effect. Healthy older adults scored overall higher in 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.

  18. 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

  19. 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.

  20. 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.

  1. 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,…

  2. Novel associative-memory-based self-learning neurocontrol model

    Science.gov (United States)

    Chen, Ke

    1992-09-01

    Intelligent control is an important field of AI application, which is closely related to machine learning, and the neurocontrol is a kind of intelligent control that controls actions of a physical system or a plant. Linear associative memory model is a good analytic tool for artificial neural networks. In this paper, we present a novel self-learning neurocontrol on the basis of the linear associative memory model to support intelligent control. Using our self-learning neurocontrol model, the learning process is viewed as an extension of one of J. Piaget's developmental stages. After a particular linear associative model developed by us is presented, a brief introduction to J. Piaget's cognitive theory is described as the basis of our self-learning style control. It follows that the neurocontrol model is presented, which usually includes two learning stages, viz. primary learning and high-level learning. As a demonstration of our neurocontrol model, an example is also presented with simulation techniques, called that `bird' catches an aim. The tentative experimental results show that the learning and controlling performance of this approach is surprisingly good. In conclusion, future research is pointed out to improve our self-learning neurocontrol model and explore other areas of application.

  3. Temporal lobe epilepsy as a model to understand human memory: the distinction between explicit and implicit memory.

    Science.gov (United States)

    Leritz, Elizabeth C; Grande, Laura J; Bauer, Russell M

    2006-08-01

    Decades of research have provided substantial evidence of memory impairments in patients with temporal lobe epilepsy (TLE), including deficits in the encoding, storage, and retrieval of new information. These findings are not surprising, given the associated underlying neuroanatomy, including the hippocampus and surrounding medial temporal lobe structures. Because of its associated anatomic and cognitive characteristics, TLE has provided an excellent model by which to examine specific aspects of human memory functioning, including classic distinctions such as that between explicit and implicit memory. Various clinical and experimental research studies have supported the idea that both conscious and unconscious processes support memory functioning, but the role of relevant brain structures has been the subject of debate. This review is concerned with a discussion of the current status of this research and, importantly, how TLE can inform future studies of memory distinctions.

  4. Simulation of Human Episodic Memory by Using a Computational Model of the Hippocampus

    OpenAIRE

    Naoyuki Sato; Yoko Yamaguchi

    2010-01-01

    The episodic memory, the memory of personal events and history, is essential for understanding the mechanism of human intelligence. Neuroscience evidence has shown that the hippocampus, a part of the limbic system, plays an important role in the encoding and the retrieval of the episodic memory. This paper reviews computational models of the hippocampus and introduces our own computational model of human episodic memory based on neural synchronization. Results from computer simulations demons...

  5. 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.

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

    Directory of Open Access Journals (Sweden)

    Claude F. Touzet

    2008-11-01

    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.

  7. 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.

  8. Instrumental learning: an animal model for sleep dependent memory enhancement.

    Science.gov (United States)

    Leenaars, Cathalijn H C; Girardi, Carlos E N; Joosten, Ruud N J M A; Lako, Irene M; Ruimschotel, Emma; Hanegraaf, Maaike A J; Dematteis, Maurice; Feenstra, Matthijs G P; Van Someren, Eus J W

    2013-07-15

    The relationship between learning and sleep is multifaceted; learning influences subsequent sleep characteristics, which may in turn influence subsequent memory. Studies in humans indicate that sleep may not only prevent degradation of acquired memories, but even enhance performance without further practice. In a rodent instrumental learning task, individual differences occur in how fast rats learn to associate lever pressing with food reward. Rats habitually sleep between learning sessions, and may differ in this respect. The current study assessed if the instrumental leaning paradigm could serve as a model to study sleep-dependent memory enhancement. Male Wistar rats performed 2 sessions of instrumental learning per day for 1-3 days. Electroencephalography was recorded both before and after the sessions. Sleep deprivation (3 h) was applied between the first and second session in a subgroup of rats. Measurements comprised the number of lever presses in each session, slow wave sleep (SWS) duration, Rapid Eye Movement Sleep (REMS) duration and sleep spindles. Baseline sleep parameters were similar for fast and slow learning rats. Task-exposure increased REMS-duration. The increase in REMS-duration was observed specifically after sessions in which learning occurred, but not after a later session. Sleep deprivation during the 3h period between the initial two sessions interfered with performance enhancement, but did not prevent this in all rats. Our considered movement control protocol induced partial sleep deprivation and also interfered with performance enhancement. The classic instrumental learning task provides a practical model for animal studies on sleep-dependent memory enhancement. Copyright © 2013 Elsevier B.V. All rights reserved.

  9. 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.)

  10. Detrended fluctuation analysis: A scale-free view on neuronal oscillations

    NARCIS (Netherlands)

    Hardstone, R.E.; Poil, S.S.; Schiavone, G.; Nikulin, V.V.; Mansvelder, H.D.; Linkenkaer Hansen, K.

    2012-01-01

    Recent years of research have shown that the complex temporal structure of ongoing oscillations is scale-free and characterized by long-range temporal correlations. Detrended fluctuation analysis (DFA) has proven particularly useful, revealing that genetic variation, normal development, or disease

  11. 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.

  12. Emergence of Super Cooperation of Prisoner’s Dilemma Games on Scale-Free Networks

    Science.gov (United States)

    Li, Angsheng; Yong, Xi

    2015-01-01

    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. PMID:25643279

  13. 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.

  14. 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

  15. 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.

  16. A mathematical model of dengue transmission with memory

    Science.gov (United States)

    Sardar, Tridip; Rana, Sourav; Chattopadhyay, Joydev

    2015-05-01

    We propose and analyze a new compartmental model of dengue transmission with memory between human-to-mosquito and mosquito-to-human. The memory is incorporated in the model by using a fractional differential operator. A threshold quantity R0 , similar to the basic reproduction number, is worked out. We determine the stability condition of the disease-free equilibrium (DFE) E0 with respect to the order of the fractional derivative α and R0 . We determine α dependent threshold values for R0 , below which DFE (E0) is always stable, above which DFE is always unstable, and at which the system exhibits a Hopf-type bifurcation. It is shown that even though R0 is less than unity, the DFE may not be always stable, and the system exhibits a Hopf-type bifurcation. Thus, making R0 models. It is also shown that R0 > 1 may not be a sufficient condition for the persistence of the disease. For a special case, when α = 1/2, we analytically verify our findings and determine the critical value of R0 in terms of some important model parameters. Finally, we discuss about some dengue control strategies in light of the threshold quantity R0 .

  17. Numerical modeling of shape memory alloy linear actuator

    Science.gov (United States)

    Jani, Jaronie Mohd; Huang, Sunan; Leary, Martin; Subic, Aleksandar

    2015-09-01

    The demand for shape memory alloy (SMA) actuators in high-technology applications is increasing; however, there exist technical challenges to the commercial application of SMA actuator technologies, especially associated with actuation duration. Excessive activation duration results in actuator damage due to overheating while excessive deactivation duration is not practical for high-frequency applications. Analytical and finite difference equation models were developed in this work to predict the activation and deactivation durations and associated SMA thermomechanical behavior under variable environmental and design conditions. Relevant factors, including latent heat effect, induced stress and material property variability are accommodated. An existing constitutive model was integrated into the proposed models to generate custom SMA stress-strain curves. Strong agreement was achieved between the proposed numerical models and experimental results; confirming their applicability for predicting the behavior of SMA actuators with variable thermomechanical conditions.

  18. Improved thermodynamic model for magnetic shape memory alloys

    Science.gov (United States)

    Waldauer, Alex B.; Feigenbaum, Heidi P.; Ciocanel, Constantin; Bruno, Nickolaus M.

    2012-09-01

    Magnetic shape memory alloys (MSMAs) are a class of materials that can exhibit up to 10% recoverable strain as a result of the application of either magnetic field or compressive stress. This unique property makes MSMAs potentially suitable for commercial applications such as sensors, power harvesters, or actuators. Before any commercial applications are fully realized, effective models capable of accurately predicting the magneto-mechanical behavior of MSMAs need to be developed. This paper builds on an existing thermodynamic based constitutive model for MSMAs by accounting for the three-dimensional nature of the demagnetization phenomenon. In particular, the importance of using a demagnetization factor that comes from a solution to the three-dimensional magneto-static boundary value problem is highlighted. Also, the magnetic field present in directions other than that applied because of demagnetization is included in the model. Finally, this work proposes a more flexible means of calibrating thermodynamic based constitutive models for MSMAs.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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...

  4. On a model of pattern regeneration based on cell memory.

    Directory of Open Access Journals (Sweden)

    Nikolai Bessonov

    Full Text Available We present here a new model of the cellular dynamics that enable regeneration of complex biological morphologies. Biological cell structures are considered as an ensemble of mathematical points on the plane. Each cell produces a signal which propagates in space and is received by other cells. The total signal received by each cell forms a signal distribution defined on the cell structure. This distribution characterizes the geometry of the cell structure. If a part of this structure is removed, the remaining cells have two signals. They keep the value of the signal which they had before the amputation (memory, and they receive a new signal produced after the amputation. Regeneration of the cell structure is stimulated by the difference between the old and the new signals. It is stopped when the two signals coincide. The algorithm of regeneration contains certain rules which are essential for its functioning, being the first quantitative model of cellular memory that implements regeneration of complex patterns to a specific target morphology. Correct regeneration depends on the form and the size of the cell structure, as well as on some parameters of regeneration.

  5. Automaticity and Control in Prospective Memory: A Computational Model

    Science.gov (United States)

    Gilbert, Sam J.; Hadjipavlou, Nicola; Raoelison, Matthieu

    2013-01-01

    Prospective memory (PM) refers to our ability to realize delayed intentions. In event-based PM paradigms, participants must act on an intention when they detect the occurrence of a pre-established cue. Some theorists propose that in such paradigms PM responding can only occur when participants deliberately initiate processes for monitoring their environment for appropriate cues. Others propose that perceptual processing of PM cues can directly trigger PM responding in the absence of strategic monitoring, at least under some circumstances. In order to address this debate, we present a computational model implementing the latter account, using a parallel distributed processing (interactive activation) framework. In this model PM responses can be triggered directly as a result of spreading activation from units representing perceptual inputs. PM responding can also be promoted by top-down monitoring for PM targets. The model fits a wide variety of empirical findings from PM paradigms, including the effect of maintaining PM intentions on ongoing response time and the intention superiority effect. The model also makes novel predictions concerning the effect of stimulus degradation on PM performance, the shape of response time distributions on ongoing and prospective memory trials, and the effects of instructing participants to make PM responses instead of ongoing responses or alongside them. These predictions were confirmed in two empirical experiments. We therefore suggest that PM should be considered to result from the interplay between bottom-up triggering of PM responses by perceptual input, and top-down monitoring for appropriate cues. We also show how the model can be extended to simulate encoding new intentions and subsequently deactivating them, and consider links between the model’s performance and results from neuroimaging. PMID:23555807

  6. Critical behavior of the contact process in annealed scale-free networks

    OpenAIRE

    Noh, Jae Dong; Park, Hyunggyu

    2008-01-01

    Critical behavior of the contact process is studied in annealed scale-free networks by mapping it on the random walk problem. We obtain the analytic results for the critical scaling, using the event-driven dynamics approach. These results are confirmed by numerical simulations. The disorder fluctuation induced by the sampling disorder in annealed networks is also explored. Finally, we discuss over the discrepancy of the finite-size-scaling theory in annealed and quenched networks in spirit of...

  7. Instrumental learning: An animal model for sleep dependent memory enhancement

    NARCIS (Netherlands)

    Leenaars, Cathalijn H. C.; Girardi, Carlos E. N.; Joosten, Ruud N. J. M. A.; Lako, Irene M.; Ruimschotel, Emma; Hanegraaf, Maaike A. J.; Dematteis, Maurice; Feenstra, Matthijs G. P.; van Someren, Eus J. W.

    2013-01-01

    The relationship between learning and sleep is multifaceted; learning influences subsequent sleep characteristics, which may in turn influence subsequent memory. Studies in humans indicate that sleep may not only prevent degradation of acquired memories, but even enhance performance without further

  8. Mean field analysis of algorithms for scale-free networks in molecular biology.

    Science.gov (United States)

    Konini, S; Janse van Rensburg, E J

    2017-01-01

    The sampling of scale-free networks in Molecular Biology is usually achieved by growing networks from a seed using recursive algorithms with elementary moves which include the addition and deletion of nodes and bonds. These algorithms include the Barabási-Albert algorithm. Later algorithms, such as the Duplication-Divergence algorithm, the Solé algorithm and the iSite algorithm, were inspired by biological processes underlying the evolution of protein networks, and the networks they produce differ essentially from networks grown by the Barabási-Albert algorithm. In this paper the mean field analysis of these algorithms is reconsidered, and extended to variant and modified implementations of the algorithms. The degree sequences of scale-free networks decay according to a powerlaw distribution, namely P(k) ∼ k-γ, where γ is a scaling exponent. We derive mean field expressions for γ, and test these by numerical simulations. Generally, good agreement is obtained. We also found that some algorithms do not produce scale-free networks (for example some variant Barabási-Albert and Solé networks).

  9. Yin and Yang of disease genes and death genes between reciprocally scale-free biological networks.

    Science.gov (United States)

    Han, Hyun Wook; Ohn, Jung Hun; Moon, Jisook; Kim, Ju Han

    2013-11-01

    Biological networks often show a scale-free topology with node degree following a power-law distribution. Lethal genes tend to form functional hubs, whereas non-lethal disease genes are located at the periphery. Uni-dimensional analyses, however, are flawed. We created and investigated two distinct scale-free networks; a protein-protein interaction (PPI) and a perturbation sensitivity network (PSN). The hubs of both networks exhibit a low molecular evolutionary rate (P genes but not with disease genes, whereas PSN hubs are highly enriched with disease genes and drug targets but not with lethal genes. PPI hub genes are enriched with essential cellular processes, but PSN hub genes are enriched with environmental interaction processes, having more TATA boxes and transcription factor binding sites. It is concluded that biological systems may balance internal growth signaling and external stress signaling by unifying the two opposite scale-free networks that are seemingly opposite to each other but work in concert between death and disease.

  10. Detrended fluctuation analysis: A scale-free view on neuronal oscillations

    Directory of Open Access Journals (Sweden)

    Richard eHardstone

    2012-11-01

    Full Text Available Recent years of research have shown that the complex temporal structure of ongoing oscillations is scale-free and characterized by long-range temporal correlations. Detrended fluctuation analysis (DFA has proven particularly useful, revealing that genetic variation, normal development, or disease can lead to differences in the scale-free amplitude modulation of oscillations. Furthermore, amplitude dynamics is remarkably independent of the time-averaged oscillation power, indicating that the DFA provides unique insights into the functional organization of neuronal systems. To facilitate understanding and encourage wider use of scaling analysis of neuronal oscillations, we provide a pedagogical explanation of the DFA algorithm and its underlying theory. Practical advice on applying DFA to oscillations is supported by MATLAB scripts from the Neurophysiological Biomarker Toolbox (NBT and links to the NBT tutorial website (http://www.nbtwiki.net/. Finally, we provide a brief overview of insights derived from the application of DFA to ongoing oscillations in health and disease, and discuss the putative relevance of criticality for understanding the mechanism underlying scale-free modulation of oscillations.

  11. Detrended fluctuation analysis: a scale-free view on neuronal oscillations.

    Science.gov (United States)

    Hardstone, Richard; Poil, Simon-Shlomo; Schiavone, Giuseppina; Jansen, Rick; Nikulin, Vadim V; Mansvelder, Huibert D; Linkenkaer-Hansen, Klaus

    2012-01-01

    Recent years of research have shown that the complex temporal structure of ongoing oscillations is scale-free and characterized by long-range temporal correlations. Detrended fluctuation analysis (DFA) has proven particularly useful, revealing that genetic variation, normal development, or disease can lead to differences in the scale-free amplitude modulation of oscillations. Furthermore, amplitude dynamics is remarkably independent of the time-averaged oscillation power, indicating that the DFA provides unique insights into the functional organization of neuronal systems. To facilitate understanding and encourage wider use of scaling analysis of neuronal oscillations, we provide a pedagogical explanation of the DFA algorithm and its underlying theory. Practical advice on applying DFA to oscillations is supported by MATLAB scripts from the Neurophysiological Biomarker Toolbox (NBT) and links to the NBT tutorial website http://www.nbtwiki.net/. Finally, we provide a brief overview of insights derived from the application of DFA to ongoing oscillations in health and disease, and discuss the putative relevance of criticality for understanding the mechanism underlying scale-free modulation of oscillations.

  12. The computational implementation of the landscape model: modeling inferential processes and memory representations of text comprehension.

    Science.gov (United States)

    Tzeng, Yuhtsuen; van den Broek, Paul; Kendeou, Panayiota; Lee, Chengyuan

    2005-05-01

    The complexity of text comprehension demands a computational approach to describe the cognitive processes involved. In this article, we present the computational implementation of the landscape model of reading. This model captures both on-line comprehension processes during reading and the off-line memory representation after reading is completed, incorporating both memory-based and coherence-based mechanisms of comprehension. The overall architecture and specific parameters of the program are described, and a running example is provided. Several studies comparing computational and behavioral data indicate that the implemented model is able to account for cycle-by-cycle comprehension processes and memory for a variety of text types and reading situations.

  13. 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.

  14. 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…

  15. 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

  16. A Gradient-Based Constitutive Model for Shape Memory Alloys

    Science.gov (United States)

    Tabesh, Majid; Boyd, James; Lagoudas, Dimitris

    2017-06-01

    Constitutive models are necessary to design shape memory alloy (SMA) components at nano- and micro-scales in NEMS and MEMS. The behavior of small-scale SMA structures deviates from that of the bulk material. Unfortunately, this response cannot be modeled using conventional constitutive models which lack an intrinsic length scale. At small scales, size effects are often observed along with large gradients in the stress or strain. Therefore, a gradient-based thermodynamically consistent constitutive framework is established. Generalized surface and body forces are assumed to contribute to the free energy as work conjugates to the martensite volume fraction, transformation strain tensor, and their spatial gradients. The rates of evolution of these variables are obtained by invoking the principal of maximum dissipation after assuming a transformation surface, which is a differential equation in space. This approach is compared to the theories that use a configurational force (microforce) balance law. The developed constitutive model includes energetic and dissipative length scales that can be calibrated experimentally. Boundary value problems, including pure bending of SMA beams and simple torsion of SMA cylindrical bars, are solved to demonstrate the capabilities of this model. These problems contain the differential equation for the transformation surface as well as the equilibrium equation and are solved analytically and numerically. The simplest version of the model, containing only the additional gradient of martensite volume fraction, predicts a response with greater transformation hardening for smaller structures.

  17. 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.

  18. A Hamiltonian Driven Quantum-Like Model for Overdistribution in Episodic Memory Recollection

    Directory of Open Access Journals (Sweden)

    Jan B. Broekaert

    2017-06-01

    Full Text Available 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. [1] for the episodic memory overdistribution in the experimental immediate item false memory paradigm [1–3]. Following the Hamiltonian method of Busemeyer and Bruza [4] our model adds time-evolution of the perceived memory state through the stages of the experimental process based on psychologically interpretable parameters—γc for recollection capability of cues, κp 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.

  19. 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

    National Research Council Canada - National Science Library

    Aleksandra Gruszka; Jaroslaw Orzechowski

    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...

  20. Properties of Coupled Oscillator Model for Bidirectional Associative Memory

    Science.gov (United States)

    Kawaguchi, Satoshi

    2016-08-01

    In this study, we consider the stationary state and dynamical properties of a coupled oscillator model for bidirectional associative memory. For the stationary state, we apply the replica method to obtain self-consistent order parameter equations. The theoretical results for the storage capacity and overlap agree well with the numerical simulation. For the retrieval process, we apply statistical neurodynamics to include temporal noise correlations. For the successful retrieval process, the theoretical result obtained with the fourth-order approximation qualitatively agrees with the numerical simulation. However, for the unsuccessful retrieval process, higher-order noise correlations suppress severely; therefore, the maximum value of the overlap and the relaxation time are smaller than those of the numerical simulation. The reasons for the discrepancies between the theoretical result and numerical simulation, and the validity of our analysis are discussed.

  1. Working memory and intraindividual variability as neurocognitive indicators in ADHD: examining competing model predictions.

    Science.gov (United States)

    Kofler, Michael J; Alderson, R Matt; Raiker, Joseph S; Bolden, Jennifer; Sarver, Dustin E; Rapport, Mark D

    2014-05-01

    The current study examined competing predictions of the default mode, cognitive neuroenergetic, and functional working memory models of attention-deficit/hyperactivity disorder (ADHD) regarding the relation between neurocognitive impairments in working memory and intraindividual variability. Twenty-two children with ADHD and 15 typically developing children were assessed on multiple tasks measuring intraindividual reaction time (RT) variability (ex-Gaussian: tau, sigma) and central executive (CE) working memory. Latent factor scores based on multiple, counterbalanced tasks were created for each construct of interest (CE, tau, sigma) to reflect reliable variance associated with each construct and remove task-specific, test-retest, and random error. Bias-corrected, bootstrapped mediation analyses revealed that CE working memory accounted for 88% to 100% of ADHD-related RT variability across models, and between-group differences in RT variability were no longer detectable after accounting for the mediating role of CE working memory. In contrast, RT variability accounted for 10% to 29% of between-group differences in CE working memory, and large magnitude CE working memory deficits remained after accounting for this partial mediation. Statistical comparison of effect size estimates across models suggests directionality of effects, such that the mediation effects of CE working memory on RT variability were significantly greater than the mediation effects of RT variability on CE working memory. The current findings question the role of RT variability as a primary neurocognitive indicator in ADHD and suggest that ADHD-related RT variability may be secondary to underlying deficits in CE working memory.

  2. 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.

  3. 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

  4. 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…

  5. 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.

  6. Characterization and modeling of light activated shape memory polymer

    Science.gov (United States)

    Beblo, Richard Vincent

    Shape memory polymers have recently become the focus of research for their unique ability to switch between two modulus states, allowing them to both recover from large amounts of strain as well as support complex loads. Part of this research involves engineering new formulas specifically designed for applications where traditional thermally activated SMPs are not ideal by tailoring the activation method used to transition the polymer. One such class of polymers is those that utilize optical energy at specific wavelengths to create and cleave crosslinks. It is the development of this new class of light activated shape memory polymers (LASMP) that is the focus of the presented work. Experimental methods are newly created for this novel class of active materials. Several candidate LASMP formulas are then subjected to this set of experiments characterizing their mechanical and optical properties. Experimentally observed variations among the formulae include virgin state modulus, percent change in modulus with stimulus, and in some instances inelastic response. To expedite the development of LASMP, a first principles multi-scale model based on the polymer's molecular structure is presented and used to predict the stress response of the candidate formulas. Rotational isomeric state (RIS) theory is used to build a molecular model of a phantom polymer chain. Assessment of the resulting conformation is then made via the Johnson family of statistical distributions and Boltzmann statistical thermodynamics. The ability of the presented model to predict material properties based on the molecular structure of the polymer reduces the time and resources required to test new candidate formulas of LASMP as well as aiding in the ability to tailor the polymer to specific application requirements. While the first principles model works well to identify promising formulas, it lacks precision. The stress contribution from the constraints on the polymer chain's junctions and neighboring

  7. Using chaotic artificial neural networks to model memory in the brain

    Science.gov (United States)

    Aram, Zainab; Jafari, Sajad; Ma, Jun; Sprott, Julien C.; Zendehrouh, Sareh; Pham, Viet-Thanh

    2017-03-01

    In the current study, a novel model for human memory is proposed based on the chaotic dynamics of artificial neural networks. This new model explains a biological fact about memory which is not yet explained by any other model: There are theories that the brain normally works in a chaotic mode, while during attention it shows ordered behavior. This model uses the periodic windows observed in a previously proposed model for the brain to store and then recollect the information.

  8. 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

  9. Filament Formation in Molecular Clouds as a Scale-Free Process

    Science.gov (United States)

    Vázquez-Semadeni, Enrique; Gómez, Gilberto

    We discuss the formation of filaments in molecular clouds (MCs) as the result of large-scale collapse in the clouds. We first give arguments suggesting that self-gravity dominates the nonthermal motions, and then briefly describe the resulting structure, similar to that found in molecular-line and dust observations of the filaments in the clouds. The filaments exhibit a hierarchical structure in both density and velocity, suggesting a scale-free nature, similar to that of the cosmic web, resulting from the domination of self-gravity from the MC down to the core scale.

  10. Explosive synchronization in clustered scale-free networks: Revealing the existence of chimera state

    Science.gov (United States)

    Berec, V.

    2016-02-01

    The collective dynamics of Kuramoto oscillators with a positive correlation between the incoherent and fully coherent domains in clustered scale-free networks is studied. Emergence of chimera states for the onsets of explosive synchronization transition is observed during an intermediate coupling regime when degree-frequency correlation is established for the hubs with the highest degrees. Diagnostic of the abrupt synchronization is revealed by the intrinsic spectral properties of the network graph Laplacian encoded in the heterogeneous phase space manifold, through extensive analytical investigation, presenting realistic MC simulations of nonlocal interactions in discrete time dynamics evolving on the network.

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

    Science.gov (United States)

    Wu, Liang; Zhu, Shiqun

    2011-11-01

    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.

  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

    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. Deficit of the "primacy effect" in parkinsonians interpreted by means of the working memory model.

    Science.gov (United States)

    Della Sala, S; Pasetti, C; Sempio, P

    1987-01-01

    29 Parkinsonians and 29 controls matched for age and schooling were tested for memory by means of a free recall test (serial position curve) and two spans (verbal and non-verbal). The free recall test yields three measures: primacy (item 1); secondary memory (items 2-7) and recency (items 8-12). The Parkinsonians displayed a selective deficit of primacy, which is taken to be evidence of defective functioning of the Central Executive in the Working Memory model.

  14. Solvable random-walk model with memory and its relations with Markovian models of anomalous diffusion

    Science.gov (United States)

    Boyer, D.; Romo-Cruz, J. C. R.

    2014-10-01

    Motivated by studies on the recurrent properties of animal and human mobility, we introduce a path-dependent random-walk model with long-range memory for which not only the mean-square displacement (MSD) but also the propagator can be obtained exactly in the asymptotic limit. The model consists of a random walker on a lattice, which, at a constant rate, stochastically relocates at a site occupied at some earlier time. This time in the past is chosen randomly according to a memory kernel, whose temporal decay can be varied via an exponent parameter. In the weakly non-Markovian regime, memory reduces the diffusion coefficient from the bare value. When the mean backward jump in time diverges, the diffusion coefficient vanishes and a transition to an anomalous subdiffusive regime occurs. Paradoxically, at the transition, the process is an anticorrelated Lévy flight. Although in the subdiffusive regime the model exhibits some features of the continuous time random walk with infinite mean waiting time, it belongs to another universality class. If memory is very long-ranged, a second transition takes place to a regime characterized by a logarithmic growth of the MSD with time. In this case the process is asymptotically Gaussian and effectively described as a scaled Brownian motion with a diffusion coefficient decaying as 1 /t .

  15. 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.

  16. 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

  17. 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 two dynamic benchmark problems...

  18. 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…

  19. A seasonal periodic long memory model for monthly river flows

    NARCIS (Netherlands)

    M. Ooms (Marius); Ph.H.B.F. Franses (Philip Hans)

    1998-01-01

    textabstractBased on simple time series plots and periodic sample autocorrelations, we document that monthly river flow data display long memory, in addition to pronounced seasonality. In fact, it appears that the long memory characteristics vary with the season. To describe these two properties

  20. 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

  1. 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.

  2. 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.

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

    Directory of Open Access Journals (Sweden)

    Jing Lu

    Full Text Available 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.

  4. 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

  5. Analysis of a Car-Following Model with Driver Memory Effect

    Science.gov (United States)

    Xin, Zhi; Xu, Jian

    A nonlinear car-following model considering memory effect of human drivers is studied by means of theoretical analysis and numerical simulation. We model the memory effect of the response of drivers to the traffic situation for a car-following model by introducing a system variable related to velocity. The memory effect of the drivers is a kind of state-dependent delay. The stability of the car-following model with two kinds of time delay is studied. The hysteresis loop of traffic flow from different initial states is compared. The effect of the maximum time delay on the stability is discussed.

  6. Thermoelectric control of shape memory alloy microactuators: a thermal model

    Science.gov (United States)

    Abadie, J.; Chaillet, Nicolas; Lexcellent, Christian; Bourjault, Alain

    1999-06-01

    Microtechnologies and microsystems engineering use new active materials. These materials are interesting to realize microactuators and microsensors. In this category of materials, Shape Memory Alloys (SMA) are good candidates for microactuation. SMA wires, or thin plates, can be used as active material in microfingers. These microstructures are able to provide very important forces, but have low dynamic response, especially for cooling, in confined environment. The control of the SMA phase transformations, and then the mechanical power generation, is made by the temperature. The Joule effect is an easy and efficiency way to heat the SMA wires, but cooling is not so easy. The dynamic response of the actuator depends on cooling capabilities. The thermal convection and conduction are the traditional ways to cool the SMA, but have limitations for microsystems. We are looking for a reversible way of heating and cooling SMA microactuators, based on the thermoelectric effects. Using Peltier effect, a positive or a negative electrical courant is able to pump or produce heat, in the SMA actuator. A physical model based on thermal exchanges between a Nickel/Titanium (NiTi) SMA, and Bismuth/Telluride (Te3Bi2) thermoelectric material has been developed. For simulation, we use a numerical resolution of our model, with finite elements, which takes into account the Peltier effect, the Joule effect, the convection, the conduction and the phase transformation of the SMA. We have also developed the corresponding experimental system, with two thermoelectric junctions, where the SMA actuator is one of the element of each junction. In this paper, the physical model and its numerical resolution are given, the experimental system used to validate the model is described, and experimental results are shown.

  7. Shape memory behavior of epoxy-based model materials: Tailoring approaches and thermo-mechanical modeling

    Science.gov (United States)

    Pandini, Stefano; Avanzini, Andrea; Battini, Davide; Berardi, Mario; Baldi, Francesco; Bignotti, Fabio

    2016-05-01

    A series of structurally related epoxy resins were prepared as model systems for the investigation of the shape memory response, with the aim to assess the possibility of tailoring their thermo-mechanical response and conveniently describing their strain evolution under triggering stimuli with a simple thermoviscoelastic model. The resins formulation was varied in order to obtain systems with controlled glass transition temperature and crosslink density. The shape memory response was investigated by means of properly designed thermo-mechanical cycles, which allowed to measure both the ability to fully recover the applied strain and to exert a stress on a confining medium. The results were also compared with the predictions obtained by finite element simulations of the thermo-mechanical cycle by the employ of a model whose parameters were implemented from classical DMA analysis.

  8. Compact Modeling Solutions for Oxide-Based Resistive Switching Memories (OxRAM

    Directory of Open Access Journals (Sweden)

    Marc Bocquet

    2014-01-01

    Full Text Available Emerging non-volatile memories based on resistive switching mechanisms attract intense R&D efforts from both academia and industry. Oxide-based Resistive Random Acces Memories (OxRAM gather noteworthy performances, such as fast write/read speed, low power and high endurance outperforming therefore conventional Flash memories. To fully explore new design concepts such as distributed memory in logic, OxRAM compact models have to be developed and implemented into electrical simulators to assess performances at a circuit level. In this paper, we present compact models of the bipolar OxRAM memory based on physical phenomenons. This model was implemented in electrical simulators for single device up to circuit level.

  9. Statistical Mechanics Model of the Speed - Accuracy Tradeoff in Spatial and Lexical Memory

    Science.gov (United States)

    Kaufman, Miron; Allen, Philip

    2000-03-01

    The molar neural network model of P. Allen, M. Kaufman, A. F. Smith, R. E. Popper, Psychology and Aging 13, 501 (1998) and Experimental Aging Research, 24, 307 (1998) is extended to incorporate reaction times. In our model the entropy associated with a particular task determines the reaction time. We use this molar neural model to directly analyze experimental data on episodic (spatial) memory and semantic (lexical) memory tasks. In particular we are interested in the effect of aging on the two types of memory. We find that there is no difference in performance levels for lexical memory tasks between younger and older adults. In the case spatial memory tasks we find that aging has a detrimental effect on the performance level. This work is supported by NIH/NIA grant AG09282-06.

  10. An improved car-following model considering headway changes with memory

    Science.gov (United States)

    Yu, Shaowei; Shi, Zhongke

    2015-03-01

    To describe car-following behaviors in complex situations better, increase roadway traffic mobility and minimize cars' fuel consumptions, the linkage between headway changes with memory and car-following behaviors was explored with the field car-following data by using the gray correlation analysis method, and then an improved car-following model considering headway changes with memory on a single lane was proposed based on the full velocity difference model. Some numerical simulations were carried out by employing the improved car-following model to explore how headway changes with memory affected each car's velocity, acceleration, headway and fuel consumptions. The research results show that headway changes with memory have significant effects on car-following behaviors and fuel consumptions and that considering headway changes with memory in designing the adaptive cruise control strategy can improve the traffic flow stability and minimize cars' fuel consumptions.

  11. 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…

  12. A single-system model predicts recognition memory and repetition priming in amnesia

    NARCIS (Netherlands)

    Berry, C.J.; Kessels, R.P.C.; Wester, A.J.; Shanks, D.R.

    2014-01-01

    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

  13. 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.

  14. Examining the influence of working memory on updating mental models.

    Science.gov (United States)

    Valadao, Derick F; Anderson, Britt; Danckert, James

    2015-01-01

    The ability to accurately build and update mental representations of our environment depends on our ability to integrate information over a variety of time scales and detect changes in the regularity of events. As such, the cognitive mechanisms that support model building and updating are likely to interact with those involved in working memory (WM). To examine this, we performed three experiments that manipulated WM demands concurrently with the need to attend to regularities in other stimulus properties (i.e., location and shape). That is, participants completed a prediction task while simultaneously performing an n-back WM task with either no load or a moderate load. The distribution of target locations (Experiment 1) or shapes (Experiments 2 and 3) included some level of probabilistic regularity, which, unbeknown to participants, changed abruptly within each block. Moderate WM load hampered the ability to benefit from target regularities and to adapt to changes in those regularities (i.e., the prediction task). This was most pronounced when both prediction and WM requirements shared the same target feature. Our results show that representational updating depends on free WM resources in a domain-specific fashion.

  15. Generating life episodes for the purpose of testing of episodic memory models

    OpenAIRE

    Běhan, Zdeněk

    2012-01-01

    The goal of this work is to create a generator that provides a corpora of input episodes in the specified format, which can be used as an input to test episodic memory models. More specifically, the methods used should ensure the scope to be in years up to a possible lifetime of a typical human agent. It also attempts to verify this on an actual episodic memory model, and test if the generated data has high enough quality to be used for testing psychological paradigms on memory models.

  16. 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

  17. Execution Models for Mapping Programs onto Distributed Memory Parallel Computers

    Science.gov (United States)

    1992-03-01

    DISTRIBUTED MEMORY PARALLEL COMPUTERS Alan Sussman Contract No. NAS1-18605 March 1992 Institute for Computer Applications in Science and Engineering NASA...MEMORY PARALLEL COMPUTERS Alan Sussman 1 Institute for Computer Applications in Science and Engineering NASA Langley Research Center Hampton, VA 23665...Computation onto Distributed Mem- ory Parallel Computers . PhD thesis, Carnegie Mellon University, September 1991. Also available as Technical Report

  18. Nonlinear analysis of an improved continuum model considering headway change with memory

    Science.gov (United States)

    Cheng, Rongjun; Wang, Jufeng; Ge, Hongxia; Li, Zhipeng

    2018-01-01

    Considering the effect of headway changes with memory, an improved continuum model of traffic flow is proposed in this paper. By means of linear stability theory, the new model’s linear stability with the effect of headway changes with memory is obtained. Through nonlinear analysis, the KdV-Burgers equation is derived to describe the propagating behavior of traffic density wave near the neutral stability line. Numerical simulation is carried out to study the improved traffic flow model, which explores how the headway changes with memory affected each car’s velocity, density and energy consumption. Numerical results show that when considering the effects of headway changes with memory, the traffic jams can be suppressed efficiently. Furthermore, research results demonstrate that the effect of headway changes with memory can avoid the disadvantage of historical information, which will improve the stability of traffic flow and minimize car energy consumption.

  19. Computational cognitive models of spatial memory in navigation space: a review.

    Science.gov (United States)

    Madl, Tamas; Chen, Ke; Montaldi, Daniela; Trappl, Robert

    2015-05-01

    Spatial memory refers to the part of the memory system that encodes, stores, recognizes and recalls spatial information about the environment and the agent's orientation within it. Such information is required to be able to navigate to goal locations, and is vitally important for any embodied agent, or model thereof, for reaching goals in a spatially extended environment. In this paper, a number of computationally implemented cognitive models of spatial memory are reviewed and compared. Three categories of models are considered: symbolic models, neural network models, and models that are part of a systems-level cognitive architecture. Representative models from each category are described and compared in a number of dimensions along which simulation models can differ (level of modeling, types of representation, structural accuracy, generality and abstraction, environment complexity), including their possible mapping to the underlying neural substrate. Neural mappings are rarely explicated in the context of behaviorally validated models, but they could be useful to cognitive modeling research by providing a new approach for investigating a model's plausibility. Finally, suggested experimental neuroscience methods are described for verifying the biological plausibility of computational cognitive models of spatial memory, and open questions for the field of spatial memory modeling are outlined. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  20. Influence of dynamical condensation on epidemic spreading in scale-free networks.

    Science.gov (United States)

    Tang, Ming; Liu, Li; Liu, Zonghua

    2009-01-01

    Considering the accumulation phenomenon in public places, we investigate how the condensation of moving bosonic particles influences the epidemic spreading in scale-free metapopulation networks. Our mean-field theory shows that condensation can significantly enhance the effect of epidemic spreading and reduce the threshold for epidemic to survive, in contrast to the case of without condensation. In the stationary state, the number of infected particles increases with the degree k linearly when kk_{c}, where k_{c} denotes the crossover degree of the nodes with unity particle. The dependence of critical infective rate beta_{c} on the parameters k_{max}, micro, and delta, is figured out, where k_{max}, micro, and delta denote the largest degree, recovery rate, and jumping exponent, respectively. Numerical simulations have confirmed the theoretical predictions.

  1. Robustness of cooperation on scale-free networks under continuous topological change

    CERN Document Server

    Ichinose, Genki; Tanizawa, Toshihiro

    2013-01-01

    In this paper, we numerically investigate the robustness of cooperation clusters in prisoner's dilemma played on scale-free networks, where their network topologies change by continuous removal and addition of nodes. Each of these removal and addition can be either random or intentional. We therefore have four different strategies in changing network topology: random removal and random addition (RR), random removal and preferential addition (RP), targeted removal and random addition (TR), and targeted removal and preferential addition (TP). We find that cooperation clusters are the most fragile against TR, while they are the most robust against RP even in high temptation coefficients for defect. The effect of the degree mixing pattern of the network is not the primary factor for the robustness of cooperation under continuous change in network topology due to consequential removal and addition of nodes, which is quite different from the cases observed in static networks. Cooperation clusters become more robust...

  2. An improved local immunization strategy for scale-free networks with a high degree of clustering

    Science.gov (United States)

    Xia, Lingling; Jiang, Guoping; Song, Yurong; Song, Bo

    2017-01-01

    The design of immunization strategies is an extremely important issue for disease or computer virus control and prevention. In this paper, we propose an improved local immunization strategy based on node's clustering which was seldom considered in the existing immunization strategies. The main aim of the proposed strategy is to iteratively immunize the node which has a high connectivity and a low clustering coefficient. To validate the effectiveness of our strategy, we compare it with two typical local immunization strategies on both real and artificial networks with a high degree of clustering. Simulations on these networks demonstrate that the performance of our strategy is superior to that of two typical strategies. The proposed strategy can be regarded as a compromise between computational complexity and immune effect, which can be widely applied in scale-free networks of high clustering, such as social network, technological networks and so on. In addition, this study provides useful hints for designing optimal immunization strategy for specific network.

  3. On the visualization of social and other scale-free networks.

    Science.gov (United States)

    Jia, Yuntao; Hoberock, Jared; Garland, Michael; Hart, John C

    2008-01-01

    This paper proposes novel methods for visualizing specifically the large power-law graphs that arise in sociology and the sciences. In such cases a large portion of edges can be shown to be less important and removed while preserving component connectedness and other features (e.g. cliques) to more clearly reveal the network's underlying connection pathways. This simplification approach deterministically filters (instead of clustering) the graph to retain important node and edge semantics, and works both automatically and interactively. The improved graph filtering and layout is combined with a novel computer graphics anisotropic shading of the dense crisscrossing array of edges to yield a full social network and scale-free graph visualization system. Both quantitative analysis and visual results demonstrate the effectiveness of this approach.

  4. A Congestion Control Strategy for Power Scale-Free Communication Network

    Directory of Open Access Journals (Sweden)

    Min Xiang

    2017-10-01

    Full Text Available The scale-free topology of power communication network leads to more data flow in less hub nodes, which can cause local congestion. Considering the differences of the nodes’ delivery capacity and cache capacity, an integrated routing based on the communication service classification is proposed to reduce network congestion. In the power communication network, packets can be classified as key operational services (I-level and affairs management services (II-level. The shortest routing, which selects the path of the least hops, is adopted to transmit I-level packets. The load-balanced global dynamic routing, which uses the node’s queue length and delivery capacity to establish the cost function and chooses the path with minimal cost, is adopted to transmit II-level packets. The simulation results show that the integrated routing has a larger critical packet generation rate and can effectively reduce congestion.

  5. Turbulence and other processes for the scale-free texture of the fast solar wind

    Science.gov (United States)

    Hnat, B.; Chapman, S. C.; Gogoberidze, G.; Wicks, R. T.

    2012-04-01

    The higher-order statistics of magnetic field magnitude fluctuations in the fast quiet solar wind are quantified systematically, scale by scale. We find a single global non-Gaussian scale-free behavior from minutes to over 5 hours. This spans the signature of an inertial range of magnetohydrodynamic turbulence and a ˜1/f range in magnetic field components. This global scaling in field magnitude fluctuations is an intrinsic component of the underlying texture of the solar wind which co-exists with the signature of MHD turbulence but extends to lower frequencies. Importantly, scaling and non- Gaussian statistics of fluctuations are not unique to turbulence and can imply other physical mechanisms- our results thus place a strong constraint on theories of the dynamics of the solar corona and solar wind. Intriguingly, the magnetic field and velocity components also show scale-dependent dynamic alignment outside of the inertial range of MHD turbulence.

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

    Directory of Open Access Journals (Sweden)

    Dan Wu

    Full Text Available 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.

  8. 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.

  9. 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…

  10. Identification of Nascent Memory CD8 T Cells and Modeling of Their Ontogeny.

    Science.gov (United States)

    Crauste, Fabien; Mafille, Julien; Boucinha, Lilia; Djebali, Sophia; Gandrillon, Olivier; Marvel, Jacqueline; Arpin, Christophe

    2017-03-22

    Primary immune responses generate short-term effectors and long-term protective memory cells. The delineation of the genealogy linking naive, effector, and memory cells has been complicated by the lack of phenotypes discriminating effector from memory differentiation stages. Using transcriptomics and phenotypic analyses, we identify Bcl2 and Mki67 as a marker combination that enables the tracking of nascent memory cells within the effector phase. We then use a formal approach based on mathematical models describing the dynamics of population size evolution to test potential progeny links and demonstrate that most cells follow a linear naive→early effector→late effector→memory pathway. Moreover, our mathematical model allows long-term prediction of memory cell numbers from a few early experimental measurements. Our work thus provides a phenotypic means to identify effector and memory cells, as well as a mathematical framework to investigate their genealogy and to predict the outcome of immunization regimens in terms of memory cell numbers generated. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  11. Model reference adaptive control based on kp model for magnetically controlled shape memory alloy actuators.

    Science.gov (United States)

    Zhou, Miaolei; Zhang, Yannan; Ji, Kun; Zhu, Dong

    2017-06-16

    Magnetically controlled shape memory alloy (MSMA) actuators take advantages of their large deformation and high controllability. However, the intricate hysteresis nonlinearity often results in low positioning accuracy and slow actuator response. In this paper, a modified Krasnosel'skii-Pokrovskii model was adopted to describe the complicated hysteresis phenomenon in the MSMA actuators. Adaptive recursive algorithm was employed to identify the density parameters of the adopted model. Subsequently, to further eliminate the hysteresis nonlinearity and improve the positioning accuracy, the model reference adaptive control method was proposed to optimize the model and inverse model compensation. The simulation experiments show that the model reference adaptive control adopted in the paper significantly improves the control precision of the actuators, with a maximum tracking error of 0.0072 mm. The results prove that the model reference adaptive control method is efficient to eliminate hysteresis nonlinearity and achieves a higher positioning accuracy of the MSMA actuators.

  12. An ideal model for stress-induced martensitic transformations in shape-memory alloys

    National Research Council Canada - National Science Library

    Michele Marino

    2014-01-01

    ... (both for transformation and stiffness properties). The model is developed under the assumption of ideal behavior during martensitic transformation, and the predicted response is governed by few parameters, standard in the context of shape-memory...

  13. Memory in a fractional-order cardiomyocyte model alters properties of alternans and spontaneous activity

    Science.gov (United States)

    Comlekoglu, T.; Weinberg, S. H.

    2017-09-01

    Cardiac memory is the dependence of electrical activity on the prior history of one or more system state variables, including transmembrane potential (Vm), ionic current gating, and ion concentrations. While prior work has represented memory either phenomenologically or with biophysical detail, in this study, we consider an intermediate approach of a minimal three-variable cardiomyocyte model, modified with fractional-order dynamics, i.e., a differential equation of order between 0 and 1, to account for history-dependence. Memory is represented via both capacitive memory, due to fractional-order Vm dynamics, that arises due to non-ideal behavior of membrane capacitance; and ionic current gating memory, due to fractional-order gating variable dynamics, that arises due to gating history-dependence. We perform simulations for varying Vm and gating variable fractional-orders and pacing cycle length and measure action potential duration (APD) and incidence of alternans, loss of capture, and spontaneous activity. In the absence of ionic current gating memory, we find that capacitive memory, i.e., decreased Vm fractional-order, typically shortens APD, suppresses alternans, and decreases the minimum cycle length (MCL) for loss of capture. However, in the presence of ionic current gating memory, capacitive memory can prolong APD, promote alternans, and increase MCL. Further, we find that reduced Vm fractional order (typically less than 0.75) can drive phase 4 depolarizations that promote spontaneous activity. Collectively, our results demonstrate that memory reproduced by a fractional-order model can play a role in alternans formation and pacemaking, and in general, can greatly increase the range of electrophysiological characteristics exhibited by a minimal model.

  14. Memory in a fractional-order cardiomyocyte model alters properties of alternans and spontaneous activity.

    Science.gov (United States)

    Comlekoglu, T; Weinberg, S H

    2017-09-01

    Cardiac memory is the dependence of electrical activity on the prior history of one or more system state variables, including transmembrane potential (Vm), ionic current gating, and ion concentrations. While prior work has represented memory either phenomenologically or with biophysical detail, in this study, we consider an intermediate approach of a minimal three-variable cardiomyocyte model, modified with fractional-order dynamics, i.e., a differential equation of order between 0 and 1, to account for history-dependence. Memory is represented via both capacitive memory, due to fractional-order Vm dynamics, that arises due to non-ideal behavior of membrane capacitance; and ionic current gating memory, due to fractional-order gating variable dynamics, that arises due to gating history-dependence. We perform simulations for varying Vm and gating variable fractional-orders and pacing cycle length and measure action potential duration (APD) and incidence of alternans, loss of capture, and spontaneous activity. In the absence of ionic current gating memory, we find that capacitive memory, i.e., decreased Vm fractional-order, typically shortens APD, suppresses alternans, and decreases the minimum cycle length (MCL) for loss of capture. However, in the presence of ionic current gating memory, capacitive memory can prolong APD, promote alternans, and increase MCL. Further, we find that reduced Vm fractional order (typically less than 0.75) can drive phase 4 depolarizations that promote spontaneous activity. Collectively, our results demonstrate that memory reproduced by a fractional-order model can play a role in alternans formation and pacemaking, and in general, can greatly increase the range of electrophysiological characteristics exhibited by a minimal model.

  15. A Memory Insensitive Technique for Large Model Simplification

    Energy Technology Data Exchange (ETDEWEB)

    Lindstrom, P; Silva, C

    2001-08-07

    In this paper we propose three simple, but significant improvements to the OoCS (Out-of-Core Simplification) algorithm of Lindstrom [20] which increase the quality of approximations and extend the applicability of the algorithm to an even larger class of compute systems. The original OoCS algorithm has memory complexity that depends on the size of the output mesh, but no dependency on the size of the input mesh. That is, it can be used to simplify meshes of arbitrarily large size, but the complexity of the output mesh is limited by the amount of memory available. Our first contribution is a version of OoCS that removes the dependency of having enough memory to hold (even) the simplified mesh. With our new algorithm, the whole process is made essentially independent of the available memory on the host computer. Our new technique uses disk instead of main memory, but it is carefully designed to avoid costly random accesses. Our two other contributions improve the quality of the approximations generated by OoCS. We propose a scheme for preserving surface boundaries which does not use connectivity information, and a scheme for constraining the position of the ''representative vertex'' of a grid cell to an optimal position inside the cell.

  16. Spatial working memory deficits in GluA1 AMPA receptor subunit knockout mice reflect impaired short-term habituation: Evidence for Wagner's dual-process memory model

    Science.gov (United States)

    Sanderson, David J.; McHugh, Stephen B.; Good, Mark A.; Sprengel, Rolf; Seeburg, Peter H.; Rawlins, J. Nicholas P.; Bannerman, David M.

    2010-01-01

    Genetically modified mice, lacking the GluA1 AMPA receptor subunit, are impaired on spatial working memory tasks, but display normal acquisition of spatial reference memory tasks. One explanation for this dissociation is that working memory, win-shift performance engages a GluA1-dependent, non-associative, short-term memory process through which animals choose relatively novel arms in preference to relatively familiar options. In contrast, spatial reference memory, as exemplified by the Morris water maze task, reflects a GluA1-independent, associative, long-term memory mechanism. These results can be accommodated by Wagner's dual-process model of memory in which short and long-term memory mechanisms exist in parallel and, under certain circumstances, compete with each other. According to our analysis, GluA1−/− mice lack short-term memory for recently experienced spatial stimuli. One consequence of this impairment is that these stimuli should remain surprising and thus be better able to form long-term associative representations. Consistent with this hypothesis, we have recently shown that long-term spatial memory for recently visited locations is enhanced in GluA1−/− mice, despite impairments in hippocampal synaptic plasticity. Taken together, these results support a role for GluA1-containing AMPA receptors in short-term habituation, and in modulating the intensity or perceived salience of stimuli. PMID:20350557

  17. 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...... effects can be as large as 50% to the total barrier. For collective diffusion, the role of memory effects is in general less pronounced.......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...

  18. Styrene-based shape memory foam: fabrication and mathematical modeling

    Science.gov (United States)

    Yao, Yongtao; Zhou, Tianyang; Qin, Chao; Liu, Yanju; Leng, Jinsong

    2016-10-01

    Shape memory polymer foam is a promising kind of structure in the biomedical and aerospace field. Shape memory styrene foam with uniform and controlled open-cell structure was successfully fabricated using a salt particulate leaching method. Shape recovery capability exists for foam programming in both high-temperature compression and low-temperature compression (Shape recovery properties such as shape fixing property and shape recovery ratio were also characterized. In order to provide guidance for the future fabrication of shape memory foam, the theories of Gibson and Ashby as well as differential micromechanics theory were applied to predict Young’s modulus and the mechanical behavior of SMP styrene foams during the compression process.

  19. 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.

  20. 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...... behavioral model capable of an improved performance when used for the modeling and predistortion of RF PAs deployed in ET transceivers. The proposed solution consists in a 2D behavioral model having as a dual-input the PA complex baseband envelope and the modulated supply waveform, peculiar of the ET case...... 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...

  1. Using model-based functional MRI to locate working memory updates and declarative memory retrievals in the fronto-parietal network

    NARCIS (Netherlands)

    Borst, Jelmer P.; Anderson, John R.

    2013-01-01

    In this study, we used model-based functional MRI (fMRI) to locate two functions of the fronto-parietal network: declarative memory retrievals and updating of working memory. Because regions in the fronto-parietal network are by definition coherently active, locating functions within this network is

  2. 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.

  3. Navigation in small-world networks: a scale-free continuum model

    NARCIS (Netherlands)

    Franceschetti, M.; Meester, R.W.J.

    2006-01-01

    The small-world phenomenon, the principle that we are all linked by a short chain of intermediate acquaintances, has been investigated in mathematics and social sciences. It has been shown to be pervasive both in nature and in engineering systems like the World Wide Web. Work of Jon Kleinberg has

  4. Fragile X syndrome: Neural network models of sequencing and memory

    NARCIS (Netherlands)

    Johnson, M.C.

    2008-01-01

    A comparative framework of memory processes in males with fragile X syndrome (FXS) and typically developing (TYP) mental age-match children is presented. Results indicate a divergence in sequencing skills, such that males with FXS recall sequences similarly to TYP children around five and a half

  5. A Working Memory Model Applied to Mathematical Word Problem Solving

    Science.gov (United States)

    Alamolhodaei, Hassan

    2009-01-01

    The main objective of this study is (a) to explore the relationship among cognitive style (field dependence/independence), working memory, and mathematics anxiety and (b) to examine their effects on students' mathematics problem solving. A sample of 161 school girls (13-14 years old) were tested on (1) the Witkin's cognitive style (Group Embedded…

  6. A nonlinear long memory model for US unemployment

    NARCIS (Netherlands)

    D.J.C. van Dijk (Dick); Ph.H.B.F. Franses (Philip Hans); R. Paap (Richard)

    2000-01-01

    textabstractTwo important empirical features of monthly US unemployment are that shocks to the series seem rather persistent and that unemployment seems to rise faster in recessions than that it falls during expansions. To jointly capture these features of long memory and nonlinearity, respectively,

  7. Modeling Learning and Memory Using Verbal Learning Tests: Results From ACTIVE

    Science.gov (United States)

    Gross, Alden L.

    2013-01-01

    Objective. To investigate the influence of memory training on initial recall and learning. Method. 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. Results. 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. Discussion. 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. PMID:22929389

  8. 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 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.

  9. 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.

  10. Computation of the memory functions in the generalized Langevin models for collective dynamics of macromolecules.

    Science.gov (United States)

    Chen, Minxin; Li, Xiantao; Liu, Chun

    2014-08-14

    We present a numerical method to approximate the memory functions in the generalized Langevin models for the collective dynamics of macromolecules. We first derive the exact expressions of the memory functions, obtained from projection to subspaces that correspond to the selection of coarse-grain variables. In particular, the memory functions are expressed in the forms of matrix functions, which will then be approximated by Krylov-subspace methods. It will also be demonstrated that the random noise can be approximated under the same framework, and the second fluctuation-dissipation theorem is automatically satisfied. The accuracy of the method is examined through several numerical examples.

  11. 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.

  12. Dissociating models of visual working memory by reaction-time distribution analysis.

    Science.gov (United States)

    Park, Hyung-Bum; Zhang, Weiwei; Hyun, Joo-Seok

    2017-02-01

    There have been heated debates on whether visual working memory (VWM) represents information in discrete-slots or a reservoir of flexible-resources. However, one key aspect of the models has gone unnoticed, the speed of processing when stored information in memory is assessed for accuracy. The present study evaluated contrasting predictions from the two models regarding the change detection decision times spent on the assessment of stored information by estimating the ex-Gaussian parameters from change detection RT distributions across different set sizes (2, 4, 6, or 8). The estimation showed that the Gaussian components μ and σ became larger as the set size increased from 2 to 4, but stayed constant as it reached 6 and 8, with an exponential component τ increasing at above-capacity set sizes. Moreover, we found that an individual's capacity limit correlates with the memory set size where the Gaussian μ reaches a plateau. These results indicate that the decision time for assessing in-memory items is constant regardless of memory set sizes whereas the time for the remaining not-in-memory items increases as the set size exceeds VWM storage capacity. The findings suggest that the discrete-slot model explains the observed RT distributions better than the flexible-resource model. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Using model-based functional MRI to locate working memory updates and declarative memory retrievals in the fronto-parietal network.

    Science.gov (United States)

    Borst, Jelmer P; Anderson, John R

    2013-01-29

    In this study, we used model-based functional MRI (fMRI) to locate two functions of the fronto-parietal network: declarative memory retrievals and updating of working memory. Because regions in the fronto-parietal network are by definition coherently active, locating functions within this network is difficult. To overcome this problem, we applied model-based fMRI, an analysis method that uses predictions of a computational model to inform the analysis. We applied model-based fMRI to five previously published datasets with associated computational cognitive models, and subsequently integrated the results in a meta-analysis. The meta-analysis showed that declarative memory retrievals correlated with activity in the inferior frontal gyrus and the anterior cingulate, whereas updating of working memory corresponded to activation in the inferior parietal lobule, as well as to activation around the inferior frontal gyrus and the anterior cingulate.

  14. Memory conformity affects inaccurate memories more than accurate memories.

    Science.gov (United States)

    Wright, Daniel B; Villalba, Daniella K

    2012-01-01

    After controlling for initial confidence, inaccurate memories were shown to be more easily distorted than accurate memories. In two experiments groups of participants viewed 50 stimuli and were then presented with these stimuli plus 50 fillers. During this test phase participants reported their confidence that each stimulus was originally shown. This was followed by computer-generated responses from a bogus participant. After being exposed to this response participants again rated the confidence of their memory. The computer-generated responses systematically distorted participants' responses. Memory distortion depended on initial memory confidence, with uncertain memories being more malleable than confident memories. This effect was moderated by whether the participant's memory was initially accurate or inaccurate. Inaccurate memories were more malleable than accurate memories. The data were consistent with a model describing two types of memory (i.e., recollective and non-recollective memories), which differ in how susceptible these memories are to memory distortion.

  15. Cognitive theories as reinforcement history surrogates: the case of likelihood ratio models of human recognition memory.

    Science.gov (United States)

    Wixted, John T; Gaitan, Santino C

    2002-11-01

    B. F. Skinner (1977) once argued that cognitive theories are essentially surrogates for the organism's (usually unknown) reinforcement history. In this article, we argue that this notion applies rather directly to a class of likelihood ratio models of human recognition memory. The point is not that such models are fundamentally flawed or that they are not useful and should be abandoned. Instead, the point is that the role of reinforcement history in shaping memory decisions could help to explain what otherwise must be explained by assuming that subjects are inexplicably endowed with the relevant distributional information and computational abilities. To the degree that a role for an organism's reinforcement history is appreciated, the importance of animal memory research in understanding human memory comes into clearer focus. As Skinner was also fond of pointing out, it is only in the animal laboratory that an organism's history of reinforcement can be precisely controlled and its effects on behavior clearly understood.

  16. 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…

  17. 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.

  18. Emergency response to disaster-struck scale-free network with redundant systems

    Science.gov (United States)

    Ouyang, Min; Yu, Ming-Hui; Huang, Xiang-Zhao; Luan, En-Jie

    2008-07-01

    Disasters cause tremendous damage every year. In this paper, we have specifically studied emergency response to disaster-struck scale-free networks when some nodes in the network have redundant systems. If one node collapses, its redundant system will substitute it to work for a period of time. In the first part, according to the network structure, several redundant strategies have been formulated, and then our studies focused on their effectiveness by means of simulation. Results show that the strategy based on total degrees is the most effective one. However, many nodes still collapse in the end if redundant systems do not have sufficient capability, so emergency responses are necessary. Several emergent strategies controlling the distribution of external resources have been proposed in the second part. The effectiveness of those emergent strategies are then studied from three aspects, such as the effect of strategies on spreading processes, minimum sufficient quantities of external resources and determination of the most appropriate emergent strategy. In addition, the effects of redundant intensity on these aspects have been discussed as well.

  19. Global scale- free behaviour in compressive fluctuations in the fast solar wind, and pseudo- dynamic alignment

    Science.gov (United States)

    Hnat, B.; Chapman, S. C.; Gogoberidze, G.; Wicks, R. T.

    2011-12-01

    We present the first scale-by-scale quantitative comparison of the higher order statistics of magnetic field magnitude and component temporal fluctuations in the fast quiet solar wind. The magnetic field magnitude fluctuations show a single global intermittent non-Gaussian scale free behaviour from minutes to over 5 hours. This coexists with the signature in the field components of an inertial range of magnetohydrodynamic (MHD) turbulence up to ~ 30 minutes and a ~ 1/f range of coronal origin on longer timescales. This is found both in the ecliptic with ACE and in ULLYSES polar passes. This suggests a single stochastic process for magnetic field magnitude fluctuations operating across the full range of MHD timescales supported by the solar wind. Fluctuations in velocity and magnetic field show the strongest 'dynamic' alignment on scales in the ~ 1/f range. We wil discuss how uncertainties in velocity and magnetic field measurements propagate through 'compound' measures of the turbulence properties of the flow in this context. Observational evidence of incompressible MHD turbulence in the solar wind must thus be understood in the context of this global scaling of the compressive 'texture' of the solar wind.

  20. A Computational Model of Semantic Memory Impairment: Modality- Specificity and Emergent Category-Specificity

    Science.gov (United States)

    1991-09-01

    living things only when know.ledge is probed verbally . A /A 1 ii t A computational model of semantic memory impairment: Modality-specificity and...can account for a recent observation of impaired knowledge of living thngs only when knowledge is probed verbally . 3 How is semantic memory organized...just one modality (e.g. visual or auditory agnosia) or impaired manipulation of objects with specific uses, despite intact recognition of them ( apraxia

  1. A model of late long-term potentiation simulates aspects of memory maintenance.

    Directory of Open Access Journals (Sweden)

    Paul Smolen

    Full Text Available Late long-term potentiation (L-LTP denotes long-lasting strengthening of synapses between neurons. L-LTP appears essential for the formation of long-term memory, with memories at least partly encoded by patterns of strengthened synapses. How memories are preserved for months or years, despite molecular turnover, is not well understood. Ongoing recurrent neuronal activity, during memory recall or during sleep, has been hypothesized to preferentially potentiate strong synapses, preserving memories. This hypothesis has not been evaluated in the context of a mathematical model representing ongoing activity and biochemical pathways important for L-LTP. In this study, ongoing activity was incorporated into two such models - a reduced model that represents some of the essential biochemical processes, and a more detailed published model. The reduced model represents synaptic tagging and gene induction simply and intuitively, and the detailed model adds activation of essential kinases by Ca(2+. Ongoing activity was modeled as continual brief elevations of Ca(2+. In each model, two stable states of synaptic strength/weight resulted. Positive feedback between synaptic weight and the amplitude of ongoing Ca(2+ transients underlies this bistability. A tetanic or theta-burst stimulus switches a model synapse from a low basal weight to a high weight that is stabilized by ongoing activity. Bistability was robust to parameter variations in both models. Simulations illustrated that prolonged periods of decreased activity reset synaptic strengths to low values, suggesting a plausible forgetting mechanism. However, episodic activity with shorter inactive intervals maintained strong synapses. Both models support experimental predictions. Tests of these predictions are expected to further understanding of how neuronal activity is coupled to maintenance of synaptic strength. Further investigations that examine the dynamics of activity and synaptic maintenance can be

  2. 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.

  3. Memory effects on epidemic evolution: The susceptible-infected-recovered epidemic model

    Science.gov (United States)

    Saeedian, M.; Khalighi, M.; Azimi-Tafreshi, N.; Jafari, G. R.; Ausloos, M.

    2017-02-01

    Memory has a great impact on the evolution of every process related to human societies. Among them, the evolution of an epidemic is directly related to the individuals' experiences. Indeed, any real epidemic process is clearly sustained by a non-Markovian dynamics: memory effects play an essential role in the spreading of diseases. Including memory effects in the susceptible-infected-recovered (SIR) epidemic model seems very appropriate for such an investigation. Thus, the memory prone SIR model dynamics is investigated using fractional derivatives. The decay of long-range memory, taken as a power-law function, is directly controlled by the order of the fractional derivatives in the corresponding nonlinear fractional differential evolution equations. Here we assume "fully mixed" approximation and show that the epidemic threshold is shifted to higher values than those for the memoryless system, depending on this memory "length" decay exponent. We also consider the SIR model on structured networks and study the effect of topology on threshold points in a non-Markovian dynamics. Furthermore, the lack of access to the precise information about the initial conditions or the past events plays a very relevant role in the correct estimation or prediction of the epidemic evolution. Such a "constraint" is analyzed and discussed.

  4. Making working memory work: a computational model of learning in the prefrontal cortex and basal ganglia.

    Science.gov (United States)

    O'Reilly, Randall C; Frank, Michael J

    2006-02-01

    The prefrontal cortex has long been thought to subserve both working memory (the holding of information online for processing) and executive functions (deciding how to manipulate working memory and perform processing). Although many computational models of working memory have been developed, the mechanistic basis of executive function remains elusive, often amounting to a homunculus. This article presents an attempt to deconstruct this homunculus through powerful learning mechanisms that allow a computational model of the prefrontal cortex to control both itself and other brain areas in a strategic, task-appropriate manner. These learning mechanisms are based on subcortical structures in the midbrain, basal ganglia, and amygdala, which together form an actor-critic architecture. The critic system learns which prefrontal representations are task relevant and trains the actor, which in turn provides a dynamic gating mechanism for controlling working memory updating. Computationally, the learning mechanism is designed to simultaneously solve the temporal and structural credit assignment problems. The model's performance compares favorably with standard backpropagation-based temporal learning mechanisms on the challenging 1-2-AX working memory task and other benchmark working memory tasks.

  5. 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.

  6. 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.

  7. 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.

  8. A low memory cost model based reconstruction algorithm exploiting translational symmetry for photoacustic microscopy.

    Science.gov (United States)

    Aguirre, Juan; Giannoula, Alexia; Minagawa, Taisuke; Funk, Lutz; Turon, Pau; Durduran, Turgut

    2013-01-01

    A model based reconstruction algorithm that exploits translational symmetries for photoacoustic microscopy to drastically reduce the memory cost is presented. The memory size needed to store the model matrix is independent of the number of acquisitions at different positions. This helps us to overcome one of the main limitations of previous algorithms. Furthermore, using the algebraic reconstruction technique and building the model matrix "on the fly", we have obtained fast reconstructions of simulated and experimental data on both two- and three-dimensional grids using a traditional dark field photoacoustic microscope and a standard personal computer.

  9. Extracting climate memory using Fractional Integrated Statistical Model: A new perspective on climate prediction

    Science.gov (United States)

    Yuan, Naiming; Fu, Zuntao; Liu, Shida

    2014-01-01

    Long term memory (LTM) in climate variability is studied by means of fractional integral techniques. By using a recently developed model, Fractional Integral Statistical Model (FISM), we in this report proposed a new method, with which one can estimate the long-lasting influences of historical climate states on the present time quantitatively, and further extract the influence as climate memory signals. To show the usability of this method, two examples, the Northern Hemisphere monthly Temperature Anomalies (NHTA) and the Pacific Decadal Oscillation index (PDO), are analyzed in this study. We find the climate memory signals indeed can be extracted and the whole variations can be further decomposed into two parts: the cumulative climate memory (CCM) and the weather-scale excitation (WSE). The stronger LTM is, the larger proportion the climate memory signals will account for in the whole variations. With the climate memory signals extracted, one can at least determine on what basis the considered time series will continue to change. Therefore, this report provides a new perspective on climate prediction. PMID:25300777

  10. Extraction and restoration of hippocampal spatial memories with nonlinear dynamical modeling

    Directory of Open Access Journals (Sweden)

    Dong eSong

    2014-05-01

    Full Text Available To build a cognitive prosthesis that can replace the memory function of the hippocampus, it is essential to model the input-output function of the damaged hippocampal region, so the prosthetic device can stimulate the downstream hippocampal region, e.g., CA1, with the output signal, e.g., CA1 spike trains, predicted from the ongoing input signal, e.g., CA3 spike trains, and the identified input-output function, e.g., CA3-CA1 model. In order for the downstream region to form appropriate long-term memories based on the restored output signal, furthermore, the output signal should contain sufficient information about the memories that the animal has formed. In this study, we verify this premise by applying regression and classification modelings of the spatio-temporal patterns of spike trains to the hippocampal CA3 and CA1 data recorded from rats performing a memory-dependent delayed nonmatch-to-sample (DNMS task. The regression model is essentially the multiple-input, multiple-output (MIMO nonlinear dynamical model of spike train transformation. It predicts the output spike trains based on the input spike trains and thus restores the output signal. In addition, the classification model interprets the signal by relating the spatio-temporal patterns to the memory events. We have found that: (1 both hippocampal CA3 and CA1 spike trains contain sufficient information for predicting the locations of the sample responses (i.e., left and right memories during the DNMS task; and more importantly (2 the CA1 spike trains predicted from the CA3 spike trains by the MIMO model also are sufficient for predicting the locations on a single-trial basis. These results show quantitatively that, with a moderate number of unitary recordings from the hippocampus, the MIMO nonlinear dynamical model is able to extract and restore spatial memory information for the formation of long-term memories and thus can serve as the computational basis of the hippocampal memory

  11. 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.

  12. 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.

  13. Distinct Effects of Perceptual Quality on Auditory Word Recognition, Memory Formation and Recall in a Neural Model of Sequential Memory

    Science.gov (United States)

    Miller, Paul; Wingfield, Arthur

    2010-01-01

    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. PMID:20631822

  14. 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. PMID:27092090

  15. 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.

  16. 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…

  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. 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...

  19. 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.

  20. 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…

  1. Sparse generalized volterra model of human hippocampal spike train transformation for memory prostheses.

    Science.gov (United States)

    Song, Dong; Robinson, Brian S; Hampson, Robert E; Marmarelis, Vasilis Z; Deadwyler, Sam A; Berger, Theodore W

    2015-01-01

    In order to build hippocampal prostheses for restoring memory functions, we build multi-input, multi-output (MIMO) nonlinear dynamical models of the human hippocampus. Spike trains are recorded from the hippocampal CA3 and CA1 regions of epileptic patients performing a memory-dependent delayed match-to-sample task. Using CA3 and CA1 spike trains as inputs and outputs respectively, second-order sparse generalized Laguerre-Volterra models are estimated with group lasso and local coordinate descent methods to capture the nonlinear dynamics underlying the spike train transformations. These models can accurately predict the CA1 spike trains based on the ongoing CA3 spike trains and thus will serve as the computational basis of the hippocampal memory prosthesis.

  2. 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

  3. 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.

  4. 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.

  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. PMID:24023690

  6. 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.

  7. 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.

  8. How is working memory content consciously experienced? The 'conscious copy' model of WM introspection.

    Science.gov (United States)

    Jacobs, Christianne; Silvanto, Juha

    2015-08-01

    We address the issue of how visual information stored in working memory (WM) is introspected. In other words, how do we become aware of WM content in order to consciously examine or manipulate it? Influential models of WM have suggested that WM representations are either conscious by definition, or directly accessible for conscious inspection. We propose that WM introspection does not operate on the actual memory trace but rather requires a new representation to be created for the conscious domain. This conscious representation exists in addition and in parallel to the actual memory representation. The existence of such a separate representation is revealed by and reflected in the qualitatively different functional characteristics between the actual memory trace and its conscious experience, and their distinct interactions within external visual input. Our model differs from state-based models in that WM introspection does not involve a change in the state of WM content, but rather involves the creation of a new, second representation existing in parallel to the original memory trace. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  9. 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.

  10. Thermo-mechanical modeling of semi-crystalline thermoplastic shape memory polymer under large strain

    Science.gov (United States)

    Bouaziz, R.; Roger, F.; Prashantha, K.

    2017-05-01

    In this work, a constitutive mechanical model is proposed to describe the thermo-mechanical cycle of a semi-crystalline shape memory polyurethane which is able to recover its initial shape after applying more than 100% strain during a shape memory cycle. To explore this performance, experimental tests were conducted to determine the cyclic thermo-mechanical behavior of a polymer submitted to five shape memory cycles. Indeed, uniaxial tensile tests at small strain rates were performed at 60 °C in order to analyze its hyper-elastic response. At the end of the previous tensile loading, relaxation tests were carried out to determine the viscoelastic behavior during the shape memory cycle. The shape memory effect was investigated by means of free and constrained recovery experiments. These experimental results are used to identify the parameters of the constitutive model by means of curve-fitting algorithm employing least-squares optimization approach. The proposed model is then implemented in the finite element software Comsol Multiphysics© and predicts quite well an in-plane strained cylindrical ring.

  11. 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

    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...... 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...

  12. 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.

  13. A link between neuroscience and informatics: large-scale modeling of memory processes.

    Science.gov (United States)

    Horwitz, Barry; Smith, Jason F

    2008-04-01

    Utilizing advances in functional neuroimaging and computational neural modeling, neuroscientists have increasingly sought to investigate how distributed networks, composed of functionally defined subregions, combine to produce cognition. Large-scale, biologically realistic neural models, which integrate data from cellular, regional, whole brain, and behavioral sources, delineate specific hypotheses about how these interacting neural populations might carry out high-level cognitive tasks. In this review, we discuss neuroimaging, neural modeling, and the utility of large-scale biologically realistic models using modeling of short-term memory as an example. We present a sketch of the data regarding the neural basis of short-term memory from non-human electrophysiological, computational and neuroimaging perspectives, highlighting the multiple interacting brain regions believed to be involved. Through a review of several efforts, including our own, to combine neural modeling and neuroimaging data, we argue that large scale neural models provide specific advantages in understanding the distributed networks underlying cognition and behavior.

  14. 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).

  15. The Enhanced Rise and Delayed Fall of Memory in a Model of Synaptic Integration: Extension to Discrete State Synapses.

    Science.gov (United States)

    Elliott, Terry

    2016-09-01

    Integrate-and-express models of synaptic plasticity propose that synapses may act as low-pass filters, integrating synaptic plasticity induction signals in order to discern trends before expressing synaptic plasticity. We have previously shown that synaptic filtering strongly controls destabilizing fluctuations in developmental models. When applied to palimpsest memory systems that learn new memories by forgetting old ones, we have also shown that with binary-strength synapses, integrative synapses lead to an initial memory signal rise before its fall back to equilibrium. Such an initial rise is in dramatic contrast to nonintegrative synapses, in which the memory signal falls monotonically. We now extend our earlier analysis of palimpsest memories with synaptic filters to consider the more general case of discrete state, multilevel synapses. We derive exact results for the memory signal dynamics and then consider various simplifying approximations. We show that multilevel synapses enhance the initial rise in the memory signal and then delay its subsequent fall by inducing a plateau-like region in the memory signal. Such dynamics significantly increase memory lifetimes, defined by a signal-to-noise ratio (SNR). We derive expressions for optimal choices of synaptic parameters (filter size, number of strength states, number of synapses) that maximize SNR memory lifetimes. However, we find that with memory lifetimes defined via mean-first-passage times, such optimality conditions do not exist, suggesting that optimality may be an artifact of SNRs.

  16. 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.

  17. 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.

  18. The Implications of the Working Memory Model for the Evolution of Modern Cognition

    Directory of Open Access Journals (Sweden)

    Thomas Wynn

    2011-01-01

    Full Text Available What distinguishes the cognition of biologically modern humans from that of more archaic populations such as Neandertals? The norm in paleoanthropology has been to emphasize the role of language and symbolism. But the modern mind is more than just an archaic mind enhanced by symbol use. It also possesses an important problem solving and planning component. In cognitive neuroscience these advanced planning abilities have been extensively investigated through a formal model known as working memory. The working memory model is now well-enough established to provide a powerful lens through which paleoanthropologists can view the fossil and archaeological records. The challenge is methodological. The following essay reviews the controversial hypothesis that a recent enhancement of working memory capacity was the final piece in the evolution of modern cognition.

  19. Computational Modeling of the Negative Priming Effect Based on Inhibition Patterns and Working Memory

    Directory of Open Access Journals (Sweden)

    Dongil eChung

    2013-11-01

    Full Text Available Negative priming (NP, slowing down of the response for target stimuli that have been previously exposed, but ignored, has been reported in multiple psychological paradigms including the Stroop task. Although NP likely results from the interplay of selective attention, episodic memory retrieval, working memory, and inhibition mechanisms, a comprehensive theoretical account of NP is currently unavailable. This lacuna may result from the complexity of stimuli combinations in NP. Thus, we aimed to investigate the presence of different degrees of the NP effect according to prime-probe combinations within a classic Stroop task. We recorded reaction times (RTs from 66 healthy participants during Stroop task performance and examined three different NP subtypes, defined according to the type of the Stroop probe in prime-probe pairs. Our findings show significant RT differences among NP subtypes that are putatively due to the presence of differential disinhibition, i.e., release from inhibition. Among the several potential origins for differential subtypes of NP, we investigated the involvement of selective attention and/or working memory using a parallel distributed processing (PDP model (employing selective attention only and a modified PDP model with working memory (PDP-WM, employing both selective attention and working memory. Our findings demonstrate that, unlike the conventional PDP model, the PDP-WM successfully simulates different levels of NP effects that closely follow the behavioral data. This outcome suggests that working memory engages in the re-accumulation of the evidence for target response and induces differential NP effects. Our computational model complements earlier efforts and may pave the road to further insights into an integrated theoretical account of complex NP effects.

  20. Synaptic augmentation in a cortical circuit model reproduces serial dependence in visual working memory.

    Science.gov (United States)

    Bliss, Daniel P; D'Esposito, Mark

    2017-01-01

    Recent work has established that visual working memory is subject to serial dependence: current information in memory blends with that from the recent past as a function of their similarity. This tuned temporal smoothing likely promotes the stability of memory in the face of noise and occlusion. Serial dependence accumulates over several seconds in memory and deteriorates with increased separation between trials. While this phenomenon has been extensively characterized in behavior, its neural mechanism is unknown. In the present study, we investigate the circuit-level origins of serial dependence in a biophysical model of cortex. We explore two distinct kinds of mechanisms: stable persistent activity during the memory delay period and dynamic "activity-silent" synaptic plasticity. We find that networks endowed with both strong reverberation to support persistent activity and dynamic synapses can closely reproduce behavioral serial dependence. Specifically, elevated activity drives synaptic augmentation, which biases activity on the subsequent trial, giving rise to a spatiotemporally tuned shift in the population response. Our hybrid neural model is a theoretical advance beyond abstract mathematical characterizations, offers testable hypotheses for physiological research, and demonstrates the power of biological insights to provide a quantitative explanation of human behavior.

  1. 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.

  2. 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

    2017-03-01

    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. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  3. 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

  4. A note on Cattaneo-Hristov model with non-singular fading memory

    Directory of Open Access Journals (Sweden)

    Alkahtani Badr Saad T.

    2017-01-01

    Full Text Available Using the new trend of fractional differentiation based on the concept of exponential decay law, the Cattaneo model of diffusion in elastic medium was extended by Hristov. This model displays more physical properties than the first version. However no solution of this new equation is suggested in the literature. Therefore, this paper is devoted to the analysis of numerical solution of the Cattaneo-Hristov model with non-singular fading memory.

  5. A dual-subsystem model of the brain's default network: self-referential processing, memory retrieval processes, and autobiographical memory retrieval.

    Science.gov (United States)

    Kim, Hongkeun

    2012-07-16

    Most internally oriented mental activities are known to strongly activate the default network, which includes remembering the past, future thinking and social cognition, and are heavily self-referential, and demanding of memory retrieval processes. Based on these observations and building on related findings from the literature, the present article proposed a simple, dual-subsystem model of the default network. The ability of the model to estimate brain activity during autobiographical memory (AM) retrieval and related reference conditions was then tested by performing a quantitative meta-analysis of relevant literature. The model divided the default network into two subsystems. The first, called the 'cortical midline subsystem (CMS)', was comprised of the anteromedial prefrontal cortex and posterior cingulate cortex, and primarily mediates self-referential processing. The other, termed the 'parieto-temporal subsystem (PTS)', included the inferior parietal lobule, medial temporal lobe and lateral temporal cortex, and mainly supports memory retrieval processes. The meta-analysis of AM retrieval contrasts yielded a double dissociation that was consistent with this model. First, CMS regions associated more with an AM>laboratory-based memory (LM) contrast than with an AM>rest contrast, confirming that these regions play more critical roles in self-referential processing than memory retrieval processes. Second, all three PTS regions showed a greater association with an AM>rest contrast than with an AM>LM contrast, confirming that their role in memory retrieval processes is greater than in self-referential processing. Although the present model is limited in scope, both in terms of anatomical and functional specifications, it integrates diverse processes such as self-referential processing, episodic and semantic memory and subsystem interface, and provides useful heuristics that can guide further research on fractionation of the default network. Copyright © 2012

  6. A memory-based model for blood viscosity

    Science.gov (United States)

    Ionescu, Clara M.

    2017-04-01

    This paper presents a comparison between existing models for non-Newtonian fluid viscosity as a function of shear rate variations. A novel model is introduced whose parameters are linked to physiological phenomena in the blood. The end use of such models is to predict changes in viscosity to adapt the speed of a nanorobot device for targeted drug delivery purposes. Simulation results show the agreement between the proposed model and available models from literature. A laboratory scale validation of the proposed model for a fluid mimicking non-Newtonian properties has been performed. Conceptual perspectives are also given in this work.

  7. 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

  8. A New Extension Model: The Memorial Middle School Agricultural Extension and Education Center

    Science.gov (United States)

    Skelton, Peter; Seevers, Brenda

    2010-01-01

    The Memorial Middle School Agricultural Extension and Education Center is a new model for Extension. The center applies the Cooperative Extension Service System philosophy and mission to developing public education-based programs. Programming primarily serves middle school students and teachers through agricultural and natural resource science…

  9. 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…

  10. Spacing and repetition effects in human memory: application of the SAM model

    National Research Council Canada - National Science Library

    Raaijmakers, Jeroen G.W

    2003-01-01

    ... the probability of storing the trace in long-term memory (e.g., models of the all-or-none type, Bower, 1961 ), or increase the strength of the trace. A related issue concerns the effects of spacing of individual repetitions. A well-known phenomenon that has been observed in many learning paradigms is the distributed practice or spacing effect . As ...

  11. 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…

  12. 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.

  13. Extending distributed shared memory for the cell broadband engine to a channel model

    DEFF Research Database (Denmark)

    Skovhede, Kenneth; Larsen, Morten Nørgaard; Vinter, Brian

    2010-01-01

    at the price of a quite complex programming model. In this paper we present an easy-to-use, CSP-like, communication method, which enables transfers of shared memory objects. The channel based communication method can significantly reduce the complexity of massively parallel programs. By implementing a few...

  14. 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…

  15. 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.

  16. 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…

  17. 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

  18. A stochastic model of chromatin modification: cell population coding of winter memory in plants.

    Science.gov (United States)

    Satake, Akiko; Iwasa, Yoh

    2012-06-07

    Biological memory, a sustained cellular response to a transient stimulus, has been found in many natural systems. The best example in plants is the winter memory by which plants can flower in favorable conditions in spring. For this winter memory, epigenetic regulation of FLOWERING LOCUS C (FLC), which acts as a floral repressor, plays a key role. Exposure to prolonged periods of cold results in the gradual suppression of FLC, which allows plants to measure the length of cold and to flower only after a sufficiently long winter. Although many genes involved in histone modifications have been isolated, molecular mechanisms of winter memory are not well understood. Here, we develop a model for chromatin modification, in which the dynamics of a single nucleosome are aggregated to on/off behavior of FLC expression at the cellular level and further integrated to a change of FLC expression at the whole-plant level. We propose cell-population coding of winter memory: each cell is described as a bistable system that shows heterogeneous timing of the transition from on to off in FLC expression under cold and measures the length of cold as the proportion of cells in the off state. This mechanism well explains robust FLC regulation and stable inheritance of winter memory after cell division in response to noisy signals. Winter memory lasts longer if deposition of the repressive histone mark occurs faster. A difference in deposition speed would discriminate between stable maintenance of FLC repression in annuals and transient expression in perennials. Copyright © 2012 Elsevier Ltd. All rights reserved.

  19. 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.

  20. Memory, modelling and Marr: a commentary on Marr (1971) 'Simple memory: a theory of archicortex'.

    Science.gov (United States)

    Willshaw, D J; Dayan, P; Morris, R G M

    2015-04-19

    David Marr's theory of the archicortex, a brain structure now more commonly known as the hippocampus and hippocampal formation, is an epochal contribution to theoretical neuroscience. Addressing the problem of how information about 10 000 events could be stored in the archicortex during the day so that they can be retrieved using partial information and then transferred to the neocortex overnight, the paper presages a whole wealth of later empirical and theoretical work, proving impressively prescient. Despite this impending success, Marr later apparently grew dissatisfied with this style of modelling, but he went on to make seminal suggestions that continue to resonate loudly throughout the field of theoretical neuroscience. We describe Marr's theory of the archicortex and his theory of theories, setting them into their original and a contemporary context, and assessing their impact. This commentary was written to celebrate the 350th anniversary of the journal Philosophical Transactions of the Royal Society.

  1. Dynamic Hedging Based on Fractional Order Stochastic Model with Memory Effect

    Directory of Open Access Journals (Sweden)

    Qing Li

    2016-01-01

    Full Text Available Many researchers have established various hedge models to get the optimal hedge ratio. However, most of the hedge models only discuss the discrete-time processes. In this paper, we construct the minimum variance model for the estimation of the optimal hedge ratio based on the stochastic differential equation. At the same time, also by considering memory effects, we establish the continuous-time hedge model with memory based on the fractional order stochastic differential equation driven by a fractional Brownian motion to estimate the optimal dynamic hedge ratio. In addition, we carry on the empirical analysis to examine the effectiveness of our proposed hedge models from both in-sample test and out-of-sample test.

  2. Critical percolation phase and thermal Berezinskii-Kosterlitz-Thouless transition in a scale-free network with short-range and long-range random bonds.

    Science.gov (United States)

    Berker, A Nihat; Hinczewski, Michael; Netz, Roland R

    2009-10-01

    Percolation in a scale-free hierarchical network is solved exactly by renormalization-group theory in terms of the different probabilities of short-range and long-range bonds. A phase of critical percolation, with algebraic [Berezinskii-Kosterlitz-Thouless (BKT)] geometric order, occurs in the phase diagram in addition to the ordinary (compact) percolating phase and the nonpercolating phase. It is found that no connection exists between, on the one hand, the onset of this geometric BKT behavior and, on the other hand, the onsets of the highly clustered small-world character of the network and of the thermal BKT transition of the Ising model on this network. Nevertheless, both geometric and thermal BKT behaviors have inverted characters, occurring where disorder is expected, namely, at low bond probability and high temperature, respectively. This may be a general property of long-range networks.

  3. 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.

  4. Vascular system modeling in parallel environment - distributed and shared memory approaches.

    Science.gov (United States)

    Jurczuk, Krzysztof; Kretowski, Marek; Bezy-Wendling, Johanne

    2011-07-01

    This paper presents two approaches in parallel modeling of vascular system development in internal organs. In the first approach, new parts of tissue are distributed among processors and each processor is responsible for perfusing its assigned parts of tissue to all vascular trees. Communication between processors is accomplished by passing messages, and therefore, this algorithm is perfectly suited for distributed memory architectures. The second approach is designed for shared memory machines. It parallelizes the perfusion process during which individual processing units perform calculations concerning different vascular trees. The experimental results, performed on a computing cluster and multicore machines, show that both algorithms provide a significant speedup.

  5. 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...

  6. 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.

  7. Development of prospective memory: tasks based on the prefrontal-lobe model.

    Science.gov (United States)

    Ward, Heather; Shum, David; McKinlay, Lynne; Baker-Tweney, Simone; Wallace, Geoff

    2005-12-01

    This study investigated the development of prospective memory using tasks based on the prefrontal-lobe model. Three groups each of 30 children, adolescents, and young adults were compared on prospective-memory performance using ongoing tasks with two levels of cognitive demand (low and high), and two levels of importance (unstressed and stressed) of remembering prospective cues. The Self-Ordered Pointing Task (SOPT), Stroop Color Word Interference Test, and Tower of London were also used to assess relationships between prospective memory and prefrontal-lobe functions. The children remembered fewer prospective cues than either the adolescents or adults, but the adolescents and adults remembered equally well. This trend increased significantly as the cognitive demand of the ongoing tasks increased. However, stressing or not stressing the importance of remembering made no difference to prospective-memory performance. Performance on the SOPT and Stroop Colour Word Interference predicted performance on the high- but not on the low-demand condition. These findings implicate the maturation of the brain's prefrontal region in the development of prospective memory.

  8. Onset of hippocampus-dependent memory impairments in 5XFAD transgenic mouse model of Alzheimer's disease.

    Science.gov (United States)

    Girard, Stéphane D; Jacquet, Marlyse; Baranger, Kévin; Migliorati, Martine; Escoffier, Guy; Bernard, Anne; Khrestchatisky, Michel; Féron, François; Rivera, Santiago; Roman, François S; Marchetti, Evelyne

    2014-07-01

    The 5XFAD mice are an early-onset transgenic model of Alzheimer's disease (AD) in which amyloid plaques are first observed between two and four months of age in the cortical layer five and in the subiculum of the hippocampal formation. Although cognitive alterations have been described in these mice, there are no studies that focused on the onset of hippocampus-dependent memory deficits, which are a hallmark of the prodromal stage of AD. To identify when the first learning and memory impairments appear, 5XFAD mice of two, four, and six months of age were compared with their respective wild-type littermates using the olfactory tubing maze, which is a very sensitive hippocampal-dependent task. Deficits in learning and memory started at four months with a substantial increase at six months of age while no olfactory impairments were observed. The volumetric study using magnetic resonance imaging of the whole brain and specific areas (olfactory bulb, striatum, and hippocampus) did not reveal neuro-anatomical difference. Slight memory deficits appeared at 4 months of age in correlation with an increased astrogliosis and amyloid plaque formation. This early impairment in learning and memory related to the hippocampal dysfunction is particularly suited to assess preclinical therapeutic strategies aiming to delay or suppress the onset of AD. © 2014 Wiley Periodicals, Inc.

  9. Modelling 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) randomised controlled trial in order to test (1) the degree to which SDM declines with advancing age, (2) the predictors of these age-related declines and (3) 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, were 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.

  10. 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

  11. SIRT1 Regulates Cognitive Performance and Ability of Learning and Memory in Diabetic and Nondiabetic Models

    Directory of Open Access Journals (Sweden)

    Yue Cao

    2017-01-01

    Full Text Available Type 2 diabetes mellitus is a complex age-related metabolic disease. Cognitive dysfunction and learning and memory deficits are main characteristics of age-related metabolic diseases in the central nervous system. The underlying mechanisms contributing to cognitive decline are complex, especially cognitive dysfunction associated with type 2 diabetes mellitus. SIRT1, as one of the modulators in insulin resistance, is indispensable for learning and memory. In the present study, deacetylation, oxidative stress, mitochondrial dysfunction, inflammation, microRNA, and tau phosphorylation are considered in the context of mechanism and significance of SIRT1 in learning and memory in diabetic and nondiabetic murine models. In addition, future research directions in this field are discussed, including therapeutic potential of its activator, resveratrol, and application of other compounds in cognitive improvement. Our findings suggest that SIRT1 might be a potential therapeutic target for the treatment of cognitive impairment induced by type 2 diabetes mellitus.

  12. A Four–Component Model of Age–Related Memory Change

    Science.gov (United States)

    Healey, M. Karl; Kahana, Michael J.

    2015-01-01

    We develop a novel, computationally explicit, theory of age–related memory change within the framework of the context maintenance and retrieval (CMR2) model of memory search. We introduce a set of benchmark findings from the free recall and recognition tasks that includes aspects of memory performance that show both age-related stability and decline. We test aging theories by lesioning the corresponding mechanisms in a model fit to younger adult free recall data. When effects are considered in isolation, many theories provide an adequate account, but when all effects are considered simultaneously, the existing theories fail. We develop a novel theory by fitting the full model (i.e., allowing all parameters to vary) to individual participants and comparing the distributions of parameter values for older and younger adults. This theory implicates four components: 1) the ability to sustain attention across an encoding episode, 2) the ability to retrieve contextual representations for use as retrieval cues, 3) the ability to monitor retrievals and reject intrusions, and 4) the level of noise in retrieval competitions. We extend CMR2 to simulate a recognition memory task using the same mechanisms the free recall model uses to reject intrusions. Without fitting any additional parameters, the four–component theory that accounts for age differences in free recall predicts the magnitude of age differences in recognition memory accuracy. Confirming a prediction of the model, free recall intrusion rates correlate positively with recognition false alarm rates. Thus we provide a four–component theory of a complex pattern of age differences across two key laboratory tasks. PMID:26501233

  13. Uncertainty-Dependent Extinction of Fear Memory in an Amygdala-mPFC Neural Circuit Model

    Science.gov (United States)

    Li, Yuzhe; Nakae, Ken; Ishii, Shin; Naoki, Honda

    2016-01-01

    Uncertainty of fear conditioning is crucial for the acquisition and extinction of fear memory. Fear memory acquired through partial pairings of a conditioned stimulus (CS) and an unconditioned stimulus (US) is more resistant to extinction than that acquired through full pairings; this effect is known as the partial reinforcement extinction effect (PREE). Although the PREE has been explained by psychological theories, the neural mechanisms underlying the PREE remain largely unclear. Here, we developed a neural circuit model based on three distinct types of neurons (fear, persistent and extinction neurons) in the amygdala and medial prefrontal cortex (mPFC). In the model, the fear, persistent and extinction neurons encode predictions of net severity, of unconditioned stimulus (US) intensity, and of net safety, respectively. Our simulation successfully reproduces the PREE. We revealed that unpredictability of the US during extinction was represented by the combined responses of the three types of neurons, which are critical for the PREE. In addition, we extended the model to include amygdala subregions and the mPFC to address a recent finding that the ventral mPFC (vmPFC) is required for consolidating extinction memory but not for memory retrieval. Furthermore, model simulations led us to propose a novel procedure to enhance extinction learning through re-conditioning with a stronger US; strengthened fear memory up-regulates the extinction neuron, which, in turn, further inhibits the fear neuron during re-extinction. Thus, our models increased the understanding of the functional roles of the amygdala and vmPFC in the processing of uncertainty in fear conditioning and extinction. PMID:27617747

  14. 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

  15. 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.

  16. Stochastic dynamic causal modeling of working memory connections in cocaine dependence.

    Science.gov (United States)

    Ma, Liangsuo; Steinberg, Joel L; Hasan, Khader M; Narayana, Ponnada A; Kramer, Larry A; Moeller, F Gerard

    2014-03-01

    Although reduced working memory brain activation has been reported in several brain regions of cocaine-dependent subjects compared with controls, very little is known about whether there is altered connectivity of working memory pathways in cocaine dependence. This study addresses this issue by using functional magnetic resonance imaging-based stochastic dynamic causal modeling (DCM) analysis to study the effective connectivity of 19 cocaine-dependent subjects and 14 healthy controls while performing a working memory task. Stochastic DCM is an advanced method that has recently been implemented in SPM8 that can obtain improved estimates, relative to deterministic DCM, of hidden neuronal causes before convolution with the hemodynamic response. Thus, stochastic DCM may be less influenced by the confounding effects of variations in blood oxygen level-dependent response caused by disease or drugs. Based on the significant regional activation common to both groups and consistent with previous working memory activation studies, seven regions of interest were chosen as nodes for DCM analyses. Bayesian family level inference, Bayesian model selection analyses, and Bayesian model averaging (BMA) were conducted. BMA showed that the cocaine-dependent subjects had large differences compared with the control subjects in the strengths of prefrontal-striatal modulatory (B matrix) DCM parameters. These findings are consistent with altered cortical-striatal networks that may be related to reduced dopamine function in cocaine dependence. As far as we are aware, this is the first between-group DCM study using stochastic methodology. Copyright © 2012 Wiley Periodicals, Inc.

  17. Visuospatial cues for reinstating mental models in working memory during interrupted reading.

    Science.gov (United States)

    Schneider, Darryl W; Dixon, Peter

    2009-09-01

    Reading involves constructing a mental representation in long-term working memory of the world described by the text. Disrupting short-term working memory can interfere with the maintenance of mental models (sets of retrieval cues) needed to access these representations, producing detrimental effects on reading time. In two experiments, subjects read passages that included pairs of coreferential sentences interrupted by unrelated text. As in previous research, reading times increased for the first sentence after the interruption, likely reflecting a reinstatement process for mental models in working memory. In the present research, pictures were provided as visuospatial cues to aid the reinstatement process. The interruption effect was found to be smaller with pictures related to the passages than with unrelated pictures (Experiment 1) or titles (Experiment 2); however, both of these effects occurred only for slow readers. The authors hypothesize that slow readers take the time needed to integrate visuospatial information into their mental models, providing more resilient access to long-term working memory.

  18. Different developmental trajectories across feature types support a dynamic field model of visual working memory development.

    Science.gov (United States)

    Simmering, Vanessa R; Miller, Hilary E; Bohache, Kevin

    2015-05-01

    Research on visual working memory has focused on characterizing the nature of capacity limits as "slots" or "resources" based almost exclusively on adults' performance with little consideration for developmental change. Here we argue that understanding how visual working memory develops can shed new light onto the nature of representations. We present an alternative model, the Dynamic Field Theory (DFT), which can capture effects that have been previously attributed either to "slot" or "resource" explanations. The DFT includes a specific developmental mechanism to account for improvements in both resolution and capacity of visual working memory throughout childhood. Here we show how development in the DFT can account for different capacity estimates across feature types (i.e., color and shape). The current paper tests this account by comparing children's (3, 5, and 7 years of age) performance across different feature types. Results showed that capacity for colors increased faster over development than capacity for shapes. A second experiment confirmed this difference across feature types within subjects, but also showed that the difference can be attenuated by testing memory for less familiar colors. Model simulations demonstrate how developmental changes in connectivity within the model-purportedly arising through experience-can capture differences across feature types.

  19. A brief comparison of fuzzy associative memory models for guiding autonomous problems

    Directory of Open Access Journals (Sweden)

    Guilherme Augusto de Lima Freitas

    2011-09-01

    Full Text Available Fuzzy associative memories (FAMs are models inspired in the human brain ability to store and recall information. These models can be used for the storage of associations of fuzzy sets and, thus, they can be used as inference engines in fuzzy controllers. Several FAM models have been developed in the last years, but we are not aware of a work comparing the performance of novel FAMs in control. In this paper, we briefly investigate the performance of some FAMs in the automatic guidance problems of backing-up a truck (BT and backing-up a truck and trailer (BTT. In particular, we note that the dual implicative fuzzy associative memories (co-IFAMs constitute an interesting alternative to traditional models such as that of Kosko and Mamdani.

  20. Linking Working Memory and Long-Term Memory: A Computational Model of the Learning of New Words

    Science.gov (United States)

    Jones, Gary; Gobet, Fernand; Pine, Julian M.

    2007-01-01

    The nonword repetition (NWR) test has been shown to be a good predictor of children's vocabulary size. NWR performance has been explained using phonological working memory, which is seen as a critical component in the learning of new words. However, no detailed specification of the link between phonological working memory and long-term memory…

  1. From distributed resources to limited slots in multiple-item working memory: a spiking network model with normalization

    National Research Council Canada - National Science Library

    Wei, Ziqiang; Wang, Xiao-Jing; Wang, Da-Hui

    2012-01-01

    ...: a "discrete-slot" model in which memory items are stored in a limited number of slots, and a "shared-resource" model in which the neural representation of items is distributed across a limited pool of resources...

  2. Ginsenoside Rg1 ameliorates hippocampal long-term potentiation and memory in an Alzheimer's disease model.

    Science.gov (United States)

    Li, Fengling; Wu, Xiqing; Li, Jing; Niu, Qingliang

    2016-06-01

    The complex etiopathogenesis of Alzheimer's disease (AD) has limited progression in the identification of effective therapeutic agents. Amyloid precursor protein (APP) and presenilin‑1 (PS1) are always overexpressed in AD, and are considered to be the initiators of the formation of β‑amyloid plaques and the symptoms of AD. In the present study, a transgenic AD model, constructed via the overexpression of APP and PS1, was used to verify the protective effects of ginsenoside Rg1 on memory performance and synaptic plasticity. AD mice (6‑month‑old) were treated via intraperitoneal injection of 0.1‑10 mg/kg ginsenoside Rg1. Long‑term memory, synaptic plasticity, and the levels of AD‑associated and synaptic plasticity‑associated proteins were measured following treatment. Memory was measured using a fear conditioning task and protein expression levels were investigated using western blotting. All the data was analyzed by one-way analysis of variance or t‑test. Following 30 days of consecutive treatment, memory in the AD mouse model was ameliorated in the 10 mg/kg ginsenoside Rg1 treatment group. As demonstrated by biochemical experiments, ginsenoside Rg1 treatment reduced the accumulations of β‑amyloid 1‑42 and phosphorylated (p)‑Tau in the AD model. Additionally, brain-derived neurotrophic factor (BDNF) and p‑TrkB synaptic plasticity‑associated proteins were upregulated following ginsenoside Rg1 application. Correspondingly, long‑term potentiation (LTP) was restored following ginsenoside Rg1 application in the AD mice model. Taken together, ginsenoside Rg1 repaired hippocampal LTP and memory, likely through facilitating the clearance of AD‑associated proteins and through activation of the BDNF‑TrkB pathway. Therefore, ginsenoside Rg1 may be a candidate drug for the treatment of AD.

  3. 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

    2012-07-01

    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 understanding verbal materials, especially when words are mentally combined to form multiword units or chunks. Toward a more comprehensive theory of capacity limits, we examined models of forced-choice recognition of words within printed lists, using materials designed to produce multiword chunks in memory (e.g., leather brief case). Several simple models were tested against data from a variety of list lengths and potential chunk sizes, with test conditions that only imperfectly elicited the interword associations. According to the most successful model, participants retained about 3 chunks on average in a capacity-limited region of WM, with some chunks being only subsets of the presented associative information (e.g., leather brief case retained with leather as one chunk and brief case as another). The addition to the model of an activated long-term memory component unlimited in capacity was needed. A fixed-capacity limit appears critical to account for immediate verbal recognition and other forms of WM. We advance a model-based approach that allows capacity to be assessed despite other important processing contributions. Starting with a psychological-process model of WM capacity developed to understand visual arrays, we arrive at a more unified and complete model. Copyright 2012 APA, all rights reserved.

  4. Why some colors appear more memorable than others: A model combining categories and particulars in color working memory.

    Science.gov (United States)

    Bae, Gi-Yeul; Olkkonen, Maria; Allred, Sarah R; Flombaum, Jonathan I

    2015-08-01

    Categorization with basic color terms is an intuitive and universal aspect of color perception. Yet research on visual working memory capacity has largely assumed that only continuous estimates within color space are relevant to memory. As a result, the influence of color categories on working memory remains unknown. We propose a dual content model of color representation in which color matches to objects that are either present (perception) or absent (memory) integrate category representations along with estimates of specific values on a continuous scale ("particulars"). We develop and test the model through 4 experiments. In a first experiment pair, participants reproduce a color target, both with and without a delay, using a recently influential estimation paradigm. In a second experiment pair, we use standard methods in color perception to identify boundary and focal colors in the stimulus set. The main results are that responses drawn from working memory are significantly biased away from category boundaries and toward category centers. Importantly, the same pattern of results is present without a memory delay. The proposed dual content model parsimoniously explains these results, and it should replace prevailing single content models in studies of visual working memory. More broadly, the model and the results demonstrate how the main consequence of visual working memory maintenance is the amplification of category related biases and stimulus-specific variability that originate in perception. (c) 2015 APA, all rights reserved).

  5. Enhanced stability of car-following model upon incorporation of short-term driving memory

    Science.gov (United States)

    Liu, Da-Wei; Shi, Zhong-Ke; Ai, Wen-Huan

    2017-06-01

    Based on the full velocity difference model, a new car-following model is developed to investigate the effect of short-term driving memory on traffic flow in this paper. Short-term driving memory is introduced as the influence factor of driver's anticipation behavior. The stability condition of the newly developed model is derived and the modified Korteweg-de Vries (mKdV) equation is constructed to describe the traffic behavior near the critical point. Via numerical method, evolution of a small perturbation is investigated firstly. The results show that the improvement of this new car-following model over the previous ones lies in the fact that the new model can improve the traffic stability. Starting and breaking processes of vehicles in the signalized intersection are also investigated. The numerical simulations illustrate that the new model can successfully describe the driver's anticipation behavior, and that the efficiency and safety of the vehicles passing through the signalized intersection are improved by considering short-term driving memory.

  6. Disease-associated pathophysiologic structures in pediatric rheumatic diseases show characteristics of scale-free networks seen in physiologic systems: implications for pathogenesis and treatment

    Directory of Open Access Journals (Sweden)

    McGhee Timothy

    2009-02-01

    Full Text Available Abstract Background While standard reductionist approaches have provided some insights into specific gene polymorphisms and molecular pathways involved in disease pathogenesis, our understanding of complex traits such as atherosclerosis or type 2 diabetes remains incomplete. Gene expression profiling provides an unprecedented opportunity to understand complex human diseases by providing a global view of the multiple interactions across the genome that are likely to contribute to disease pathogenesis. Thus, the goal of gene expression profiling is not to generate lists of differentially expressed genes, but to identify the physiologic or pathogenic processes and structures represented in the expression profile. Methods RNA was separately extracted from peripheral blood neutrophils and mononuclear leukocytes, labeled, and hybridized to genome level microarrays to generate expression profiles of children with polyarticular juvenile idiopathic arthritis, juvenile dermatomyositis relative to childhood controls. Statistically significantly differentially expressed genes were identified from samples of each disease relative to controls. Functional network analysis identified interactions between products of these differentially expressed genes. Results In silico models of both diseases demonstrated similar features with properties of scale-free networks previously described in physiologic systems. These networks were observable in both cells of the innate immune system (neutrophils and cells of the adaptive immune system (peripheral blood mononuclear cells. Conclusion Genome-level transcriptional profiling from childhood onset rheumatic diseases suggested complex interactions in two arms of the immune system in both diseases. The disease associated networks showed scale-free network patterns similar to those reported in normal physiology. We postulate that these features have important implications for therapy as such networks are relatively resistant

  7. Lifelong modelling of properties for materials with technological memory

    Science.gov (United States)

    Falaleev, AP; Meshkov, VV; Vetrogon, AA; Ogrizkov, SV; Shymchenko, AV

    2016-10-01

    An investigation of real automobile parts produced from dual phase steel during standard periods of life cycle is presented, which considers such processes as stamping, exploitation, automobile accident, and further repair. The development of the phenomenological model of the mechanical properties of such parts was based on the two surface plastic theory of Chaboche. As a consequence of the composite structure of dual phase steel, it was shown that local mechanical properties of parts produced from this material change significantly their during their life cycle, depending on accumulated plastic deformations and thermal treatments. Such mechanical property changes have a considerable impact on the accuracy of the computer modelling of automobile behaviour. The most significant errors of modelling were obtained at the critical operating conditions, such as crashes and accidents. The model developed takes into account the kinematics (Bauschinger effect), isotropic hardening, non-linear elastic steel behaviour and changes caused by the thermal treatment. Using finite element analysis, the model allows the evaluation of the passive safety of a repaired car body, and enables increased restoration accuracy following an accident. The model was confirmed experimentally for parts produced from dual phase steel DP780.

  8. Effects of Astragalus polysaccharides on memory impairment in a diabetic rat model

    Directory of Open Access Journals (Sweden)

    Dun C

    2016-07-01

    Full Text Available Changping Dun,1 Junqian Liu,1 Fucheng Qiu,1 Xueda Wu,2 Yakun Wang,3 Yongyan Zhao,4 Ping Gu1 1Department of Neurology, the First Hospital of Hebei Medical University, 2Department of Cardiac Surgery, the Second Hospital of Hebei Medical University, 3Department of Endocrinology, the Fourth Hospital of Hebei Medical University, Shijiazhuang, 4Department of Nursing, Maternal and Child Health Hospital of Tangshan City, Tangshan, People’s Republic of China Objective: Astragalus polysaccharides (APS are active constituents of Astragalus membranaceus. In this study, we aimed to investigate the effects of APS on memory impairment in a diabetic rat model and their mechanisms. Methods: A diabetic model was established in 50 male Wistar rats with streptozotocin intraperitoneal injection. A blood glucose level higher than 16.7 mmol/L obtained 72 hours after the injection was regarded as a successful diabetic model. The modeled rats were divided into model group, high, medium, and low doses of APS, and piracetam groups (positive control. A group of ten rats without streptozotocin-induced diabetes were used as a normal control. After respective consecutive 8-week treatments, the levels of blood fasting plasma glucose, insulin, hemoglobin A1c, memory performance, hippocampal malondialdehyde, and superoxide dismutase were determined. Results: After the 8-week APS treatment, serum fasting plasma glucose, hemoglobin A1c, and insulin levels were decreased compared with those of the model group (P<0.05. Importantly, memory impairment in the diabetic model was reversed by APS treatments. In addition, hippocampal malondialdehyde concentration was lowered, whereas that of superoxide dismutase was higher after APS treatments. Conclusion: APS are important active components responsible for memory improvement in rats with streptozotocin-induced diabetes. The potential mechanism of action is associated with the effects of APS on glucose and lipid metabolism, and

  9. Functional connectivity in a rat model of Alzheimer's disease during a working memory task.

    Science.gov (United States)

    Liu, Tiaotiao; Bai, Wenwen; Yi, Hu; Tan, Tao; Wei, Jing; Wang, Ju; Tian, Xin

    2014-01-01

    Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive loss of memory. Impairment of working memory was typically observed in AD. The concept of brain functional connectivity plays an important role in neuroscience as a useful tool to understand the organized behavior of brain. Hence, the purpose of this study is to investigate the possible mechanism of working memory deficits in AD from a new perspective of functional connectivity. Rats were randomly divided into 2 groups: Aβ injection group (Aβ₁₋₄₂-induced toxicity rat model) and control group. Multi-channel local field potentials (LFPs) were obtained from rat prefrontal cortex with implanted microelectrode arrays while the rats performed a Y-maze working memory task. The short-time Fourier transform was utilized to analyze the power changes in LFPs and sub-bands (in particular theta and low gamma bands) were extracted via band filtering. Then the Directed transfer function (DTF) method was applied to calculate the functional connections among LFPs. From the DTF calculation, the causal networks in the sub-bands were identified. DTFmean (mean of connectivity matrix elements) was used to quantify connection strength as well as global efficiency (Eglob) was calculated to quantitatively describe the efficient of information transfer in the network. Our results showed that both connection strength and efficient of information transfer increased during the working memory task in the control group; by contrast, there was no significantly change in the Aβ injection group. These findings could lead to improve the understanding of the mechanism of working memory deficits in AD.

  10. Grouping influences output interference in short-term memory: a mixture modeling study

    Directory of Open Access Journals (Sweden)

    Min-Suk eKang

    2016-05-01

    Full Text Available Output interference is a source of forgetting induced by recalling. We investigated how grouping influences output interference in short-term memory. In Experiment 1, the participants were asked to remember four colored items. Those items were grouped by temporal coincidence as well as spatial alignment: two items were presented in the first memory array and two were presented in the second, and the items in both arrays were either vertically or horizontally aligned as well. The participants then performed two recall tasks in sequence by selecting a color presented at a cued location from a color wheel. In the same-group condition, the participants reported both items from the same memory array; however, in the different-group condition, the participants reported one item from each memory array. We analyzed participant responses with a mixture model, which yielded two measures: guess rate and precision of recalled memories. The guess rate in the second recall was higher for the different-group condition than for the same-group condition; however, the memory precisions obtained for both conditions were similarly degraded in the second recall. In Experiment 2, we varied the probability of the same- and different-group conditions with a ratio of 3 to 7. We expected output interference to be higher in the same-group condition than in the different-group condition. This is because items of the other group are more likely to be probed in the second recall phase and, thus, protecting those items during the first recall phase leads to a better performance. Nevertheless, the same pattern of results was robustly reproduced, suggesting grouping shields the grouped items from output interference because of the secured accessibility. We discussed how grouping influences output interference.

  11. Learning and memory impairments in a neuroendocrine mouse model of anxiety/depression

    Directory of Open Access Journals (Sweden)

    Flavie eDarcet

    2014-05-01

    Full Text Available Cognitive disturbances are often reported as serious incapacitating symptoms by patients suffering from major depressive disorders. Such deficits have been observed in various animal models based on environmental stress.Here, we performed a complete characterization of cognitive functions in a neuroendocrine mouse model of depression based on a chronic (4 weeks corticosterone administration (CORT. Cognitive performances were assessed using behavioral tests measuring episodic (novel object recognition test, NORT, associative (one-trial contextual fear conditioning, CFC and visuo-spatial (Morris water maze, MWM; Barnes maze, BM learning/memory. Altered emotional phenotype after chronic corticosterone treatment was confirmed in mice using tests predictive of anxiety or depression-related behaviors.In the NORT, CORT-treated mice showed a decrease in time exploring the novel object during the test session and a lower discrimination index compared to control mice, characteristic of recognition memory impairment. Associative memory was also impaired, as observed with a decrease in freezing duration in CORT-treated mice in the CFC, thus pointing out the cognitive alterations in this model. In the MWM and in the BM, spatial learning performance but also short-term spatial memory were altered in CORT-treated mice. In the MWM, unlike control animals, CORT-treated animals failed to learn a new location during the reversal phase, suggesting a loss of cognitive flexibility. Finally, in the BM, the lack of preference for the target quadrant during the recall probe trial in animals receiving corticosterone regimen demonstrates that long-term retention was also affected in this paradigm. Taken together, our results highlight that CORT-induced anxio-depressive-like phenotype is associated with a cognitive deficit affecting all aspects of memory tested.

  12. Real-world-time simulation of memory consolidation in a large-scale cerebellar model

    Directory of Open Access Journals (Sweden)

    Masato eGosui

    2016-03-01

    Full Text Available We report development of a large-scale spiking network model of thecerebellum composed of more than 1 million neurons. The model isimplemented on graphics processing units (GPUs, which are dedicatedhardware for parallel computing. Using 4 GPUs simultaneously, we achieve realtime simulation, in which computer simulation ofcerebellar activity for 1 sec completes within 1 sec in thereal-world time, with temporal resolution of 1 msec.This allows us to carry out a very long-term computer simulationof cerebellar activity in a practical time with millisecond temporalresolution. Using the model, we carry out computer simulationof long-term gain adaptation of optokinetic response (OKR eye movementsfor 5 days aimed to study the neural mechanisms of posttraining memoryconsolidation. The simulation results are consistent with animal experimentsand our theory of posttraining memory consolidation. These resultssuggest that realtime computing provides a useful means to studya very slow neural process such as memory consolidation in the brain.

  13. A memory diffusion model for molecular anisotropic diffusion in siliceous β-zeolite.

    Science.gov (United States)

    Ji, Xiangfei; An, Zhuanzhuan; Yang, Xiaofeng

    2016-01-01

    A memory diffusion model of molecules on β-zeolite is proposed. In the model, molecular diffusion in β-zeolites is treated as jumping from one adsorption site to its neighbors and the jumping probability is a compound probability which includes that provided by the transitional state theory as well as that derived from the information about which direction the target molecule comes from. The proposed approach reveals that the diffusivities along two crystal axes on β-zeolite are correlated. The model is tested by molecular dynamics simulations on diffusion of benzene and other simple molecules in β-zeolites. The results show that the molecules with larger diameters fit the prediction much better and that the "memory effects" are important in all cases.

  14. Impact of interaction style and degree on the evolution of cooperation on Barabási-Albert scale-free network.

    Science.gov (United States)

    Xie, Fengjie; Shi, Jing; Lin, Jun

    2017-01-01

    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.

  15. 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.

  16. Model Considerations for Memory-based Automatic Music Transcription

    Science.gov (United States)

    Albrecht, Štěpán; Šmídl, Václav

    2009-12-01

    The problem of automatic music description is considered. The recorded music is modeled as a superposition of known sounds from a library weighted by unknown weights. Similar observation models are commonly used in statistics and machine learning. Many methods for estimation of the weights are available. These methods differ in the assumptions imposed on the weights. In Bayesian paradigm, these assumptions are typically expressed in the form of prior probability density function (pdf) on the weights. In this paper, commonly used assumptions about music signal are summarized and complemented by a new assumption. These assumptions are translated into pdfs and combined into a single prior density using combination of pdfs. Validity of the model is tested in simulation using synthetic data.

  17. Long Memory in Stock Market Volatility and the Volatility-in-Mean Effect: The FIEGARCH-M Model

    DEFF Research Database (Denmark)

    Christensen, Bent Jesper; Nielsen, Morten Ørregaard; Zhu, Jie

    We extend the fractionally integrated exponential GARCH (FIEGARCH) model for daily stock return data with long memory in return volatility of Bollerslev and Mikkelsen (1996) by introducing a possible volatility-in-mean effect. To avoid that the long memory property of volatility carries over to r...

  18. Transition to success on the model room task: the importance of improvements in working memory.

    Science.gov (United States)

    Hartstein, Lauren E; Berthier, Neil E

    2017-02-22

    Previous work has shown that children under age 3 often perform very poorly on the model room task, in which they are asked to find a hidden toy based on its location in a scale model. One prominent theory for their failure is that they lack the ability to understand the model as both a physical object and as a symbolic representation of the larger room. A hypothesized additional component is that they need to overcome weak, competing representations of where the object was on a previous trial, and where it is in the present trial, in order to succeed in their search. Children aged 33-39 months were tested on the model room task, as well as on measures of cognitive inhibitory control, cognitive flexibility, and working memory. Results showed that performance on the model room task was not predicted by measures of inhibitory control or cognitive flexibility, but was predicted by performance on the Delayed Recognition Span Test (DRST), a measure of working memory. These findings lend support to the theory of competing representations and demonstrate the necessity of updating and maintaining strong representations in working memory to succeed in the search task. © 2017 John Wiley & Sons Ltd.

  19. Dynamic Delayed Duplicate Detection for External Memory Model Checking

    DEFF Research Database (Denmark)

    Evangelista, Sami

    2008-01-01

    Duplicate detection is an expensive operation of disk-based model checkers. It consists of comparing some potentially new states, the candidate states, to previous visited states. We propose a new approach to this technique called dynamic delayed duplicate detection. This one exploits some typica...

  20. A Comparative Study of the Effects of the Neurocognitive-Based Model and the Conventional Model on Learner Attention, Working Memory and Mood

    Science.gov (United States)

    Srikoon, Sanit; Bunterm, Tassanee; Nethanomsak, Teerachai; Ngang, Tang Keow

    2017-01-01

    Purpose: The attention, working memory, and mood of learners are the most important abilities in the learning process. This study was concerned with the comparison of contextualized attention, working memory, and mood through a neurocognitive-based model (5P) and a conventional model (5E). It sought to examine the significant change in attention,…

  1. Collaging Memories

    Science.gov (United States)

    Wallach, Michele

    2011-01-01

    Even middle school students can have memories of their childhoods, of an earlier time. The art of Romare Bearden and the writings of Paul Auster can be used to introduce ideas about time and memory to students and inspire works of their own. Bearden is an exceptional role model for young artists, not only because of his astounding art, but also…

  2. Main Memory

    NARCIS (Netherlands)

    P.A. Boncz (Peter); L. Liu (Lei); M. Tamer Özsu

    2008-01-01

    htmlabstractPrimary storage, presently known as main memory, is the largest memory directly accessible to the CPU in the prevalent Von Neumann model and stores both data and instructions (program code). The CPU continuously reads instructions stored there and executes them. It is also called Random

  3. Micromagnetic Modeling and Analysis for Memory and Processing Applications

    Science.gov (United States)

    Lubarda, Marko V.

    Magnetic nanostructures are vital components of numerous existing and prospective magnetic devices, including hard disk drives, magnetic sensors, and microwave generators. The ability to examine and predict the behavior of magnetic nanostructures is essential for improving existing devices and exploring new technologies and areas of application. This thesis consists of three parts. In part I, key concepts of magnetism are covered (chapter 1), followed by an introduction to micromagnetics (chapter 2). Key interactions are discussed. The Landau-Lifshitz-Gilbert equation is introduced, and the variational approach of W. F. Brown is presented. Part II is devoted to computational micromagnetics. Interaction energies, fields and torques, introduced in part I, are transcribed from the continuum to their finite element form. The validity of developed models is discussed with reference to physical assumptions and discretization criteria. Chapter 3 introduces finite element modeling, and provides derivations of micromagnetic fields in the linear basis representation. Spin transfer torques are modeled in chapter 4. Thermal effects are included in the computational framework in chapter 5. Chapter 6 discusses an implementation of the nudged elastic band method for the computation of energy barriers. A model accounting for polycrystallinity is developed in chapter 7. The model takes into account the wide variety of distributions and imperfections which characterize true systems. The modeling presented in chapters 3-7 forms a general framework for the computational study of diverse magnetic phenomena in contemporary structures and devices. Chapter 8 concludes part II with an outline of powerful acceleration schemes, which were essential for the large-scale micromagnetic simulations presented in part III. Part III begins with the analysis of the perpendicular magnetic recording system (chapter 9). A simulation study of the recording process with readback analysis is presented

  4. 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.

  5. A tractable prescription for large-scale free flight expansion of wavefunctions

    Science.gov (United States)

    Deuar, P.

    2016-11-01

    A numerical recipe is given for obtaining the density image of an initially compact quantum mechanical wavefunction that has expanded by a large but finite factor under free flight. The recipe given avoids the memory storage problems that plague this type of calculation by reducing the problem to the sum of a number of fast Fourier transforms carried out on the relatively small initial lattice. The final expanded state is given exactly on a coarser magnified grid with the same number of points as the initial state. An important application of this technique is the simulation of measured time-of-flight images in ultracold atom experiments, especially when the initial clouds contain superfluid defects. It is shown that such a finite-time expansion, rather than a far-field approximation is essential to correctly predict images of defect-laden clouds, even for long flight times. Examples shown are: an expanding quasicondensate with soliton defects and a matter-wave interferometer in 3D.

  6. A memory model for internet hits after media exposure

    Science.gov (United States)

    Chessa, Antonio G.; Murre, Jaap M. J.

    2004-02-01

    We present a cognitive model, based on the mathematical theory of point processes, which extends the results of two studies by Johansen (Physica A 276 (2000) 338; Physica A 296 (2001) 539) on download relaxation dynamics. Responses from subjects are considered as single events, which are received from original listeners or readers and from a network of social contacts, through which a message may propagate further. We collected data on the number of daily visits at our web site after a radio interview with the second author, in which the name of the web site was mentioned. A model based on an exponential hit time distribution and a homogeneous point process for regular visitors fits our data and Johansen's very well and is superior to both the power law and the logarithmic function. The fits suggest that hit data from different sources share the same cognitive mechanism, which are controlled merely by the encoding and retrieval of the target information memorised.

  7. How hippocampus and cortex contribute to recognition memory: Revisiting the Complementary Learning Systems model

    Science.gov (United States)

    Norman, Kenneth A.

    2012-01-01

    We describe how the Complementary Learning Systems neural network model of recognition memory (Norman & O’Reilly, 2003) can shed light on current debates regarding hippocampal and cortical contributions to recognition memory. We review simulation results illustrating three critical differences in how (according to the model) hippocampus and cortex contribute to recognition memory, all of which derive from the hippocampus’ use of pattern separated representations. Pattern separation makes the hippocampus especially well-suited for discriminating between studied items and related lures; it makes the hippocampus especially poorly suited for computing global match; and it imbues the hippocampal ROC curve with a Y-intercept > 0. We also describe a key boundary condition on these differences: When the average level of similarity between items in an experiment is very high, hippocampal pattern separation can fail, at which point the hippocampal model will start to behave like the cortical model. We describe the implications of these simulation results for extant debates over how to describe hippocampal vs. cortical contributions and how to measure these contributions. PMID:20857486

  8. EVALUATING MODELS OF WORKING MEMORY THROUGH THE EFFECTS OF CONCURRENT IRRELEVANT INFORMATION

    Science.gov (United States)

    Chein, Jason M.; Fiez, Julie A.

    2010-01-01

    Working memory is believed to play a central role in almost all domains of higher cognition, yet the specific mechanisms involved in working memory are still fiercely debated. We describe a neuroimaging experiment using fMRI, and a companion behavioral experiment, both seeking to adjudicate between alternative theoretical models of working memory based on the effects of interference from articulatory suppression, irrelevant speech, and irrelevant nonspeech. Experiment 1 examined fMRI signal changes induced by each type of irrelevant information while subjects performed a probed recall task. Within a principally frontal and left-lateralized network of brain regions, articulatory suppression caused an increase in activity during item presentation, while both irrelevant speech and nonspeech caused relative activity reductions during the subsequent delay interval. In Experiment 2, the specific timing of interference was manipulated in a delayed serial recall task. Articulatory suppression was found to be most consequential when it coincided with item presentation, while both irrelevant speech and irrelevant nonspeech effects were strongest when limited to the subsequent delay period. Taken together, these experiments provide convergent evidence for a dissociation of articulatory suppression from the two irrelevant sound conditions. Implications of these findings are considered for four prominent theories of working memory. PMID:20121315

  9. STRUKTUR DAN PROSES MEMORI

    Directory of Open Access Journals (Sweden)

    Magda Bhinnety

    2015-09-01

    Full Text Available This paper describes structures and processes of human memory system according to the modal model. Sensory memory is described as the first system to store information from outside world. Short‐term memory, or now called working memory, represents a system characterized by limited ability in storing as well as retrieving information. Long‐term memory on the hand stores information larger in amount and longer than short‐term memory

  10. A generalized voter model with time-decaying memory on a multilayer network

    Science.gov (United States)

    Zhong, Li-Xin; Xu, Wen-Juan; Chen, Rong-Da; Zhong, Chen-Yang; Qiu, Tian; Shi, Yong-Dong; Wang, Li-Liang

    2016-09-01

    By incorporating a multilayer network and time-decaying memory into the original voter model, we investigate the coupled effects of spatial and temporal accumulation of peer pressure on the consensus. Heterogeneity in peer pressure and the time-decaying mechanism are both shown to be detrimental to the consensus. We find the transition points below which a consensus can always be reached and above which two opposed opinions are more likely to coexist. Our mean-field analysis indicates that the phase transitions in the present model are governed by the cumulative influence of peer pressure and the updating threshold. We find a functional relation between the consensus threshold and the decay rate of the influence of peer is found. As to the pressure. The time required to reach a consensus is governed by the coupling of the memory length and the decay rate. An intermediate decay rate may greatly reduce the time required to reach a consensus.

  11. The Effect of an NCAM Mimetic on Learning and Memory Impairment in an Animal Model of Schizophrenia

    DEFF Research Database (Denmark)

    Secher, Thomas

    2009-01-01

    , and synaptic plasticity. Furthermore, it can act as a memory enhancer in normal animals. Schizophrenia is a heterogeneous psychiatric disorder. Disturbances in information processing and higher cognitive function including deficits in working memory are believed represent a core feature of schizophrenia...... learning and memory. The effect of FGL on these deficits was, in general, very small; however, the peptide had some normalizing effect in the working memory task. The weak effects of FGL in this animal model limit the prospect of this peptide as a possible treatment for the cognitive impairment seen....... The cognitive dysfunction is strongly related to the functional outcome of patients, but is only minimally affected by existing antipsychotic treatment. The general aim on the present project was to investigate if FGL could have a beneficial effect on learning and memory deficits in a rat model...

  12. A model for Intelligent Random Access Memory architecture (IRAM) cellular automata algorithms on the Associative String Processing machine (ASTRA)

    CERN Document Server

    Rohrbach, F; Vesztergombi, G

    1997-01-01

    In the near future, the computer performance will be completely determined by how long it takes to access memory. There are bottle-necks in memory latency and memory-to processor interface bandwidth. The IRAM initiative could be the answer by putting Processor-In-Memory (PIM). Starting from the massively parallel processing concept, one reached a similar conclusion. The MPPC (Massively Parallel Processing Collaboration) project and the 8K processor ASTRA machine (Associative String Test bench for Research \\& Applications) developed at CERN \\cite{kuala} can be regarded as a forerunner of the IRAM concept. The computing power of the ASTRA machine, regarded as an IRAM with 64 one-bit processors on a 64$\\times$64 bit-matrix memory chip machine, has been demonstrated by running statistical physics algorithms: one-dimensional stochastic cellular automata, as a simple model for dynamical phase transitions. As a relevant result for physics, the damage spreading of this model has been investigated.

  13. Tc1 mouse model of trisomy-21 dissociates properties of short- and long-term recognition memory.

    Science.gov (United States)

    Hall, Jessica H; Wiseman, Frances K; Fisher, Elizabeth M C; Tybulewicz, Victor L J; Harwood, John L; Good, Mark A

    2016-04-01

    The present study examined memory function in Tc1 mice, a transchromosomic model of Down syndrome (DS). Tc1 mice demonstrated an unusual delay-dependent deficit in recognition memory. More specifically, Tc1 mice showed intact immediate (30sec), impaired short-term (10-min) and intact long-term (24-h) memory for objects. A similar pattern was observed for olfactory stimuli, confirming the generality of the pattern across sensory modalities. The specificity of the behavioural deficits in Tc1 mice was confirmed using APP overexpressing mice that showed the opposite pattern of object memory deficits. In contrast to object memory, Tc1 mice showed no deficit in either immediate or long-term memory for object-in-place information. Similarly, Tc1 mice showed no deficit in short-term memory for object-location information. The latter result indicates that Tc1 mice were able to detect and react to spatial novelty at the same delay interval that was sensitive to an object novelty recognition impairment. These results demonstrate (1) that novelty detection per se and (2) the encoding of visuo-spatial information was not disrupted in adult Tc1 mice. The authors conclude that the task specific nature of the short-term recognition memory deficit suggests that the trisomy of genes on human chromosome 21 in Tc1 mice impacts on (perirhinal) cortical systems supporting short-term object and olfactory recognition memory. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  14. Transfer of memory trace of cerebellum-dependent motor learning in human prism adaptation: a model study.

    Science.gov (United States)

    Nagao, Soichi; Honda, Takeru; Yamazaki, Tadashi

    2013-11-01

    Accumulating experimental evidence suggests that the memory trace of ocular reflex adaptation is initially encoded in the cerebellar cortex, and later transferred to the cerebellar nuclei for consolidation through repetitions of training. However, the memory transfer is not well characterized in the learning of voluntary movement. Here, we implement our model of memory transfer to interpret the data of prism adaptation (Martin, Keating, Goodkin, Bastian, & Thach, 1996a, 1996b), assuming that the cerebellar nuclear memory formed by memory transfer is used for normal throwing. When the subject was trained to throw darts wearing prisms in 30-40 trials, the short-term memory for recalibrating the throwing direction by gaze would be formed in the cerebellar cortex, which was extinguished by throwing with normal vision in a similar number of trials. After weeks of repetitions of short-term prism adaptation, the long-term memory would be formed in the cerebellar nuclei through memory transfer, which enabled one to throw darts to the center wearing prisms without any training. These two long-term memories, one for throwing with normal vision and the other for throwing wearing prisms, are assumed to be utilized automatically under volitional control. Moreover, when the prisms were changed to new prisms, a new memory for adapting to the new prisms would be formed in the cerebellar cortex, just to counterbalance the nuclear memory of long-term adaptation to the original prisms in a similar number of trials. These results suggest that memory transfer may occur in the learning of voluntary movements. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. 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

    National Research Council Canada - National Science Library

    Aleksandra Gruszka; Jarosław Orzechowski

    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...

  16. In vivo tissue response following implantation of shape memory polyurethane foam in a porcine aneurysm model

    OpenAIRE

    Rodriguez, Jennifer N.; Clubb, Fred J.; Wilson, Thomas S.; Miller, Matthew W.; Fossum, Theresa W.; Hartman, Jonathan; Tuzun, Egemen; Singhal, Pooja; Maitland, Duncan J.

    2013-01-01

    Cerebral aneurysms treated by traditional endovascular methods using platinum coils have a tendency to be unstable, either due to chronic inflammation, compaction of coils, or growth of the aneurysm. We propose to use alternate filling methods for the treatment of intracranial aneurysms using polyurethane based shape memory polymer (SMP) foams. SMP polyurethane foams were surgically implanted in a porcine aneurysm model to determine biocompatibility, localized thrombogenicity, and their abili...

  17. Recursive models of psychodynamics for prognosis of active control systems with memory

    Directory of Open Access Journals (Sweden)

    Володимир Олександрович Касьянов

    2014-09-01

    Full Text Available Abstracts of the articles are devoted to the scientific explanation of the phenomenon of managerial decision-making in the so-called active systems. Proposed functionals allow to model dynamic processes with "memory". This approach is applicable to a quasi-closed by information systems that are able to reduce its own entropy, being closed by the energy and substance. We construct the corresponding diagrams.

  18. Characterizing and modeling the free recovery and constrained recovery behavior of a polyurethane shape memory polymer

    OpenAIRE

    Volk, Brent L.; LAGOUDAS, Dimitris C.; Maitland, Duncan J.

    2011-01-01

    In this work, tensile tests and one-dimensional constitutive modeling are performed on a high recovery force polyurethane shape memory polymer that is being considered for biomedical applications. The tensile tests investigate the free recovery (zero load) response as well as the constrained displacement recovery (stress recovery) response at extension values up to 25%, and two consecutive cycles are performed during each test. The material is observed to recover 100% of the applied deformati...

  19. On the Entropy Based Associative Memory Model with Higher-Order Correlations

    Directory of Open Access Journals (Sweden)

    Masahiro Nakagawa

    2010-01-01

    Full Text Available In this paper, an entropy based associative memory model will be proposed and applied to memory retrievals with an orthogonal learning model so as to compare with the conventional model based on the quadratic Lyapunov functional to be minimized during the retrieval process. In the present approach, the updating dynamics will be constructed on the basis of the entropy minimization strategy which may be reduced asymptotically to the above-mentioned conventional dynamics as a special case ignoring the higher-order correlations. According to the introduction of the entropy functional, one may involve higer-order correlation effects between neurons in a self-contained manner without any heuristic coupling coefficients as in the conventional manner. In fact we shall show such higher order coupling tensors are to be uniquely determined in the framework of the entropy based approach. From numerical results, it will be found that the presently proposed novel approach realizes much larger memory capacity than that of the quadratic Lyapunov functional approach, e.g., associatron.

  20. An excitable cortex and memory model successfully predicts new pseudopod dynamics.

    Directory of Open Access Journals (Sweden)

    Robert M Cooper

    Full Text Available Motile eukaryotic cells migrate with directional persistence by alternating left and right turns, even in the absence of external cues. For example, Dictyostelium discoideum cells crawl by extending distinct pseudopods in an alternating right-left pattern. The mechanisms underlying this zig-zag behavior, however, remain unknown. Here we propose a new Excitable Cortex and Memory (EC&M model for understanding the alternating, zig-zag extension of pseudopods. Incorporating elements of previous models, we consider the cell cortex as an excitable system and include global inhibition of new pseudopods while a pseudopod is active. With the novel hypothesis that pseudopod activity makes the local cortex temporarily more excitable--thus creating a memory of previous pseudopod locations--the model reproduces experimentally observed zig-zag behavior. Furthermore, the EC&M model makes four new predictions concerning pseudopod dynamics. To test these predictions we develop an algorithm that detects pseudopods via hierarchical clustering of individual membrane extensions. Data from cell-tracking experiments agrees with all four predictions of the model, revealing that pseudopod placement is a non-Markovian process affected by the dynamics of previous pseudopods. The model is also compatible with known limits of chemotactic sensitivity. In addition to providing a predictive approach to studying eukaryotic cell motion, the EC&M model provides a general framework for future models, and suggests directions for new research regarding the molecular mechanisms underlying directional persistence.

  1. Experience-driven formation of parts-based representations in a model of layered visual memory

    Directory of Open Access Journals (Sweden)

    Jenia Jitsev

    2009-09-01

    Full Text Available Growing neuropsychological and neurophysiological evidence suggests that the visual cortex uses parts-based representations to encode, store and retrieve relevant objects. In such a scheme, objects are represented as a set of spatially distributed local features, or parts, arranged in stereotypical fashion. To encode the local appearance and to represent the relations between the constituent parts, there has to be an appropriate memory structure formed by previous experience with visual objects. Here, we propose a model how a hierarchical memory structure supporting efficient storage and rapid recall of parts-based representations can be established by an experience-driven process of self-organization. The process is based on the collaboration of slow bidirectional synaptic plasticity and homeostatic unit activity regulation, both running at the top of fast activity dynamics with winner-take-all character modulated by an oscillatory rhythm. These neural mechanisms lay down the basis for cooperation and competition between the distributed units and their synaptic connections. Choosing human face recognition as a test task, we show that, under the condition of open-ended, unsupervised incremental learning, the system is able to form memory traces for individual faces in a parts-based fashion. On a lower memory layer the synaptic structure is developed to represent local facial features and their interrelations, while the identities of different persons are captured explicitly on a higher layer. An additional property of the resulting representations is the sparseness of both the activity during the recall and the synaptic patterns comprising the memory traces.

  2. What's statistical about learning? Insights from modelling statistical learning as a set of memory processes.

    Science.gov (United States)

    Thiessen, Erik D

    2017-01-05

    Statistical learning has been studied in a variety of different tasks, including word segmentation, object identification, category learning, artificial grammar learning and serial reaction time tasks (e.g. Saffran et al. 1996 Science 274: , 1926-1928; Orban et al. 2008 Proceedings of the National Academy of Sciences 105: , 2745-2750; Thiessen & Yee 2010 Child Development 81: , 1287-1303; Saffran 2002 Journal of Memory and Language 47: , 172-196; Misyak & Christiansen 2012 Language Learning 62: , 302-331). The difference among these tasks raises questions about whether they all depend on the same kinds of underlying processes and computations, or whether they are tapping into different underlying mechanisms. Prior theoretical approaches to statistical learning have often tried to explain or model learning in a single task. However, in many cases these approaches appear inadequate to explain performance in multiple tasks. For example, explaining word segmentation via the computation of sequential statistics (such as transitional probability) provides little insight into the nature of sensitivity to regularities among simultaneously presented features. In this article, we will present a formal computational approach that we believe is a good candidate to provide a unifying framework to explore and explain learning in a wide variety of statistical learning tasks. This framework suggests that statistical learning arises from a set of processes that are inherent in memory systems, including activation, interference, integration of information and forgetting (e.g. Perruchet & Vinter 1998 Journal of Memory and Language 39: , 246-263; Thiessen et al. 2013 Psychological Bulletin 139: , 792-814). From this perspective, statistical learning does not involve explicit computation of statistics, but rather the extraction of elements of the input into memory traces, and subsequent integration across those memory traces that emphasize consistent information (Thiessen and Pavlik

  3. Designer receptors enhance memory in a mouse model of Down syndrome.

    Science.gov (United States)

    Fortress, Ashley M; Hamlett, Eric D; Vazey, Elena M; Aston-Jones, Gary; Cass, Wayne A; Boger, Heather A; Granholm, Ann-Charlotte E

    2015-01-28

    Designer receptors exclusively activated by designer drugs (DREADDs) are novel and powerful tools to investigate discrete neuronal populations in the brain. We have used DREADDs to stimulate degenerating neurons in a Down syndrome (DS) model, Ts65Dn mice. Individuals with DS develop Alzheimer's disease (AD) neuropathology and have elevated risk for dementia starting in their 30s and 40s. Individuals with DS often exhibit working memory deficits coupled with degeneration of the locus coeruleus (LC) norepinephrine (NE) neurons. It is thought that LC degeneration precedes other AD-related neuronal loss, and LC noradrenergic integrity is important for executive function, working memory, and attention. Previous studies have shown that LC-enhancing drugs can slow the progression of AD pathology, including amyloid aggregation, oxidative stress, and inflammation. We have shown that LC degeneration in Ts65Dn mice leads to exaggerated memory loss and neuronal degeneration. We used a DREADD, hM3Dq, administered via adeno-associated virus into the LC under a synthetic promoter, PRSx8, to selectively stimulate LC neurons by exogenous administration of the inert DREADD ligand clozapine-N-oxide. DREADD stimulation of LC-NE enhanced performance in a novel object recognition task and reduced hyperactivity in Ts65Dn mice, without significant behavioral effects in controls. To confirm that the noradrenergic transmitter system was responsible for the enhanced memory function, the NE prodrug l-threo-dihydroxyphenylserine was administered in Ts65Dn and normosomic littermate control mice, and produced similar behavioral results. Thus, NE stimulation may prevent memory loss in Ts65Dn mice, and may hold promise for treatment in individuals with DS and dementia. Copyright © 2015 the authors 0270-6474/15/351343-11$15.00/0.

  4. Effect of exercise on learning and memory in a rat model of developmental stress.

    Science.gov (United States)

    Grace, Laurian; Hescham, Sarah; Kellaway, Lauriston A; Bugarith, Kishor; Russell, Vivienne A

    2009-12-01

    Adverse life events occurring in early development can result in long-term effects on behavioural, physiological and cognitive processes. In particular, perinatal stressors impair neurogenesis in the hippocampus which consequently impairs memory formation. Exercise has previously been shown to have antidepressant effects and to increase cognitive functioning by increasing neurogenesis and neurotrophins in the hippocampus. The current study examined the effects of maternal separation, which has been shown to model anxiety in animals, and the effects of exercise on learning and memory. Forty-five male Sprague-Dawley rats were divided into four groups, maternally separated / non-runners, maternally separated / runners, non-separated / runners and non-separated / non-runners. Maternal separation occurred from postnatal day 2 (P2) to 14 (P14) for 3 h per day. Exercised rats were given voluntary access to individual running wheels attached to their cages from P29 to P49. Behavioural testing (Morris water maze (MWM) and object recognition tests) took place from P49 to P63. Maternally separated rats showed no significant difference in anxiety levels in the elevated plus maze and the open field compared to the normally reared controls. However, rats that were allowed voluntary access to running wheels showed increased levels of anxiety in the elevated plus maze and in the open field. Maternal separation did not have any effect on memory performance in the MWM or the object recognition tasks. Exercise increased spatial learning and memory in the MWM with the exercised rats displaying a decreased latency in locating the hidden platform than the non-exercised rats. The exercised rats spent significantly less time exploring the most recently encountered object in the temporal order task in comparison to the non-exercised controls, therefore showing improved temporal recognition memory. All groups performed the same on the other recognition tasks, with all rats showing intact

  5. Linking microcircuit dysfunction to cognitive impairment: effects of disinhibition associated with schizophrenia in a cortical working memory model

    National Research Council Canada - National Science Library

    Murray, John D; Anticevic, Alan; Gancsos, Mark; Ichinose, Megan; Corlett, Philip R; Krystal, John H; Wang, Xiao-Jing

    2014-01-01

    .... To elucidate the link between these phenomena, we incorporated synaptic disinhibition, via N-methyl-D-aspartate receptor perturbation on interneurons, into a network model of spatial working memory (WM...

  6. Working-memory capacity protects model-based learning from stress.

    Science.gov (United States)

    Otto, A Ross; Raio, Candace M; Chiang, Alice; Phelps, Elizabeth A; Daw, Nathaniel D

    2013-12-24

    Accounts of decision-making have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental advances suggest that this classic distinction between habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning, called model-free and model-based learning. Popular neurocomputational accounts of reward processing emphasize the involvement of the dopaminergic system in model-free learning and prefrontal, central executive-dependent control systems in model-based choice. Here we hypothesized that the hypothalamic-pituitary-adrenal (HPA) axis stress response--believed to have detrimental effects on prefrontal cortex function--should selectively attenuate model-based contributions to behavior. To test this, we paired an acute stressor with a sequential decision-making task that affords distinguishing the relative contributions of the two learning strategies. We assessed baseline working-memory (WM) capacity and used salivary cortisol levels to measure HPA axis stress response. We found that stress response attenuates the contribution of model-based, but not model-free, contributions to behavior. Moreover, stress-induced behavioral changes were modulated by individual WM capacity, such that low-WM-capacity individuals were more susceptible to detrimental stress effects than high-WM-capacity individuals. These results enrich existing accounts of the interplay between acute stress, working memory, and prefrontal function and suggest that executive function may be protective against the deleterious effects of acute stress.

  7. A Constitutive Model for Superelastic Shape Memory Alloys Considering the Influence of Strain Rate

    Directory of Open Access Journals (Sweden)

    Hui Qian

    2013-01-01

    Full Text Available Shape memory alloys (SMAs are a relatively new class of functional materials, exhibiting special thermomechanical behaviors, such as shape memory effect and superelasticity, which enable their applications in seismic engineering as energy dissipation devices. This paper investigates the properties of superelastic NiTi shape memory alloys, emphasizing the influence of strain rate on superelastic behavior under various strain amplitudes by cyclic tensile tests. A novel constitutive equation based on Graesser and Cozzarelli’s model is proposed to describe the strain-rate-dependent hysteretic behavior of superelastic SMAs at different strain levels. A stress variable including the influence of strain rate is introduced into Graesser and Cozzarelli’s model. To verify the effectiveness of the proposed constitutive equation, experiments on superelastic NiTi wires with different strain rates and strain levels are conducted. Numerical simulation results based on the proposed constitutive equation and experimental results are in good agreement. The findings in this paper will assist the future design of superelastic SMA-based energy dissipation devices for seismic protection of structures.

  8. Cusp catastrophe models for cognitive workload and fatigue in a verbally cued pictorial memory task.

    Science.gov (United States)

    Guastello, Stephen J; Boeh, Henry; Schimmels, Michael; Gorin, Hillary; Huschen, Samuel; Davis, Erin; Peters, Natalie E; Fabisch, Megan; Poston, Kirsten

    2012-10-01

    The aim of this study was to evaluate two cusp catastrophe models for cognitive workload and fatigue. They share similar cubic polynomial structures but derive from different underlying processes and contain variables that contribute to flexibility with respect to load and the ability to compensate for fatigue. Cognitive workload and fatigue both have a negative impact on performance and have been difficult to separate. Extended time on task can produce fatigue, but it can also produce a positive effect from learning or automaticity. In this two-part experiment, 129 undergraduates performed tasks involving spelling, arithmetic, memory, and visual search. The fatigue cusp for the central memory task was supported with the quantity of work performed and performance on an episodic memory task acting as the control parameters. There was a strong linear effect, however. The load manipulations for the central task were competition with another participant for rewards, incentive conditions, and time pressure. Results supported the workload cusp in which trait anxiety and the incentive manipulation acted as the control parameters. The cusps are generally better than linear models for analyzing workload and fatigue phenomena; practice effects can override fatigue. Future research should investigate multitasking and task sequencing issues, physical-cognitive task combinations, and a broader range of variables that contribute to flexibility with respect to load or compensate for fatigue. The new experimental medium and analytic strategy can be generalized to virtually any real-world cognitively demanding tasks. The particular results are generalizable to tasks involving visual search.

  9. A Reaction-Diffusion Model for Synapse Growth and Long-Term Memory

    Science.gov (United States)

    Liu, Kang; Lisman, John; Hagan, Michael

    Memory storage involves strengthening of synaptic transmission known as long-term potentiation (LTP). The late phase of LTP is associated with structural processes that enlarge the synapse. Yet, synapses must be stable, despite continual subunit turnover, over the lifetime of an encoded memory. These considerations suggest that synapses are variable-size stable structure (VSSS), meaning they can switch between multiple metastable structures with different sizes. The mechanisms underlying VSSS are poorly understood. While experiments and theory have suggested that the interplay between diffusion and receptor-scaffold interactions can lead to a preferred stable size for synaptic domains, such a mechanism cannot explain how synapses adopt widely different sizes. Here we develop a minimal reaction-diffusion model of VSSS for synapse growth, incorporating the recent observation from super-resolution microscopy that neural activity can build compositional heterogeneities within synaptic domains. We find that introducing such heterogeneities can change the stable domain size in a controlled manner. We discuss a potential connection between this model and experimental data on synapse sizes, and how it provides a possible mechanism to structurally encode graded long-term memory. We acknowledge the support from NSF INSPIRE Award number IOS-1526941 (KL, MFH, JL) and the Brandeis Center for Bioinspired Soft Materials, an NSF MRSEC, DMR- 1420382 (MFH).

  10. Directional Congestion and Regime Switching in a Long Memory Model for Electricity Prices

    DEFF Research Database (Denmark)

    Haldrup, Niels; Nielsen, Morten Ø.

    The functioning of electricity markets has experienced increasing complexityas a result of deregulation in recent years. Consequently this affects the multilateral price behaviour across regions with physical exchange of power. It has been documented elsewhere that features such aslong memory...... and regime switching reflecting congestion and non-congestion periods are empirically relevant and hence are features that need to be taken into account when modeling price behavior. In the present paper we further elaborate on the co-existence of long memory and regime switches by focusing on the effect...... that the direction of possible congestion episodes has on the price dynamics. Under non-congestion prices are identical. The direction of possible congestion is identified by the region with excess demand of power through the sign of price differences and hence three different states can be considered: Non...

  11. Olfactory memory is impaired in a triple transgenic model of Alzheimer disease.

    Science.gov (United States)

    Cassano, Tommaso; Romano, Adele; Macheda, Teresa; Colangeli, Roberto; Cimmino, Concetta Stefania; Petrella, Antonio; LaFerla, Frank M; Cuomo, Vincenzo; Gaetani, Silvana

    2011-10-31

    Olfactory memory dysfunctions were investigated in the triple-transgenic murine model of Alzheimer's disease (3 × Tg-AD). In the social transmission of food preference test, 3 × Tg-AD mice presented severe deficits in odor-based memory, without gross changes in general odor-ability. Aβ and tau immunoreactivity was not observed in the primary processing regions for odor, the olfactory bulbs (OBs), whereas marked immunostaining was present in the piriform, entorhinal, and orbitofrontal cortex, as well as in the hippocampus. Our results suggest that the impairment in olfactory-based information processing might arise from degenerative mechanisms mostly affecting higher cortical regions and limbic areas, such as the hippocampus. Copyright © 2011 Elsevier B.V. All rights reserved.

  12. Characterization of neuropeptide Y, Y(2) receptor knockout mice in two animal models of learning and memory processing.

    Science.gov (United States)

    Redrobe, John Paul; Dumont, Yvan; Herzog, Herbert; Quirion, Rémi

    2004-01-01

    Neuropeptide Y (NPY) and, in particular, the Y2 receptor subtype, has been suggested to be involved in learning and memory processing. However, the precise role of Y2 receptors in learning and memory remains unclear. In the present study, mice lacking NPY Y2-type receptors were assessed in two animal models of learning and memory processing. We found that NPY Y2-/- mice displayed a deficit on the probe trial in the Morris water maze task, whereas acquisition performance, swim speed, and visible platform performance did not differ significantly between groups. In addition, NPY Y2-/- mice exhibited a marked deterioration in object memory 6 h, but not 1 h, following initial exposure in the object recognition test. Both groups of mice showed similar locomotor activity profiles in a low-stress, open field test. These data support the hypothesis that Y2 receptors are involved in the regulation of learning and memory processing.

  13. A 3D finite strain phenomenological constitutive model for shape memory alloys considering martensite reorientation

    Science.gov (United States)

    Arghavani, J.; Auricchio, F.; Naghdabadi, R.; Reali, A.; Sohrabpour, S.

    2010-06-01

    Most devices based on shape memory alloys experience both finite deformations and non-proportional loading conditions in engineering applications. This motivates the development of constitutive models considering finite strain as well as martensite variant reorientation. To this end, in the present article, based on the principles of continuum thermodynamics with internal variables, a three-dimensional finite strain phenomenological constitutive model is proposed taking its basis from the recent model in the small strain regime proposed by Panico and Brinson (J Mech Phys Solids 55:2491-2511, 2007). In the finite strain constitutive model derivation, a multiplicative decomposition of the deformation gradient into elastic and inelastic parts, together with an additive decomposition of the inelastic strain rate tensor into transformation and reorientation parts is adopted. Moreover, it is shown that, when linearized, the proposed model reduces exactly to the original small strain model.

  14. Experimental static and dynamic tests on a large-scale free-form Voronoi grid shell mock-up in comparison with finite-element method results

    Science.gov (United States)

    Froli, Maurizio; Laccone, Francesco

    2017-09-01

    Grid shells supporting transparent or opaque panels are largely used to cover long-spanned spaces because of their lightness, the easy setup, and economy. This paper presents the results of experimental static and dynamic investigations carried out on a large-scale free-form grid shell mock-up, whose geometry descended from an innovative Voronoi polygonal pattern. Accompanying finite-element method (FEM) simulations followed. To these purposes, a four-step procedure was adopted: (1) a perfect FEM model was analyzed; (2) using the modal shapes scaled by measuring the mock-up, a deformed unloaded geometry was built, which took into account the defects caused by the assembly phase; (3) experimental static tests were executed by affixing weights to the mock-up, and a simplified representative FEM model was calibrated, choosing the nodes stiffness and the material properties as parameters; and (4) modal identification was performed through operational modal analysis and impulsive tests, and then, a simplified FEM dynamical model was calibrated. Due to the high deformability of the mock-up, only a symmetric load case configuration was adopted.

  15. Gender-schema development and children's constructive story memory: evidence for a developmental model.

    Science.gov (United States)

    Welch-Ross, M K; Schmidt, C R

    1996-06-01

    The objectives of the present research were to (a) provide a developmental model based on script research for describing how changes in memory for gender-related information are related to changes in gender-role stereotypes, (b) examine developmental differences in the effect of stereotype manipulations on the construction of new memories, and (c) examine the relation between stereotyped activity preferences and memory for gender-related information. 4-, 6-, and 8-year-olds listened to a story in which characters performed behaviors typical and atypical of gender-role stereotypes. An introduction preceded the story in which story characters' activities and preferences were described as either consistent or inconsistent with gender-role stereotypes. Dependent variables were the percentage of typical and atypical story items correctly recognized and the percentage of false alarms made for new items. Gender-role knowledge, stereotyped preferences, and gender-role flexibility were assessed. Results for false alarms, but not hit rates, supported the hypotheses of the model: (a) 6-year-olds falsely recognized typical distractors more than atypical distractors (this effect was nonsignificant for 4- and 8-year-olds), (b) false alarms for atypical distractors decreased between ages 4 and 6, and (c) false alarms for typical distractors decreased between ages 6 and 8. Contrary to expectation, stereotype manipulation effects did not interact with age, but were influenced by gender. Stereotyped preferences were strongly related to memory for gender-related information for both males and females. Results are discussed in terms of developmental and individual differences in gender-schema strength and composition.

  16. Kinetic order-disorder transitions in a pause-and-go swarming model with memory.

    Science.gov (United States)

    Rimer, Oren; Ariel, Gil

    2017-04-21

    A two dimensional model of self-propelled particles combining both a pause-and-go movement pattern and memory is studied in simulations. It is shown, that in contrast to previously studied agent based models in two-dimensions, order and disorder are metastable states that can co-exist at some parameter range. In particular, this implies that the formation and decay of global order in swarms may be kinetic rather than a phase transition. Our results explain metastability recently observed in swarming locust and fish. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Graph-Theoretic Properties of Networks Based on Word Association Norms: Implications for Models of Lexical Semantic Memory

    Science.gov (United States)

    Gruenenfelder, Thomas M.; Recchia, Gabriel; Rubin, Tim; Jones, Michael N.

    2016-01-01

    We compared the ability of three different contextual models of lexical semantic memory (BEAGLE, Latent Semantic Analysis, and the Topic model) and of a simple associative model (POC) to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network…

  18. NAAG Peptidase Inhibitors Act via mGluR3: Animal Models of Memory, Alzheimer's, and Ethanol Intoxication.

    Science.gov (United States)

    Olszewski, Rafal T; Janczura, Karolina J; Bzdega, Tomasz; Der, Elise K; Venzor, Faustino; O'Rourke, Brennen; Hark, Timothy J; Craddock, Kirsten E; Balasubramanian, Shankar; Moussa, Charbel; Neale, Joseph H

    2017-09-01

    Glutamate carboxypeptidase II (GCPII) inactivates the peptide neurotransmitter N-acetylaspartylglutamate (NAAG) following synaptic release. Inhibitors of GCPII increase extracellular NAAG levels and are efficacious in animal models of clinical disorders via NAAG activation of a group II metabotropic glutamate receptor. mGluR2 and mGluR3 knock-out (ko) mice were used to test the hypothesis that mGluR3 mediates the activity of GCPII inhibitors ZJ43 and 2-PMPA in animal models of memory and memory loss. Short- (1.5 h) and long- (24 h) term novel object recognition tests were used to assess memory. Treatment with ZJ43 or 2-PMPA prior to acquisition trials increased long-term memory in mGluR2, but not mGluR3, ko mice. Nine month-old triple transgenic Alzheimer's disease model mice exhibited impaired short-term novel object recognition memory that was rescued by treatment with a NAAG peptidase inhibitor. NAAG peptidase inhibitors and the group II mGluR agonist, LY354740, reversed the short-term memory deficit induced by acute ethanol administration in wild type mice. 2-PMPA also moderated the effect of ethanol on short-term memory in mGluR2 ko mice but failed to do so in mGluR3 ko mice. LY354740 and ZJ43 blocked ethanol-induced motor activation. Both GCPII inhibitors and LY354740 also significantly moderated the loss of motor coordination induced by 2.1 g/kg ethanol treatment. These data support the conclusion that inhibitors of glutamate carboxypeptidase II are efficacious in object recognition models of normal memory and memory deficits via an mGluR3 mediated process, actions that could have widespread clinical applications.

  19. Mitochondrial Superoxide Contributes to Hippocampal Synaptic Dysfunction and Memory Deficits in Angelman Syndrome Model Mice.

    Science.gov (United States)

    Santini, Emanuela; Turner, Kathryn L; Ramaraj, Akila B; Murphy, Michael P; Klann, Eric; Kaphzan, Hanoch

    2015-12-09

    Angelman syndrome (AS) is a neurodevelopmental disorder associated with developmental delay, lack of speech, motor dysfunction, and epilepsy. In the majority of the patients, AS is caused by the deletion of small portions of maternal chromosome 15 harboring the UBE3A gene. This results in a lack of expression of the UBE3A gene because the paternal allele is genetically imprinted. The UBE3A gene encodes an enzyme termed ubiquitin ligase E3A (E6-AP) that targets proteins for degradation by the 26S proteasome. Because neurodegenerative disease and other neurodevelopmental disorders have been linked to oxidative stress, we asked whether mitochondrial reactive oxygen species (ROS) played a role in impaired synaptic plasticity and memory deficits exhibited by AS model mice. We discovered that AS mice have increased levels of superoxide in area CA1 of the hippocampus that is reduced by MitoQ 10-methanesuflonate (MitoQ), a mitochondria-specific antioxidant. In addition, we found that MitoQ rescued impairments in hippocampal synaptic plasticity and deficits in contextual fear memory exhibited by AS model mice. Our findings suggest that mitochondria-derived oxidative stress contributes to hippocampal pathophysiology in AS model mice and that targeting mitochondrial ROS pharmacologically could benefit individuals with AS. Oxidative stress has been hypothesized to contribute to the pathophysiology of neurodevelopmental disorders, including autism spectrum disorders and Angelman syndrome (AS). Herein, we report that AS model mice exhibit elevated levels of mitochondria-derived reactive oxygen species in pyramidal neurons in hippocampal area CA1. Moreover, we demonstrate that the administration of MitoQ (MitoQ 10-methanesuflonate), a mitochondria-specific antioxidant, to AS model mice normalizes synaptic plasticity and restores memory. Finally, our findings suggest that antioxidants that target the mitochondria could be used therapeutically to ameliorate synaptic and cognitive

  20. Dynamic source routing strategy for two-level flows on scale-free networks.

    Science.gov (United States)

    Jiang, Zhong-Yuan; Liang, Man-Gui; Wu, Jia-Jing

    2013-01-01

    Packets transmitting in real communication networks such as the Internet can be classified as time-sensitive or time-insensitive. To better support the real-time and time-insensitive applications, we propose a two-level flow traffic model in which packets are labeled as level-1 or level-2, and those with level-1 have higher priority to be transmitted. In order to enhance the traffic capacity of the two-level flow traffic model, we expand the global dynamic routing strategy and propose a new dynamic source routing which supports no routing-flaps, high traffic capacity, and diverse traffic flows. As shown in this paper, the proposed dynamic source routing can significantly enhance the traffic capacity and quality of time-sensitive applications compared with the global shortest path routing strategy.

  1. Hirano body expression impairs spatial working memory in a novel mouse model.

    Science.gov (United States)

    Furgerson, Matthew; Clark, Jason K; Crystal, Jonathon D; Wagner, John J; Fechheimer, Marcus; Furukawa, Ruth

    2014-09-02

    Hirano bodies are actin-rich intracellular inclusions found in the brains of patients with neurodegenerative conditions such as Alzheimer's disease or frontotemporal lobar degeneration-tau. While Hirano body ultrastructure and protein composition have been well studied, little is known about the physiological function of Hirano bodies in an animal model system. Utilizing a Cre/Lox system, we have generated a new mouse model which develops an age-dependent increase in the number of model Hirano bodies present in both the CA1 region of the hippocampus and frontal cortex. These mice develop normally and experience no overt neuron loss. Mice presenting model Hirano bodies have no abnormal anxiety or locomotor activity as measured by the open field test. However, mice with model Hirano bodies develop age-dependent impairments in spatial working memory performance assessed using a delayed win-shift task in an 8-arm radial maze. Synaptic transmission, short-term plasticity, and long-term plasticity was measured in the CA1 region from slices obtained from both the ventral and dorsal hippocampus in the same mice whose spatial working memory was assessed. Baseline synaptic responses, paired pulse stimulation and long-term potentiation measurements in the ventral hippocampus were indistinguishable from control mice. In contrast, in the dorsal hippocampus, synaptic transmission at higher stimulus intensities were suppressed in 3 month old mice with Hirano bodies as compared with control mice. In addition, long-term potentiation was enhanced in the dorsal hippocampus of 8 month old mice with Hirano bodies, concurrent with observed impairment of spatial working memory. Finally, an inflammatory response was observed at 8 months of age in mice with Hirano bodies as assessed by the presence of reactive astrocytes. This study shows that the presence of model Hirano bodies initiates an inflammatory response, alters hippocampal synaptic responses, and impairs spatial working memory

  2. Ordered Short-Term Memory Differs in Signers and Speakers: Implications for Models of Short-Term Memory

    Science.gov (United States)

    Bavelier, Daphne; Newport, Elissa L.; Hall, Matt; Supalla, Ted; Boutla, Mrim

    2008-01-01

    Capacity limits in linguistic short-term memory (STM) are typically measured with forward span tasks in which participants are asked to recall lists of words in the order presented. Using such tasks, native signers of American Sign Language (ASL) exhibit smaller spans than native speakers ([Boutla, M., Supalla, T., Newport, E. L., & Bavelier, D.…

  3. Effects of degraded sensory input on memory for speech: Behavioral data and a test of biologically constrained computational models

    Science.gov (United States)

    Piquado, Tepring; Cousins, Katheryn A.Q.; Wingfield, Arthur; Miller, Paul

    2010-01-01

    Poor hearing acuity reduces memory for spoken words, even when the words are presented with enough clarity for correct recognition. An "effortful hypothesis" suggests that the perceptual effort needed for recognition draws from resources that would otherwise be available for encoding the word in memory. To assess this hypothesis, we conducted a behavioral task requiring immediate free recall of word-lists, some of which contained an acoustically masked word that was just above perceptual threshold. Results show that masking a word reduces the recall of that word and words prior to it, as well as weakening the linking associations between the masked and prior words. In contrast, recall probabilities of words following the masked word are not affected. To account for this effect we conducted computational simulations testing two classes of models: associative linking models and short-term memory buffer models. Only a model that integrated both contextual linking and buffer components matched all of the effects of masking observed in our behavioral data. In this Linking-Buffer model, the masked word disrupts a short-term memory buffer, causing associative links of words in the buffer to be weakened, affecting memory for the masked word and the word prior to it, while allowing links of words following the masked word to be spared. We suggest that these data account for the so-called "effortful hypothesis", where distorted input has a detrimental impact on prior information stored in short-term memory. PMID:20875801

  4. Emergence of scale-free close-knit friendship structure in online social networks.

    Directory of Open Access Journals (Sweden)

    Ai-Xiang Cui

    Full Text Available Although the structural properties of online social networks have attracted much attention, the properties of the close-knit friendship structures remain an important question. Here, we mainly focus on how these mesoscale structures are affected by the local and global structural properties. Analyzing the data of four large-scale online social networks reveals several common structural properties. It is found that not only the local structures given by the indegree, outdegree, and reciprocal degree distributions follow a similar scaling behavior, the mesoscale structures represented by the distributions of close-knit friendship structures also exhibit a similar scaling law. The degree correlation is very weak over a wide range of the degrees. We propose a simple directed network model that captures the observed properties. The model incorporates two mechanisms: reciprocation and preferential attachment. Through rate equation analysis of our model, the local-scale and mesoscale structural properties are derived. In the local-scale, the same scaling behavior of indegree and outdegree distributions stems from indegree and outdegree of nodes both growing as the same function of the introduction time, and the reciprocal degree distribution also shows the same power-law due to the linear relationship between the reciprocal degree and in/outdegree of nodes. In the mesoscale, the distributions of four closed triples representing close-knit friendship structures are found to exhibit identical power-laws, a behavior attributed to the negligible degree correlations. Intriguingly, all the power-law exponents of the distributions in the local-scale and mesoscale depend only on one global parameter, the mean in/outdegree, while both the mean in/outdegree and the reciprocity together determine the ratio of the reciprocal degree of a node to its in/outdegree. Structural properties of numerical simulated networks are analyzed and compared with each of the four

  5. A novel approach to an old problem: analysis of systematic errors in two models of recognition memory.

    Science.gov (United States)

    Dede, Adam J O; Squire, Larry R; Wixted, John T

    2014-01-01

    For more than a decade, the high threshold dual process (HTDP) model has served as a guide for studying the functional neuroanatomy of recognition memory. The HTDP model's utility has been that it provides quantitative estimates of recollection and familiarity, two processes thought to support recognition ability. Important support for the model has been the observation that it fits experimental data well. The continuous dual process (CDP) model also fits experimental data well. However, this model does not provide quantitative estimates of recollection and familiarity, making it less immediately useful for illuminating the functional neuroanatomy of recognition memory. These two models are incompatible and cannot both be correct, and an alternative method of model comparison is needed. We tested for systematic errors in each model's ability to fit recognition memory data from four independent data sets from three different laboratories. Across participants and across data sets, the HTDP model (but not the CDP model) exhibited systematic error. In addition, the pattern of errors exhibited by the HTDP model was predicted by the CDP model. We conclude that the CDP model provides a better account of recognition memory than the HTDP model. © 2013 Published by Elsevier Ltd.

  6. Working Memory and Decision-Making in a Frontoparietal Circuit Model.

    Science.gov (United States)

    Murray, John D; Jaramillo, Jorge; Wang, Xiao-Jing

    2017-12-13

    Working memory (WM) and decision-making (DM) are fundamental cognitive functions involving a distributed interacting network of brain areas, with the posterior parietal cortex (PPC) and prefrontal cortex (PFC) at the core. However, the shared and distinct roles of these areas and the nature of their coordination in cognitive function remain poorly understood. Biophysically based computational models of cortical circuits have provided insights into the mechanisms supporting these functions, yet they have primarily focused on the local microcircuit level, raising questions about the principles for distributed cognitive computation in multiregional networks. To examine these issues, we developed a distributed circuit model of two reciprocally interacting modules representing PPC and PFC circuits. The circuit architecture includes hierarchical differences in local recurrent structure and implements reciprocal long-range projections. This parsimonious model captures a range of behavioral and neuronal features of frontoparietal circuits across multiple WM and DM paradigms. In the context of WM, both areas exhibit persistent activity, but, in response to intervening distractors, PPC transiently encodes distractors while PFC filters distractors and supports WM robustness. With regard to DM, the PPC module generates graded representations of accumulated evidence supporting target selection, while the PFC module generates more categorical responses related to action or choice. These findings suggest computational principles for distributed, hierarchical processing in cortex during cognitive function and provide a framework for extension to multiregional models.SIGNIFICANCE STATEMENT Working memory and decision-making are fundamental "building blocks" of cognition, and deficits in these functions are associated with neuropsychiatric disorders such as schizophrenia. These cognitive functions engage distributed networks with prefrontal cortex (PFC) and posterior parietal cortex

  7. New perspectives on the brain lesion approach - implications for theoretical models of human memory.

    Science.gov (United States)

    Irish, Muireann; van Kesteren, Marlieke T R

    2017-11-06

    Human lesion studies represent the cornerstone of modern day neuropsychology and provide an important adjunct to functional neuroimaging methods. The study of human lesion groups with damage to distinct regions of the brain permits the identification of underlying mechanisms and structures not only associated with, but essential for, complex cognitive processes. Here, we consider a recent review by McCormick et al. in which the power of the lesion model approach is elegantly presented with respect to a host of sophisticated cognitive endeavours, including autobiographical memory, future thinking, spatial navigation, and decision-making. By comparing profiles of loss and sparing in hippocampal (HC) and ventromedial prefrontal cortex (vmPFC) lesion groups, the authors provide new insights into the underlying neuroarchitecture of these diverse cognitive functions. Building on this framework, we consider how vmPFC and HC degeneration, in the context of large-scale network dysfunction in dementia, impacts discrete facets of memory and social cognition. Notably, we find remarkable concordance between the available evidence in dementia and that of the HC and vmPFC lesion literature. We further assess the role of the prefrontal cortex in modulating aspects of spatial navigation and discuss the role of schema-related processing in the service of memory more broadly. Far from being obsolete, we contend that human lesion work occupies a crucial position in cognitive neuroscience and offers an array of exciting areas for future study within this field. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

  8. Exercise can rescue recognition memory impairment in a model with reduced adult hippocampal neurogenesis

    Directory of Open Access Journals (Sweden)

    Pauline Lafenetre

    2010-02-01

    Full Text Available Running is a potent stimulator of cell proliferation in the adult dentate gyrus and these newly generated hippocampal neurons seem to be implicated in memory functions. Here we have used a mouse model expressing activated Ras under the direction of the neuronal Synapsin I promoter (named synRas mice. These mice develop down-regulated proliferation of adult hippocampal precursor cells and show decreased short-term recognition memory performances. Voluntary physical activity reversed the genetically blocked generation of hippocampal proliferating cells and enhanced the dendritic arborisation of the resulting doublecortin newly generated neurons. Moreover, running improved novelty recognition in both wild type and synRas littermates, compensating their memory deficits. Brain-derived neurotrophic factor (BDNF has been proposed to be a potential mediator of physical exercise acting in the hippocampus on dentate neurons and their precursors. This was confirmed here by the identification of doublecortin-immunoreactive cells expressing TrkB BDNF receptor. While no difference in BDNF levels were detected in basal conditions between the synRas mice and their wild type littermates, running was associated with enhanced BDNF expression levels. Thus increased BDNF signalling is a candidate mechanism to explain the observed effects of running. Our studies demonstrate that voluntary physical activity has a robust beneficial effect even in mice with genetically restricted neurogenesis and cognition.

  9. Moringa oleifera Mitigates Memory Impairment and Neurodegeneration in Animal Model of Age-Related Dementia

    Directory of Open Access Journals (Sweden)

    Chatchada Sutalangka

    2013-01-01

    Full Text Available To date, the preventive strategy against dementia is still essential due to the rapid growth of its prevalence and the limited therapeutic efficacy. Based on the crucial role of oxidative stress in age-related dementia and the antioxidant and nootropic activities of Moringa oleifera, the enhancement of spatial memory and neuroprotection of M. oleifera leaves extract in animal model of age-related dementia was determined. The possible underlying mechanism was also investigated. Male Wistar rats, weighing 180–220 g, were orally given M. oleifera leaves extract at doses of 100, 200, and 400 mg/kg at a period of 7 days before and 7 days after the intracerebroventricular administration of AF64A bilaterally. Then, they were assessed memory, neuron density, MDA level, and the activities of SOD, CAT, GSH-Px, and AChE in hippocampus. The results showed that the extract improved spatial memory and neurodegeneration in CA1, CA2, CA3, and dentate gyrus of hippocampus together with the decreased MDA level and AChE activity but increased SOD and CAT activities. Therefore, our data suggest that M. oleifera leaves extract is the potential cognitive enhancer and neuroprotectant. The possible mechanism might occur partly via the decreased oxidative stress and the enhanced cholinergic function. However, further explorations concerning active ingredient(s are still required.

  10. A mismatch-based model for memory reconsolidation and extinction in attractor networks.

    Directory of Open Access Journals (Sweden)

    Remus Osan

    Full Text Available The processes of memory reconsolidation and extinction have received increasing attention in recent experimental research, as their potential clinical applications begin to be uncovered. A number of studies suggest that amnestic drugs injected after reexposure to a learning context can disrupt either of the two processes, depending on the behavioral protocol employed. Hypothesizing that reconsolidation represents updating of a memory trace in the hippocampus, while extinction represents formation of a new trace, we have built a neural network model in which either simple retrieval, reconsolidation or extinction of a stored attractor can occur upon contextual reexposure, depending on the similarity between the representations of the original learning and reexposure sessions. This is achieved by assuming that independent mechanisms mediate Hebbian-like synaptic strengthening and mismatch-driven labilization of synaptic changes, with protein synthesis inhibition preferentially affecting the former. Our framework provides a unified mechanistic explanation for experimental data showing (a the effect of reexposure duration on the occurrence of reconsolidation or extinction and (b the requirement of memory updating during reexposure to drive reconsolidation.

  11. Mitochondrial modulators improve lipid composition and attenuate memory deficits in experimental model of Huntington's disease.

    Science.gov (United States)

    Mehrotra, Arpit; Sood, Abhilasha; Sandhir, Rajat

    2015-12-01

    3-Nitropropionic acid (3-NP) is an irreversible inhibitor of succinate dehydrogenase and induces neuropathological changes similar to those observed in Huntington's disease (HD). The objective of the present study was to investigate neuroprotective effect of mitochondrial modulators; alpha-lipoic acid (ALA) and acetyl-L-carnitine (ALCAR) on 3-NP-induced alterations in mitochondrial lipid composition, mitochondrial structure and memory functions. Experimental model of HD was developed by administering 3-NP at sub-chronic doses, twice daily for 17 days. The levels of conjugated dienes, cholesterol and glycolipids were significantly increased, whereas the levels of phospholipids (phosphatidylethanolamine, phosphatidylcholine, phosphatidylserine) including cardiolipin were significantly decreased in the mitochondria isolated from the striatum of 3-NP-treated animals. In addition, the difference in molecular composition of each phospholipid class was also evaluated using mass spectrometry. Mitochondria lipid from 3-NP-treated animals showed increased cholesterol to phospholipid ratio, suggesting decreased mitochondrial membrane fluidity. 3-NP administration also resulted in ultra-structural changes in mitochondria, accompanied by swelling as assessed by transmission electron microscopy. The 3-NP administered animals had impaired spatial memory evaluated using elevated plus maze test. However, combined supplementation with ALA + ALCAR for 21 days normalized mitochondrial lipid composition, improved mitochondrial structure and ameliorated memory impairments in 3-NP-treated animals, suggesting an imperative role of these two modulators in combination in the management of HD.

  12. A Collective Study on Modeling and Simulation of Resistive Random Access Memory.

    Science.gov (United States)

    Panda, Debashis; Sahu, Paritosh Piyush; Tseng, Tseung Yuen

    2018-01-10

    In this work, we provide a comprehensive discussion on the various models proposed for the design and description of resistive random access memory (RRAM), being a nascent technology is heavily reliant on accurate models to develop efficient working designs and standardize its implementation across devices. This review provides detailed information regarding the various physical methodologies considered for developing models for RRAM devices. It covers all the important models reported till now and elucidates their features and limitations. Various additional effects and anomalies arising from memristive system have been addressed, and the solutions provided by the models to these problems have been shown as well. All the fundamental concepts of RRAM model development such as device operation, switching dynamics, and current-voltage relationships are covered in detail in this work. Popular models proposed by Chua, HP Labs, Yakopcic, TEAM, Stanford/ASU, Ielmini, Berco-Tseng, and many others have been compared and analyzed extensively on various parameters. The working and implementations of the window functions like Joglekar, Biolek, Prodromakis, etc. has been presented and compared as well. New well-defined modeling concepts have been discussed which increase the applicability and accuracy of the models. The use of these concepts brings forth several improvements in the existing models, which have been enumerated in this work. Following the template presented, highly accurate models would be developed which will vastly help future model developers and the modeling community.

  13. A Collective Study on Modeling and Simulation of Resistive Random Access Memory

    Science.gov (United States)

    Panda, Debashis; Sahu, Paritosh Piyush; Tseng, Tseung Yuen

    2018-01-01

    In this work, we provide a comprehensive discussion on the various models proposed for the design and description of resistive random access memory (RRAM), being a nascent technology is heavily reliant on accurate models to develop efficient working designs and standardize its implementation across devices. This review provides detailed information regarding the various physical methodologies considered for developing models for RRAM devices. It covers all the important models reported till now and elucidates their features and limitations. Various additional effects and anomalies arising from memristive system have been addressed, and the solutions provided by the models to these problems have been shown as well. All the fundamental concepts of RRAM model development such as device operation, switching dynamics, and current-voltage relationships are covered in detail in this work. Popular models proposed by Chua, HP Labs, Yakopcic, TEAM, Stanford/ASU, Ielmini, Berco-Tseng, and many others have been compared and analyzed extensively on various parameters. The working and implementations of the window functions like Joglekar, Biolek, Prodromakis, etc. has been presented and compared as well. New well-defined modeling concepts have been discussed which increase the applicability and accuracy of the models. The use of these concepts brings forth several improvements in the existing models, which have been enumerated in this work. Following the template presented, highly accurate models would be developed which will vastly help future model developers and the modeling community.

  14. Large-scale free surface measurement for the analysis of ship waves in a towing tank

    Science.gov (United States)

    Gomit, Guillaume; Chatellier, Ludovic; Calluaud, Damien; David, Laurent; Fréchou, Didier; Boucheron, Romuald; Perelman, Olivier; Hubert, Christian

    2015-10-01

    This paper is presenting an optical method for free surface measurement of a stationary flow suitable for large-scale experiments in a large towing tank. The new measurement device is based on the projection of laser beams on the surface of the fluid and on the use of a stereoscopic system. The principle of the method is to detect the impact of the laser beams on the air/water interface in order to determine the height of the surface by triangulation for a given number of positions. This method is applied to the measurement of the stationary wave field around a ship model at 1/10th scale. The paper also emphasizes that for low Froude numbers, (( F L = U/√( gL), where U is the ship velocity and L the ship length), the effects of the scale on the flow characteristics are limited. These scale effects are studied by comparison with measurements taken in a smaller towing tank around the same ship model at scale 1/77.5. The free surface and the velocity field near the hull at the two scales are compared.

  15. How scale-free networks and large-scale collective cooperation emerge in complex homogeneous social systems.

    Science.gov (United States)

    Li, Wei; Zhang, Xiaoming; Hu, Gang

    2007-10-01

    We study how heterogeneous degree distributions and large-scale collective cooperation in social networks emerge in complex homogeneous systems by a simple local rule: learning from the best in both strategy selections and linking choices. The prisoner's dilemma game is used as the local dynamics. We show that the social structure may evolve into single-scale, broad-scale, and scale-free (SF) degree distributions for different control parameters. In particular, in a relatively strong-selfish parameter region the SF property can be self-organized in social networks by dynamic evolutions and these SF structures help the whole node community to reach a high level of cooperation under the poor condition of a high selfish intention of individuals.

  16. A Bayesian hierarchical model for the measurement of working memory capacity

    NARCIS (Netherlands)

    Morey, Richard D.

    Working memory is the memory system that allows for conscious storage and manipulation of information. The capacity of working memory is extremely limited. Measurements of this limit, and what affects it, are critical to understanding working memory. Cowan (2001) and Pashler (1988) suggested

  17. Persistent short-term memory defects following sleep deprivation in a drosophila model of Parkinson disease.

    Science.gov (United States)

    Seugnet, Laurent; Galvin, James E; Suzuki, Yasuko; Gottschalk, Laura; Shaw, Paul J

    2009-08-01

    Parkinson disease (PD) is the second most common neurodegenerative disorder in the United States. It is associated with motor deficits, sleep disturbances, and cognitive impairment. The pathology associated with PD and the effects of sleep deprivation impinge, in part, upon common molecular pathways suggesting that sleep loss may be particularly deleterious to the degenerating brain. Thus we investigated the long-term consequences of sleep deprivation on shortterm memory using a Drosophila model of Parkinson disease. Transgenic strains of Drosophila melanogaster. Using the GAL4-UAS system, human alpha-synuclein was expressed throughout the nervous system of adult flies. Alpha-synuclein expressing flies (alpha S flies) and the corresponding genetic background controls were sleep deprived for 12 h at age 16 days and allowed to recover undisturbed for at least 3 days. Short-term memory was evaluated using aversive phototaxis suppression. Dopaminergic systems were assessed using mRNA profiling and immunohistochemistry. MEASURMENTS AND RESULTS: When sleep deprived at an intermediate stage of the pathology, alpha S flies showed persistent short-term memory deficits that lasted > or = 3 days. Cognitive deficits were not observed in younger alpha S flies nor in genetic background controls. Long-term impairments were not associated with accelerated loss of dopaminergic neurons. However mRNA expression of the dopamine receptors dDA1 and DAMB were significantly increased in sleep deprived alpha S flies. Blocking D1-like receptors during sleep deprivation prevented persistent shortterm memory deficits. Importantly, feeding flies the polyphenolic compound curcumin blocked long-term learning deficits. These data emphasize the importance of sleep in a degenerating/reorganizing brain and shows that pathological processes induced by sleep deprivation can be dissected at the molecular and cellular level using Drosophila genetics.

  18. Xenon impairs reconsolidation of fear memories in a rat model of post-traumatic stress disorder (PTSD).

    Science.gov (United States)

    Meloni, Edward G; Gillis, Timothy E; Manoukian, Jasmine; Kaufman, Marc J

    2014-01-01

    Xenon (Xe) is a noble gas that has been developed for use in people as an inhalational anesthestic and a diagnostic imaging agent. Xe inhibits glutamatergic N-methyl-D-aspartate (NMDA) receptors involved in learning and memory and can affect synaptic plasticity in the amygdala and hippocampus, two brain areas known to play a role in fear conditioning models of post-traumatic stress disorder (PTSD). Because glutamate receptors also have been shown to play a role in fear memory reconsolidation--a state in which recalled memories become susceptible to modification--we examined whether Xe administered after fear memory reactivation could affect subsequent expression of fear-like behavior (freezing) in rats. Male Sprague-Dawley rats were trained for contextual and cued fear conditioning and the effects of inhaled Xe (25%, 1 hr) on fear memory reconsolidation were tested using conditioned freezing measured days or weeks after reactivation/Xe administration. Xe administration immediately after fear memory reactivation significantly reduced conditioned freezing when tested 48 h, 96 h or 18 d after reactivation/Xe administration. Xe did not affect freezing when treatment was delayed until 2 h after reactivation or when administered in the absence of fear memory reactivation. These data suggest that Xe substantially and persistently inhibits memory reconsolidation in a reactivation and time-dependent manner, that it could be used as a new research tool to characterize reconsolidation and other memory processes, and that it could be developed to treat people with PTSD and other disorders related to emotional memory.

  19. Xenon Impairs Reconsolidation of Fear Memories in a Rat Model of Post-Traumatic Stress Disorder (PTSD)

    Science.gov (United States)

    Meloni, Edward G.; Gillis, Timothy E.; Manoukian, Jasmine; Kaufman, Marc J.

    2014-01-01

    Xenon (Xe) is a noble gas that has been developed for use in people as an inhalational anesthestic and a diagnostic imaging agent. Xe inhibits glutamatergic N-methyl-D-aspartate (NMDA) receptors involved in learning and memory and can affect synaptic plasticity in the amygdala and hippocampus, two brain areas known to play a role in fear conditioning models of post-traumatic stress disorder (PTSD). Because glutamate receptors also have been shown to play a role in fear memory reconsolidation – a state in which recalled memories become susceptible to modification – we examined whether Xe administered after fear memory reactivation could affect subsequent expression of fear-like behavior (freezing) in rats. Male Sprague-Dawley rats were trained for contextual and cued fear conditioning and the effects of inhaled Xe (25%, 1 hr) on fear memory reconsolidation were tested using conditioned freezing measured days or weeks after reactivation/Xe administration. Xe administration immediately after fear memory reactivation significantly reduced conditioned freezing when tested 48 h, 96 h or 18 d after reactivation/Xe administration. Xe did not affect freezing when treatment was delayed until 2 h after reactivation or when administered in the absence of fear memory reactivation. These data suggest that Xe substantially and persistently inhibits memory reconsolidation in a reactivation and time-dependent manner, that it could be used as a new research tool to characterize reconsolidation and other memory processes, and that it could be developed to treat people with PTSD and other disorders related to emotional memory. PMID:25162644

  20. Xenon impairs reconsolidation of fear memories in a rat model of post-traumatic stress disorder (PTSD.

    Directory of Open Access Journals (Sweden)

    Edward G Meloni

    Full Text Available Xenon (Xe is a noble gas that has been developed for use in people as an inhalational anesthestic and a diagnostic imaging agent. Xe inhibits glutamatergic N-methyl-D-aspartate (NMDA receptors involved in learning and memory and can affect synaptic plasticity in the amygdala and hippocampus, two brain areas known to play a role in fear conditioning models of post-traumatic stress disorder (PTSD. Because glutamate receptors also have been shown to play a role in fear memory reconsolidation--a state in which recalled memories become susceptible to modification--we examined whether Xe administered after fear memory reactivation could affect subsequent expression of fear-like behavior (freezing in rats. Male Sprague-Dawley rats were trained for contextual and cued fear conditioning and the effects of inhaled Xe (25%, 1 hr on fear memory reconsolidation were tested using conditioned freezing measured days or weeks after reactivation/Xe administration. Xe administration immediately after fear memory reactivation significantly reduced conditioned freezing when tested 48 h, 96 h or 18 d after reactivation/Xe administration. Xe did not affect freezing when treatment was delayed until 2 h after reactivation or when administered in the absence of fear memory reactivation. These data suggest that Xe substantially and persistently inhibits memory reconsolidation in a reactivation and time-dependent manner, that it could be used as a new research tool to characterize reconsolidation and other memory processes, and that it could be developed to treat people with PTSD and other disorders related to emotional memory.

  1. Physical electro-thermal model of resistive switching in bi-layered resistance-change memory.

    Science.gov (United States)

    Kim, Sungho; Kim, Sae-Jin; Kim, Kyung Min; Lee, Seung Ryul; Chang, Man; Cho, Eunju; Kim, Young-Bae; Kim, Chang Jung; Chung, U -In; Yoo, In-Kyeong

    2013-01-01

    Tantalum-oxide-based bi-layered resistance-change memories (RRAMs) have recently improved greatly with regard to their memory performances. The formation and rupture of conductive filaments is generally known to be the mechanism that underlies resistive switching. The nature of the filament has been studied intensively and several phenomenological models have consistently predicted the resistance-change behavior. However, a physics-based model that describes a complete bi-layered RRAM structure has not yet been demonstrated. Here, a complete electro-thermal resistive switching model based on the finite element method is proposed. The migration of oxygen vacancies is simulated by the local temperature and electric field derived from carrier continuity and heat equations fully coupled in a 3-D geometry, which considers a complete bi-layered structure that includes the top and bottom electrodes. The proposed model accurately accounts for the set/reset characteristics, which provides an in-depth understanding of the nature of resistive switching.

  2. The Role of Life-Space, Social Activity, and Depression on the Subjective Memory Complaints of Community-Dwelling Filipino Elderly: A Structural Equation Model

    Science.gov (United States)

    de Guzman, Allan B.; Lagdaan, Lovely France M.; Lagoy, Marie Lauren V.

    2015-01-01

    Subjective memory complaints are one of the major concerns of the elderly and remain a challenging area in gerontology. There are previous studies that identify different factors affecting subjective memory complaints. However, an extended model that correlates life-space on subjective memory complaints remains a blank spot. The objective of this…

  3. Object Location and Object Recognition Memory Impairments, Motivation Deficits and Depression in a Model of Gulf War Illness

    Directory of Open Access Journals (Sweden)

    Bharathi eHattiangady

    2014-03-01

    Full Text Available Memory and mood deficits are the enduring brain-related symptoms in Gulf War illness (GWI. Both animal model and epidemiological investigations have indicated that these impairments in a majority of GW veterans are linked to exposures to chemicals such as pyridostigmine bromide (PB, an anti nerve gas drug, permethrin (PM, an insecticide and DEET (a mosquito repellant encountered during the Persian Gulf War-1. Our previous study in a rat model has shown that combined exposures to low doses of GWI-related (GWIR chemicals PB, PM and DEET with or without 5-minutes of restraint stress (a mild stress paradigm causes hippocampus-dependent spatial memory dysfunction in a water maze test and increased depressive-like behavior in a forced swim test. In this study, using a larger cohort of rats exposed to GWIR-chemicals and stress, we investigated whether the memory deficiency identified earlier in a water maze test is reproducible with an alternative and stress free hippocampus-dependent memory test such as the object location test. We also ascertained the possible co-existence of hippocampus-independent memory dysfunction using a novel object recognition test, and alterations in mood function with additional tests for motivation and depression. Our results provide new evidence that exposure to low doses of GWIR-chemicals and stress for four weeks causes deficits in hippocampus-dependent object location memory and perirhinal cortex-dependent novel object recognition memory. An open field test performed prior to other behavioral analyses revealed that memory impairments were not associated with increased anxiety or deficits in general motor ability. However, behavioral tests for mood function such as a voluntary physical exercise paradigm and a novelty suppressed feeding test showed decreased motivation and depression. Thus, exposure to GWIR-chemicals and stress causes both hippocampus-dependent and hippocampus-independent memory impairments as well as

  4. Smaller, scale-free gene networks increase quantitative trait heritability and result in faster population recovery.

    Directory of Open Access Journals (Sweden)

    Jacob W Malcom

    Full Text Available One of the goals of biology is to bridge levels of organization. Recent technological advances are enabling us to span from genetic sequence to traits, and then from traits to ecological dynamics. The quantitative genetics parameter heritability describes how quickly a trait can evolve, and in turn describes how quickly a population can recover from an environmental change. Here I propose that we can link the details of the genetic architecture of a quantitative trait--i.e., the number of underlying genes and their relationships in a network--to population recovery rates by way of heritability. I test this hypothesis using a set of agent-based models in which individuals possess one of two network topologies or a linear genotype-phenotype map, 16-256 genes underlying the trait, and a variety of mutation and recombination rates and degrees of environmental change. I find that the network architectures introduce extensive directional epistasis that systematically hides and reveals additive genetic variance and affects heritability: network size, topology, and recombination explain 81% of the variance in average heritability in a stable environment. Network size and topology, the width of the fitness function, pre-change additive variance, and certain interactions account for ∼75% of the variance in population recovery times after a sudden environmental change. These results suggest that not only the amount of additive variance, but importantly the number of loci across which it is distributed, is important in regulating the rate at which a trait can evolve and populations can recover. Taken in conjunction with previous research focused on differences in degree of network connectivity, these results provide a set of theoretical expectations and testable hypotheses for biologists working to span levels of organization from the genotype to the phenotype, and from the phenotype to the environment.

  5. The Cognitive Processes Underlying Event-Based Prospective Memory In School Age Children and Young Adults: A Formal Model-Based Study

    OpenAIRE

    Smith, Rebekah E.; Bayen, Ute Johanna; Martin, Claudia

    2010-01-01

    Fifty 7-year-olds (29 female), 53 10-year-olds (29 female), and 36 young adults (19 female), performed a computerized event-based prospective memory task. All three groups differed significantly in prospective memory performance with adults showing the best performance and 7-year-olds the poorest performance. We used a formal multinomial process tree model of event-based prospective memory to decompose age differences in cognitive processes that jointly contribute to prospective memory perfor...

  6. Serial recall of colors: Two models of memory for serial order applied to continuous visual stimuli.

    Science.gov (United States)

    Peteranderl, Sonja; Oberauer, Klaus

    2018-01-01

    This study investigated the effects of serial position and temporal distinctiveness on serial recall of simple visual stimuli. Participants observed lists of five colors presented at varying, unpredictably ordered interitem intervals, and their task was to reproduce the colors in their order of presentation by selecting colors on a continuous-response scale. To control for the possibility of verbal labeling, articulatory suppression was required in one of two experimental sessions. The predictions were derived through simulation from two computational models of serial recall: SIMPLE represents the class of temporal-distinctiveness models, whereas SOB-CS represents event-based models. According to temporal-distinctiveness models, items that are temporally isolated within a list are recalled more accurately than items that are temporally crowded. In contrast, event-based models assume that the time intervals between items do not affect recall performance per se, although free time following an item can improve memory for that item because of extended time for the encoding. The experimental and the simulated data were fit to an interference measurement model to measure the tendency to confuse items with other items nearby on the list-the locality constraint-in people as well as in the models. The continuous-reproduction performance showed a pronounced primacy effect with no recency, as well as some evidence for transpositions obeying the locality constraint. Though not entirely conclusive, this evidence favors event-based models over a role for temporal distinctiveness. There was also a strong detrimental effect of articulatory suppression, suggesting that verbal codes can be used to support serial-order memory of simple visual stimuli.

  7. Ordered short-term memory differs in signers and speakers: Implications for models of short-term memory

    OpenAIRE

    Bavelier, Daphne; Newport, Elissa L.; Hall, Matt; Supalla, Ted; Boutla, Mrim

    2008-01-01

    Capacity limits in linguistic short-term memory (STM) are typically measured with forward span tasks in which participants are asked to recall lists of words in the order presented. Using such tasks, native signers of American Sign Language (ASL) exhibit smaller spans than native speakers (Boutla, Supalla, Newport, & Bavelier, 2004). Here, we test the hypothesis that this population difference reflects differences in the way speakers and signers maintain temporal order information in short-te...

  8. Modeling of filamentary resistive memory by concentric cylinders with variable conductivity

    Science.gov (United States)

    Lohn, Andrew J.; Mickel, Patrick R.; Marinella, Matthew J.

    2014-11-01

    We demonstrate a method for modeling memristors (resistive random access memories) where the filament is composed of a set of nanoscale or sub-nanoscale concentric cylinders, each having its own conductivity. This approach allows for the inclusion of multiple state variables, which, we show experimentally, can be used to control electrical behavior. The simulations accurately reproduce the current-voltage hysteresis loop as well as these more complex experimental behaviors resulting from intricate switching histories. The simulations can be both static and dynamic, and are based upon physical design parameters, so optimized values from simulation can be easily linked to device design.

  9. Response of a Shape Memory Alloy Beam Model under Narrow Band Noise Excitation

    Directory of Open Access Journals (Sweden)

    Gen Ge

    2014-01-01

    Full Text Available To describe the hysteretic nonlinear characteristic of the strain-stress relation of shape memory alloy (SMA, a Van-der-Pol hysteretic cycle is applied to simulate the hysteretic loops. Then, the model of a simply supported SMA beam subject to transverse narrow band noise excitation with nonlinear damping was proposed. The deterministic and the stochastic responses are studied, respectively, applying the multiple scale method. The stability of the steady state responses is analyzed by Floquet theory and the moment method. The numerical simulation results quite agree with the theoretical analysis.

  10. Is prospective memory related to depression and anxiety? A hierarchical MPT modelling approach.

    Science.gov (United States)

    Arnold, Nina R; Bayen, Ute J; Böhm, Mateja F

    2015-01-01

    Prospective memory (PM) refers to remembering to perform an action in the future. One hundred and twenty-nine students completed a laboratory event-based PM task as well as depression and anxiety questionnaires. The data were analysed with the beta-MPT version of the multinomial processing tree model of event-based PM. Thereby, the prospective and retrospective components of PM were estimated for each participant and were then correlated with depression and anxiety. State anxiety was negatively correlated with the prospective component of PM. Neither depression nor trait anxiety were related to either component of PM.

  11. Ice plant (Mesembryanthemum crystallinum) improves hyperglycaemia and memory impairments in a Wistar rat model of streptozotocin-induced diabetes.

    Science.gov (United States)

    Lee, Bao-Hong; Lee, Chia-Chen; Wu, She-Ching

    2014-08-01

    Ice plant (Mesembryanthemum crystallinum) has been used as an anti-diabetic agent in Japan because it contains d-pinitol. The efficacy of ice plant in the regulation of blood glucose is unclear at present. Recently, memory impairment and development of Alzheimer's disease found in diabetic patients are thought to be caused by high blood glucose. The mechanism by which ice plant protects against the impairment of memory and learning abilities caused by high blood glucose remains unclear. The aim of this study was to evaluate the protection of ice plant water extracts (IPE) and D-pinitol against memory impairments in a Wistar rat model of streptozotocin (STZ)-induced diabetes. We hypothesised that IPE and D-pinitol could suppress blood glucose and elevate insulin sensitivity in these rats. For memory evaluation, IPE and D-pinitol also improved the passive avoidance task and the working memory task. In addition, inhibition of acetylcholinesterase activity in hippocampus and cortex was found in this rat model administered IPE or D-pinitol. IPE and D-pinitol also markedly elevated superoxide dismutase activity against oxidative stress and reduced malondialdehyde production in hippocampus and cortex of the rats. These findings indicated that IPE and D-pinitol possess beneficial effects for neural protection and memory ability in a rat model of diabetes. © 2013 Society of Chemical Industry.

  12. Non-volatile memories

    CERN Document Server

    Lacaze, Pierre-Camille

    2014-01-01

    Written for scientists, researchers, and engineers, Non-volatile Memories describes the recent research and implementations in relation to the design of a new generation of non-volatile electronic memories. The objective is to replace existing memories (DRAM, SRAM, EEPROM, Flash, etc.) with a universal memory model likely to reach better performances than the current types of memory: extremely high commutation speeds, high implantation densities and retention time of information of about ten years.

  13. A Thrombus Generation Model Applied to Aneurysms Treated with Shape Memory Polymer Foam and Metal Coils

    Science.gov (United States)

    Horn, John; Ortega, Jason; Hartman, Jonathan; Maitland, Duncan

    2015-11-01

    To prevent their rupture, intracranial aneurysms are often treated with endovascular metal coils which fill the aneurysm sac and isolate it from the arterial flow. Despite its widespread use, this method can result in suboptimal outcomes leading to aneurysm recurrence. Recently, shape memory polymer foam has been proposed as an alternative aneurysm filler. In this work, a computational model has been developed to predict thrombus formation in blood in response to such cardiovascular implantable devices. The model couples biofluid and biochemical phenomena present as the blood interacts with a device and stimulates thrombus formation. This model is applied to simulations of both metal coil and shape memory polymer foam treatments within an idealized 2D aneurysm geometry. Using the predicted thrombus responses, the performance of these treatments is evaluated and compared. The results suggest that foam-treated aneurysms may fill more quickly and more completely with thrombus than coil-filled aneurysms, potentially leading to improved long-term aneurysm healing. This work was performed in part under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  14. Probability state modeling of memory CD8⁺ T-cell differentiation.

    Science.gov (United States)

    Inokuma, Margaret S; Maino, Vernon C; Bagwell, C Bruce

    2013-11-29

    Flow cytometric analysis enables the simultaneous single-cell interrogation of multiple biomarkers for phenotypic and functional identification of heterogeneous populations. Analysis of polychromatic data has become increasingly complex with more measured parameters. Furthermore, manual gating of multiple populations using standard analysis techniques can lead to errors in data interpretation and difficulties in the standardization of analyses. To characterize high-dimensional cytometric data, we demonstrate the use of probability state modeling (PSM) to visualize the differentiation of effector/memory CD8⁺ T cells. With this model, four major CD8⁺ T-cell subsets can be easily identified using the combination of three markers, CD45RA, CCR7 (CD197), and CD28, with the selection markers CD3, CD4, CD8, and side scatter (SSC). PSM enables the translation of complex multicolor flow cytometric data to pathway-specific cell subtypes, the capability of developing averaged models of healthy donor populations, and the analysis of phenotypic heterogeneity. In this report, we also illustrate the heterogeneity in memory T-cell subpopulations as branched differentiation markers that include CD127, CD62L, CD27, and CD57. © 2013. Published by Elsevier B.V. All rights reserved.

  15. New non-linear model of groundwater recharge: Inclusion of memory, heterogeneity and visco-elasticity

    Directory of Open Access Journals (Sweden)

    Spannenberg Jescica

    2017-09-01

    Full Text Available Fractional differentiation has adequate use for investigating real world scenarios related to geological formations associated with elasticity, heterogeneity, viscoelasticity, and the memory effect. Since groundwater systems exist in these geological formations, modelling groundwater recharge as a real world scenario is a challenging task to do because existing recharge estimation methods are governed by linear equations which make use of constant field parameters. This is inadequate because in reality these parameters are a function of both space and time. This study therefore concentrates on modifying the recharge equation governing the EARTH model, by application of the Eton approach. Accordingly, this paper presents a modified equation which is non-linear, and accounts for parameters in a way that it is a function of both space and time. To be more specific, herein, recharge and drainage resistance which are parameters within the equation, became a function of both space and time. Additionally, the study entailed solving the non-linear equation using an iterative method as well as numerical solutions by means of the Crank-Nicolson scheme. The numerical solutions were used alongside the Riemann-Liouville, Caputo-Fabrizio, and Atangana-Baleanu derivatives, so that account was taken for elasticity, heterogeneity, viscoelasticity, and the memory effect. In essence, this paper presents a more adequate model for recharge estimation.

  16. New non-linear model of groundwater recharge: Inclusion of memory, heterogeneity and visco-elasticity

    Science.gov (United States)

    Spannenberg, Jescica; Atangana, Abdon; Vermeulen, P. D.

    2017-09-01

    Fractional differentiation has adequate use for investigating real world scenarios related to geological formations associated with elasticity, heterogeneity, viscoelasticity, and the memory effect. Since groundwater systems exist in these geological formations, modelling groundwater recharge as a real world scenario is a challenging task to do because existing recharge estimation methods are governed by linear equations which make use of constant field parameters. This is inadequate because in reality these parameters are a function of both space and time. This study therefore concentrates on modifying the recharge equation governing the EARTH model, by application of the Eton approach. Accordingly, this paper presents a modified equation which is non-linear, and accounts for parameters in a way that it is a function of both space and time. To be more specific, herein, recharge and drainage resistance which are parameters within the equation, became a function of both space and time. Additionally, the study entailed solving the non-linear equation using an iterative method as well as numerical solutions by means of the Crank-Nicolson scheme. The numerical solutions were used alongside the Riemann-Liouville, Caputo-Fabrizio, and Atangana-Baleanu derivatives, so that account was taken for elasticity, heterogeneity, viscoelasticity, and the memory effect. In essence, this paper presents a more adequate model for recharge estimation.

  17. The trauma film paradigm as an experimental psychopathology model of psychological trauma: intrusive memories and beyond.

    Science.gov (United States)

    James, Ella L; Lau-Zhu, Alex; Clark, Ian A; Visser, Renée M; Hagenaars, Muriel A; Holmes, Emily A

    2016-07-01

    A better understanding of psychological trauma is fundamental to clinical psychology. Following traumatic event(s), a clinically significant number of people develop symptoms, including those of Acute Stress Disorder and/or Post Traumatic Stress Disorder. The trauma film paradigm offers an experimental psychopathology model to study both exposure and reactions to psychological trauma, including the hallmark symptom of intrusive memories. We reviewed 74 articles that have used this paradigm since the earliest review (Holmes & Bourne, 2008) until July 2014. Highlighting the different stages of trauma processing, i.e. pre-, peri- and post-trauma, the studies are divided according to manipulations before, during and after film viewing, for experimental as well as correlational designs. While the majority of studies focussed on the frequency of intrusive memories, other reactions to trauma were also modelled. We discuss the strengths and weaknesses of the trauma film paradigm as an experimental psychopathology model of trauma, consider ethical issues, and suggest future directions. By understanding the basic mechanisms underlying trauma symptom development, we can begin to translate findings from the laboratory to the clinic, test innovative science-driven interventions, and in the future reduce the debilitating effects of psychopathology following stressful and/or traumatic events. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  18. Effects of l-arginine and creatine administration on spatial memory in rats subjected to a chronic variable stress model.

    Science.gov (United States)

    dos Santos, Fabio Seidel; da Silva, Luiz Augusto; Pochapski, José Augusto; Raczenski, Alan; da Silva, Weber Claudio; Grassiolli, Sabrina; Malfatti, Carlos Ricardo Maneck

    2014-08-01

    Chronic stress results from repeated exposure to one or more types of stressors over a period, ranging from days to months, and can be associated with physical, behavioral, and neuropsychiatric manifestations. Some physiological alterations resulting from chronic stress can potentially cause deficits on spatial learning and memory. This study investigated the effects of chronic variable stress (CVS) and administration of l-arginine and creatine on spatial memory in rats. Furthermore, body, heart, adrenal weight, and plasma glucose and corticosterone levels were analyzed. Male Wistar rats were subjected to a CVS model for 40 days and evaluated for spatial memory after the stress period. Chronically stressed animals were treated daily by gavage with: 0.5% carboxymethylcellulose (Group Cs), 500 mg/kg l-arginine (Group Cs/La), 300 mg/kg creatine (Group Cs/Cr); and 500 mg/kg l-arginine and 300 mg/kg creatine (Group Cs/La + Cr) during the entire experimental period. Our results showed that animals in the Cs/Cr and Cs/La + Cr groups presented significantly decreased corticosterone levels compared to group Cs (p working memory task, compared to all other groups (p memory retention compared to controls (p working memory efficiency, and, when co-administrated with l-arginine, improves reference memory retention, a phenomenon that is possibly associated with increased creatine/phosphocreatine levels and l-arginine-derived NO synthesis.

  19. A memory-efficient staining algorithm in 3D seismic modelling and imaging

    Science.gov (United States)

    Jia, Xiaofeng; Yang, Lu

    2017-08-01

    The staining algorithm has been proven to generate high signal-to-noise ratio (S/N) images in poorly illuminated areas in two-dimensional cases. In the staining algorithm, the stained wavefield relevant to the target area and the regular source wavefield forward propagate synchronously. Cross-correlating these two wavefields with the backward propagated receiver wavefield separately, we obtain two images: the local image of the target area and the conventional reverse time migration (RTM) image. This imaging process costs massive computer memory for wavefield storage, especially in large scale three-dimensional cases. To make the staining algorithm applicable to three-dimensional RTM, we develop a method to implement the staining algorithm in three-dimensional acoustic modelling in a standard staggered grid finite difference (FD) scheme. The implementation is adaptive to the order of spatial accuracy of the FD operator. The method can be applied to elastic, electromagnetic, and other wave equations. Taking the memory requirement into account, we adopt a random boundary condition (RBC) to backward extrapolate the receiver wavefield and reconstruct it by reverse propagation using the final wavefield snapshot only. Meanwhile, we forward simulate the stained wavefield and source wavefield simultaneously using the nearly perfectly matched layer (NPML) boundary condition. Experiments on a complex geologic model indicate that the RBC-NPML collaborative strategy not only minimizes the memory consumption but also guarantees high quality imaging results. We apply the staining algorithm to three-dimensional RTM via the proposed strategy. Numerical results show that our staining algorithm can produce high S/N images in the target areas with other structures effectively muted.

  20. Brain neuroplastic changes accompany anxiety and memory deficits in a model of complex regional pain syndrome.

    Science.gov (United States)

    Tajerian, Maral; Leu, David; Zou, Yani; Sahbaie, Peyman; Li, Wenwu; Khan, Hamda; Hsu, Vivian; Kingery, Wade; Huang, Ting Ting; Becerra, Lino; Clark, J David

    2014-10-01

    Complex regional pain syndrome (CRPS) is a painful condition with approximately 50,000 annual new cases in the United States. It is a major cause of work-related disability, chronic pain after limb fractures, and persistent pain after extremity surgery. Additionally, CRPS patients often experience cognitive changes, anxiety, and depression. The supraspinal mechanisms linked to these CRPS-related comorbidities remain poorly understood. The authors used a previously characterized mouse model of tibia fracture/cast immobilization showing the principal stigmata of CRPS (n = 8 to 20 per group) observed in humans. The central hypothesis was that fracture/cast mice manifest changes in measures of thigmotaxis (indicative of anxiety) and working memory reflected in neuroplastic changes in amygdala, perirhinal cortex, and hippocampus. The authors demonstrate that nociceptive sensitization in these mice is accompanied by altered thigmotactic behaviors in the zero maze but not open field assay, and working memory dysfunction in novel object recognition and social memory but not in novel location recognition. Furthermore, the authors found evidence of structural changes and synaptic plasticity including changes in dendritic architecture and decreased levels of synaptophysin and brain-derived neurotrophic factor in specific brain regions. The study findings provide novel observations regarding behavioral changes and brain plasticity in a mouse model of CRPS. In addition to elucidating some of the supraspinal correlates of the syndrome, this work supports the potential use of therapeutic interventions that not only directly target sensory input and other peripheral mechanisms, but also attempt to ameliorate the broader pain experience by modifying its associated cognitive and emotional comorbidities.

  1. Maximizing students' retention via spaced review: practical guidance from computational models of memory.

    Science.gov (United States)

    Khajah, Mohammad M; Lindsey, Robert V; Mozer, Michael C

    2014-01-01

    During each school semester, students face an onslaught of material to be learned. Students work hard to achieve initial mastery of the material, but when they move on, the newly learned facts, concepts, and skills degrade in memory. Although both students and educators appreciate that review can help stabilize learning, time constraints result in a trade-off between acquiring new knowledge and preserving old knowledge. To use time efficiently, when should review take place? Experimental studies have shown benefits to long-term retention with spaced study, but little practical advice is available to students and educators about the optimal spacing of study. The dearth of advice is due to the challenge of conducting experimental studies of learning in educational settings, especially where material is introduced in blocks over the time frame of a semester. In this study, we turn to two established models of memory-ACT-R and MCM-to conduct simulation studies exploring the impact of study schedule on long-term retention. Based on the premise of a fixed time each week to review, converging evidence from the two models suggests that an optimal review schedule obtains significant benefits over haphazard (suboptimal) review schedules. Furthermore, we identify two scheduling heuristics that obtain near optimal review performance: (a) review the material from μ-weeks back, and (b) review material whose predicted memory strength is closest to a particular threshold. The former has implications for classroom instruction and the latter for the design of digital tutors. Copyright © 2013 Cognitive Science Society, Inc.

  2. Petri Nets Based Modelling of Control Flow for Memory-Aid Interactive Programs in Telemedicine

    CERN Document Server

    Khoromskaia, V K

    2004-01-01

    Petri Nets (PN) based modelling of the control flow for the interactive memory assistance programs designed for personal pocket computers and having special requirements for robustness is considered. The proposed concept allows one to elaborate the programs which can give users a variety of possibilities for a day-time planning in the presence of environmental and time restrictions. First, a PN model for a known simple algorithm is constructed and analyzed using the corresponding state equations and incidence matrix. Then a PN graph for a complicated algorithm with overlapping actions and choice possibilities is designed, supplemented by an example of its analysis. Dynamic behaviour of this graph is tested by tracing of all possible paths of the flow of control using the PN simulator. It is shown that PN based modelling provides reliably predictable performance of interactive algorithms with branched structures and concurrency requirements.

  3. Application of the dual-component model of working memory to ADHD:Greater secondary memory deficit despite confounded cognitive differences.

    Science.gov (United States)

    Gibson, Bradley S; Gondoli, Dawn M; Ralph, Kathryn J; Sztybel, Pedro

    2018-01-01

    The dual-component model postulates that working memory capacity consists of two dissociable components: maintenance in primary memory (PM) and retrieval from secondary memory (SM). Recent application of this model to attention-deficit/hyperactivity disorder (ADHD) has revealed that the SM component is more deficient than the PM component across both verbal and spatial modalities. The present study attempts to strengthen this conclusion by addressing two weaknesses in the previous study. First, the present study shows that the SM component continues to be more deficient than the PM component across both modalities under conditions in which (1) all participants were instructed to use the same recall strategy (resulting in the exclusion of fewer participants); and, (2) individual differences in this strategy were controlled. Second, the present study also documents a group difference in word reading efficiency that is confounded with diagnostic status and that might have influenced estimates of PM and SM capacities in the verbal modality. However, although the SM component is more deficient than the PM component in the ADHD group, the magnitude of this interaction does not vary as a function task modality. These findings are interpreted to suggest that the pattern of WM deficiencies observed are part of a causal pathway that can lead to the symptoms of ADHD, as well as to impairments in reading (and intelligence) due to overlapping cue-dependent retrieval mechanisms. These findings provide additional support for the notion that the SM component of WM is an important and neglected target for treatment.

  4. Molecular control of memory in nematode Caenorhabditis elegans

    OpenAIRE

    Ye, Hua-Yue; Ye, Bo-Ping; Wang, Da-Yong

    2008-01-01

    Model invertebrate organism Caenorhabditis elegans has become an ideal model to unravel the complex processes of memory. C. elegans has three simple forms of memory: memory for thermosensation, memory for chemosensation, and memory for mechanosensation. In the form of memory for mechanosensation, short-term memory, intermediate-term memory, and long-term memory have been extensively studied. The short-term memory and intermediate-term memory may occur in the presynaptic sensory neurons, where...

  5. Effect of dehydroepiandrosterone (DHEA) on memory and brain derived neurotrophic factor (BDNF) in a rat model of vascular dementia.

    Science.gov (United States)

    Sakr, H F; Khalil, K I; Hussein, A M; Zaki, M S A; Eid, R A; Alkhateeb, M

    2014-02-01

    The effect of dehydroepiandrosterone (DHEA) on memory and cognition in experimental animals is well known, but its efficacy in clinical dementia is unproven. So, the aim of the present study was to investigate the effect of DHEA on learning and memory activities in a rat model of vascular dementia (VD). Forty-eight male rats that positively passed the holeboard memory test were chosen for the study before bilateral permanent occlusion of the common carotid artery. They were divided into four groups (n=12, each) as follows (i) untreated control, (ii) rats exposed to surgical permanent bilateral occlusion of the common carotid arteries (BCCAO) leading to chronic cerebral hypoperfusion, (iii) rats exposed to BCCAO then received DHEA (BCCAO + DHEA) and (i.v.) rats exposed to BCCAO then received donepezil (BCCAO + DON). Holeboard memory test was used to assess the time, latency, working memory and reference memory. Central level of acetylcholine, norepinephrine and dopamine in the hippocampus were measured. Furthermore, the expression of brain derived neurotrophic factor (BDNF) in the hippocampus was determined. Histopathological studies of the cerebral cortex and transmission electron microscope of the hippocampus were performed. BCCAO decreased the learning and memory activities in the holeboard memory. Also, it decreased the expression of BDNF as well as the central level of acetylcholine, noradrenaline and dopamine as compared to control rats. Treatment with DHEA and donepezil increased the working and reference memories, BDNF expression as well as the central acetylcholine in the hippocampus as compared to BCCAO rats. DHEA produced neuroprotective effects through increasing the expression of BDNF as well as increasing the central level of acetylcholine and catecholamines which are non-comparable to donepezil effects.

  6. The concentric model of human working memory: A validation study using complex span and updating tasks

    Directory of Open Access Journals (Sweden)

    Velichkovsky B. B.

    2017-09-01

    Full Text Available Background. Working memory (WM seems to be central to most forms of high-level cognition. This fact is fueling the growing interest in studying its structure and functional organization. The influential “concentric model” (Oberauer, 2002 suggests that WM contains a processing component and two storage components with different capacity limitations and sensitivity to interference. There is, to date, only limited support for the concentric model in the research literature, and it is limited to a number of specially designed tasks. Objective. In the present paper, we attempted to validate the concentric model by testing its major predictions using complex span and updating tasks in a number of experimental paradigms. Method. The model predictions were tested with the help of review of data obtained primarily in our own experiments in several research domains, including Sternberg’s additive factors method; factor structure of WM; serial position effects in WM; and WM performance in a sample with episodic long-term memory deficits. Results. Predictions generated by the concentric model were shown to hold in all these domains. In addition, several new properties of WM were identified. In particular, we recently found that WM indeed contains a processing component which functions independent of storage components. In turn, the latter were found to form a storage hierarchy which balances fast access to selected items, with the storing of large amounts of potentially relevant information. Processing and storage in WM were found to be dependent on shared cognitive resources which are dynamically allocated between WM components according to actual task requirements. e implications of these findings for the theory of WM are discussed. Conclusion. The concentric model was shown to be valid with respect to standard WM tasks. The concentric model others promising research perspectives for the study of higher- order cognition, including underlying

  7. Highly compact and accurate circuit-level macro modeling of gate-all-around charge-trap flash memory

    Science.gov (United States)

    Kim, Seunghyun; Lee, Sang-Ho; Kim, Young-Goan; Cho, Seongjae; Park, Byung-Gook

    2017-01-01

    In this paper, a highly reliable circuit model of gate-all-around (GAA) charge-trap flash (CTF) memory cell is proposed, considering the transient behaviors for describing the program operations with improved accuracy. Although several compact models have been reported in the previous literature, time-dependent behaviors have not been precisely reflected and the failures tend to get worse as the operation time elapses. Furthermore, the developed SPICE models in this work have been verified by the measurement results of the fabricated flash memory cells having silicon-oxide-nitride-oxide-silicon (SONOS). This more realistic model would be beneficial in designing the system architectures and setting up the operation schemes for the leading three-dimensional (3D) stack CTF memory.

  8. Learning Quantum Chemical Model with Learning Media Concept Map and Power Point Viewed from Memory and Creativity Skills Students

    Directory of Open Access Journals (Sweden)

    Agus Wahidi

    2017-03-01

    Full Text Available This research is experimental, using first class learning a quantum model of learning with concept maps media and the second media using real environments by power point presentation. The population is all class XI Science, number 2 grade. The sampling technique is done by purposive random sampling. Data collection techniques to test for cognitive performance and memory capabilities, with a questionnaire for creativity. Hypothesis testing using three-way ANOVA different cells with the help of software Minitab 15.Based on the results of data processing, concluded: (1 there is no influence of the quantum model of learning with media learning concept maps and real environments for learning achievement chemistry, (2 there is a high impact memory ability and low on student achievement, (3 there is no the effect of high and low creativity in student performance, (4 there is no interaction learning model quantum media learning concept maps and real environments with memory ability on student achievement, (5 there is no interaction learning model quantum media learning concept maps and real environments with creativity of student achievement, (6 there is no interaction memory skills and creativity of student achievement, (7 there is no interaction learning model quantum media learning concept maps and real environments, memory skills, and creativity on student achievement.

  9. Alcohol's dissociation of implicit and explicit memory processes: implications of a parallel distributed processing model of semantic priming.

    Science.gov (United States)

    Ray, Suchismita; Bates, Marsha E; Ely, Benjamin Martin

    2004-05-01

    Alcohol's dissociation of implicit (unintentional) and explicit (intentional) memory processes in social drinkers was examined. It was hypothesized that an alcohol challenge would lower the percentage of words recalled and result in more retroactive interference in explicit recall tasks but would not lengthen reaction time in an implicit semantic priming task involving highly semantically similar words. Men and women completed all memory tasks in each of 2 counterbalanced sessions (alcohol challenge vs. no-alcohol) separated by 1 week. Alcohol significantly degraded processing in both explicit memory tasks, yet implicit semantic priming remained intact. A parallel distributed processing model that simulates semantic memory is presented. When this system is strongly activated, it does not appear to be altered during moderate alcohol intoxication. ((c) 2004 APA, all rights reserved)

  10. Novel effects of Rosa damascena extract on memory and neurogenesis in a rat model of Alzheimer's disease.

    Science.gov (United States)

    Esfandiary, Ebrahim; Karimipour, Mohammad; Mardani, Mohammad; Alaei, Hojjatallah; Ghannadian, Mustafa; Kazemi, Mohammad; Mohammadnejad, Daryoush; Hosseini, Nasrin; Esmaeili, Abolghasem

    2014-04-01

    The number of older people who are suffering from memory impairment is increasing among populations throughout the world. Alzheimer's disease (AD) affects about 5% of people over 65 years old. The hippocampus, a brain area critical for learning and memory, is especially vulnerable to damage in the early stages of AD. Emerging evidence suggests that loss of neurons and synapses are correlated with dementia in this devastating disease. Therefore, neurogenesis and synaptogenesis in adulthood could serve as a preventive as well as a therapeutic target for AD. This study investigated the effect of Rosa damascena extract on neurogenesis and synaptogenesis in an animal model of AD. Molecular, cellular, and behavioral experiments revealed that this treatment could induce neurogenesis and synaptic plasticity and improve memory in AD. Our study suggests that R. damascena is a promising treatment for mild memory impairments and AD. Copyright © 2013 Wiley Periodicals, Inc.

  11. The relations between network-operation and topological-property in a scale-free and small-world network with community structure

    Science.gov (United States)

    Ma, Fei; Yao, Bing

    2017-10-01

    It is always an open, demanding and difficult task for generating available model to simulate dynamical functions and reveal inner principles from complex systems and networks. In this article, due to lots of real-life and artificial networks are built from series of simple and small groups (components), we discuss some interesting and helpful network-operation to generate more realistic network models. In view of community structure (modular topology), we present a class of sparse network models N(t , m) . At the moment, we capture the fact the N(t , 4) has not only scale-free feature, which means that the probability that a randomly selected vertex with degree k decays as a power-law, following P(k) ∼k-γ, where γ is the degree exponent, but also small-world property, which indicates that the typical distance between two uniform randomly chosen vertices grows proportionally to logarithm of the order of N(t , 4) , namely, relatively shorter diameter and lower average path length, simultaneously displays higher clustering coefficient. Next, as a new topological parameter correlating to reliability, synchronization capability and diffusion properties of networks, the number of spanning trees over a network is studied in more detail, an exact analytical solution for the number of spanning trees of the N(t , 4) is obtained. Based on the network-operation, part hub-vertex linking with each other will be helpful for structuring various network models and investigating the rules related with real-life networks.

  12. Searching for targets in visual working memory: investigating a dimensional feature bundle (DFB) model.

    Science.gov (United States)

    Töllner, Thomas; Mink, Maurice; Müller, Hermann J

    2015-03-01

    The human visual working memory (WM) system enables us to store a limited amount of task-relevant visual information temporally in mind. One actively debated issue in cognitive neuroscience centers around the question of how this WM information is maintained. The currently dominant views advocated by prominent WM models hold that the units of memory are configured either as independent feature representations, integrated bound objects, or a combination of both. Here, we approached this issue by measuring lateralized brain electrical activity during a retro-cue paradigm, in order to track people's ability to access WM representations as a function of the dimensional relation between WM items and task settings. Both factors were revealed to selectively influence WM access: whereas cross relative to intradimensional WM targets gave rise to enhanced contralateral delay activity (CDA) amplitudes, localization relative to identification task demands yielded speeded CDA and manual response times. As these dimension-based findings are not reconcilable with contemporary feature- and/or object-based accounts, an alternative view that is based on the hierarchical feature-bundle model is proposed. We argue that WM units may consist of three hierarchically structured levels of representations, with an intermediate dimensionally organized level that mediates between top-level object and lower-level feature representations. © 2015 New York Academy of Sciences.

  13. From distributed resources to limited slots in multiple-item working memory: a spiking network model with normalization.

    Science.gov (United States)

    Wei, Ziqiang; Wang, Xiao-Jing; Wang, Da-Hui

    2012-08-15

    Recent behavioral studies have given rise to two contrasting models for limited working memory capacity: a "discrete-slot" model in which memory items are stored in a limited number of slots, and a "shared-resource" model in which the neural representation of items is distributed across a limited pool of resources. To elucidate the underlying neural processes, we investigated a continuous network model for working memory of an analog feature. Our model network fundamentally operates with a shared resource mechanism, and stimuli in cue arrays are encoded by a distributed neural population. On the other hand, the network dynamics and performance are also consistent with the discrete-slot model, because multiple objects are maintained by distinct localized population persistent activity patterns (bump attractors). We identified two phenomena of recurrent circuit dynamics that give rise to limited working memory capacity. As the working memory load increases, a localized persistent activity bump may either fade out (so the memory of the corresponding item is lost) or merge with another nearby bump (hence the resolution of mnemonic representation for the merged items becomes blurred). We identified specific dependences of these two phenomena on the strength and tuning of recurrent synaptic excitation, as well as network normalization: the overall population activity is invariant to set size and delay duration; therefore, a constant neural resource is shared by and dynamically allocated to the memorized items. We demonstrate that the model reproduces salient observations predicted by both discrete-slot and shared-resource models, and propose testable predictions of the merging phenomenon.

  14. A phenomenological two-phase constitutive model for porous shape memory alloys

    KAUST Repository

    El Sayed, Tamer S.

    2012-07-01

    We present a two-phase constitutive model for pseudoelastoplastic behavior of porous shape memory alloys (SMAs). The model consists of a dense SMA phase and a porous plasticity phase. The overall response of the porous SMA is obtained by a weighted average of responses of individual phases. Based on the chosen constitutive model parameters, the model incorporates the pseudoelastic and pseudoplastic behavior simultaneously (commonly reported for porous SMAs) as well as sequentially (i.e. dense SMAs; pseudoelastic deformation followed by the pseudoplastic deformation until failure). The presented model also incorporates failure due to the deviatoric (shear band formation) and volumetric (void growth and coalescence) plastic deformation. The model is calibrated by representative volume elements (RVEs) with different sizes of spherical voids that are solved by unit cell finite element calculations. The overall response of the model is tested against experimental results from literature. Finally, application of the presented constitutive model has been presented by performing finite element simulations of the deformation and failure in unaixial dog-bone shaped specimen and compact tension (CT) test specimen. Results show a good agreement with the experimental data reported in the literature. © 2012 Elsevier B.V. All rights reserved.

  15. A working memory model for serial order that stores information in the intrinsic excitability properties of neurons.

    Science.gov (United States)

    Conde-Sousa, Eduardo; Aguiar, Paulo

    2013-10-01

    Models for temporary information storage in neuronal populations are dominated by mechanisms directly dependent on synaptic plasticity. There are nevertheless other mechanisms available that are well suited for creating short-term memories. Here we present a model for working memory which relies on the modulation of the intrinsic excitability properties of neurons, instead of synaptic plasticity, to retain novel information for periods of seconds to minutes. We show that it is possible to effectively use this mechanism to store the serial order in a sequence of patterns of activity. For this we introduce a functional class of neurons, named gate interneurons, which can store information in their membrane dynamics and can literally act as gates routing the flow of activations in the principal neurons population. The presented model exhibits properties which are in close agreement with experimental results in working memory. Namely, the recall process plays an important role in stabilizing and prolonging the memory trace. This means that the stored information is correctly maintained as long as it is being used. Moreover, the working memory model is adequate for storing completely new information, in time windows compatible with the notion of "one-shot" learning (hundreds of milliseconds).

  16. Concept hierarchy memory model: a neural architecture for conceptual knowledge representation, learning, and commonsense reasoning.

    Science.gov (United States)

    Tan, A H; Soon, H S

    1996-07-01

    This article introduces a neural network based cognitive architecture termed Concept Hierarchy Memory Model (CHMM) for conceptual knowledge representation and commonsense reasoning. CHMM is composed of two subnetworks: a Concept Formation Network (CFN), that acquires concepts based on their sensory representations; and a Concept Hierarchy Network (CHN), that encodes hierarchical relationships between concepts. Based on Adaptive Resonance Associative Map (ARAM), a supervised Adaptive Resonance Theory (ART) model, CHMM provides a systematic treatment for concept formation and organization of a concept hierarchy. Specifically, a concept can be learned by sampling activities across multiple sensory fields. By chunking relations between concepts as cognitive codes, a concept hierarchy can be learned/modified through experience. Also, fuzzy relations between concepts can now be represented in terms of the weights on the links connecting them. Using a unified inferencing mechanism based on code firing, CHMM performs an important class of commonsense reasoning, including concept recognition and property inheritance.

  17. Phenomenological validity of an OCD-memory model and the remember/know distinction

    NARCIS (Netherlands)

    van den Hout, M.; Kindt, M.

    2003-01-01

    In earlier experiments using interactive computer animation with healthy subjects, it was found that displaying compulsive-like repeated checking behavior affects memory. That is, checking does not alter actual memory accuracy, but it does affect 'meta-memory': as checking continues, recollections

  18. A stochastic approach for model reduction and memory function design in hydrogeophysical inversion

    Science.gov (United States)

    Hou, Z.; Kellogg, A.; Terry, N.

    2009-12-01

    Geophysical (e.g., seismic, electromagnetic, radar) techniques and statistical methods are essential for research related to subsurface characterization, including monitoring subsurface flow and transport processes, oil/gas reservoir identification, etc. For deep subsurface characterization such as reservoir petroleum exploration, seismic methods have been widely used. Recently, electromagnetic (EM) methods have drawn great attention in the area of reservoir characterization. However, considering the enormous computational demand corresponding to seismic and EM forward modeling, it is usually a big problem to have too many unknown parameters in the modeling domain. For shallow subsurface applications, the characterization can be very complicated considering the complexity and nonlinearity of flow and transport processes in the unsaturated zone. It is warranted to reduce the dimension of parameter space to a reasonable level. Another common concern is how to make the best use of time-lapse data with spatial-temporal correlations. This is even more critical when we try to monitor subsurface processes using geophysical data collected at different times. The normal practice is to get the inverse images individually. These images are not necessarily continuous or even reasonably related, because of the non-uniqueness of hydrogeophysical inversion. We propose to use a stochastic framework by integrating minimum-relative-entropy concept, quasi Monto Carlo sampling techniques, and statistical tests. The approach allows efficient and sufficient exploration of all possibilities of model parameters and evaluation of their significances to geophysical responses. The analyses enable us to reduce the parameter space significantly. The approach can be combined with Bayesian updating, allowing us to treat the updated ‘posterior’ pdf as a memory function, which stores all the information up to date about the distributions of soil/field attributes/properties, then consider the

  19. Brain scale-free properties in awake rest and NREM sleep: a simultaneous EEG/fMRI study.

    Science.gov (United States)

    Lei, Xu; Wang, Yulin; Yuan, Hong; Chen, Antao

    2015-03-01

    Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) studies revealed that spontaneous activity in the brain has scale-invariant properties, as indicated by a frequency spectrum that follows a power-law distribution. However, current knowledge about the exact relationship between scaling properties in EEG and fMRI signals is very limited. To address this question, we collected simultaneous EEG-fMRI data in healthy individuals during resting wakefulness and non-rapid eye movement (NREM) sleep. For either of these conditions, we found that both EEG and fMRI power spectra followed a power-law distribution. Furthermore, the EEG and fMRI scaling exponents were highly variable across subjects, and sensitive to the choice of reference and nuisance variables in EEG and fMRI data, respectively. Interestingly, the EEG exponent of the whole brain selectively corresponded to the fMRI exponent of the thalamus during NREM sleep. Together, our findings suggest that scale-free brain activity is characterized by robust temporal structures and behavioral significance. This motivates future studies to unravel its physiological mechanisms, as well as its relevance to behavior.

  20. Redesigned-Scale-Free CORDIC Algorithm Based FPGA Implementation of Window Functions to Minimize Area and Latency

    Directory of Open Access Journals (Sweden)

    Supriya Aggarwal

    2012-01-01

    Full Text Available One of the most important steps in spectral analysis is filtering, where window functions are generally used to design filters. In this paper, we modify the existing architecture for realizing the window functions using CORDIC processor. Firstly, we modify the conventional CORDIC algorithm to reduce its latency and area. The proposed CORDIC algorithm is completely scale-free for the range of convergence that spans the entire coordinate space. Secondly, we realize the window functions using a single CORDIC processor as against two serially connected CORDIC processors in existing technique, thus optimizing it for area and latency. The linear CORDIC processor is replaced by a shift-add network which drastically reduces the number of pipelining stages required in the existing design. The proposed design on an average requires approximately 64% less pipeline stages and saves up to 44.2% area. Currently, the processor is designed to implement Blackman windowing architecture, which with slight modifications can be extended to other widow functions as well. The details of the proposed architecture are discussed in the paper.

  1. Specific impairment of "what-where-when" episodic-like memory in experimental models of temporal lobe epilepsy.

    Science.gov (United States)

    Inostroza, Marion; Brotons-Mas, Jorge R; Laurent, François; Cid, Elena; de la Prida, Liset Menendez

    2013-11-06

    Episodic memory deficit is a common cognitive disorder in human temporal lobe epilepsy (TLE). However, no animal model of TLE has been shown to specifically replicate this cognitive dysfunction, which has limited its translational appeal. Here, using a task that tests for nonverbal correlates of episodic-like memory in rats, we show that kainate-treated TLE rats exhibit a selective impairment of the "what-where-when" memory while preserving other forms of hippocampal-dependent memories. Assisted by multisite silicon probes, we recorded from the dorsal hippocampus of behaving animals to control for seizure-related factors and to look for electrophysiological signatures of cognitive impairment. Analyses of hippocampal local field potentials showed that both the power of theta rhythm and its coordination across CA1 and the DG-measured as theta coherence and phase locking-were selectively disrupted. This disruption represented a basal condition of the chronic epileptic hippocampus that was linked to different features of memory impairment. Theta power was more correlated with the spatial than with the temporal component of the task, while measures of theta coordination correlated with the temporal component. We conclude that episodic-like memory, as tested in the what-where-when task, is specifically affected in experimental TLE and that the impairment of hippocampal theta activity might be central to this dysfunction.

  2. Exercise improves recognition memory and synaptic plasticity in the prefrontal cortex for rats modelling vascular dementia.

    Science.gov (United States)

    Dong, Juntao; Zhao, Jingpu; Lin, Yangyang; Liang, Huiying; He, Xiaokuo; Zheng, Xiuyuan; Sui, Minghong; Zhuang, Zhiqiang; Yan, Tiebin

    2018-01-01

    Functional electrical stimulation (FES) may induce involuntary exercise and make beneficial effects on vascular dementia (VD) by strengthening the BDNF-pCREB-mediated pathway and hippocampal plasticity. Whether FES improves recognition memory and synaptic plasticity in the prefrontal cortex (PFC) was investigated by establishing a VD model. The VD rats were administered with two weeks of voluntary exercise, forced exercise, or involuntary exercise induced with FES. Sham-operated and control groups were also included. The behavioral changes were assessed with the novel object recognition test and novel object location test. The expression levels of key proteins related to synaptic plasticity in the PFC were also detected. All types of exercise improved the rats' novel object recognition index, but only voluntary exercise and involuntary exercise induced with FES improved the novel object location index. Any sort of exercise enhanced the expression of key proteins in the PFC. Involuntary exercise induced with FES can improve recognition memory in VD better than forced exercise. The mechanism is associated with increased synaptic plasticity in the PFC. FES may be a useful alternative tool for cognitive rehabilitation.

  3. Scanning ultrasound removes amyloid-β and restores memory in an Alzheimer's disease mouse model.

    Science.gov (United States)

    Leinenga, Gerhard; Götz, Jürgen

    2015-03-11

    Amyloid-β (Aβ) peptide has been implicated in the pathogenesis of Alzheimer's disease (AD). We present a nonpharmacological approach for removing Aβ and restoring memory function in a mouse model of AD in which Aβ is deposited in the brain. We used repeated scanning ultrasound (SUS) treatments of the mouse brain to remove Aβ, without the need for any additional therapeutic agent such as anti-Aβ antibody. Spinning disk confocal microscopy and high-resolution three-dimensional reconstruction revealed extensive internalization of Aβ into the lysosomes of activated microglia in mouse brains subjected to SUS, with no concomitant increase observed in the number of microglia. Plaque burden was reduced in SUS-treated AD mice compared to sham-treated animals, and cleared plaques were observed in 75% of SUS-treated mice. Treated AD mice also displayed improved performance on three memory tasks: the Y-maze, the novel object recognition test, and the active place avoidance task. Our findings suggest that repeated SUS is useful for removing Aβ in the mouse brain without causing overt damage, and should be explored further as a noninvasive method with therapeutic potential in AD. Copyright © 2015, American Association for the Advancement of Science.

  4. Cyclophilin D deficiency improves mitochondrial function and learning/memory in aging Alzheimer disease mouse model.

    Science.gov (United States)

    Du, Heng; Guo, Lan; Zhang, Wensheng; Rydzewska, Monika; Yan, Shidu

    2011-03-01

    Mitochondrial stress is one of the early features of Alzheimer disease (AD). Mitochondrial Aβ has been linked to mitochondrial toxicity. Our recent study demonstrated that cyclophilin D (CypD) mediated mitochondrial permeability transition pore (mPTP) is an important mechanism for neuronal and synaptic stress induced by both Aβ and oxidative stress. In transgenic AD-type mice overexpressing mutant amyloid precursor protein (APP) and Aβ (mAPP), CypD deficiency improves mitochondrial and synaptic function and learning/memory up to 12 months old. Here we provide evidence of the protective effects of CypD deficiency in aged AD mice (22-24 months). Cyp D deficient mAPP mice demonstrate less calcium-induced mitochondrial swelling, increased mitochondrial calcium uptake capacity, preserved mitochondrial respiratory function and improved spatial learning/memory even in old age (known to be the age for late stage AD pathology and synaptic dysfunction). These data demonstrate that abrogation of CypD results in persistent life-long protection against Aβ toxicity in an Alzheimer's disease mouse model, thereby suggesting that blockade of CypD may be of benefit for Alzheimer disease treatment. Copyright © 2009 Elsevier Inc. All rights reserved.

  5. TECHNICAL NOTE: Thermal modelling of shape memory alloy fixator for medical application

    Science.gov (United States)

    Song, C.; Campbell, P. A.; Frank, T. G.; Cuschieri, A.

    2002-04-01

    Shape memory alloy has been recently used for tissue fixation in minimal access surgery (MAS). It offers an alternative to conventional thread-based suturing of human tissue, with the advantage that its deployment is faster and requires fewer surgical skills. To minimize the damage to surrounding tissue, thermal analysis of tissue-fixator interactions has been done to optimize the heating method, and to predict the heating effect and affected range. The finite-difference method has been used to solve the one-dimensional transient heat transfer problem, with fixator-tissue conduction boundary condition, and the finite-element method was used to build a three-dimensional model for the design optimization. The predicted temperature responses of tissue are considered within a safety range. Tissue temperature drops quickly after heating, and the affected tissue is limited to a layer 1 mm thick next to the fixator. Further in vivo animal studies on the use of the shape memory alloy fixator are ongoing for future applications of tissue suturing in MAS.

  6. Moderate exercise ameliorates dysregulated hippocampal glycometabolism and memory function in a rat model of type 2 diabetes.

    Science.gov (United States)

    Shima, Takeru; Matsui, Takashi; Jesmin, Subrina; Okamoto, Masahiro; Soya, Mariko; Inoue, Koshiro; Liu, Yu-Fan; Torres-Aleman, Ignacio; McEwen, Bruce S; Soya, Hideaki

    2017-03-01

    Type 2 diabetes is likely to be an independent risk factor for hippocampal-based memory dysfunction, although this complication has yet to be investigated in detail. As dysregulated glycometabolism in peripheral tissues is a key symptom of type 2 diabetes, it is hypothesised that diabetes-mediated memory dysfunction is also caused by hippocampal glycometabolic dysfunction. If so, such dysfunction should also be ameliorated with moderate exercise by normalising hippocampal glycometabolism, since 4 weeks of moderate exercise enhances memory function and local hippocampal glycogen levels in normal animals. The hippocampal glycometabolism in OLETF rats (model of human type 2 diabetes) was assessed and, subsequently, the effects of exercise on memory function and hippocampal glycometabolism were investigated. OLETF rats, which have memory dysfunction, exhibited higher levels of glycogen in the hippocampus than did control rats, and breakdown of hippocampal glycogen with a single bout of exercise remained unimpaired. However, OLETF rats expressed lower levels of hippocampal monocarboxylate transporter 2 (MCT2, a transporter for lactate to neurons). Four weeks of moderate exercise improved spatial memory accompanied by further increase in hippocampal glycogen levels and restoration of MCT2 expression independent of neurotrophic factor and clinical symptoms in OLETF rats. Our findings are the first to describe detailed profiles of glycometabolism in the type 2 diabetic hippocampus and to show that 4 weeks of moderate exercise improves memory dysfunction in type 2 diabetes via amelioration of dysregulated hippocampal glycometabolism. Dysregulated hippocampal lactate-transport-related glycometabolism is a possible aetiology of type-2-diabetes-mediated memory dysfunction.

  7. Effect of Rheum Ribes Hydro-Alcoholic Extract on Memory Impairments in Rat Model of Alzheimer's Disease

    OpenAIRE

    ZAHEDI, MARYAM; Hojjati, Mohammad Reza; Fathpour, Hossein; Rabiei, Zahra; Alibabaei, Zahra; Basim, Arezoo

    2015-01-01

    Some animal models have been used to study Alzheimer's disease (AD). AD is an irreversible progressive neurodegenerative disease and the most common cause of dementia. Animal studies have shown that there is a relation between decrease in cholinergic functions in the nucleus basalis of Meynert (NBM) and loss of learning capability and memory. The aim of this study was to investigate the effect of Rheum ribes extract (RR) on memory deficit in one of the rat models of AD. Plant (1500gr) was col...

  8. Hybrid micro-macro-mechanical constitutive model for shape-memory alloys

    Science.gov (United States)

    Wong, Franklin C.; Boissonneault, Olivier; Terriault, Patrick

    2005-05-01

    A substantial reduction in the size of control actuation systems employed in today's aerospace vehicles can enhance overall vehicle performance by reducing envelope volume requirements and inert weight. Functional materials such as shape memory alloys (SMA's) offer the opportunity to create compact, solid-state actuation systems by virtue of the material's ability to convert electrical energy to thermal energy to mechanical energy within its microstructure. A hybrid micro-macro-mechanical SMA model is developed for future closed-loop actuator development studies. The constitutive model is a combination of concepts originally presented by Likhatchev for microstructural modeling and Brinson for modeling of transformation kinetics. Global strain of the heterogeneous solid or polycrystal, where the grains are assumed to be randomly oriented, was calculated by averaging the elastic, thermal, stress-induced and autoaccomodation strains of each grain over the total material volume. The introduction of a frequency distribution function in the micromechanical model provided a convenient way to quantify texture. The model was successfully tested under constant temperature conditions and constant load-low frequency cycling conditions.

  9. Serotonergic modulation of spatial working memory: predictions from a computational network model

    Directory of Open Access Journals (Sweden)

    Maria eCano-Colino

    2013-09-01

    Full Text Available Serotonin (5-HT receptors of types 1A and 2A are massively expressed in prefrontal cortex (PFC neurons, an area associated with cognitive function. Hence, 5-HT could be effective in modulating prefrontal-dependent cognitive functions, such as spatial working memory (SWM. However, a direct association between 5-HT and SWM has proved elusive in psycho-pharmacological studies. Recently, a computational network model of the PFC microcircuit was used to explore the relationship between 5‑HT and SWM (Cano-Colino et al. 2013. This study found that both excessive and insufficient 5-HT levels lead to impaired SWM performance in the network, and it concluded that analyzing behavioral responses based on confidence reports could facilitate the experimental identification of SWM behavioral effects of 5‑HT neuromodulation. Such analyses may have confounds based on our limited understanding of metacognitive processes. Here, we extend these results by deriving three additional predictions from the model that do not rely on confidence reports. Firstly, only excessive levels of 5-HT should result in SWM deficits that increase with delay duration. Secondly, excessive 5-HT baseline concentration makes the network vulnerable to distractors at distances that were robust to distraction in control conditions, while the network still ignores distractors efficiently for low 5‑HT levels that impair SWM. Finally, 5-HT modulates neuronal memory fields in neurophysiological experiments: Neurons should be better tuned to the cued stimulus than to the behavioral report for excessive 5-HT levels, while the reverse should happen for low 5-HT concentrations. In all our simulations agonists of 5-HT1A receptors and antagonists of 5-HT2A receptors produced behavioral and physiological effects in line with global 5-HT level increases. Our model makes specific predictions to be tested experimentally and advance our understanding of the neural basis of SWM and its neuromodulation

  10. A multi-branch finite deformation constitutive model for a shape memory polymer based syntactic foam

    Science.gov (United States)

    Gu, Jianping; Sun, Huiyu; Fang, Changqing

    2015-02-01

    A multi-branch thermoviscoelastic-themoviscoplastic finite deformation constitutive model incorporated with structural and stress relaxation is developed for a thermally activated shape memory polymer (SMP) based syntactic foam. In this paper, the total mechanical deformation of the foam is divided into the components of the SMP and the elastic glass microballoons by using the mixture rule. The nonlinear Adam-Gibbs model is used to describe the structural relaxation of the SMP as the temperature crosses the glass transition temperature (Tg). Further, a multi-branch model combined with the modified Eying model of viscous flow is used to capture the multitude of relaxation processes of the SMP. The deformation of the glass microballoons could be split into elastic and inelastic components. In addition, the phenomenological evolution rule is implemented in order to further characterize the macroscopic post-yield strain softening behaviors of the syntactic foam. A comparison between the numerical simulation and the thermomechanical experiment shows an acceptable agreement. Moreover, a parametric study is conducted to examine the predictability of the model and to provide guidance for reasonable design of the syntactic foam.

  11. Tree shrew models: a chronic social defeat model of depression and a one-trial captive conditioning model of learning and memory.

    Science.gov (United States)

    Wang, Jing; Zhou, Qi-Xin; Tian, Men; Yang, Yue-Xiong; Xu, Lin

    2011-02-01

    Recent genome studies indicate that tree shrew is in the order or a closest sister of primates, and thus may be one of the best animals to model human diseases. In this paper, we report on a social defeat model of depression in tree shrew (Tupaia belangeri chinensis). Two male tree shrews were housed in a pair-cage consisting of two independent cages separated by a wire mesh partition with a door connecting the two cages. After one week adaptation, the connecting door was opened and a brief fighting occurs between the two male tree shrews and this social conflict session consisted of 1 h direct conflict (fighting) and 23 h indirect influence (e.g. smell, visual cues) per day for 21 days. The defeated tree shrew was considered the subordinate. Compared with naive animals, subordinate tree shrews at the final week of social conflict session showed alterations in body weight, locomotion, avoidance behavior and urinary cortisol levels. Remarkably, these alterations persisted for over two weeks. We also report on a novel captive conditioning model of learning and memory in tree shrew. An automatic trapping cage was placed in a small closed room with a freely-moving tree shrew. For the first four trials, the tree shrew was not trapped when it entered the cage and ate the bait apple, but it was trapped and kept in the cage for 1 h on the fifth trial. Latency was defined as the time between release of the tree shrew and when it entered the captive cage. Latencies during the five trials indicated adaptation. A test trial 24 h later was used to measure whether the one-trial trapping during the fifth trial could form captive memory. Tree shrews showed much longer trapping latencies in the test trial than the adaptation trials. The N-methyl-d-aspartate (NMDA) receptor antagonist MK-801 (0.2 mg/kg, i.p.), known to prevent the formation of memory, did not affect latencies in the adaptation trails, but did block captive memory as it led to much shorter trapping latencies compared

  12. Detecting memory and structure in human navigation patterns using Markov chain models of varying order.

    Directory of Open Access Journals (Sweden)

    Philipp Singer

    Full Text Available One of the most frequently used models for understanding human navigation on the Web is the Markov chain model, where Web pages are represented as states and hyperlinks as probabilities of navigating from one page to another. Predominantly, human navigation on the Web has been thought to satisfy the memoryless Markov property stating that the next page a user visits only depends on her current page and not on previously visited ones. This idea has found its way in numerous applications such as Google's PageRank algorithm and others. Recently, new studies suggested that human navigation may better be modeled using higher order Markov chain models, i.e., the next page depends on a longer history of past clicks. Yet, this finding is preliminary and does not account for the higher complexity of higher order Markov chain models which is why the memoryless model is still widely used. In this work we thoroughly present a diverse array of advanced inference methods for determining the appropriate Markov chain order. We highlight strengths and weaknesses of each method and apply them for investigating memory and structure of human navigation on the Web. Our experiments reveal that the complexity of higher order models grows faster than their utility, and thus we confirm that the memoryless model represents a quite practical model for human navigation on a page level. However, when we expand our analysis to a topical level, where we abstract away from specific page transitions to transitions between topics, we find that the memoryless assumption is violated and specific regularities can be observed. We report results from experiments with two types of navigational datasets (goal-oriented vs. free form and observe interesting structural differences that make a strong argument for more contextual studies of human navigation in future work.

  13. Detecting memory and structure in human navigation patterns using Markov chain models of varying order.

    Science.gov (United States)

    Singer, Philipp; Helic, Denis; Taraghi, Behnam; Strohmaier, Markus

    2014-01-01

    One of the most frequently used models for understanding human navigation on the Web is the Markov chain model, where Web pages are represented as states and hyperlinks as probabilities of navigating from one page to another. Predominantly, human navigation on the Web has been thought to satisfy the memoryless Markov property stating that the next page a user visits only depends on her current page and not on previously visited ones. This idea has found its way in numerous applications such as Google's PageRank algorithm and others. Recently, new studies suggested that human navigation may better be modeled using higher order Markov chain models, i.e., the next page depends on a longer history of past clicks. Yet, this finding is preliminary and does not account for the higher complexity of higher order Markov chain models which is why the memoryless model is still widely used. In this work we thoroughly present a diverse array of advanced inference methods for determining the appropriate Markov chain order. We highlight strengths and weaknesses of each method and apply them for investigating memory and structure of human navigation on the Web. Our experiments reveal that the complexity of higher order models grows faster than their utility, and thus we confirm that the memoryless model represents a quite practical model for human navigation on a page level. However, when we expand our analysis to a topical level, where we abstract away from specific page transitions to transitions between topics, we find that the memoryless assumption is violated and specific regularities can be observed. We report results from experiments with two types of navigational datasets (goal-oriented vs. free form) and observe interesting structural differences that make a strong argument for more contextual studies of human navigation in future work.

  14. Tartary buckwheat improves cognition and memory function in an in vivo amyloid-β-induced Alzheimer model.

    Science.gov (United States)

    Choi, Ji Yeon; Cho, Eun Ju; Lee, Hae Song; Lee, Jeong Min; Yoon, Young-Ho; Lee, Sanghyun

    2013-03-01

    Protective effects of Tartary buckwheat (TB) and common buckwheat (CB) on amyloid beta (Aβ)-induced impairment of cognition and memory function were investigated in vivo in order to identify potential therapeutic agents against Alzheimer's disease (AD) and its associated progressive memory deficits, cognitive impairment, and personality changes. An in vivo mouse model of AD was created by injecting the brains of ICR mice with Aβ(25-35), a fragment of the full-length Aβ protein. Damage of mice recognition ability through following Aβ(25-35) brain injections was confirmed using the T-maze test, the object recognition test, and the Morris water maze test. Results of behavior tests in AD model showed that oral administration of the methanol (MeOH) extracts of TB and CB improved cognition and memory function following Aβ(25-35) injections. Furthermore, in groups receiving the MeOH extracts of TB and CB, lipid peroxidation was significantly inhibited, and nitric oxide levels in tissue, which are elevated by injection of Aβ(25-35), were also decrease. In particular, the MeOH extract of TB exerted a stronger protective activity than CB against Aβ(25-35)-induced memory and cognition impairment. The results indicate that TB may play a promising role in preventing or reversing memory and cognition loss associated with Aβ(25-35)-induced AD. Copyright © 2012 Elsevier Ltd. All rights reserved.

  15. In vivo tissue response following implantation of shape memory polyurethane foam in a porcine aneurysm model

    Science.gov (United States)

    Rodriguez, Jennifer N.; Clubb, Fred J.; Wilson, Thomas S.; Miller, Matthew W.; Fossum, Theresa W.; Hartman, Jonathan; Tuzun, Egemen; Singhal, Pooja; Maitland, Duncan J.

    2014-01-01

    Cerebral aneurysms treated by traditional endovascular methods using platinum coils have a tendency to be unstable, either due to chronic inflammation, compaction of coils, or growth of the aneurysm. We propose to use alternate filling methods for the treatment of intracranial aneurysms using polyurethane based shape memory polymer (SMP) foams. SMP polyurethane foams were surgically implanted in a porcine aneurysm model to determine biocompatibility, localized thrombogenicity, and their ability to serve as a stable filler material within an aneurysm. The degree of healing was evaluated via gross observation, histopathology and low vacuum scanning electron microscopy (LV-SEM) imaging after zero, thirty and ninety days. Clotting was initiated within the SMP foam at time zero (less than one hour exposure to blood prior to euthanization), partial healing was observed at thirty days, and almost complete healing had occurred at ninety days in vivo, with minimal inflammatory response. PMID:23650278

  16. In vivo response to an implanted shape memory polyurethane foam in a porcine aneurysm model.

    Science.gov (United States)

    Rodriguez, Jennifer N; Clubb, Fred J; Wilson, Thomas S; Miller, Matthew W; Fossum, Theresa W; Hartman, Jonathan; Tuzun, Egemen; Singhal, Pooja; Maitland, Duncan J

    2014-05-01

    Cerebral aneurysms treated by traditional endovascular methods using platinum coils have a tendency to be unstable, either due to chronic inflammation, compaction of coils, or growth of the aneurysm. We propose to use alternate filling methods for the treatment of intracranial aneurysms using polyurethane-based shape memory polymer (SMP) foams. SMP polyurethane foams were surgically implanted in a porcine aneurysm model to determine biocompatibility, localized thrombogenicity, and their ability to serve as a stable filler material within an aneurysm. The degree of healing was evaluated via gross observation, histopathology, and low vacuum scanning electron microscopy imaging after 0, 30, and 90 days. Clotting was initiated within the SMP foam at time 0 (<1 h exposure to blood before euthanization), partial healing was observed at 30 days, and almost complete healing had occurred at 90 days in vivo, with minimal inflammatory response. Copyright © 2013 Wiley Periodicals, Inc.

  17. Energy-based fatigue model for shape memory alloys including thermomechanical coupling

    Science.gov (United States)

    Zhang, Yahui; Zhu, Jihong; Moumni, Ziad; Van Herpen, Alain; Zhang, Weihong

    2016-03-01

    This paper is aimed at developing a low cycle fatigue criterion for pseudoelastic shape memory alloys to take into account thermomechanical coupling. To this end, fatigue tests are carried out at different loading rates under strain control at room temperature using NiTi wires. Temperature distribution on the specimen is measured using a high speed thermal camera. Specimens are tested to failure and fatigue lifetimes of specimens are measured. Test results show that the fatigue lifetime is greatly influenced by the loading rate: as the strain rate increases, the fatigue lifetime decreases. Furthermore, it is shown that the fatigue cracks initiate when the stored energy inside the material reaches a critical value. An energy-based fatigue criterion is thus proposed as a function of the irreversible hysteresis energy of the stabilized cycle and the loading rate. Fatigue life is calculated using the proposed model. The experimental and computational results compare well.

  18. Coupling Multi-Component Models with MPH on Distributed MemoryComputer Architectures

    Energy Technology Data Exchange (ETDEWEB)

    He, Yun; Ding, Chris

    2005-03-24

    A growing trend in developing large and complex applications on today's Teraflop scale computers is to integrate stand-alone and/or semi-independent program components into a comprehensive simulation package. One example is the Community Climate System Model which consists of atmosphere, ocean, land-surface and sea-ice components. Each component is semi-independent and has been developed at a different institution. We study how this multi-component, multi-executable application can run effectively on distributed memory architectures. For the first time, we clearly identify five effective execution modes and develop the MPH library to support application development utilizing these modes. MPH performs component-name registration, resource allocation and initial component handshaking in a flexible way.

  19. Modified stretched exponential model of computer system resources management limitations-The case of cache memory

    Science.gov (United States)

    Strzałka, Dominik; Dymora, Paweł; Mazurek, Mirosław

    2018-02-01

    In this paper we present some preliminary results in the field of computer systems management with relation to Tsallis thermostatistics and the ubiquitous problem of hardware limited resources. In the case of systems with non-deterministic behaviour, management of their resources is a key point that guarantees theirs acceptable performance and proper working. This is very wide problem that stands for many challenges in financial, transport, water and food, health, etc. areas. We focus on computer systems with attention paid to cache memory and propose to use an analytical model that is able to connect non-extensive entropy formalism, long-range dependencies, management of system resources and queuing theory. Obtained analytical results are related to the practical experiment showing interesting and valuable results.

  20. A Grey NGM(1,1, k) Self-Memory Coupling Prediction Model for Energy Consumption Prediction

    Science.gov (United States)

    Guo, Xiaojun; Liu, Sifeng; Wu, Lifeng; Tang, Lingling

    2014-01-01

    Energy consumption prediction is an important issue for governments, energy sector investors, and other related corporations. Although there are several prediction techniques, selection of the most appropriate technique is of vital importance. As for the approximate nonhomogeneous exponential data sequence often emerging in the energy system, a novel grey NGM(1,1, k) self-memory coupling prediction model is put forward in order to promote the predictive performance. It achieves organic integration of the self-memory principle of dynamic system and grey NGM(1,1, k) model. The traditional grey model's weakness as being sensitive to initial value can be overcome by the self-memory principle. In this study, total energy, coal, and electricity consumption of China is adopted for demonstration by using the proposed coupling prediction technique. The results show the superiority of NGM(1,1, k) self-memory coupling prediction model when compared with the results from the literature. Its excellent prediction performance lies in that the proposed coupling model can take full advantage of the systematic multitime historical data and catch the stochastic fluctuation tendency. This work also makes a significant contribution to the enrichment of grey prediction theory and the extension of its application span. PMID:25054174