Multifractal analysis of the Korean agricultural market

NASA Astrophysics Data System (ADS)

Kim, Hongseok; Oh, Gabjin; Kim, Seunghwan

2011-11-01

We have studied the long-term memory effects of the Korean agricultural market using the detrended fluctuation analysis (DFA) method. In general, the return time series of various financial data, including stock indices, foreign exchange rates, and commodity prices, are uncorrelated in time, while the volatility time series are strongly correlated. However, we found that the return time series of Korean agricultural commodity prices are anti-correlated in time, while the volatility time series are correlated. The n-point correlations of time series were also examined, and it was found that a multifractal structure exists in Korean agricultural market prices.

Efficient Bayesian inference for natural time series using ARFIMA processes

NASA Astrophysics Data System (ADS)

Graves, Timothy; Gramacy, Robert; Franzke, Christian; Watkins, Nicholas

2016-04-01

Many geophysical quantities, such as atmospheric temperature, water levels in rivers, and wind speeds, have shown evidence of long memory (LM). LM implies that these quantities experience non-trivial temporal memory, which potentially not only enhances their predictability, but also hampers the detection of externally forced trends. Thus, it is important to reliably identify whether or not a system exhibits LM. We present a modern and systematic approach to the inference of LM. We use the flexible autoregressive fractional integrated moving average (ARFIMA) model, which is widely used in time series analysis, and of increasing interest in climate science. Unlike most previous work on the inference of LM, which is frequentist in nature, we provide a systematic treatment of Bayesian inference. In particular, we provide a new approximate likelihood for efficient parameter inference, and show how nuisance parameters (e.g., short-memory effects) can be integrated over in order to focus on long-memory parameters and hypothesis testing more directly. We illustrate our new methodology on the Nile water level data and the central England temperature (CET) time series, with favorable comparison to the standard estimators [1]. In addition we show how the method can be used to perform joint inference of the stability exponent and the memory parameter when ARFIMA is extended to allow for alpha-stable innovations. Such models can be used to study systems where heavy tails and long range memory coexist. [1] Graves et al, Nonlin. Processes Geophys., 22, 679-700, 2015; doi:10.5194/npg-22-679-2015.

The Hurst exponent in energy futures prices

NASA Astrophysics Data System (ADS)

Serletis, Apostolos; Rosenberg, Aryeh Adam

2007-07-01

This paper extends the work in Elder and Serletis [Long memory in energy futures prices, Rev. Financial Econ., forthcoming, 2007] and Serletis et al. [Detrended fluctuation analysis of the US stock market, Int. J. Bifurcation Chaos, forthcoming, 2007] by re-examining the empirical evidence for random walk type behavior in energy futures prices. In doing so, it uses daily data on energy futures traded on the New York Mercantile Exchange, over the period from July 2, 1990 to November 1, 2006, and a statistical physics approach-the ‘detrending moving average’ technique-providing a reliable framework for testing the information efficiency in financial markets as shown by Alessio et al. [Second-order moving average and scaling of stochastic time series, Eur. Phys. J. B 27 (2002) 197-200] and Carbone et al. [Time-dependent hurst exponent in financial time series. Physica A 344 (2004) 267-271; Analysis of clusters formed by the moving average of a long-range correlated time series. Phys. Rev. E 69 (2004) 026105]. The results show that energy futures returns display long memory and that the particular form of long memory is anti-persistence.

Bayesian Analysis of Non-Gaussian Long-Range Dependent Processes

NASA Astrophysics Data System (ADS)

Graves, T.; Franzke, C.; Gramacy, R. B.; Watkins, N. W.

2012-12-01

Recent studies have strongly suggested that surface temperatures exhibit long-range dependence (LRD). The presence of LRD would hamper the identification of deterministic trends and the quantification of their significance. It is well established that LRD processes exhibit stochastic trends over rather long periods of time. Thus, accurate methods for discriminating between physical processes that possess long memory and those that do not are an important adjunct to climate modeling. We have used Markov Chain Monte Carlo algorithms to perform a Bayesian analysis of Auto-Regressive Fractionally-Integrated Moving-Average (ARFIMA) processes, which are capable of modeling LRD. Our principal aim is to obtain inference about the long memory parameter, d,with secondary interest in the scale and location parameters. We have developed a reversible-jump method enabling us to integrate over different model forms for the short memory component. We initially assume Gaussianity, and have tested the method on both synthetic and physical time series such as the Central England Temperature. Many physical processes, for example the Faraday time series from Antarctica, are highly non-Gaussian. We have therefore extended this work by weakening the Gaussianity assumption. Specifically, we assume a symmetric α -stable distribution for the innovations. Such processes provide good, flexible, initial models for non-Gaussian processes with long memory. We will present a study of the dependence of the posterior variance σ d of the memory parameter d on the length of the time series considered. This will be compared with equivalent error diagnostics for other measures of d.

Memory and long-range correlations in chess games

NASA Astrophysics Data System (ADS)

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

2014-01-01

In this paper we report the existence of long-range memory in the opening moves of a chronologically ordered set of chess games using an extensive chess database. We used two mapping rules to build discrete time series and analyzed them using two methods for detecting long-range correlations; rescaled range analysis and detrended fluctuation analysis. We found that long-range memory is related to the level of the players. When the database is filtered according to player levels we found differences in the persistence of the different subsets. For high level players, correlations are stronger at long time scales; whereas in intermediate and low level players they reach the maximum value at shorter time scales. This can be interpreted as a signature of the different strategies used by players with different levels of expertise. These results are robust against the assignation rules and the method employed in the analysis of the time series.

A univariate model of river water nitrate time series

NASA Astrophysics Data System (ADS)

Worrall, F.; Burt, T. P.

1999-01-01

Four time series were taken from three catchments in the North and South of England. The sites chosen included two in predominantly agricultural catchments, one at the tidal limit and one downstream of a sewage treatment works. A time series model was constructed for each of these series as a means of decomposing the elements controlling river water nitrate concentrations and to assess whether this approach could provide a simple management tool for protecting water abstractions. Autoregressive (AR) modelling of the detrended and deseasoned time series showed a "memory effect". This memory effect expressed itself as an increase in the winter-summer difference in nitrate levels that was dependent upon the nitrate concentration 12 or 6 months previously. Autoregressive moving average (ARMA) modelling showed that one of the series contained seasonal, non-stationary elements that appeared as an increasing trend in the winter-summer difference. The ARMA model was used to predict nitrate levels and predictions were tested against data held back from the model construction process - predictions gave average percentage errors of less than 10%. Empirical modelling can therefore provide a simple, efficient method for constructing management models for downstream water abstraction.

Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory

PubMed Central

Tao, Qing

2017-01-01

Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM. PMID:29391864

Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory.

PubMed

Yang, Haimin; Pan, Zhisong; Tao, Qing

2017-01-01

Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM.

Time Series Model Identification by Estimating Information, Memory, and Quantiles.

DTIC Science & Technology

1983-07-01

Standards, Sect. D, 68D, 937-951. Parzen, Emanuel (1969) "Multiple time series modeling" Multivariate Analysis - II, edited by P. Krishnaiah , Academic... Krishnaiah , North Holland: Amsterdam, 283-295. Parzen, Emanuel (1979) "Forecasting and Whitening Filter Estimation" TIMS Studies in the Management...principle. Applications of Statistics, P. R. Krishnaiah , ed. North Holland: Amsterdam, 27-41. Box, G. E. P. and Jenkins, G. M. (1970) Time Series Analysis

A Study of Memory Effects in a Chess Database.

PubMed

Schaigorodsky, Ana L; Perotti, Juan I; Billoni, Orlando V

2016-01-01

A series of recent works studying a database of chronologically sorted chess games-containing 1.4 million games played by humans between 1998 and 2007- have shown that the popularity distribution of chess game-lines follows a Zipf's law, and that time series inferred from the sequences of those game-lines exhibit long-range memory effects. The presence of Zipf's law together with long-range memory effects was observed in several systems, however, the simultaneous emergence of these two phenomena were always studied separately up to now. In this work, by making use of a variant of the Yule-Simon preferential growth model, introduced by Cattuto et al., we provide an explanation for the simultaneous emergence of Zipf's law and long-range correlations memory effects in a chess database. We find that Cattuto's Model (CM) is able to reproduce both, Zipf's law and the long-range correlations, including size-dependent scaling of the Hurst exponent for the corresponding time series. CM allows an explanation for the simultaneous emergence of these two phenomena via a preferential growth dynamics, including a memory kernel, in the popularity distribution of chess game-lines. This mechanism results in an aging process in the chess game-line choice as the database grows. Moreover, we find burstiness in the activity of subsets of the most active players, although the aggregated activity of the pool of players displays inter-event times without burstiness. We show that CM is not able to produce time series with bursty behavior providing evidence that burstiness is not required for the explanation of the long-range correlation effects in the chess database. Our results provide further evidence favoring the hypothesis that long-range correlations effects are a consequence of the aging of game-lines and not burstiness, and shed light on the mechanism that operates in the simultaneous emergence of Zipf's law and long-range correlations in a community of chess players.

A Study of Memory Effects in a Chess Database

PubMed Central

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

2016-01-01

A series of recent works studying a database of chronologically sorted chess games–containing 1.4 million games played by humans between 1998 and 2007– have shown that the popularity distribution of chess game-lines follows a Zipf’s law, and that time series inferred from the sequences of those game-lines exhibit long-range memory effects. The presence of Zipf’s law together with long-range memory effects was observed in several systems, however, the simultaneous emergence of these two phenomena were always studied separately up to now. In this work, by making use of a variant of the Yule-Simon preferential growth model, introduced by Cattuto et al., we provide an explanation for the simultaneous emergence of Zipf’s law and long-range correlations memory effects in a chess database. We find that Cattuto’s Model (CM) is able to reproduce both, Zipf’s law and the long-range correlations, including size-dependent scaling of the Hurst exponent for the corresponding time series. CM allows an explanation for the simultaneous emergence of these two phenomena via a preferential growth dynamics, including a memory kernel, in the popularity distribution of chess game-lines. This mechanism results in an aging process in the chess game-line choice as the database grows. Moreover, we find burstiness in the activity of subsets of the most active players, although the aggregated activity of the pool of players displays inter-event times without burstiness. We show that CM is not able to produce time series with bursty behavior providing evidence that burstiness is not required for the explanation of the long-range correlation effects in the chess database. Our results provide further evidence favoring the hypothesis that long-range correlations effects are a consequence of the aging of game-lines and not burstiness, and shed light on the mechanism that operates in the simultaneous emergence of Zipf’s law and long-range correlations in a community of chess players. PMID:28005922

A statistical approach for segregating cognitive task stages from multivariate fMRI BOLD time series.

PubMed

Demanuele, Charmaine; Bähner, Florian; Plichta, Michael M; Kirsch, Peter; Tost, Heike; Meyer-Lindenberg, Andreas; Durstewitz, Daniel

2015-01-01

Multivariate pattern analysis can reveal new information from neuroimaging data to illuminate human cognition and its disturbances. Here, we develop a methodological approach, based on multivariate statistical/machine learning and time series analysis, to discern cognitive processing stages from functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) time series. We apply this method to data recorded from a group of healthy adults whilst performing a virtual reality version of the delayed win-shift radial arm maze (RAM) task. This task has been frequently used to study working memory and decision making in rodents. Using linear classifiers and multivariate test statistics in conjunction with time series bootstraps, we show that different cognitive stages of the task, as defined by the experimenter, namely, the encoding/retrieval, choice, reward and delay stages, can be statistically discriminated from the BOLD time series in brain areas relevant for decision making and working memory. Discrimination of these task stages was significantly reduced during poor behavioral performance in dorsolateral prefrontal cortex (DLPFC), but not in the primary visual cortex (V1). Experimenter-defined dissection of time series into class labels based on task structure was confirmed by an unsupervised, bottom-up approach based on Hidden Markov Models. Furthermore, we show that different groupings of recorded time points into cognitive event classes can be used to test hypotheses about the specific cognitive role of a given brain region during task execution. We found that whilst the DLPFC strongly differentiated between task stages associated with different memory loads, but not between different visual-spatial aspects, the reverse was true for V1. Our methodology illustrates how different aspects of cognitive information processing during one and the same task can be separated and attributed to specific brain regions based on information contained in multivariate patterns of voxel activity.

Fluctuations and Noise in Stochastic Spread of Respiratory Infection Epidemics in Social Networks

NASA Astrophysics Data System (ADS)

Yulmetyev, Renat; Emelyanova, Natalya; Demin, Sergey; Gafarov, Fail; Hänggi, Peter; Yulmetyeva, Dinara

2003-05-01

For the analysis of epidemic and disease dynamics complexity, it is necessary to understand the basic principles and notions of its spreading in long-time memory media. Here we considering the problem from a theoretical and practical viewpoint, presenting the quantitative evidence confirming the existence of stochastic long-range memory and robust chaos in a real time series of respiratory infections of human upper respiratory track. In this work we present a new statistical method of analyzing the spread of grippe and acute respiratory track infections epidemic process of human upper respiratory track by means of the theory of discrete non-Markov stochastic processes. We use the results of our recent theory (Phys. Rev. E 65, 046107 (2002)) for the study of statistical effects of memory in real data series, describing the epidemic dynamics of human acute respiratory track infections and grippe. The obtained results testify to an opportunity of the strict quantitative description of the regular and stochastic components in epidemic dynamics of social networks with a view to time discreteness and effects of statistical memory.

Multifractal detrended fluctuation analysis of sheep livestock prices in origin

NASA Astrophysics Data System (ADS)

Pavón-Domínguez, P.; Serrano, S.; Jiménez-Hornero, F. J.; Jiménez-Hornero, J. E.; Gutiérrez de Ravé, E.; Ariza-Villaverde, A. B.

2013-10-01

The multifractal detrended fluctuation analysis (MF-DFA) is used to verify whether or not the returns of time series of prices paid to farmers in original markets can be described by the multifractal approach. By way of example, 5 weekly time series of prices of different breeds, slaughter weight and market differentiation from 2000 to 2012 are analyzed. Results obtained from the multifractal parameters and multifractal spectra show that the price series of livestock products are of a multifractal nature. The Hurst exponent shows that these time series are stationary signals, some of which exhibit long memory (Merino milk-fed in Seville and Segureña paschal in Jaen), short memory (Merino paschal in Cordoba and Segureña milk-fed in Jaen) or even are close to an uncorrelated signals (Merino paschal in Seville). MF-DFA is able to discern the different underlying dynamics that play an important role in different types of sheep livestock markets, such as degree and source of multifractality. In addition, the main source of multifractality of these time series is due to the broadness of the probability function, instead of the long-range correlation properties between small and large fluctuations, which play a clearly secondary role.

Electrical Evaluation of RCA MWS5501D Random Access Memory, Volume 2, Appendix a

NASA Technical Reports Server (NTRS)

Klute, A.

1979-01-01

The electrical characterization and qualification test results are presented for the RCA MWS5001D random access memory. The tests included functional tests, AC and DC parametric tests, AC parametric worst-case pattern selection test, determination of worst-case transition for setup and hold times, and a series of schmoo plots. The address access time, address readout time, the data hold time, and the data setup time are some of the results surveyed.

A comment on measuring the Hurst exponent of financial time series

NASA Astrophysics Data System (ADS)

Couillard, Michel; Davison, Matt

2005-03-01

A fundamental hypothesis of quantitative finance is that stock price variations are independent and can be modeled using Brownian motion. In recent years, it was proposed to use rescaled range analysis and its characteristic value, the Hurst exponent, to test for independence in financial time series. Theoretically, independent time series should be characterized by a Hurst exponent of 1/2. However, finite Brownian motion data sets will always give a value of the Hurst exponent larger than 1/2 and without an appropriate statistical test such a value can mistakenly be interpreted as evidence of long term memory. We obtain a more precise statistical significance test for the Hurst exponent and apply it to real financial data sets. Our empirical analysis shows no long-term memory in some financial returns, suggesting that Brownian motion cannot be rejected as a model for price dynamics.

Memory, mental time travel and The Moustachio Quartet

PubMed Central

Wilkins, Clive

2017-01-01

Mental time travel allows us to revisit our memories and imagine future scenarios, and this is why memories are not only about the past, but they are also prospective. These episodic memories are not a fixed store of what happened, however, they are reassessed each time they are revisited and depend on the sequence in which events unfold. In this paper, we shall explore the complex relationships between memory and human experience, including through a series of novels ‘The Moustachio Quartet’ that can be read in any order. To do so, we shall integrate evidences from science and the arts to explore the subjective nature of memory and mental time travel, and argue that it has evolved primarily for prospection as opposed to retrospection. Furthermore, we shall question the notion that mental time travel is a uniquely human construct, and argue that some of the best evidence for the evolution of mental time travel comes from our distantly related cousins, the corvids, that cache food for the future and rely on long-lasting and highly accurate memories of what, where and when they stored their stashes of food. PMID:28479980

Memory, mental time travel and The Moustachio Quartet.

PubMed

Clayton, Nicola; Wilkins, Clive

2017-06-06

Mental time travel allows us to revisit our memories and imagine future scenarios, and this is why memories are not only about the past, but they are also prospective. These episodic memories are not a fixed store of what happened, however, they are reassessed each time they are revisited and depend on the sequence in which events unfold. In this paper, we shall explore the complex relationships between memory and human experience, including through a series of novels 'The Moustachio Quartet' that can be read in any order. To do so, we shall integrate evidences from science and the arts to explore the subjective nature of memory and mental time travel, and argue that it has evolved primarily for prospection as opposed to retrospection. Furthermore, we shall question the notion that mental time travel is a uniquely human construct, and argue that some of the best evidence for the evolution of mental time travel comes from our distantly related cousins, the corvids, that cache food for the future and rely on long-lasting and highly accurate memories of what, where and when they stored their stashes of food.

Electrical Evaluation of RCA MWS5001D Random Access Memory, Volume 4, Appendix C

NASA Technical Reports Server (NTRS)

Klute, A.

1979-01-01

The electrical characterization and qualification test results are presented for the RCA MWS5001D random access memory. The tests included functional tests, AC and DC parametric tests, AC parametric worst-case pattern selection test, determination of worst-case transition for setup and hold times, and a series of schmoo plots. Statistical analysis data is supplied along with write pulse width, read cycle time, write cycle time, and chip enable time data.

Changing Behavior by Memory Aids: A Social Psychological Model of Prospective Memory and Habit Development Tested with Dynamic Field Data

ERIC Educational Resources Information Center

Tobias, Robert

2009-01-01

This article presents a social psychological model of prospective memory and habit development. The model is based on relevant research literature, and its dynamics were investigated by computer simulations. Time-series data from a behavior-change campaign in Cuba were used for calibration and validation of the model. The model scored well in…

Limited capacity of working memory in unihemispheric random walks implies conceivable slow dispersal.

PubMed

Wei, Kun; Zhong, Suchuan

2017-08-01

Phenomenologically inspired by dolphins' unihemispheric sleep, we introduce a minimal model for random walks with physiological memory. The physiological memory consists of long-term memory which includes unconscious implicit memory and conscious explicit memory, and working memory which serves as a multi-component system for integrating, manipulating and managing short-term storage. The model assumes that the sleeping state allows retrievals of episodic objects merely from the episodic buffer where these memory objects are invoked corresponding to the ambient objects and are thus object-oriented, together with intermittent but increasing use of implicit memory in which decisions are unconsciously picked up from historical time series. The process of memory decay and forgetting is constructed in the episodic buffer. The walker's risk attitude, as a product of physiological heuristics according to the performance of objected-oriented decisions, is imposed on implicit memory. The analytical results of unihemispheric random walks with the mixture of object-oriented and time-oriented memory, as well as the long-time behavior which tends to the use of implicit memory, are provided, indicating the common sense that a conservative risk attitude is inclinable to slow movement.

Performance of FORTRAN floating-point operations on the Flex/32 multicomputer

NASA Technical Reports Server (NTRS)

Crockett, Thomas W.

1987-01-01

A series of experiments has been run to examine the floating-point performance of FORTRAN programs on the Flex/32 (Trademark) computer. The experiments are described, and the timing results are presented. The time required to execute a floating-point operation is found to vary considerbaly depending on a number of factors. One factor of particular interest from an algorithm design standpoint is the difference in speed between common memory accesses and local memory accesses. Common memory accesses were found to be slower, and guidelines are given for determinig when it may be cost effective to copy data from common to local memory.

Boosting Maintenance in Working Memory with Temporal Regularities

ERIC Educational Resources Information Center

Plancher, Gaën; Lévêque, Yohana; Fanuel, Lison; Piquandet, Gaëlle; Tillmann, Barbara

2018-01-01

Music cognition research has provided evidence for the benefit of temporally regular structures guiding attention over time. The present study investigated whether maintenance in working memory can benefit from an isochronous rhythm. Participants were asked to remember series of 6 letters for serial recall. In the rhythm condition of Experiment…

Memory effects in stock price dynamics: evidences of technical trading

PubMed Central

Garzarelli, Federico; Cristelli, Matthieu; Pompa, Gabriele; Zaccaria, Andrea; Pietronero, Luciano

2014-01-01

Technical trading represents a class of investment strategies for Financial Markets based on the analysis of trends and recurrent patterns in price time series. According standard economical theories these strategies should not be used because they cannot be profitable. On the contrary, it is well-known that technical traders exist and operate on different time scales. In this paper we investigate if technical trading produces detectable signals in price time series and if some kind of memory effects are introduced in the price dynamics. In particular, we focus on a specific figure called supports and resistances. We first develop a criterion to detect the potential values of supports and resistances. Then we show that memory effects in the price dynamics are associated to these selected values. In fact we show that prices more likely re-bounce than cross these values. Such an effect is a quantitative evidence of the so-called self-fulfilling prophecy, that is the self-reinforcement of agents' belief and sentiment about future stock prices' behavior. PMID:24671011

Memory effects in stock price dynamics: evidences of technical trading

NASA Astrophysics Data System (ADS)

Garzarelli, Federico; Cristelli, Matthieu; Pompa, Gabriele; Zaccaria, Andrea; Pietronero, Luciano

2014-03-01

Technical trading represents a class of investment strategies for Financial Markets based on the analysis of trends and recurrent patterns in price time series. According standard economical theories these strategies should not be used because they cannot be profitable. On the contrary, it is well-known that technical traders exist and operate on different time scales. In this paper we investigate if technical trading produces detectable signals in price time series and if some kind of memory effects are introduced in the price dynamics. In particular, we focus on a specific figure called supports and resistances. We first develop a criterion to detect the potential values of supports and resistances. Then we show that memory effects in the price dynamics are associated to these selected values. In fact we show that prices more likely re-bounce than cross these values. Such an effect is a quantitative evidence of the so-called self-fulfilling prophecy, that is the self-reinforcement of agents' belief and sentiment about future stock prices' behavior.

Bessel function expansion to reduce the calculation time and memory usage for cylindrical computer-generated holograms.

PubMed

Sando, Yusuke; Barada, Daisuke; Jackin, Boaz Jessie; Yatagai, Toyohiko

2017-07-10

This study proposes a method to reduce the calculation time and memory usage required for calculating cylindrical computer-generated holograms. The wavefront on the cylindrical observation surface is represented as a convolution integral in the 3D Fourier domain. The Fourier transformation of the kernel function involving this convolution integral is analytically performed using a Bessel function expansion. The analytical solution can drastically reduce the calculation time and the memory usage without any cost, compared with the numerical method using fast Fourier transform to Fourier transform the kernel function. In this study, we present the analytical derivation, the efficient calculation of Bessel function series, and a numerical simulation. Furthermore, we demonstrate the effectiveness of the analytical solution through comparisons of calculation time and memory usage.

Bayesian Analysis of Non-Gaussian Long-Range Dependent Processes

NASA Astrophysics Data System (ADS)

Graves, Timothy; Watkins, Nicholas; Franzke, Christian; Gramacy, Robert

2013-04-01

Recent studies [e.g. the Antarctic study of Franzke, J. Climate, 2010] have strongly suggested that surface temperatures exhibit long-range dependence (LRD). The presence of LRD would hamper the identification of deterministic trends and the quantification of their significance. It is well established that LRD processes exhibit stochastic trends over rather long periods of time. Thus, accurate methods for discriminating between physical processes that possess long memory and those that do not are an important adjunct to climate modeling. As we briefly review, the LRD idea originated at the same time as H-selfsimilarity, so it is often not realised that a model does not have to be H-self similar to show LRD [e.g. Watkins, GRL Frontiers, 2013]. We have used Markov Chain Monte Carlo algorithms to perform a Bayesian analysis of Auto-Regressive Fractionally-Integrated Moving-Average ARFIMA(p,d,q) processes, which are capable of modeling LRD. Our principal aim is to obtain inference about the long memory parameter, d, with secondary interest in the scale and location parameters. We have developed a reversible-jump method enabling us to integrate over different model forms for the short memory component. We initially assume Gaussianity, and have tested the method on both synthetic and physical time series. Many physical processes, for example the Faraday Antarctic time series, are significantly non-Gaussian. We have therefore extended this work by weakening the Gaussianity assumption, assuming an alpha-stable distribution for the innovations, and performing joint inference on d and alpha. Such a modified FARIMA(p,d,q) process is a flexible, initial model for non-Gaussian processes with long memory. We will present a study of the dependence of the posterior variance of the memory parameter d on the length of the time series considered. This will be compared with equivalent error diagnostics for other measures of d.

Differential Entropy Preserves Variational Information of Near-Infrared Spectroscopy Time Series Associated With Working Memory.

PubMed

Keshmiri, Soheil; Sumioka, Hidenubo; Yamazaki, Ryuji; Ishiguro, Hiroshi

2018-01-01

Neuroscience research shows a growing interest in the application of Near-Infrared Spectroscopy (NIRS) in analysis and decoding of the brain activity of human subjects. Given the correlation that is observed between the Blood Oxygen Dependent Level (BOLD) responses that are exhibited by the time series data of functional Magnetic Resonance Imaging (fMRI) and the hemoglobin oxy/deoxy-genation that is captured by NIRS, linear models play a central role in these applications. This, in turn, results in adaptation of the feature extraction strategies that are well-suited for discretization of data that exhibit a high degree of linearity, namely, slope and the mean as well as their combination, to summarize the informational contents of the NIRS time series. In this article, we demonstrate that these features are inefficient in capturing the variational information of NIRS data, limiting the reliability and the adequacy of the conclusion on their results. Alternatively, we propose the linear estimate of differential entropy of these time series as a natural representation of such information. We provide evidence for our claim through comparative analysis of the application of these features on NIRS data pertinent to several working memory tasks as well as naturalistic conversational stimuli.

Common data buffer

NASA Technical Reports Server (NTRS)

Byrne, F.

1981-01-01

Time-shared interface speeds data processing in distributed computer network. Two-level high-speed scanning approach routes information to buffer, portion of which is reserved for series of "first-in, first-out" memory stacks. Buffer address structure and memory are protected from noise or failed components by error correcting code. System is applicable to any computer or processing language.

The Effect of the Underlying Distribution in Hurst Exponent Estimation

PubMed Central

Sánchez, Miguel Ángel; Trinidad, Juan E.; García, José; Fernández, Manuel

2015-01-01

In this paper, a heavy-tailed distribution approach is considered in order to explore the behavior of actual financial time series. We show that this kind of distribution allows to properly fit the empirical distribution of the stocks from S&P500 index. In addition to that, we explain in detail why the underlying distribution of the random process under study should be taken into account before using its self-similarity exponent as a reliable tool to state whether that financial series displays long-range dependence or not. Finally, we show that, under this model, no stocks from S&P500 index show persistent memory, whereas some of them do present anti-persistent memory and most of them present no memory at all. PMID:26020942

Memory persistency and nonlinearity in daily mean dew point across India

NASA Astrophysics Data System (ADS)

Ray, Rajdeep; Khondekar, Mofazzal Hossain; Ghosh, Koushik; Bhattacharjee, Anup Kumar

2016-04-01

Enterprising endeavour has been taken in this work to realize and estimate the persistence in memory of the daily mean dew point time series obtained from seven different weather stations viz. Kolkata, Chennai (Madras), New Delhi, Mumbai (Bombay), Bhopal, Agartala and Ahmedabad representing different geographical zones in India. Hurst exponent values reveal an anti-persistent behaviour of these dew point series. To affirm the Hurst exponent values, five different scaling methods have been used and the corresponding results are compared to synthesize a finer and reliable conclusion out of it. The present analysis also bespeaks that the variation in daily mean dew point is governed by a non-stationary process with stationary increments. The delay vector variance (DVV) method has been exploited to investigate nonlinearity, and the present calculation confirms the presence of deterministic nonlinear profile in the daily mean dew point time series of the seven stations.

Data series embedding and scale invariant statistics.

PubMed

Michieli, I; Medved, B; Ristov, S

2010-06-01

Data sequences acquired from bio-systems such as human gait data, heart rate interbeat data, or DNA sequences exhibit complex dynamics that is frequently described by a long-memory or power-law decay of autocorrelation function. One way of characterizing that dynamics is through scale invariant statistics or "fractal-like" behavior. For quantifying scale invariant parameters of physiological signals several methods have been proposed. Among them the most common are detrended fluctuation analysis, sample mean variance analyses, power spectral density analysis, R/S analysis, and recently in the realm of the multifractal approach, wavelet analysis. In this paper it is demonstrated that embedding the time series data in the high-dimensional pseudo-phase space reveals scale invariant statistics in the simple fashion. The procedure is applied on different stride interval data sets from human gait measurements time series (Physio-Bank data library). Results show that introduced mapping adequately separates long-memory from random behavior. Smaller gait data sets were analyzed and scale-free trends for limited scale intervals were successfully detected. The method was verified on artificially produced time series with known scaling behavior and with the varying content of noise. The possibility for the method to falsely detect long-range dependence in the artificially generated short range dependence series was investigated. (c) 2009 Elsevier B.V. All rights reserved.

Binary collision approximations for the memory function for density fluctuations in equilibrium atomic liquids

NASA Astrophysics Data System (ADS)

Noah, Joyce E.

Time correlation functions of density fluctuations of liquids at equilibrium can be used to relate the microscopic dynamics of a liquid to its macroscopic transport properties. Time correlation functions are especially useful since they can be generated in a variety of ways, from scattering experiments to computer simulation to analytic theory. The kinetic theory of fluctuations in equilibrium liquids is an analytic theory for calculating correlation functions using memory functions. In this work, we use a diagrammatic formulation of the kinetic theory to develop a series of binary collision approximations for the collisional part of the memory function. We define binary collisions as collisions between two distinct density fluctuations whose identities are fixed during the duration of a collsion. R approximations are for the short time part of the memory function, and build upon the work of Ranganathan and Andersen. These approximations have purely repulsive interactions between the fluctuations. The second type of approximation, RA approximations, is for the longer time part of the memory function, where the density fluctuations now interact via repulsive and attractive forces. Although RA approximations are a natural extension of R approximations, they permit two density fluctuations to become trapped in the wells of the interaction potential, leading to long-lived oscillatory behavior, which is unphysical. Therefore we consider S approximations which describe binary particles which experience the random effect of the surroundings while interacting via repulsive or repulsive and attractive interactions. For each of these approximations for the memory function we numerically solve the kinetic equation to generate correlation functions. These results are compared to molecular dynamics results for the correlation functions. Comparing the successes and failures of the different approximations, we conclude that R approximations give more accurate intermediate and long time results while RA and S approximations do particularly well at predicting the short time behavior. Lastly, we also develop a series of non-graphically derived approximations and use an optimization procedure to determine the underlying memory function from the simulation data. These approaches provide valuable information about the memory function that will be used in the development of future kinetic theories.

Electrical Evaluation of RCA MWS5001D Random Access Memory, Volume 5, Appendix D

NASA Technical Reports Server (NTRS)

Klute, A.

1979-01-01

The electrical characterization and qualification test results are presented for the RCA MWS 5001D random access memory. The tests included functional tests, AC and DC parametric tests, AC parametric worst-case pattern selection test, determination of worst-case transition for setup and hold times, and a series of schmoo plots. Average input high current, worst case input high current, output low current, and data setup time are some of the results presented.

Application of computational mechanics to the analysis of natural data: an example in geomagnetism.

PubMed

Clarke, Richard W; Freeman, Mervyn P; Watkins, Nicholas W

2003-01-01

We discuss how the ideal formalism of computational mechanics can be adapted to apply to a noninfinite series of corrupted and correlated data, that is typical of most observed natural time series. Specifically, a simple filter that removes the corruption that creates rare unphysical causal states is demonstrated, and the concept of effective soficity is introduced. We believe that computational mechanics cannot be applied to a noisy and finite data series without invoking an argument based upon effective soficity. A related distinction between noise and unresolved structure is also defined: Noise can only be eliminated by increasing the length of the time series, whereas the resolution of previously unresolved structure only requires the finite memory of the analysis to be increased. The benefits of these concepts are demonstrated in a simulated times series by (a) the effective elimination of white noise corruption from a periodic signal using the expletive filter and (b) the appearance of an effectively sofic region in the statistical complexity of a biased Poisson switch time series that is insensitive to changes in the word length (memory) used in the analysis. The new algorithm is then applied to an analysis of a real geomagnetic time series measured at Halley, Antarctica. Two principal components in the structure are detected that are interpreted as the diurnal variation due to the rotation of the Earth-based station under an electrical current pattern that is fixed with respect to the Sun-Earth axis and the random occurrence of a signature likely to be that of the magnetic substorm. In conclusion, some useful terminology for the discussion of model construction in general is introduced.

Differential Entropy Preserves Variational Information of Near-Infrared Spectroscopy Time Series Associated With Working Memory

PubMed Central

Keshmiri, Soheil; Sumioka, Hidenubo; Yamazaki, Ryuji; Ishiguro, Hiroshi

2018-01-01

Neuroscience research shows a growing interest in the application of Near-Infrared Spectroscopy (NIRS) in analysis and decoding of the brain activity of human subjects. Given the correlation that is observed between the Blood Oxygen Dependent Level (BOLD) responses that are exhibited by the time series data of functional Magnetic Resonance Imaging (fMRI) and the hemoglobin oxy/deoxy-genation that is captured by NIRS, linear models play a central role in these applications. This, in turn, results in adaptation of the feature extraction strategies that are well-suited for discretization of data that exhibit a high degree of linearity, namely, slope and the mean as well as their combination, to summarize the informational contents of the NIRS time series. In this article, we demonstrate that these features are inefficient in capturing the variational information of NIRS data, limiting the reliability and the adequacy of the conclusion on their results. Alternatively, we propose the linear estimate of differential entropy of these time series as a natural representation of such information. We provide evidence for our claim through comparative analysis of the application of these features on NIRS data pertinent to several working memory tasks as well as naturalistic conversational stimuli. PMID:29922144

Surface Soil Moisture Memory Estimated from Models and SMAP Observations

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

The long-range correlation and evolution law of centennial-scale temperatures in Northeast China.

PubMed

Zheng, Xiaohui; Lian, Yi; Wang, Qiguang

2018-01-01

This paper applies the detrended fluctuation analysis (DFA) method to investigate the long-range correlation of monthly mean temperatures from three typical measurement stations at Harbin, Changchun, and Shenyang in Northeast China from 1909 to 2014. The results reveal the memory characteristics of the climate system in this region. By comparing the temperatures from different time periods and investigating the variations of its scaling exponents at the three stations during these different time periods, we found that the monthly mean temperature has long-range correlation, which indicates that the temperature in Northeast China has long-term memory and good predictability. The monthly time series of temperatures over the past 106 years also shows good long-range correlation characteristics. These characteristics are also obviously observed in the annual mean temperature time series. Finally, we separated the centennial-length temperature time series into two time periods. These results reveal that the long-range correlations at the Harbin station over these two time periods have large variations, whereas no obvious variations are observed at the other two stations. This indicates that warming affects the regional climate system's predictability differently at different time periods. The research results can provide a quantitative reference point for regional climate predictability assessment and future climate model evaluation.

The Hippocampus Remains Activated over the Long Term for the Retrieval of Truly Episodic Memories

PubMed Central

Harand, Caroline; Bertran, Françoise; La Joie, Renaud; Landeau, Brigitte; Mézenge, Florence; Desgranges, Béatrice; Peigneux, Philippe; Eustache, Francis; Rauchs, Géraldine

2012-01-01

The role of the hippocampus in declarative memory consolidation is a matter of intense debate. We investigated the neural substrates of memory retrieval for recent and remote information using functional magnetic resonance imaging (fMRI). 18 young, healthy participants learned a series of pictures. Then, during two fMRI recognition sessions, 3 days and 3 months later, they had to determine whether they recognized or not each picture using the “Remember/Know” procedure. Presentation of the same learned images at both delays allowed us to track the evolution of memories and distinguish consistently episodic memories from those that were initially episodic and then became familiar or semantic over time and were retrieved without any contextual detail. Hippocampal activation decreased over time for initially episodic, later semantic memories, but remained stable for consistently episodic ones, at least in its posterior part. For both types of memories, neocortical activations were observed at both delays, notably in the ventromedial prefrontal and anterior cingulate cortices. These activations may reflect a gradual reorganization of memory traces within neural networks. Our data indicate maintenance and strengthening of hippocampal and cortico-cortical connections in the consolidation and retrieval of episodic memories over time, in line with the Multiple Trace theory (Nadel and Moscovitch, 1997). At variance, memories becoming semantic over time consolidate through strengthening of cortico-cortical connections and progressive disengagement of the hippocampus. PMID:22937055

Development and Evaluation of a Casualty Evacuation Model for a European Conflict.

DTIC Science & Technology

1985-12-01

EVAC, the computer code which implements our technique, has been used to solve a series of test problems in less time and requiring less memory than...the order of 1/K the amount of main memory for a K-commodity problem, so it can solve significantly larger problems than MCNF. I . 10 CHAPTER II A...technique may require only half the memory of the general L.P. package [6]. These advances are due to the efficient data structures which have been

Sequential Monte Carlo for inference of latent ARMA time-series with innovations correlated in time

NASA Astrophysics Data System (ADS)

Urteaga, Iñigo; Bugallo, Mónica F.; Djurić, Petar M.

2017-12-01

We consider the problem of sequential inference of latent time-series with innovations correlated in time and observed via nonlinear functions. We accommodate time-varying phenomena with diverse properties by means of a flexible mathematical representation of the data. We characterize statistically such time-series by a Bayesian analysis of their densities. The density that describes the transition of the state from time t to the next time instant t+1 is used for implementation of novel sequential Monte Carlo (SMC) methods. We present a set of SMC methods for inference of latent ARMA time-series with innovations correlated in time for different assumptions in knowledge of parameters. The methods operate in a unified and consistent manner for data with diverse memory properties. We show the validity of the proposed approach by comprehensive simulations of the challenging stochastic volatility model.

Memory interface simulator: A computer design aid

NASA Technical Reports Server (NTRS)

Taylor, D. S.; Williams, T.; Weatherbee, J. E.

1972-01-01

Results are presented of a study conducted with a digital simulation model being used in the design of the Automatically Reconfigurable Modular Multiprocessor System (ARMMS), a candidate computer system for future manned and unmanned space missions. The model simulates the activity involved as instructions are fetched from random access memory for execution in one of the system central processing units. A series of model runs measured instruction execution time under various assumptions pertaining to the CPU's and the interface between the CPU's and RAM. Design tradeoffs are presented in the following areas: Bus widths, CPU microprogram read only memory cycle time, multiple instruction fetch, and instruction mix.

In Search of Decay in Verbal Short-Term Memory

PubMed Central

Berman, Marc G.; Jonides, John; Lewis, Richard L.

2014-01-01

Is forgetting in the short term due to decay with the mere passage of time, interference from other memoranda, or both? Past research on short-term memory has revealed some evidence for decay and a plethora of evidence showing that short-term memory is worsened by interference. However, none of these studies has directly contrasted decay and interference in short-term memory in a task that rules out the use of rehearsal processes. In this article the authors present a series of studies using a novel paradigm to address this problem directly, by interrogating the operation of decay and interference in short-term memory without rehearsal confounds. The results of these studies indicate that short-term memories are subject to very small decay effects with the mere passage of time but that interference plays a much larger role in their degradation. The authors discuss the implications of these results for existing models of memory decay and interference. PMID:19271849

In search of decay in verbal short-term memory.

PubMed

Berman, Marc G; Jonides, John; Lewis, Richard L

2009-03-01

Is forgetting in the short term due to decay with the mere passage of time, interference from other memoranda, or both? Past research on short-term memory has revealed some evidence for decay and a plethora of evidence showing that short-term memory is worsened by interference. However, none of these studies has directly contrasted decay and interference in short-term memory in a task that rules out the use of rehearsal processes. In this article the authors present a series of studies using a novel paradigm to address this problem directly, by interrogating the operation of decay and interference in short-term memory without rehearsal confounds. The results of these studies indicate that short-term memories are subject to very small decay effects with the mere passage of time but that interference plays a much larger role in their degradation. The authors discuss the implications of these results for existing models of memory decay and interference. (c) 2009 APA, all rights reserved

Prediction of Sea Surface Temperature Using Long Short-Term Memory

NASA Astrophysics Data System (ADS)

Zhang, Qin; Wang, Hui; Dong, Junyu; Zhong, Guoqiang; Sun, Xin

2017-10-01

This letter adopts long short-term memory(LSTM) to predict sea surface temperature(SST), which is the first attempt, to our knowledge, to use recurrent neural network to solve the problem of SST prediction, and to make one week and one month daily prediction. We formulate the SST prediction problem as a time series regression problem. LSTM is a special kind of recurrent neural network, which introduces gate mechanism into vanilla RNN to prevent the vanished or exploding gradient problem. It has strong ability to model the temporal relationship of time series data and can handle the long-term dependency problem well. The proposed network architecture is composed of two kinds of layers: LSTM layer and full-connected dense layer. LSTM layer is utilized to model the time series relationship. Full-connected layer is utilized to map the output of LSTM layer to a final prediction. We explore the optimal setting of this architecture by experiments and report the accuracy of coastal seas of China to confirm the effectiveness of the proposed method. In addition, we also show its online updated characteristics.

Visuospatial and verbal memory in mental arithmetic.

PubMed

Clearman, Jack; Klinger, Vojtěch; Szűcs, Dénes

2017-09-01

Working memory allows complex information to be remembered and manipulated over short periods of time. Correlations between working memory and mathematics achievement have been shown across the lifespan. However, only a few studies have examined the potentially distinct contributions of domain-specific visuospatial and verbal working memory resources in mental arithmetic computation. Here we aimed to fill this gap in a series of six experiments pairing addition and subtraction tasks with verbal and visuospatial working memory and interference tasks. In general, we found higher levels of interference between mental arithmetic and visuospatial working memory tasks than between mental arithmetic and verbal working memory tasks. Additionally, we found that interference that matched the working memory domain of the task (e.g., verbal task with verbal interference) lowered working memory performance more than mismatched interference (verbal task with visuospatial interference). Findings suggest that mental arithmetic relies on domain-specific working memory resources.

Studies and applications of NiTi shape memory alloys in the medical field in China.

PubMed

Dai, K; Chu, Y

1996-01-01

The biomedical study of NiTi shape memory alloys has been undertaken in China since 1978. A series of stimulating corrosion tests, histological observations, toxicity tests, carcinogenicity tests, trace nickel elements analysis and a number of clinical trials have been conducted. The results showed that the NiTi shape memory alloy is a good biomaterial with good biocompatibility and no obvious local tissue reaction, carcinogenesis or erosion of implants were found experimentally or clinically. In 1981, on the basis of fundamental studies, a shape memory staple was used for the first time inside the human body. Subsequently, various shape memory devices were designed and applied clinically for internal fixation of fractures, spine surgery, endoprostheses, gynaecological and craniofacial surgery. Since 1990, a series of internal stents have been developed for the management of biliary, tracheal and esophageal strictures and urethrostenosis as well as vascular obturator for tumour management. Several thousand cases have been treated and had a 1-10 year follow-up and good clinical results with a rather low complication rate were obtained.

Analysis of the influence of memory content of auditory stimuli on the memory content of EEG signal

PubMed Central

Namazi, Hamidreza; Kulish, Vladimir V.

2016-01-01

One of the major challenges in brain research is to relate the structural features of the auditory stimulus to structural features of Electroencephalogram (EEG) signal. Memory content is an important feature of EEG signal and accordingly the brain. On the other hand, the memory content can also be considered in case of stimulus. Beside all works done on analysis of the effect of stimuli on human EEG and brain memory, no work discussed about the stimulus memory and also the relationship that may exist between the memory content of stimulus and the memory content of EEG signal. For this purpose we consider the Hurst exponent as the measure of memory. This study reveals the plasticity of human EEG signals in relation to the auditory stimuli. For the first time we demonstrated that the memory content of an EEG signal shifts towards the memory content of the auditory stimulus used. The results of this analysis showed that an auditory stimulus with higher memory content causes a larger increment in the memory content of an EEG signal. For the verification of this result, we benefit from approximate entropy as indicator of time series randomness. The capability, observed in this research, can be further investigated in relation to human memory. PMID:27528219

Analysis of the influence of memory content of auditory stimuli on the memory content of EEG signal.

PubMed

Namazi, Hamidreza; Khosrowabadi, Reza; Hussaini, Jamal; Habibi, Shaghayegh; Farid, Ali Akhavan; Kulish, Vladimir V

2016-08-30

One of the major challenges in brain research is to relate the structural features of the auditory stimulus to structural features of Electroencephalogram (EEG) signal. Memory content is an important feature of EEG signal and accordingly the brain. On the other hand, the memory content can also be considered in case of stimulus. Beside all works done on analysis of the effect of stimuli on human EEG and brain memory, no work discussed about the stimulus memory and also the relationship that may exist between the memory content of stimulus and the memory content of EEG signal. For this purpose we consider the Hurst exponent as the measure of memory. This study reveals the plasticity of human EEG signals in relation to the auditory stimuli. For the first time we demonstrated that the memory content of an EEG signal shifts towards the memory content of the auditory stimulus used. The results of this analysis showed that an auditory stimulus with higher memory content causes a larger increment in the memory content of an EEG signal. For the verification of this result, we benefit from approximate entropy as indicator of time series randomness. The capability, observed in this research, can be further investigated in relation to human memory.

A deep learning framework for financial time series using stacked autoencoders and long-short term memory.

PubMed

Bao, Wei; Yue, Jun; Rao, Yulei

2017-01-01

The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day's closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance.

Bounds of memory strength for power-law series.

PubMed

Guo, Fangjian; Yang, Dan; Yang, Zimo; Zhao, Zhi-Dan; Zhou, Tao

2017-05-01

Many time series produced by complex systems are empirically found to follow power-law distributions with different exponents α. By permuting the independently drawn samples from a power-law distribution, we present nontrivial bounds on the memory strength (first-order autocorrelation) as a function of α, which are markedly different from the ordinary ±1 bounds for Gaussian or uniform distributions. When 1<α≤3, as α grows bigger, the upper bound increases from 0 to +1 while the lower bound remains 0; when α>3, the upper bound remains +1 while the lower bound descends below 0. Theoretical bounds agree well with numerical simulations. Based on the posts on Twitter, ratings of MovieLens, calling records of the mobile operator Orange, and the browsing behavior of Taobao, we find that empirical power-law-distributed data produced by human activities obey such constraints. The present findings explain some observed constraints in bursty time series and scale-free networks and challenge the validity of measures such as autocorrelation and assortativity coefficient in heterogeneous systems.

Bounds of memory strength for power-law series

NASA Astrophysics Data System (ADS)

Guo, Fangjian; Yang, Dan; Yang, Zimo; Zhao, Zhi-Dan; Zhou, Tao

2017-05-01

Many time series produced by complex systems are empirically found to follow power-law distributions with different exponents α . By permuting the independently drawn samples from a power-law distribution, we present nontrivial bounds on the memory strength (first-order autocorrelation) as a function of α , which are markedly different from the ordinary ±1 bounds for Gaussian or uniform distributions. When 1 <α ≤3 , as α grows bigger, the upper bound increases from 0 to +1 while the lower bound remains 0; when α >3 , the upper bound remains +1 while the lower bound descends below 0. Theoretical bounds agree well with numerical simulations. Based on the posts on Twitter, ratings of MovieLens, calling records of the mobile operator Orange, and the browsing behavior of Taobao, we find that empirical power-law-distributed data produced by human activities obey such constraints. The present findings explain some observed constraints in bursty time series and scale-free networks and challenge the validity of measures such as autocorrelation and assortativity coefficient in heterogeneous systems.

Tone series and the nature of working memory capacity development.

PubMed

Clark, Katherine M; Hardman, Kyle O; Schachtman, Todd R; Saults, J Scott; Glass, Bret A; Cowan, Nelson

2018-04-01

Recent advances in understanding visual working memory, the limited information held in mind for use in ongoing processing, are extended here to examine auditory working memory development. Research with arrays of visual objects has shown how to distinguish the capacity, in terms of the number of objects retained, from the precision of the object representations. We adapt the technique to sequences of nonmusical tones, in an investigation including children (6-13 years, N = 84) and adults (26-50 years, N = 31). For each series of 1 to 4 tones, the participant responded by using an 80-choice scale to try to reproduce the tone at a queried serial position. Despite the much longer-lasting usefulness of sensory memory for tones compared with visual objects, the observed tone capacity was similar to previous findings for visual capacity. The results also constrain theories of childhood working memory development, indicating increases with age in both the capacity and the precision of the tone representations, similar to the visual studies, rather than age differences in time-based memory decay. The findings, including patterns of correlations between capacity, precision, and some auxiliary tasks and questionnaires, establish capacity and precision as dissociable processes and place important constraints on various hypotheses of working memory development. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Scaling of seismic memory with earthquake size

NASA Astrophysics Data System (ADS)

Zheng, Zeyu; Yamasaki, Kazuko; Tenenbaum, Joel; Podobnik, Boris; Tamura, Yoshiyasu; Stanley, H. Eugene

2012-07-01

It has been observed that discrete earthquake events possess memory, i.e., that events occurring in a particular location are dependent on the history of that location. We conduct an analysis to see whether continuous real-time data also display a similar memory and, if so, whether such autocorrelations depend on the size of earthquakes within close spatiotemporal proximity. We analyze the seismic wave form database recorded by 64 stations in Japan, including the 2011 “Great East Japan Earthquake,” one of the five most powerful earthquakes ever recorded, which resulted in a tsunami and devastating nuclear accidents. We explore the question of seismic memory through use of mean conditional intervals and detrended fluctuation analysis (DFA). We find that the wave form sign series show power-law anticorrelations while the interval series show power-law correlations. We find size dependence in earthquake autocorrelations: as the earthquake size increases, both of these correlation behaviors strengthen. We also find that the DFA scaling exponent α has no dependence on the earthquake hypocenter depth or epicentral distance.

Working memory costs of task switching.

PubMed

Liefooghe, Baptist; Barrouillet, Pierre; Vandierendonck, André; Camos, Valérie

2008-05-01

Although many accounts of task switching emphasize the importance of working memory as a substantial source of the switch cost, there is a lack of evidence demonstrating that task switching actually places additional demands on working memory. The present study addressed this issue by implementing task switching in continuous complex span tasks with strictly controlled time parameters. A series of 4 experiments demonstrate that recall performance decreased as a function of the number of task switches and that the concurrent load of item maintenance had no influence on task switching. These results indicate that task switching induces a cost on working memory functioning. Implications for theories of task switching, working memory, and resource sharing are addressed.

Diminishing returns: the influence of experience and environment on time-memory extinction in honey bee foragers.

PubMed

Moore, Darrell; Van Nest, Byron N; Seier, Edith

2011-06-01

Classical experiments demonstrated that honey bee foragers trained to collect food at virtually any time of day will return to that food source on subsequent days with a remarkable degree of temporal accuracy. This versatile time-memory, based on an endogenous circadian clock, presumably enables foragers to schedule their reconnaissance flights to best take advantage of the daily rhythms of nectar and pollen availability in different species of flowers. It is commonly believed that the time-memory rapidly extinguishes if not reinforced daily, thus enabling foragers to switch quickly from relatively poor sources to more productive ones. On the other hand, it is also commonly thought that extinction of the time-memory is slow enough to permit foragers to 'remember' the food source over a day or two of bad weather. What exactly is the time-course of time-memory extinction? In a series of field experiments, we determined that the level of food-anticipatory activity (FAA) directed at a food source is not rapidly extinguished and, furthermore, the time-course of extinction is dependent upon the amount of experience accumulated by the forager at that source. We also found that FAA is prolonged in response to inclement weather, indicating that time-memory extinction is not a simple decay function but is responsive to environmental changes. These results provide insights into the adaptability of FAA under natural conditions.

Temporal variability and memory in sediment transport in an experimental step-pool channel

NASA Astrophysics Data System (ADS)

Saletti, Matteo; Molnar, Peter; Zimmermann, André; Hassan, Marwan A.; Church, Michael

2015-11-01

Temporal dynamics of sediment transport in steep channels using two experiments performed in a steep flume (8%) with natural sediment composed of 12 grain sizes are studied. High-resolution (1 s) time series of sediment transport were measured for individual grain-size classes at the outlet of the flume for different combinations of sediment input rates and flow discharges. Our aim in this paper is to quantify (a) the relation of discharge and sediment transport and (b) the nature and strength of memory in grain-size-dependent transport. None of the simple statistical descriptors of sediment transport (mean, extreme values, and quantiles) display a clear relation with water discharge, in fact a large variability between discharge and sediment transport is observed. Instantaneous transport rates have probability density functions with heavy tails. Bed load bursts have a coarser grain-size distribution than that of the entire experiment. We quantify the strength and nature of memory in sediment transport rates by estimating the Hurst exponent and the autocorrelation coefficient of the time series for different grain sizes. Our results show the presence of the Hurst phenomenon in transport rates, indicating long-term memory which is grain-size dependent. The short-term memory in coarse grain transport increases with temporal aggregation and this reveals the importance of the sampling duration of bed load transport rates in natural streams, especially for large fractions.

Non-Markovian properties and multiscale hidden Markovian network buried in single molecule time series

NASA Astrophysics Data System (ADS)

Sultana, Tahmina; Takagi, Hiroaki; Morimatsu, Miki; Teramoto, Hiroshi; Li, Chun-Biu; Sako, Yasushi; Komatsuzaki, Tamiki

2013-12-01

We present a novel scheme to extract a multiscale state space network (SSN) from single-molecule time series. The multiscale SSN is a type of hidden Markov model that takes into account both multiple states buried in the measurement and memory effects in the process of the observable whenever they exist. Most biological systems function in a nonstationary manner across multiple timescales. Combined with a recently established nonlinear time series analysis based on information theory, a simple scheme is proposed to deal with the properties of multiscale and nonstationarity for a discrete time series. We derived an explicit analytical expression of the autocorrelation function in terms of the SSN. To demonstrate the potential of our scheme, we investigated single-molecule time series of dissociation and association kinetics between epidermal growth factor receptor (EGFR) on the plasma membrane and its adaptor protein Ash/Grb2 (Grb2) in an in vitro reconstituted system. We found that our formula successfully reproduces their autocorrelation function for a wide range of timescales (up to 3 s), and the underlying SSNs change their topographical structure as a function of the timescale; while the corresponding SSN is simple at the short timescale (0.033-0.1 s), the SSN at the longer timescales (0.1 s to ˜3 s) becomes rather complex in order to capture multiscale nonstationary kinetics emerging at longer timescales. It is also found that visiting the unbound form of the EGFR-Grb2 system approximately resets all information of history or memory of the process.

A Differential Deficit in Time- versus Event-based Prospective Memory in Parkinson's Disease

PubMed Central

Raskin, Sarah A.; Woods, Steven Paul; Poquette, Amelia J.; McTaggart, April B.; Sethna, Jim; Williams, Rebecca C.; Tröster, Alexander I.

2010-01-01

Objective The aim of the current study was to clarify the nature and extent of impairment in time- versus event-based prospective memory in Parkinson's disease (PD). Prospective memory is thought to involve cognitive processes that are mediated by prefrontal systems and are executive in nature. Given that individuals with PD frequently show executive dysfunction, it is important to determine whether these individuals may have deficits in prospective memory that could impact daily functions, such as taking medications. Although it has been reported that individuals with PD evidence impairment in prospective memory, it is still unclear whether they show a greater deficit for time- versus event-based cues. Method Fifty-four individuals with PD and 34 demographically similar healthy adults were administered a standardized measure of prospective memory that allows for a direct comparison of time-based and event-based cues. In addition, participants were administered a series of standardized measures of retrospective memory and executive functions. Results Individuals with PD demonstrated impaired prospective memory performance compared to the healthy adults, with a greater impairment demonstrated for the time-based tasks. Time-based prospective memory performance was moderately correlated with measures of executive functioning, but only the Stroop Neuropsychological Screening Test emerged as a unique predictor in a linear regression. Conclusions Findings are interpreted within the context of McDaniel and Einstein's (2000) multi-process theory to suggest that individuals with PD experience particular difficulty executing a future intention when the cue to execute the prescribed intention requires higher levels of executive control. PMID:21090895

The Superstatistical Nature and Interoccurrence Time of Atmospheric Mercury Concentration Fluctuations

EPA Science Inventory

The probability density function (PDF) of the time intervals between subsequent extreme events in atmospheric Hg0 concentration data series from different latitudes has been investigated. The Hg0 dynamic possesses a long-term memory autocorrelation function. Above a fixed thresh...

Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets

NASA Astrophysics Data System (ADS)

Gontis, V.; Kononovicius, A.

2017-10-01

We address the problem of long-range memory in the financial markets. There are two conceptually different ways to reproduce power-law decay of auto-correlation function: using fractional Brownian motion as well as non-linear stochastic differential equations. In this contribution we address this problem by analyzing empirical return and trading activity time series from the Forex. From the empirical time series we obtain probability density functions of burst and inter-burst duration. Our analysis reveals that the power-law exponents of the obtained probability density functions are close to 3 / 2, which is a characteristic feature of the one-dimensional stochastic processes. This is in a good agreement with earlier proposed model of absolute return based on the non-linear stochastic differential equations derived from the agent-based herding model.

Everyday Learning in the Kitchen. Everyday Learning Series. Volume 2, Number 4

ERIC Educational Resources Information Center

Darbyshire, Jo

2004-01-01

The "Everyday Learning" series has been developed to focus attention on the everyday ways in which children can be supported in their growth and development. Many of one's earliest memories are likely to be about time spent in the kitchen. Licking the bowl, setting the table, doing the dishes, chatting about the day, eating a meal,…

St. Augustine's Reflections on Memory and Time and the Current Concept of Subjective Time in Mental Time Travel.

PubMed

Manning, Liliann; Cassel, Daniel; Cassel, Jean-Christophe

2013-06-01

Reconstructing the past and anticipating the future, i.e., the ability of travelling in mental time, is thought to be at the heart of consciousness and, by the same token, at the center of human cognition. This extraordinary mental activity is possible thanks to the ability of being aware of 'subjective time'. In the present study, we attempt to trace back the first recorded reflections on the relations between time and memory, to the end of the fourth century's work, the Confessions, by the theologian and philosopher, St. Augustine. We concentrate on Book 11, where he extensively developed a series of articulated and detailed observations on memory and time. On the bases of selected paragraphs, we endeavor to highlight some concepts that may be considered as the product of the first or, at least, very early reflections related to our current notions of subjective time in mental time travel. We also draw a fundamental difference inherent to the frameworks within which the questions were raised. The contribution of St. Augustine on time and memory remains significant, notwithstanding the 16 centuries elapsed since it was made, likely because of the universality of its contents.

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

PubMed Central

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

Large deviation probabilities for correlated Gaussian stochastic processes and daily temperature anomalies

NASA Astrophysics Data System (ADS)

Massah, Mozhdeh; Kantz, Holger

2016-04-01

As we have one and only one earth and no replicas, climate characteristics are usually computed as time averages from a single time series. For understanding climate variability, it is essential to understand how close a single time average will typically be to an ensemble average. To answer this question, we study large deviation probabilities (LDP) of stochastic processes and characterize them by their dependence on the time window. In contrast to iid variables for which there exists an analytical expression for the rate function, the correlated variables such as auto-regressive (short memory) and auto-regressive fractionally integrated moving average (long memory) processes, have not an analytical LDP. We study LDP for these processes, in order to see how correlation affects this probability in comparison to iid data. Although short range correlations lead to a simple correction of sample size, long range correlations lead to a sub-exponential decay of LDP and hence to a very slow convergence of time averages. This effect is demonstrated for a 120 year long time series of daily temperature anomalies measured in Potsdam (Germany).

Recurrent Neural Network Applications for Astronomical Time Series

NASA Astrophysics Data System (ADS)

Protopapas, Pavlos

2017-06-01

The benefits of good predictive models in astronomy lie in early event prediction systems and effective resource allocation. Current time series methods applicable to regular time series have not evolved to generalize for irregular time series. In this talk, I will describe two Recurrent Neural Network methods, Long Short-Term Memory (LSTM) and Echo State Networks (ESNs) for predicting irregular time series. Feature engineering along with a non-linear modeling proved to be an effective predictor. For noisy time series, the prediction is improved by training the network on error realizations using the error estimates from astronomical light curves. In addition to this, we propose a new neural network architecture to remove correlation from the residuals in order to improve prediction and compensate for the noisy data. Finally, I show how to set hyperparameters for a stable and performant solution correctly. In this work, we circumvent this obstacle by optimizing ESN hyperparameters using Bayesian optimization with Gaussian Process priors. This automates the tuning procedure, enabling users to employ the power of RNN without needing an in-depth understanding of the tuning procedure.

Stochastic nature of series of waiting times.

PubMed

Anvari, Mehrnaz; Aghamohammadi, Cina; Dashti-Naserabadi, H; Salehi, E; Behjat, E; Qorbani, M; Nezhad, M Khazaei; Zirak, M; Hadjihosseini, Ali; Peinke, Joachim; Tabar, M Reza Rahimi

2013-06-01

Although fluctuations in the waiting time series have been studied for a long time, some important issues such as its long-range memory and its stochastic features in the presence of nonstationarity have so far remained unstudied. Here we find that the "waiting times" series for a given increment level have long-range correlations with Hurst exponents belonging to the interval 1/2

Macroscopic Spatial Complexity of the Game of Life Cellular Automaton: A Simple Data Analysis

NASA Astrophysics Data System (ADS)

Hernández-Montoya, A. R.; Coronel-Brizio, H. F.; Rodríguez-Achach, M. E.

In this chapter we present a simple data analysis of an ensemble of 20 time series, generated by averaging the spatial positions of the living cells for each state of the Game of Life Cellular Automaton (GoL). We show that at the macroscopic level described by these time series, complexity properties of GoL are also presented and the following emergent properties, typical of data extracted complex systems such as financial or economical come out: variations of the generated time series following an asymptotic power law distribution, large fluctuations tending to be followed by large fluctuations, and small fluctuations tending to be followed by small ones, and fast decay of linear correlations, however, the correlations associated to their absolute variations exhibit a long range memory. Finally, a Detrended Fluctuation Analysis (DFA) of the generated time series, indicates that the GoL spatial macro states described by the time series are not either completely ordered or random, in a measurable and very interesting way.

Long-Range Correlations and Memory in the Dynamics of Internet Interdomain Routing

PubMed Central

Havlin, Shlomo; Krioukov, Dmitri

2015-01-01

Data transfer is one of the main functions of the Internet. The Internet consists of a large number of interconnected subnetworks or domains, known as Autonomous Systems (ASes). Due to privacy and other reasons the information about what route to use to reach devices within other ASes is not readily available to any given AS. The Border Gateway Protocol (BGP) is responsible for discovering and distributing this reachability information to all ASes. Since the topology of the Internet is highly dynamic, all ASes constantly exchange and update this reachability information in small chunks, known as routing control packets or BGP updates. In the view of the quick growth of the Internet there are significant concerns with the scalability of the BGP updates and the efficiency of the BGP routing in general. Motivated by these issues we conduct a systematic time series analysis of BGP update rates. We find that BGP update time series are extremely volatile, exhibit long-term correlations and memory effects, similar to seismic time series, or temperature and stock market price fluctuations. The presented statistical characterization of BGP update dynamics could serve as a basis for validation of existing and developing better models of Internet interdomain routing. PMID:26529312

Long-Range Correlations and Memory in the Dynamics of Internet Interdomain Routing.

PubMed

Kitsak, Maksim; Elmokashfi, Ahmed; Havlin, Shlomo; Krioukov, Dmitri

2015-01-01

Data transfer is one of the main functions of the Internet. The Internet consists of a large number of interconnected subnetworks or domains, known as Autonomous Systems (ASes). Due to privacy and other reasons the information about what route to use to reach devices within other ASes is not readily available to any given AS. The Border Gateway Protocol (BGP) is responsible for discovering and distributing this reachability information to all ASes. Since the topology of the Internet is highly dynamic, all ASes constantly exchange and update this reachability information in small chunks, known as routing control packets or BGP updates. In the view of the quick growth of the Internet there are significant concerns with the scalability of the BGP updates and the efficiency of the BGP routing in general. Motivated by these issues we conduct a systematic time series analysis of BGP update rates. We find that BGP update time series are extremely volatile, exhibit long-term correlations and memory effects, similar to seismic time series, or temperature and stock market price fluctuations. The presented statistical characterization of BGP update dynamics could serve as a basis for validation of existing and developing better models of Internet interdomain routing.

On the multifractal effects generated by monofractal signals

NASA Astrophysics Data System (ADS)

Grech, Dariusz; Pamuła, Grzegorz

2013-12-01

We study quantitatively the level of false multifractal signal one may encounter while analyzing multifractal phenomena in time series within multifractal detrended fluctuation analysis (MF-DFA). The investigated effect appears as a result of finite length of used data series and is additionally amplified by the long-term memory the data eventually may contain. We provide the detailed quantitative description of such apparent multifractal background signal as a threshold in spread of generalized Hurst exponent values Δh or a threshold in the width of multifractal spectrum Δα below which multifractal properties of the system are only apparent, i.e. do not exist, despite Δα≠0 or Δh≠0. We find this effect quite important for shorter or persistent series and we argue it is linear with respect to autocorrelation exponent γ. Its strength decays according to power law with respect to the length of time series. The influence of basic linear and nonlinear transformations applied to initial data in finite time series with various levels of long memory is also investigated. This provides additional set of semi-analytical results. The obtained formulas are significant in any interdisciplinary application of multifractality, including physics, financial data analysis or physiology, because they allow to separate the ‘true’ multifractal phenomena from the apparent (artificial) multifractal effects. They should be a helpful tool of the first choice to decide whether we do in particular case with the signal with real multiscaling properties or not.

Stochastic nature of series of waiting times

NASA Astrophysics Data System (ADS)

Anvari, Mehrnaz; Aghamohammadi, Cina; Dashti-Naserabadi, H.; Salehi, E.; Behjat, E.; Qorbani, M.; Khazaei Nezhad, M.; Zirak, M.; Hadjihosseini, Ali; Peinke, Joachim; Tabar, M. Reza Rahimi

2013-06-01

Although fluctuations in the waiting time series have been studied for a long time, some important issues such as its long-range memory and its stochastic features in the presence of nonstationarity have so far remained unstudied. Here we find that the “waiting times” series for a given increment level have long-range correlations with Hurst exponents belonging to the interval 1/2

Different strategies in solving series completion inductive reasoning problems: an fMRI and computational study.

PubMed

Liang, Peipeng; Jia, Xiuqin; Taatgen, Niels A; Zhong, Ning; Li, Kuncheng

2014-08-01

Neural correlate of human inductive reasoning process is still unclear. Number series and letter series completion are two typical inductive reasoning tasks, and with a common core component of rule induction. Previous studies have demonstrated that different strategies are adopted in number series and letter series completion tasks; even the underlying rules are identical. In the present study, we examined cortical activation as a function of two different reasoning strategies for solving series completion tasks. The retrieval strategy, used in number series completion tasks, involves direct retrieving of arithmetic knowledge to get the relations between items. The procedural strategy, used in letter series completion tasks, requires counting a certain number of times to detect the relations linking two items. The two strategies require essentially the equivalent cognitive processes, but have different working memory demands (the procedural strategy incurs greater demands). The procedural strategy produced significant greater activity in areas involved in memory retrieval (dorsolateral prefrontal cortex, DLPFC) and mental representation/maintenance (posterior parietal cortex, PPC). An ACT-R model of the tasks successfully predicted behavioral performance and BOLD responses. The present findings support a general-purpose dual-process theory of inductive reasoning regarding the cognitive architecture. Copyright © 2014 Elsevier B.V. All rights reserved.

Strong memory in time series of human magnetoencephalograms can identify photosensitive epilepsy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yulmetyev, R. M., E-mail: rmy@theory.kazan-spu.ru; Yulmetyeva, D. G.; Haenggi, P.

2007-04-15

To discuss the salient role of statistical memory effects in human brain functioning, we have analyzed a set of stochastic memory quantifiers that reflects the dynamical characteristics of neuromagnetic responses of magnetoencephalographic signals to a flickering stimulus of different color combinations from a group of control subjects, and compared them with those for a patient with photosensitive epilepsy. We have discovered that the emergence of strong memory and the accompanying transition to a regular and robust regime of chaotic behavior of signals in separate areas for a patient most likely identifies the regions where the protective mechanism against the occurrencemore » of photosensitive epilepsy is located.« less

The Superstatistical Nature and Interoccurrence Time of Atmospheric Mercury Concentration Fluctuations

NASA Astrophysics Data System (ADS)

Carbone, F.; Bruno, A. G.; Naccarato, A.; De Simone, F.; Gencarelli, C. N.; Sprovieri, F.; Hedgecock, I. M.; Landis, M. S.; Skov, H.; Pfaffhuber, K. A.; Read, K. A.; Martin, L.; Angot, H.; Dommergue, A.; Magand, O.; Pirrone, N.

2018-01-01

The probability density function (PDF) of the time intervals between subsequent extreme events in atmospheric Hg0 concentration data series from different latitudes has been investigated. The Hg0 dynamic possesses a long-term memory autocorrelation function. Above a fixed threshold Q in the data, the PDFs of the interoccurrence time of the Hg0 data are well described by a Tsallis q-exponential function. This PDF behavior has been explained in the framework of superstatistics, where the competition between multiple mesoscopic processes affects the macroscopic dynamics. An extensive parameter μ, encompassing all possible fluctuations related to mesoscopic phenomena, has been identified. It follows a χ2 distribution, indicative of the superstatistical nature of the overall process. Shuffling the data series destroys the long-term memory, the distributions become independent of Q, and the PDFs collapse on to the same exponential distribution. The possible central role of atmospheric turbulence on extreme events in the Hg0 data is highlighted.

A deep learning framework for financial time series using stacked autoencoders and long-short term memory

PubMed Central

Bao, Wei; Rao, Yulei

2017-01-01

The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day’s closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance. PMID:28708865

Temporal pattern and memory in sediment transport in an experimental step-pool channel

NASA Astrophysics Data System (ADS)

Saletti, Matteo; Molnar, Peter; Zimmermann, André; Hassan, Marwan A.; Church, Michael; Burlando, Paolo

2015-04-01

In this work we study the complex dynamics of sediment transport and bed morphology in steep streams, using a dataset of experiments performed in a steep flume with natural sediment. High-resolution (1 sec) time series of sediment transport were measured for individual size classes at the outlet of the flume for different combinations of sediment input rates, discharges, and flume slopes. The data show that the relation between instantaneous discharge and sediment transport exhibits large variability on different levels. After dividing the time series into segments of constant water discharge, we quantify the statistical properties of transport rates by fitting the data with a Generalized Extreme Value distribution, whose 3 parameters are related to the average sediment flux. We analyze separately extreme events of transport rate in terms of their fractional composition; if only events of high magnitude are considered, coarse grains become the predominant component of the total sediment yield. We quantify the memory in grain size dependent sediment transport with variance scaling and autocorrelation analyses; more specifically, we study how the variance changes with different aggregation scales and how the autocorrelation coefficient changes with different time lags. Our results show that there is a tendency to an infinite memory regime in transport rate signals, which is limited by the intermittency of the largest fractions. Moreover, the structure of memory is both grain size-dependent and magnitude-dependent: temporal autocorrelation is stronger for small grain size fractions and when the average sediment transport rate is large. The short-term memory in coarse grain transport increases with temporal aggregation and this reveals the importance of the sampling frequency of bedload transport rates in natural streams, especially for large fractions.

Recognition Memory for Realistic Synthetic Faces

PubMed Central

Yotsumoto, Yuko; Kahana, Michael J.; Wilson, Hugh R.; Sekuler, Robert

2006-01-01

A series of experiments examined short-term recognition memory for trios of briefly-presented, synthetic human faces derived from three real human faces. The stimuli were graded series of faces, which differed by varying known amounts from the face of the average female. Faces based on each of the three real faces were transformed so as to lie along orthogonal axes in a 3-D face space. Experiment 1 showed that the synthetic faces' perceptual similarity stucture strongly influenced recognition memory. Results were fit by NEMo, a noisy exemplar model of perceptual recognition memory. The fits revealed that recognition memory was influenced both by the similarity of the probe to series items, and by the similarities among the series items themselves. Non-metric multi-dimensional scaling (MDS) showed that faces' perceptual representations largely preserved the 3-D space in which the face stimuli were arrayed. NEMo gave a better account of the results when similarity was defined as perceptual, MDS similarity rather than physical proximity of one face to another. Experiment 2 confirmed the importance of within-list homogeneity directly, without mediation of a model. We discuss the affinities and differences between visual memory for synthetic faces and memory for simpler stimuli. PMID:17948069

Changes in the Hurst exponent of heartbeat intervals during physical activity

NASA Astrophysics Data System (ADS)

Martinis, M.; Knežević, A.; Krstačić, G.; Vargović, E.

2004-07-01

The fractal scaling properties of the heartbeat time series are studied in different controlled ergometric regimes using both the improved Hurst rescaled range (R/S) analysis and the detrended fluctuation analysis (DFA). The long-time “memory effect” quantified by the value of the Hurst exponent H>0.5 is found to increase during progressive physical activity in healthy subjects, in contrast to those having stable angina pectoris, where it decreases. The results are also supported by the detrended fluctuation analysis. We argue that this finding may be used as a useful new diagnostic parameter for short heartbeat time series.

Patterns of effective connectivity during memory encoding and retrieval differ between patients with mild cognitive impairment and healthy older adults.

PubMed

Hampstead, B M; Khoshnoodi, M; Yan, W; Deshpande, G; Sathian, K

2016-01-01

Previous research has shown that there is considerable overlap in the neural networks mediating successful memory encoding and retrieval. However, little is known about how the relevant human brain regions interact during these distinct phases of memory or how such interactions are affected by memory deficits that characterize mild cognitive impairment (MCI), a condition that often precedes dementia due to Alzheimer's disease. Here we employed multivariate Granger causality analysis using autoregressive modeling of inferred neuronal time series obtained by deconvolving the hemodynamic response function from measured blood oxygenation level-dependent (BOLD) time series data, in order to examine the effective connectivity between brain regions during successful encoding and/or retrieval of object location associations in MCI patients and comparable healthy older adults. During encoding, healthy older adults demonstrated a left hemisphere dominant pattern where the inferior frontal junction, anterior intraparietal sulcus (likely involving the parietal eye fields), and posterior cingulate cortex drove activation in most left hemisphere regions and virtually every right hemisphere region tested. These regions are part of a frontoparietal network that mediates top-down cognitive control and is implicated in successful memory formation. In contrast, in the MCI patients, the right frontal eye field drove activation in every left hemisphere region examined, suggesting reliance on more basic visual search processes. Retrieval in the healthy older adults was primarily driven by the right hippocampus with lesser contributions of the right anterior thalamic nuclei and right inferior frontal sulcus, consistent with theoretical models holding the hippocampus as critical for the successful retrieval of memories. The pattern differed in MCI patients, in whom the right inferior frontal junction and right anterior thalamus drove successful memory retrieval, reflecting the characteristic hippocampal dysfunction of these patients. These findings demonstrate that neural network interactions differ markedly between MCI patients and healthy older adults. Future efforts will investigate the impact of cognitive rehabilitation of memory on these connectivity patterns. Published by Elsevier Inc.

Time reversibility from visibility graphs of nonstationary processes

NASA Astrophysics Data System (ADS)

Lacasa, Lucas; Flanagan, Ryan

2015-08-01

Visibility algorithms are a family of methods to map time series into networks, with the aim of describing the structure of time series and their underlying dynamical properties in graph-theoretical terms. Here we explore some properties of both natural and horizontal visibility graphs associated to several nonstationary processes, and we pay particular attention to their capacity to assess time irreversibility. Nonstationary signals are (infinitely) irreversible by definition (independently of whether the process is Markovian or producing entropy at a positive rate), and thus the link between entropy production and time series irreversibility has only been explored in nonequilibrium stationary states. Here we show that the visibility formalism naturally induces a new working definition of time irreversibility, which allows us to quantify several degrees of irreversibility for stationary and nonstationary series, yielding finite values that can be used to efficiently assess the presence of memory and off-equilibrium dynamics in nonstationary processes without the need to differentiate or detrend them. We provide rigorous results complemented by extensive numerical simulations on several classes of stochastic processes.

Divergent series and memory of the initial condition in the long-time solution of some anomalous diffusion problems.

PubMed

Yuste, S Bravo; Borrego, R; Abad, E

2010-02-01

We consider various anomalous d -dimensional diffusion problems in the presence of an absorbing boundary with radial symmetry. The motion of particles is described by a fractional diffusion equation. Their mean-square displacement is given by r(2) proportional, variant t(gamma)(00 , the emergence of such series in the long-time domain is a specific feature of subdiffusion problems. We present a method to regularize such series, and, in some cases, validate the procedure by using alternative techniques (Laplace transform method and numerical simulations). In the normal diffusion case, we find that the signature of the initial condition on the approach to the steady state rapidly fades away and the solution approaches a single (the main) decay mode in the long-time regime. In remarkable contrast, long-time memory of the initial condition is present in the subdiffusive case as the spatial part Psi1(r) describing the long-time decay of the solution to the steady state is determined by a weighted superposition of all spatial modes characteristic of the normal diffusion problem, the weight being dependent on the initial condition. Interestingly, Psi1(r) turns out to be independent of the anomalous diffusion exponent gamma .

St. Augustine’s Reflections on Memory and Time and the Current Concept of Subjective Time in Mental Time Travel

PubMed Central

Manning, Liliann; Cassel, Daniel; Cassel, Jean-Christophe

2013-01-01

Reconstructing the past and anticipating the future, i.e., the ability of travelling in mental time, is thought to be at the heart of consciousness and, by the same token, at the center of human cognition. This extraordinary mental activity is possible thanks to the ability of being aware of ‘subjective time’. In the present study, we attempt to trace back the first recorded reflections on the relations between time and memory, to the end of the fourth century’s work, the Confessions, by the theologian and philosopher, St. Augustine. We concentrate on Book 11, where he extensively developed a series of articulated and detailed observations on memory and time. On the bases of selected paragraphs, we endeavor to highlight some concepts that may be considered as the product of the first or, at least, very early reflections related to our current notions of subjective time in mental time travel. We also draw a fundamental difference inherent to the frameworks within which the questions were raised. The contribution of St. Augustine on time and memory remains significant, notwithstanding the 16 centuries elapsed since it was made, likely because of the universality of its contents. PMID:25379236

Studies of short and long memory in mining-induced seismic processes

NASA Astrophysics Data System (ADS)

Węglarczyk, Stanisław; Lasocki, Stanisław

2009-09-01

Memory of a stochastic process implies its predictability, understood as a possibility to gain information on the future above the random guess level. Here we search for memory in the mining-induced seismic process (MIS), that is, a process induced or triggered by mining operations. Long memory is investigated by means of the Hurst rescaled range analysis, and the autocorrelation function estimate is used to test for short memory. Both methods are complemented with result uncertainty analyses based on different resampling techniques. The analyzed data comprise event series from Rudna copper mine in Poland. The studies show that the interevent time and interevent distance processes have both long and short memory. MIS occurrences and locations are internally interrelated. Internal relations among the sizes of MIS events are apparently weaker than those of other two studied parameterizations and are limited to long term interactions.

Intervention strength does not differentially affect memory reconsolidation of strong memories.

PubMed

van Schie, Kevin; van Veen, Suzanne C; Hendriks, Yanniek R; van den Hout, Marcel A; Engelhard, Iris M

2017-10-01

Recently, it has become clear that retrieval (i.e., reactivation) of consolidated memories may return these memories into a labile state before they are restored into long-term memory ('reconsolidation'). Using behavioral manipulations, reactivated memories can be disrupted via the mechanism of novel learning. In the present study, we investigated whether changing a strong memory during reconsolidation depends on the strength of novel learning. To test this, participants (N=144) in six groups acquired a relatively strong memory on Day 1 by viewing and recalling a series of pictures three times. On Day 8, these pictures were reactivated in three groups, and they were not reactivated in the other three groups. Then, participants viewed and recalled new pictures once (weak new learning) or three times (strong new learning), or they did not learn any new pictures. On Day 9, participants performed a recognition test in which their memory for Day 1 pictures was assessed. Two main results are noted. First, the groups that reactivated pictures from Day 1 and received weak or strong new learning did not differ in memory performance. Second, these two groups consistently performed similar to groups that controlled for new learning without reactivation. Because these results contradict what was expected based on the reconsolidation hypothesis, we discuss possible explanations and implications. Copyright © 2017 Elsevier Inc. All rights reserved.

Working Memory and Processing Efficiency in Children's Reasoning.

ERIC Educational Resources Information Center

Halford, Graeme S.; And Others

A series of studies was conducted to determine whether children's reasoning is capacity-limited and whether any such capacity, if it exists, is based on the working memory system. An N-term series (transitive inference) was used as the primary task in an interference paradigm. A concurrent short-term memory load was employed as the secondary task.…

Dynamical Analysis and Visualization of Tornadoes Time Series

PubMed Central

2015-01-01

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns. PMID:25790281

Dynamical analysis and visualization of tornadoes time series.

PubMed

Lopes, António M; Tenreiro Machado, J A

2015-01-01

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.

Numerical solution methods for viscoelastic orthotropic materials

NASA Technical Reports Server (NTRS)

Gramoll, K. C.; Dillard, D. A.; Brinson, H. F.

1988-01-01

Numerical solution methods for viscoelastic orthotropic materials, specifically fiber reinforced composite materials, are examined. The methods include classical lamination theory using time increments, direction solution of the Volterra Integral, Zienkiewicz's linear Prony series method, and a new method called Nonlinear Differential Equation Method (NDEM) which uses a nonlinear Prony series. The criteria used for comparison of the various methods include the stability of the solution technique, time step size stability, computer solution time length, and computer memory storage. The Volterra Integral allowed the implementation of higher order solution techniques but had difficulties solving singular and weakly singular compliance function. The Zienkiewicz solution technique, which requires the viscoelastic response to be modeled by a Prony series, works well for linear viscoelastic isotropic materials and small time steps. The new method, NDEM, uses a modified Prony series which allows nonlinear stress effects to be included and can be used with orthotropic nonlinear viscoelastic materials. The NDEM technique is shown to be accurate and stable for both linear and nonlinear conditions with minimal computer time.

The development of a short domain-general measure of working memory capacity.

PubMed

Oswald, Frederick L; McAbee, Samuel T; Redick, Thomas S; Hambrick, David Z

2015-12-01

Working memory capacity is one of the most frequently measured individual difference constructs in cognitive psychology and related fields. However, implementation of complex span and other working memory measures is generally time-consuming for administrators and examinees alike. Because researchers often must manage the tension between limited testing time and measuring numerous constructs reliably, a short and effective measure of working memory capacity would often be a major practical benefit in future research efforts. The current study developed a shortened computerized domain-general measure of working memory capacity by representatively sampling items from three existing complex working memory span tasks: operation span, reading span, and symmetry span. Using a large archival data set (Study 1, N = 4,845), we developed and applied a principled strategy for developing the reduced measure, based on testing a series of confirmatory factor analysis models. Adequate fit indices from these models lent support to this strategy. The resulting shortened measure was then administered to a second independent sample (Study 2, N = 172), demonstrating that the new measure saves roughly 15 min (30%) of testing time on average, and even up to 25 min depending on the test-taker. On the basis of these initial promising findings, several directions for future research are discussed.

The time course of ventrolateral prefrontal cortex involvement in memory formation.

PubMed

Machizawa, Maro G; Kalla, Roger; Walsh, Vincent; Otten, Leun J

2010-03-01

Human neuroimaging studies have implicated a number of brain regions in long-term memory formation. Foremost among these is ventrolateral prefrontal cortex. Here, we used double-pulse transcranial magnetic stimulation (TMS) to assess whether the contribution of this part of cortex is crucial for laying down new memories and, if so, to examine the time course of this process. Healthy adult volunteers performed an incidental encoding task (living/nonliving judgments) on sequences of words. In separate series, the task was performed either on its own or while TMS was applied to one of two sites of experimental interest (left/right anterior inferior frontal gyrus) or a control site (vertex). TMS pulses were delivered at 350, 750, or 1,150 ms following word onset. After a delay of 15 min, memory for the items was probed with a recognition memory test including confidence judgments. TMS to all three sites nonspecifically affected the speed and accuracy with which judgments were made during the encoding task. However, only TMS to prefrontal cortex affected later memory performance. Stimulation of left or right inferior frontal gyrus at all three time points reduced the likelihood that a word would later be recognized by a small, but significant, amount (approximately 4%). These findings indicate that bilateral ventrolateral prefrontal cortex plays an essential role in memory formation, exerting its influence between > or = 350 and 1,150 ms after an event is encountered.

Skewness, long-time memory, and non-stationarity: Application to leverage effect in financial time series

NASA Astrophysics Data System (ADS)

Roman, H. E.; Porto, M.; Dose, C.

2008-10-01

We analyze daily log-returns data for a set of 1200 stocks, taken from US stock markets, over a period of 2481 trading days (January 1996-November 2005). We estimate the degree of non-stationarity in daily market volatility employing a polynomial fit, used as a detrending function. We find that the autocorrelation function of absolute detrended log-returns departs strongly from the corresponding original data autocorrelation function, while the observed leverage effect depends only weakly on trends. Such effect is shown to occur when both skewness and long-time memory are simultaneously present. A fractional derivative random walk model is discussed yielding a quantitative agreement with the empirical results.

Application of the Cluster Expansion to a Mathematical Model of the Long Memory Phenomenon in a Financial Market

NASA Astrophysics Data System (ADS)

Kuroda, Koji; Maskawa, Jun-ichi; Murai, Joshin

2013-08-01

Empirical studies of the high frequency data in stock markets show that the time series of trade signs or signed volumes has a long memory property. In this paper, we present a discrete time stochastic process for polymer model which describes trader's trading strategy, and show that a scale limit of the process converges to superposition of fractional Brownian motions with Hurst exponents and Brownian motion, provided that the index γ of the time scale about the trader's investment strategy coincides with the index δ of the interaction range in the discrete time process. The main tool for the investigation is the method of cluster expansion developed in the mathematical study of statistical mechanics.

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

NASA Astrophysics Data System (ADS)

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

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

A Cautionary Analysis of a Billion Dollar Athletic Expenditure: The History of the Renovation of California Memorial Stadium and the Construction of the Barclay Simpson Student Athlete High Performance Center. Research & Occasional Paper Series: CSHE.3.17

ERIC Educational Resources Information Center

Cummins, John

2017-01-01

This paper is a description and analysis of the history of the renovation of Memorial Stadium and the building of the Barclay Simpson Student Athlete High Performance Center (SAHPC) on the Berkeley campus, showing how incremental changes over time result in a much riskier and financially less viable project than originally anticipated. It…

Mutual information identifies spurious Hurst phenomena in resting state EEG and fMRI data

NASA Astrophysics Data System (ADS)

von Wegner, Frederic; Laufs, Helmut; Tagliazucchi, Enzo

2018-02-01

Long-range memory in time series is often quantified by the Hurst exponent H , a measure of the signal's variance across several time scales. We analyze neurophysiological time series from electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) resting state experiments with two standard Hurst exponent estimators and with the time-lagged mutual information function applied to discretized versions of the signals. A confidence interval for the mutual information function is obtained from surrogate Markov processes with equilibrium distribution and transition matrix identical to the underlying signal. For EEG signals, we construct an additional mutual information confidence interval from a short-range correlated, tenth-order autoregressive model. We reproduce the previously described Hurst phenomenon (H >0.5 ) in the analytical amplitude of alpha frequency band oscillations, in EEG microstate sequences, and in fMRI signals, but we show that the Hurst phenomenon occurs without long-range memory in the information-theoretical sense. We find that the mutual information function of neurophysiological data behaves differently from fractional Gaussian noise (fGn), for which the Hurst phenomenon is a sufficient condition to prove long-range memory. Two other well-characterized, short-range correlated stochastic processes (Ornstein-Uhlenbeck, Cox-Ingersoll-Ross) also yield H >0.5 , whereas their mutual information functions lie within the Markovian confidence intervals, similar to neural signals. In these processes, which do not have long-range memory by construction, a spurious Hurst phenomenon occurs due to slow relaxation times and heteroscedasticity (time-varying conditional variance). In summary, we find that mutual information correctly distinguishes long-range from short-range dependence in the theoretical and experimental cases discussed. Our results also suggest that the stationary fGn process is not sufficient to describe neural data, which seem to belong to a more general class of stochastic processes, in which multiscale variance effects produce Hurst phenomena without long-range dependence. In our experimental data, the Hurst phenomenon and long-range memory appear as different system properties that should be estimated and interpreted independently.

Living with extreme weather events - perspectives from climatology, geomorphological analysis, chronicles and opinion polls

NASA Astrophysics Data System (ADS)

Auer, I.; Kirchengast, A.; Proske, H.

2009-09-01

The ongoing climate change debate focuses more and more on changing extreme events. Information on past events can be derived from a number of sources, such as instrumental data, residual impacts in the landscape, but also chronicles and people's memories. A project called "A Tale of Two Valleys” within the framework of the research program "proVision” allowed to study past extreme events in two inner-alpine valleys from the sources mentioned before. Instrumental climate time series provided information for the past 200 years, however great attention had to be given to the homogeneity of the series. To derive homogenized time series of selected climate change indices methods like HOCLIS and Vincent have been applied. Trend analyses of climate change indices inform about increase or decrease of extreme events. Traces of major geomorphodynamic processes of the past (e.g. rockfalls, landslides, debris flows) which were triggered or affected by extreme weather events are still apparent in the landscape and could be evaluated by geomorphological analysis using remote sensing and field data. Regional chronicles provided additional knowledge and covered longer periods back in time, however compared to meteorological time series they enclose a high degree of subjectivity and intermittent recordings cannot be obviated. Finally, questionnaires and oral history complemented our picture of past extreme weather events. People were differently affected and have different memories of it. The joint analyses of these four data sources showed agreement to some extent, however also showed some reasonable differences: meteorological data are point measurements only with a sometimes too coarse temporal resolution. Due to land-use changes and improved constructional measures the impact of an extreme meteorological event may be different today compared to earlier times.

Long-range correlations in an online betting exchange for a football tournament

NASA Astrophysics Data System (ADS)

Hardiman, Stephen J.; Richmond, Peter; Hutzler, Stefan

2010-10-01

We analyze the changes in the market odds of football matches in an online betting exchange, Betfair.com. We identify the statistical differences between the returns that occur when the game play is under way, which we argue are driven by match events, and the returns that occur during half-time, which we ascribe to a trader-driven noise. Furthermore, using detrended fluctuation analysis we identify anti-persistence (Hurst exponent H<0.5) in odds returns and long memory (H>0.5) in the volatilities, which we attribute to the trader-driven noise. The time series of trading volume are found to be short-memory processes.

Basic Auditory Processing and Developmental Dyslexia in Chinese

ERIC Educational Resources Information Center

Wang, Hsiao-Lan Sharon; Huss, Martina; Hamalainen, Jarmo A.; Goswami, Usha

2012-01-01

The present study explores the relationship between basic auditory processing of sound rise time, frequency, duration and intensity, phonological skills (onset-rime and tone awareness, sound blending, RAN, and phonological memory) and reading disability in Chinese. A series of psychometric, literacy, phonological, auditory, and character…

R/S analysis based study on long memory about CODMn in Poyang Lake Inlet and Outlet

NASA Astrophysics Data System (ADS)

Wang, Lili

2018-02-01

Rescaled range analysis (R/S) is applied to the long memory behavior analysis of water CODMn series in Poyang Lake Inlet and Outlet in China. The results show that these CODMn series are characterized by long memory, and the characteristics have obvious differences between the Lake Inlet and Outlet. Our findings suggest that there was an obvious scale invariance, namely CODMn series in Lake Inlet for 13 weeks and CODMn in Lake Outlet for 17 weeks. Both displayed a two-power-law distribution and a similar high long memory. We made a preliminary explanation for the existence of the boundary point tc , using self-organized criticality. This work can be helpful to improvement of modelling of lake water quality.

Perturbation schedule does not alter retention of a locomotor adaptation across days.

PubMed

Hussain, Sara J; Morton, Susanne M

2014-06-15

Motor adaptation in response to gradual vs. abrupt perturbation schedules may involve different neural mechanisms, potentially leading to different levels of motor memory. However, no study has investigated whether perturbation schedules alter memory of a locomotor adaptation across days. We measured adaptation and retention (memory) of altered interlimb symmetry during walking in two groups of participants over 2 days. On day 1, participants adapted to either a single, large perturbation (abrupt schedule) or a series of small perturbations that increased in size over time (gradual schedule). Retention was examined on day 2. On day 1, initial swing time and foot placement symmetry error sizes differed between groups but overall adaptation magnitudes were similar. On day 2, participants in both groups showed similar retention, readaptation, and aftereffect sizes, although there were some trends for improved memory in the abrupt group. These results conflict with previous data but are consistent with newer studies reporting no behavioral differences following adaptation using abrupt vs. gradual schedules. Although memory levels were very similar between groups, we cannot rule out the possibility that the neural mechanisms underlying this memory storage differ. Overall, it appears that adaptation of locomotor patterns via abrupt and gradual perturbation schedules produces similar expression of locomotor memories across days. Copyright © 2014 the American Physiological Society.

The impact of storage on processing: how is information maintained in working memory?

PubMed

Vergauwe, Evie; Camos, Valérie; Barrouillet, Pierre

2014-07-01

Working memory is typically defined as a system devoted to the simultaneous maintenance and processing of information. However, the interplay between these 2 functions is still a matter of debate in the literature, with views ranging from complete independence to complete dependence. The time-based resource-sharing model assumes that a central bottleneck constrains the 2 functions to alternate in such a way that maintenance activities postpone concurrent processing, with each additional piece of information to be maintained resulting in an additional postponement. Using different kinds of memoranda, we examined in a series of 7 experiments the effect of increasing memory load on different processing tasks. The results reveal that, insofar as attention is needed for maintenance, processing times linearly increase at a rate of about 50 ms per verbal or visuospatial memory item, suggesting a very fast refresh rate in working memory. Our results also show an asymmetry between verbal and spatial information, in that spatial information can solely rely on attention for its maintenance while verbal information can also rely on a domain-specific maintenance mechanism independent from attention. The implications for the functioning of working memory are discussed, with a specific focus on how information is maintained in working memory. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Recovery of Repressed Memories in Fibromyalgia Patients Treated With Hyperbaric Oxygen – Case Series Presentation and Suggested Bio-Psycho-Social Mechanism

PubMed Central

Efrati, Shai; Hadanny, Amir; Daphna-Tekoah, Shir; Bechor, Yair; Tiberg, Kobi; Pik, Nimrod; Suzin, Gil; Lev-Wiesel, Rachel

2018-01-01

Fibromyalgia Syndrome (FMS) is a condition considered to represent a prototype of central sensitization syndrome, characterized by chronic widespread pain and along with symptoms of fatigue, non-restorative sleep and cognitive difficulties. FMS can be induced by trauma, infection or emotional stress with cumulative evidence that dissociation is relatively frequent in FMS patients. Two randomized controlled trials have shown that hyperbaric oxygen therapy (HBOT) can induce neuroplasticity and be effective in patients suffering from FMS. In this paper we present, for the first time, case series of female fibromyalgia patients who, in the course of HBOT, suddenly recalled repressed traumatic memories of childhood sexual abuse (CSA). The surfacing of the repressed (dissociative) memories decades after the sexual abuse events was sudden and utterly surprising. No psychological intervention was involved. As the memories surfaced, the physical pain related to FMS subsided. In one patient who had brain single photon emission CT (SPECT) before and after HBOT, the prefrontal cortex appeared suppressed before and reactivated after. The 3 cases reported in this article are representative of a total of nine fibromyalgia patients who experienced a retrieval of repressed memory during HBOT. These cases provide insights on dissociative amnesia and suggested mechanism hypothesis that is further discussed in the article. Obviously, prospective studies cannot be planned since patients are not aware of their repressed memories. However, it is very important to keep in mind the possibility of surfacing memories when treating fibromyalgia patients with HBOT or other interventions capable of awakening dormant brain regions. PMID:29896150

Turbulence Time Series Data Hole Filling using Karhunen-Loeve and ARIMA methods

DTIC Science & Technology

2007-01-01

memory is represented by higher values of d. 4.1. ARIMA and EMD We applied an ARIMA (0,d,0) model to predict the behaviour of the final section of the...to a simplified ARIMA (0,d,0) model , which performed better than the linear interpolant but less effectively than the KL algorithm, disregarding edge...ar X iv :p hy si cs /0 70 12 38 v1 22 J an 2 00 7 Turbulence Time Series Data Hole Filling using Karhunen-Loève and ARIMA methods M P J L

A wavelet-based evaluation of time-varying long memory of equity markets: A paradigm in crisis

NASA Astrophysics Data System (ADS)

Tan, Pei P.; Chin, Cheong W.; Galagedera, Don U. A.

2014-09-01

This study, using wavelet-based method investigates the dynamics of long memory in the returns and volatility of equity markets. In the sample of five developed and five emerging markets we find that the daily return series from January 1988 to June 2013 may be considered as a mix of weak long memory and mean-reverting processes. In the case of volatility in the returns, there is evidence of long memory, which is stronger in emerging markets than in developed markets. We find that although the long memory parameter may vary during crisis periods (1997 Asian financial crisis, 2001 US recession and 2008 subprime crisis) the direction of change may not be consistent across all equity markets. The degree of return predictability is likely to diminish during crisis periods. Robustness of the results is checked with de-trended fluctuation analysis approach.

Hippocampal replay in the awake state: a potential physiological substrate of memory consolidation and retrieval

PubMed Central

Carr, Margaret F.; Jadhav, Shantanu P.; Frank, Loren M.

2011-01-01

The hippocampus is required for the encoding, consolidation, and retrieval of event memories. While the neural mechanisms that underlie these processes are only partially understood, a series of recent papers point to awake memory replay as a potential contributor to both consolidation and retrieval. Replay is the sequential reactivation of hippocampal place cells that represent previously experienced behavioral trajectories and occurs frequently in the awake state, particularly during periods of relative immobility. Awake replay may reflect trajectories through either the current environment or previously visited environments that are spatially remote. The repetition of learned sequences on a compressed time scale is well suited to promote memory consolidation in distributed circuits beyond the hippocampus, suggesting that consolidation occurs in both the awake and sleeping animal. Moreover, sensory information can influence the content of awake replay, suggesting a role for awake replay in memory retrieval. PMID:21270783

A mechanism for multidisciplinary dialogue: the memory & … series.

PubMed

Multhaup, Kristi S; Denham, Scott; Kelly, Hilton; Lom, Barbara

2011-01-01

Neuroscientists have long explored the mechanisms of memory from molecular, physiological, cognitive, and social perspectives. Scholars from other disciplines such as history, sociology, literature, and cultural studies, that do not traditionally cross-pollinate ideas with neuroscientists, also study memory from a variety of angles. In this article, we describe the founding of a multidisciplinary discussion series in which faculty and staff from the arts, humanities, social sciences, and natural sciences come together to explain how memory is integral to their scholarship and teaching. After panelists from different disciplines present opening comments, the floor is open for discussion with the audience that includes students, staff, and community members, as well as other faculty. Each year the series is anchored by a keynote address by an eminent scholar engaged in cross-disciplinary memory research. We outline the benefits of such thematic discussion series, highlighting the synchrony with the academy's increasing focus on interdisciplinarity, and on the need to train scholars to speak clearly about their work beyond their own disciplinary boundaries. More specifically, we focus on the need to train scientists to communicate with non-scientists. We have experienced success with this series and believe that the format could be adapted to a wide range of issues that cross disciplines (e.g., development, language, music, environmental studies).

A Mechanism for Multidisciplinary Dialogue: The Memory & … Series

PubMed Central

Multhaup, Kristi S.; Denham, Scott; Kelly, Hilton; Lom, Barbara

2011-01-01

Neuroscientists have long explored the mechanisms of memory from molecular, physiological, cognitive, and social perspectives. Scholars from other disciplines such as history, sociology, literature, and cultural studies, that do not traditionally cross-pollinate ideas with neuroscientists, also study memory from a variety of angles. In this article, we describe the founding of a multidisciplinary discussion series in which faculty and staff from the arts, humanities, social sciences, and natural sciences come together to explain how memory is integral to their scholarship and teaching. After panelists from different disciplines present opening comments, the floor is open for discussion with the audience that includes students, staff, and community members, as well as other faculty. Each year the series is anchored by a keynote address by an eminent scholar engaged in cross-disciplinary memory research. We outline the benefits of such thematic discussion series, highlighting the synchrony with the academy’s increasing focus on interdisciplinarity, and on the need to train scholars to speak clearly about their work beyond their own disciplinary boundaries. More specifically, we focus on the need to train scientists to communicate with non-scientists. We have experienced success with this series and believe that the format could be adapted to a wide range of issues that cross disciplines (e.g., development, language, music, environmental studies). PMID:23626499

Unraveling chaotic attractors by complex networks and measurements of stock market complexity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cao, Hongduo; Li, Ying, E-mail: mnsliy@mail.sysu.edu.cn

2014-03-15

We present a novel method for measuring the complexity of a time series by unraveling a chaotic attractor modeled on complex networks. The complexity index R, which can potentially be exploited for prediction, has a similar meaning to the Kolmogorov complexity (calculated from the Lempel–Ziv complexity), and is an appropriate measure of a series' complexity. The proposed method is used to research the complexity of the world's major capital markets. None of these markets are completely random, and they have different degrees of complexity, both over the entire length of their time series and at a level of detail. However,more » developing markets differ significantly from mature markets. Specifically, the complexity of mature stock markets is stronger and more stable over time, whereas developing markets exhibit relatively low and unstable complexity over certain time periods, implying a stronger long-term price memory process.« less

Statistical physics approaches to financial fluctuations

NASA Astrophysics Data System (ADS)

Wang, Fengzhong

2009-12-01

Complex systems attract many researchers from various scientific fields. Financial markets are one of these widely studied complex systems. Statistical physics, which was originally developed to study large systems, provides novel ideas and powerful methods to analyze financial markets. The study of financial fluctuations characterizes market behavior, and helps to better understand the underlying market mechanism. Our study focuses on volatility, a fundamental quantity to characterize financial fluctuations. We examine equity data of the entire U.S. stock market during 2001 and 2002. To analyze the volatility time series, we develop a new approach, called return interval analysis, which examines the time intervals between two successive volatilities exceeding a given value threshold. We find that the return interval distribution displays scaling over a wide range of thresholds. This scaling is valid for a range of time windows, from one minute up to one day. Moreover, our results are similar for commodities, interest rates, currencies, and for stocks of different countries. Further analysis shows some systematic deviations from a scaling law, which we can attribute to nonlinear correlations in the volatility time series. We also find a memory effect in return intervals for different time scales, which is related to the long-term correlations in the volatility. To further characterize the mechanism of price movement, we simulate the volatility time series using two different models, fractionally integrated generalized autoregressive conditional heteroscedasticity (FIGARCH) and fractional Brownian motion (fBm), and test these models with the return interval analysis. We find that both models can mimic time memory but only fBm shows scaling in the return interval distribution. In addition, we examine the volatility of daily opening to closing and of closing to opening. We find that each volatility distribution has a power law tail. Using the detrended fluctuation analysis (DFA) method, we show long-term auto-correlations in these volatility time series. We also analyze return, the actual price changes of stocks, and find that the returns over the two sessions are often anti-correlated.

Intrinsic vs. spurious long-range memory in high-frequency records of environmental radioactivity - Critical re-assessment and application to indoor 222Rn concentrations from Coimbra, Portugal

NASA Astrophysics Data System (ADS)

Donner, Reik V.; Potirakis, Stelios M.; Barbosa, Susana M.; Matos, Jose A. O.

2015-04-01

The presence or absence of long-range correlations in environmental radioactivity fluctuations has recently attracted considerable interest. Among a multiplicity of practically relevant applications, identifying and disentangling the environmental factors controlling the variable concentrations of the radioactive noble gas Radon is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we present a critical re-assessment of a multiplicity of complementary methods that have been previously applied for evaluating the presence of long-range correlations and fractal scaling in environmental Radon variations with a particular focus on the specific properties of the underlying time series. As an illustrative case study, we subsequently re-analyze two high-frequency records of indoor Radon concentrations from Coimbra, Portugal, each of which spans several months of continuous measurements at a high temporal resolution of five minutes. Our results reveal that at the study site, Radon concentrations exhibit complex multi-scale dynamics with qualitatively different properties at different time-scales: (i) essentially white noise in the high-frequency part (up to time-scales of about one hour), (ii) spurious indications of a non-stationary, apparently long-range correlated process (at time scales between hours and one day) arising from marked periodic components probably related to tidal frequencies, and (iii) low-frequency variability indicating a true long-range dependent process, which might be dominated by a response to meteorological drivers. In the presence of such multi-scale variability, common estimators of long-range memory in time series are necessarily prone to fail if applied to the raw data without previous separation of time-scales with qualitatively different dynamics. We emphasize that similar properties can be found in other types of geophysical time series (for example, tide gauge records), calling for a careful application of time series analysis tools when studying such data.

Influence of emotional content and context on memory in mild Alzheimer's disease.

PubMed

Perrin, Margaux; Henaff, Marie-Anne; Padovan, Catherine; Faillenot, Isabelle; Merville, Adrien; Krolak-Salmon, Pierre

2012-01-01

Healthy subjects remember emotional stimuli better than neutral, as well as stimuli embedded in an emotional context. This better memory of emotional messages is linked to an amygdalo-hippocampal cooperation taking place in a larger fronto-temporal network particularly sensitive to pathological aging. Amygdala is mainly involved in gist memory of emotional messages. Whether emotional content or context enhances memory in mild Alzheimer's disease (AD) patients is still debated. The aim of the present study is to examine the influence of emotional content and emotional context on the memory in mild AD, and whether this influence is linked to amygdala volume. Fifteen patients affected by mild AD and 15 age-matched controls were submitted to series of negative, positive, and neutral pictures. Each series was embedded in an emotional or neutral sound context. At the end of each series, participants had to freely recall pictures, and answer questions about each picture. Amygdala volumes were measured on patient 3D-MRI scans. In the present study, emotional content significantly favored memory of gist but not of details in healthy elderly and in AD patients. Patients' amygdala volume was positively correlated to emotional content memory effect, implying a reduced memory benefit from emotional content when amygdala was atrophied. A positive context enhanced memory of pictures in healthy elderly, but not in AD, corroborating early fronto-temporal dysfunction and early working memory limitation in this disease.

Mnemonic convergence in social networks: The emergent properties of cognition at a collective level.

PubMed

Coman, Alin; Momennejad, Ida; Drach, Rae D; Geana, Andra

2016-07-19

The development of shared memories, beliefs, and norms is a fundamental characteristic of human communities. These emergent outcomes are thought to occur owing to a dynamic system of information sharing and memory updating, which fundamentally depends on communication. Here we report results on the formation of collective memories in laboratory-created communities. We manipulated conversational network structure in a series of real-time, computer-mediated interactions in fourteen 10-member communities. The results show that mnemonic convergence, measured as the degree of overlap among community members' memories, is influenced by both individual-level information-processing phenomena and by the conversational social network structure created during conversational recall. By studying laboratory-created social networks, we show how large-scale social phenomena (i.e., collective memory) can emerge out of microlevel local dynamics (i.e., mnemonic reinforcement and suppression effects). The social-interactionist approach proposed herein points to optimal strategies for spreading information in social networks and provides a framework for measuring and forging collective memories in communities of individuals.

Updated Electronic Testbed System

NASA Technical Reports Server (NTRS)

Brewer, Kevin L.

2001-01-01

As we continue to advance in exploring space frontiers, technology must also advance. The need for faster data recovery and data processing is crucial. In this, the less equipment used, and lighter that equipment is, the better. Because integrated circuits become more sensitive in high altitude, experimental verification and quantification is required. The Center for Applied Radiation Research (CARR) at Prairie View A&M University was awarded a grant by NASA to participate in the NASA ER-2 Flight Program, the APEX balloon flight program, and the Student Launch Program. These programs are to test anomalous errors in integrated circuits due to single event effects (SEE). CARR had already begun experiments characterizing the SEE behavior of high speed and high density SRAM's. The research center built a error testing system using a PC-104 computer unit, an Iomega Zip drive for storage, a test board with the components under test, and a latchup detection and reset unit. A test program was written to continuously monitor a stored data pattern in the SRAM chip and record errors. The devices under test were eight 4Mbit memory chips totaling 4Mbytes of memory. CARR was successful at obtaining data using the Electronic TestBed System (EBS) in various NASA ER-2 test flights. These series of high altitude flights of up to 70,000 feet, were effective at yielding the conditions which single event effects usually occur. However, the data received from the series of flights indicated one error per twenty-four hours. Because flight test time is very expensive, the initial design proved not to be cost effective. The need for orders of magnitude with more memory became essential. Therefore, a project which could test more memory within a given time was created. The goal of this project was not only to test more memory within a given time, but also to have a system with a faster processing speed, and which used less peripherals. This paper will describe procedures used to build an updated Electronic Testbed System.

Transition from Target to Gaze Coding in Primate Frontal Eye Field during Memory Delay and Memory-Motor Transformation.

PubMed

Sajad, Amirsaman; Sadeh, Morteza; Yan, Xiaogang; Wang, Hongying; Crawford, John Douglas

2016-01-01

The frontal eye fields (FEFs) participate in both working memory and sensorimotor transformations for saccades, but their role in integrating these functions through time remains unclear. Here, we tracked FEF spatial codes through time using a novel analytic method applied to the classic memory-delay saccade task. Three-dimensional recordings of head-unrestrained gaze shifts were made in two monkeys trained to make gaze shifts toward briefly flashed targets after a variable delay (450-1500 ms). A preliminary analysis of visual and motor response fields in 74 FEF neurons eliminated most potential models for spatial coding at the neuron population level, as in our previous study (Sajad et al., 2015). We then focused on the spatiotemporal transition from an eye-centered target code (T; preferred in the visual response) to an eye-centered intended gaze position code (G; preferred in the movement response) during the memory delay interval. We treated neural population codes as a continuous spatiotemporal variable by dividing the space spanning T and G into intermediate T-G models and dividing the task into discrete steps through time. We found that FEF delay activity, especially in visuomovement cells, progressively transitions from T through intermediate T-G codes that approach, but do not reach, G. This was followed by a final discrete transition from these intermediate T-G delay codes to a "pure" G code in movement cells without delay activity. These results demonstrate that FEF activity undergoes a series of sensory-memory-motor transformations, including a dynamically evolving spatial memory signal and an imperfect memory-to-motor transformation.

The epigenetic basis of memory formation and storage.

PubMed

Jarome, Timothy J; Thomas, Jasmyne S; Lubin, Farah D

2014-01-01

The formation of long-term memory requires a series of cellular and molecular changes that involve transcriptional regulation of gene expression. While these changes in gene transcription were initially thought to be largely regulated by the activation of transcription factors by intracellular signaling molecules, epigenetic mechanisms have emerged as an important regulator of transcriptional processes across multiple brain regions to form a memory circuit for a learned event or experience. Due to their self-perpetuating nature and ability to bidirectionally control gene expression, these epigenetic mechanisms have the potential to not only regulate initial memory formation but also modify and update memory over time. This chapter focuses on the established, but poorly understood, role for epigenetic mechanisms such as posttranslational modifications of histone proteins and DNA methylation at the different stages of memory storage. Additionally, this chapter emphasizes how these mechanisms interact to control the ideal epigenetic environment for memory formation and modification in neurons. The reader will gain insights into the limitations in our current understanding of epigenetic regulation of memory storage, especially in terms of their cell-type specificity and the lack of understanding in the interactions of various epigenetic modifiers to one another to impact gene expression changes during memory formation.

Age-related changes in event-cued visual and auditory prospective memory proper.

PubMed

Uttl, Bob

2006-06-01

We rely upon prospective memory proper (ProMP) to bring back to awareness previously formed plans and intentions at the right place and time, and to enable us to act upon those plans and intentions. To examine age-related changes in ProMP, younger and older participants made decisions about simple stimuli (ongoing task) and at the same time were required to respond to a ProM cue, either a picture (visually cued ProM test) or a sound (auditorily cued ProM test), embedded in a simultaneously presented series of similar stimuli (either pictures or sounds). The cue display size or loudness increased across trials until a response was made. The cue size and cue loudness at the time of response indexed ProMP. The main results showed that both visual and auditory ProMP declined with age, and that such declines were mediated by age declines in sensory functions (visual acuity and hearing level), processing resources, working memory, intelligence, and ongoing task resource allocation.

A wavelet analysis of scaling laws and long-memory in stock market volatility

NASA Astrophysics Data System (ADS)

Vuorenmaa, Tommi A.

2005-05-01

This paper studies the time-varying behavior of scaling laws and long-memory. This is motivated by the earlier finding that in the FX markets a single scaling factor might not always be sufficient across all relevant timescales: a different region may exist for intradaily time-scales and for larger time-scales. In specific, this paper investigates (i) if different scaling regions appear in stock market as well, (ii) if the scaling factor systematically differs from the Brownian, (iii) if the scaling factor is constant in time, and (iv) if the behavior can be explained by the heterogenuity of the players in the market and/or by intraday volatility periodicity. Wavelet method is used because it delivers a multiresolution decomposition and has excellent local adaptiviness properties. As a consequence, a wavelet-based OLS method allows for consistent estimation of long-memory. Thus issues (i)-(iv) shed light on the magnitude and behavior of a long-memory parameter, as well. The data are the 5-minute volatility series of Nokia Oyj at the Helsinki Stock Exchange around the burst of the IT-bubble. Period one represents the era of "irrational exuberance" and another the time after it. The results show that different scaling regions (i.e. multiscaling) may appear in the stock markets and not only in the FX markets, the scaling factor and the long-memory parameter are systematically different from the Brownian and they do not have to be constant in time, and that the behavior can be explained for a significant part by an intraday volatility periodicity called the New York effect. This effect was magnified by the frenzy trading of short-term speculators in the bubble period. The found stronger long-memory is also attributable to irrational exuberance.

Promoting the experimental dialogue between working memory and chunking: Behavioral data and simulation.

PubMed

Portrat, Sophie; Guida, Alessandro; Phénix, Thierry; Lemaire, Benoît

2016-04-01

Working memory (WM) is a cognitive system allowing short-term maintenance and processing of information. Maintaining information in WM consists, classically, in rehearsing or refreshing it. Chunking could also be considered as a maintenance mechanism. However, in the literature, it is more often used to explain performance than explicitly investigated within WM paradigms. Hence, the aim of the present paper was (1) to strengthen the experimental dialogue between WM and chunking, by studying the effect of acronyms in a computer-paced complex span task paradigm and (2) to formalize explicitly this dialogue within a computational model. Young adults performed a WM complex span task in which they had to maintain series of 7 letters for further recall while performing a concurrent location judgment task. The series to be remembered were either random strings of letters or strings containing a 3-letter acronym that appeared in position 1, 3, or 5 in the series. Together, the data and simulations provide a better understanding of the maintenance mechanisms taking place in WM and its interplay with long-term memory. Indeed, the behavioral WM performance lends evidence to the functional characteristics of chunking that seems to be, especially in a WM complex span task, an attentional time-based mechanism that certainly enhances WM performance but also competes with other processes at hand in WM. Computational simulations support and delineate such a conception by showing that searching for a chunk in long-term memory involves attentionally demanding subprocesses that essentially take place during the encoding phases of the task.

Musical and Verbal Memory in Alzheimer's Disease: A Study of Long-Term and Short-Term Memory

ERIC Educational Resources Information Center

Menard, Marie-Claude; Belleville, Sylvie

2009-01-01

Musical memory was tested in Alzheimer patients and in healthy older adults using long-term and short-term memory tasks. Long-term memory (LTM) was tested with a recognition procedure using unfamiliar melodies. Short-term memory (STM) was evaluated with same/different judgment tasks on short series of notes. Musical memory was compared to verbal…

Real-time state estimation in a flight simulator using fNIRS.

PubMed

Gateau, Thibault; Durantin, Gautier; Lancelot, Francois; Scannella, Sebastien; Dehais, Frederic

2015-01-01

Working memory is a key executive function for flying an aircraft. This function is particularly critical when pilots have to recall series of air traffic control instructions. However, working memory limitations may jeopardize flight safety. Since the functional near-infrared spectroscopy (fNIRS) method seems promising for assessing working memory load, our objective is to implement an on-line fNIRS-based inference system that integrates two complementary estimators. The first estimator is a real-time state estimation MACD-based algorithm dedicated to identifying the pilot's instantaneous mental state (not-on-task vs. on-task). It does not require a calibration process to perform its estimation. The second estimator is an on-line SVM-based classifier that is able to discriminate task difficulty (low working memory load vs. high working memory load). These two estimators were tested with 19 pilots who were placed in a realistic flight simulator and were asked to recall air traffic control instructions. We found that the estimated pilot's mental state matched significantly better than chance with the pilot's real state (62% global accuracy, 58% specificity, and 72% sensitivity). The second estimator, dedicated to assessing single trial working memory loads, led to 80% classification accuracy, 72% specificity, and 89% sensitivity. These two estimators establish reusable blocks for further fNIRS-based passive brain computer interface development.

Measuring the self-similarity exponent in Lévy stable processes of financial time series

NASA Astrophysics Data System (ADS)

Fernández-Martínez, M.; Sánchez-Granero, M. A.; Trinidad Segovia, J. E.

2013-11-01

Geometric method-based procedures, which will be called GM algorithms herein, were introduced in [M.A. Sánchez Granero, J.E. Trinidad Segovia, J. García Pérez, Some comments on Hurst exponent and the long memory processes on capital markets, Phys. A 387 (2008) 5543-5551], to efficiently calculate the self-similarity exponent of a time series. In that paper, the authors showed empirically that these algorithms, based on a geometrical approach, are more accurate than the classical algorithms, especially with short length time series. The authors checked that GM algorithms are good when working with (fractional) Brownian motions. Moreover, in [J.E. Trinidad Segovia, M. Fernández-Martínez, M.A. Sánchez-Granero, A note on geometric method-based procedures to calculate the Hurst exponent, Phys. A 391 (2012) 2209-2214], a mathematical background for the validity of such procedures to estimate the self-similarity index of any random process with stationary and self-affine increments was provided. In particular, they proved theoretically that GM algorithms are also valid to explore long-memory in (fractional) Lévy stable motions. In this paper, we prove empirically by Monte Carlo simulation that GM algorithms are able to calculate accurately the self-similarity index in Lévy stable motions and find empirical evidence that they are more precise than the absolute value exponent (denoted by AVE onwards) and the multifractal detrended fluctuation analysis (MF-DFA) algorithms, especially with a short length time series. We also compare them with the generalized Hurst exponent (GHE) algorithm and conclude that both GM2 and GHE algorithms are the most accurate to study financial series. In addition to that, we provide empirical evidence, based on the accuracy of GM algorithms to estimate the self-similarity index in Lévy motions, that the evolution of the stocks of some international market indices, such as U.S. Small Cap and Nasdaq100, cannot be modelized by means of a Brownian motion.

Practicing What Is Preached: Self-Reflections on Memory in a Memory Course

ERIC Educational Resources Information Center

Conrad, Nicole J.

2013-01-01

To apply several principles of memory covered in a first-year university memory course, I developed a series of one-page self-reflection papers on memory that require students to engage with the material in a meaningful way. These short papers cover topics related to memory, and the assignment itself applies these same principles, reinforcing…

FDTD modelling of induced polarization phenomena in transient electromagnetics

NASA Astrophysics Data System (ADS)

Commer, Michael; Petrov, Peter V.; Newman, Gregory A.

2017-04-01

The finite-difference time-domain scheme is augmented in order to treat the modelling of transient electromagnetic signals containing induced polarization effects from 3-D distributions of polarizable media. Compared to the non-dispersive problem, the discrete dispersive Maxwell system contains costly convolution operators. Key components to our solution for highly digitized model meshes are Debye decomposition and composite memory variables. We revert to the popular Cole-Cole model of dispersion to describe the frequency-dependent behaviour of electrical conductivity. Its inversely Laplace-transformed Debye decomposition results in a series of time convolutions between electric field and exponential decay functions, with the latter reflecting each Debye constituents' individual relaxation time. These function types in the discrete-time convolution allow for their substitution by memory variables, annihilating the otherwise prohibitive computing demands. Numerical examples demonstrate the efficiency and practicality of our algorithm.

Generating Dynamic Persistence in the Time Domain

NASA Astrophysics Data System (ADS)

Guerrero, A.; Smith, L. A.; Smith, L. A.; Kaplan, D. T.

2001-12-01

Many dynamical systems present long-range correlations. Physically, these systems vary from biological to economical, including geological or urban systems. Important geophysical candidates for this type of behaviour include weather (or climate) and earthquake sequences. Persistence is characterised by slowly decaying correlation function; that, in theory, never dies out. The Persistence exponent reflects the degree of memory in the system and much effort has been expended creating and analysing methods that successfully estimate this parameter and model data that exhibits persistence. The most widely used methods for generating long correlated time series are not dynamical systems in the time domain, but instead are derived from a given spectral density. Little attention has been drawn to modelling persistence in the time domain. The time domain approach has the advantage that an observation at certain time can be calculated using previous observations which is particularly suitable when investigating the predictability of a long memory process. We will describe two of these methods in the time domain. One is a traditional approach using fractional ARIMA (autoregressive and moving average) models; the second uses a novel approach to extending a given series using random Fourier basis functions. The statistical quality of the two methods is compared, and they are contrasted with weather data which shows, reportedly, persistence. The suitability of this approach both for estimating predictability and for making predictions is discussed.

Simulating Pre-Asymptotic, Non-Fickian Transport Although Doing Simple Random Walks - Supported By Empirical Pore-Scale Velocity Distributions and Memory Effects

NASA Astrophysics Data System (ADS)

Most, S.; Jia, N.; Bijeljic, B.; Nowak, W.

2016-12-01

Pre-asymptotic characteristics are almost ubiquitous when analyzing solute transport processes in porous media. These pre-asymptotic aspects are caused by spatial coherence in the velocity field and by its heterogeneity. For the Lagrangian perspective of particle displacements, the causes of pre-asymptotic, non-Fickian transport are skewed velocity distribution, statistical dependencies between subsequent increments of particle positions (memory) and dependence between the x, y and z-components of particle increments. Valid simulation frameworks should account for these factors. We propose a particle tracking random walk (PTRW) simulation technique that can use empirical pore-space velocity distributions as input, enforces memory between subsequent random walk steps, and considers cross dependence. Thus, it is able to simulate pre-asymptotic non-Fickian transport phenomena. Our PTRW framework contains an advection/dispersion term plus a diffusion term. The advection/dispersion term produces time-series of particle increments from the velocity CDFs. These time series are equipped with memory by enforcing that the CDF values of subsequent velocities change only slightly. The latter is achieved through a random walk on the axis of CDF values between 0 and 1. The virtual diffusion coefficient for that random walk is our only fitting parameter. Cross-dependence can be enforced by constraining the random walk to certain combinations of CDF values between the three velocity components in x, y and z. We will show that this modelling framework is capable of simulating non-Fickian transport by comparison with a pore-scale transport simulation and we analyze the approach to asymptotic behavior.

Complex Rotation Quantum Dynamic Neural Networks (CRQDNN) using Complex Quantum Neuron (CQN): Applications to time series prediction.

PubMed

Cui, Yiqian; Shi, Junyou; Wang, Zili

2015-11-01

Quantum Neural Networks (QNN) models have attracted great attention since it innovates a new neural computing manner based on quantum entanglement. However, the existing QNN models are mainly based on the real quantum operations, and the potential of quantum entanglement is not fully exploited. In this paper, we proposes a novel quantum neuron model called Complex Quantum Neuron (CQN) that realizes a deep quantum entanglement. Also, a novel hybrid networks model Complex Rotation Quantum Dynamic Neural Networks (CRQDNN) is proposed based on Complex Quantum Neuron (CQN). CRQDNN is a three layer model with both CQN and classical neurons. An infinite impulse response (IIR) filter is embedded in the Networks model to enable the memory function to process time series inputs. The Levenberg-Marquardt (LM) algorithm is used for fast parameter learning. The networks model is developed to conduct time series predictions. Two application studies are done in this paper, including the chaotic time series prediction and electronic remaining useful life (RUL) prediction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Stress and Memory: A Selective Review on Recent Developments in the Understanding of Stress Hormone Effects on Memory and Their Clinical Relevance.

PubMed

Wolf, O T; Atsak, P; de Quervain, D J; Roozendaal, B; Wingenfeld, K

2016-08-01

Stress causes a neuroendocrine response cascade, leading to the release of catecholamines and glucocorticoids (GCs). GCs influence learning and memory by acting on mineralocorticoid (MR) and glucocorticoid (GR) receptors. Typically, GCs enhance the consolidation of memory processing at the same time as impairing the retrieval of memory of emotionally arousing experiences. The present selective review addresses four recent developments in this area. First, the role of the endocannabinoid system in mediating the rapid, nongenomic effects of GCs on memory is illustrated in rodents. Subsequently, studies on the impact of the selective stimulation of MRs on different memory processes in humans are summarised. Next, a series of human experiments on the impact of stress or GC treatment on fear extinction and fear reconsolidation is presented. Finally, the clinical relevance of the effects of exogenous GC administration is highlighted by the description of patients with anxiety disorders who demonstrate an enhancement of extinction-based therapies by GC treatment. The review highlights the substantial progress made in our mechanistic understanding of the memory-modulating properties of GCs, as well as their clinical potential. © 2015 British Society for Neuroendocrinology.

The Comparison of Visual Working Memory Representations with Perceptual Inputs

PubMed Central

Hyun, Joo-seok; Woodman, Geoffrey F.; Vogel, Edward K.; Hollingworth, Andrew

2008-01-01

The human visual system can notice differences between memories of previous visual inputs and perceptions of new visual inputs, but the comparison process that detects these differences has not been well characterized. This study tests the hypothesis that differences between the memory of a stimulus array and the perception of a new array are detected in a manner that is analogous to the detection of simple features in visual search tasks. That is, just as the presence of a task-relevant feature in visual search can be detected in parallel, triggering a rapid shift of attention to the object containing the feature, the presence of a memory-percept difference along a task-relevant dimension can be detected in parallel, triggering a rapid shift of attention to the changed object. Supporting evidence was obtained in a series of experiments that examined manual reaction times, saccadic reaction times, and event-related potential latencies. However, these experiments also demonstrated that a slow, limited-capacity process must occur before the observer can make a manual change-detection response. PMID:19653755

Click trains and the rate of information processing: does "speeding up" subjective time make other psychological processes run faster?

PubMed

Jones, Luke A; Allely, Clare S; Wearden, John H

2011-02-01

A series of experiments demonstrated that a 5-s train of clicks that have been shown in previous studies to increase the subjective duration of tones they precede (in a manner consistent with "speeding up" timing processes) could also have an effect on information-processing rate. Experiments used studies of simple and choice reaction time (Experiment 1), or mental arithmetic (Experiment 2). In general, preceding trials by clicks made response times significantly shorter than those for trials without clicks, but white noise had no effects on response times. Experiments 3 and 4 investigated the effects of clicks on performance on memory tasks, using variants of two classic experiments of cognitive psychology: Sperling's (1960) iconic memory task and Loftus, Johnson, and Shimamura's (1985) iconic masking task. In both experiments participants were able to recall or recognize significantly more information from stimuli preceded by clicks than those preceded by silence.

Consolidation and restoration of memory traces in working memory.

PubMed

De Schrijver, Sébastien; Barrouillet, Pierre

2017-10-01

Consolidation is the process through which ephemeral sensory traces are transformed into more stable short-term memory traces. It has been shown that consolidation plays a crucial role in working memory (WM) performance, by strengthening memory traces that then better resist interference and decay. In a recent study, Bayliss, Bogdanovs, and Jarrold (Journal of Memory and Language, 81, 34-50, 2015) argued that this process is separate from the processes known to restore WM traces after degradation, such as attentional refreshing and verbal rehearsal. In the present study, we investigated the relationship between the two types of processes in the context of WM span tasks. Participants were presented with series of letters for serial recall, each letter being followed by four digits for parity judgment. Consolidation opportunity was manipulated by varying the delay between each letter and the first digit to be processed, while opportunities for restoration were manipulated by varying the pace at which the parity task had to be performed (i.e., its cognitive load, or CL). Increasing the time available for either consolidation or restoration resulted in higher WM spans, with some substitutability between the two processes. Accordingly, when consolidation time was added to restoration time in the calculation of CL, the new resulting index, called extended CL, proved a very good predictor of recall performance, a finding also observed when verbal rehearsal was prevented by articulatory suppression. This substitutability between consolidation and restoration suggests that both processes may rely on the same mechanisms.

MULTI-ELECTRODE TUBE PULSE MEMORY CIRCUIT

DOEpatents

Gundlach, J.C.; Reeves, J.B.

1958-05-20

Control circuits are described for pulse memory devices for scalers and the like, and more particularly to a driving or energizing circuit for a polycathode gaseous discharge tube having an elongated anode and a successive series of cathodes spaced opposite the anode along its length. The circuit is so arranged as to utilize an arc discharge between the anode and a cathode to count a series of pulses. Upon application of an input pulse the discharge is made to occur between the anode and the next successive cathode, and an output pulse is produced when a particular subsequent cathode is reached. The circuit means for transfering the discharge by altering the anode potential and potential of the cathodes and interconnecting the cathodes constitutes the novel aspects of the invention. A low response time and reduced number of circuit components are the practical advantages of the described circuit.

Powerful Learning Experiences and Suzuki Music Teachers

ERIC Educational Resources Information Center

Reuning-Hummel, Carrie; Meyer, Allison; Rowland, Gordon

2016-01-01

Powerful Learning Experiences (PLEs) of Suzuki music teachers were examined in this fifth study in a series. The definition of a PLE is: "Experiences that stand out in memory because of their high quality, their impact on one's thoughts and actions over time, and their transfer to a wide range of contexts and circumstances." Ten…

Faster forgetting contributes to impaired spatial memory in the PDAPP mouse: Deficit in memory retrieval associated with increased sensitivity to interference?

PubMed Central

Daumas, Stephanie; Sandin, Johan; Chen, Karen S.; Kobayashi, Dione; Tulloch, Jane; Martin, Stephen J.; Games, Dora; Morris, Richard G.M.

2008-01-01

Two experiments were conducted to investigate the possibility of faster forgetting by PDAPP mice (a well-established model of Alzheimer’s disease as reported by Games and colleagues in an earlier paper). Experiment 1, using mice aged 13–16 mo, confirmed the presence of a deficit in a spatial reference memory task in the water maze by hemizygous PDAPP mice relative to littermate controls. However, after overtraining to a criterion of equivalent navigational performance, a series of memory retention tests revealed faster forgetting in the PDAPP group. Very limited retraining was sufficient to reinstate good memory in both groups, indicating that their faster forgetting may be due to retrieval failure rather than trace decay. In Experiment 2, 6-mo-old PDAPP and controls were required to learn each of a series of spatial locations to criterion with their memory assessed 10 min after learning each location. No memory deficit was apparent in the PDAPP mice initially, but a deficit built up through the series of locations suggestive of increased sensitivity to interference. Faster forgetting and increased interference may each reflect a difficulty in accessing memory traces. This interpretation of one aspect of the cognitive deficit in human mutant APP mice has parallels to deficits observed in patients with Alzheimer’s disease, further supporting the validity of transgenic models of the disease. PMID:18772249

Characterization of exchange rate regimes based on scaling and correlation properties of volatility for ASEAN-5 countries

NASA Astrophysics Data System (ADS)

Muniandy, Sithi V.; Uning, Rosemary

2006-11-01

Foreign currency exchange rate policies of ASEAN member countries have undergone tremendous changes following the 1997 Asian financial crisis. In this paper, we study the fractal and long-memory characteristics in the volatility of five ASEAN founding members’ exchange rates with respect to US dollar. The impact of exchange rate policies implemented by the ASEAN-5 countries on the currency fluctuations during pre-, mid- and post-crisis are briefly discussed. The time series considered are daily price returns, absolute returns and aggregated absolute returns, each partitioned into three segments based on the crisis regimes. These time series are then modeled using fractional Gaussian noise, fractionally integrated ARFIMA (0,d,0) and generalized Cauchy process. The first two stationary models provide the description of long-range dependence through Hurst and fractional differencing parameter, respectively. Meanwhile, the generalized Cauchy process offers independent estimation of fractal dimension and long memory exponent. In comparison, among the three models we found that the generalized Cauchy process showed greater sensitivity to transition of exchange rate regimes that were implemented by ASEAN-5 countries.

Electrochromic conductive polymer fuses for hybrid organic/inorganic semiconductor memories

NASA Astrophysics Data System (ADS)

Möller, Sven; Forrest, Stephen R.; Perlov, Craig; Jackson, Warren; Taussig, Carl

2003-12-01

We demonstrate a nonvolatile, write-once-read-many-times (WORM) memory device employing a hybrid organic/inorganic semiconductor architecture consisting of thin film p-i-n silicon diode on a stainless steel substrate integrated in series with a conductive polymer fuse. The nonlinearity of the silicon diodes enables a passive matrix memory architecture, while the conductive polyethylenedioxythiophene:polystyrene sulfonic acid polymer serves as a reliable switch with fuse-like behavior for data storage. The polymer can be switched at ˜2 μs, resulting in a permanent decrease of conductivity of the memory pixel by up to a factor of 103. The switching mechanism is primarily due to a current and thermally dependent redox reaction in the polymer, limited by the double injection of both holes and electrons. The switched device performance does not degrade after many thousand read cycles in ambient at room temperature. Our results suggest that low cost, organic/inorganic WORM memories are feasible for light weight, high density, robust, and fast archival storage applications.

Verbal overshadowing of visual memories: some things are better left unsaid.

PubMed

Schooler, J W; Engstler-Schooler, T Y

1990-01-01

It is widely believed that verbal processing generally improves memory performance. However, in a series of six experiments, verbalizing the appearance of previously seen visual stimuli impaired subsequent recognition performance. In Experiment 1, subjects viewed a videotape including a salient individual. Later, some subjects described the individual's face. Subjects who verbalized the face performed less well on a subsequent recognition test than control subjects who did not engage in memory verbalization. The results of Experiment 2 replicated those of Experiment 1 and further clarified the effect of memory verbalization by demonstrating that visualization does not impair face recognition. In Experiments 3 and 4 we explored the hypothesis that memory verbalization impairs memory for stimuli that are difficult to put into words. In Experiment 3 memory impairment followed the verbalization of a different visual stimulus: color. In Experiment 4 marginal memory improvement followed the verbalization of a verbal stimulus: a brief spoken statement. In Experiments 5 and 6 the source of verbally induced memory impairment was explored. The results of Experiment 5 suggested that the impairment does not reflect a temporary verbal set, but rather indicates relatively long-lasting memory interference. Finally, Experiment 6 demonstrated that limiting subjects' time to make recognition decisions alleviates the impairment, suggesting that memory verbalization overshadows but does not eradicate the original visual memory. This collection of results is consistent with a recording interference hypothesis: verbalizing a visual memory may produce a verbally biased memory representation that can interfere with the application of the original visual memory.

The accuracy comparison between ARFIMA and singular spectrum analysis for forecasting the sales volume of motorcycle in Indonesia

NASA Astrophysics Data System (ADS)

Sitohang, Yosep Oktavianus; Darmawan, Gumgum

2017-08-01

This research attempts to compare between two forecasting models in time series analysis for predicting the sales volume of motorcycle in Indonesia. The first forecasting model used in this paper is Autoregressive Fractionally Integrated Moving Average (ARFIMA). ARFIMA can handle non-stationary data and has a better performance than ARIMA in forecasting accuracy on long memory data. This is because the fractional difference parameter can explain correlation structure in data that has short memory, long memory, and even both structures simultaneously. The second forecasting model is Singular spectrum analysis (SSA). The advantage of the technique is that it is able to decompose time series data into the classic components i.e. trend, cyclical, seasonal and noise components. This makes the forecasting accuracy of this technique significantly better. Furthermore, SSA is a model-free technique, so it is likely to have a very wide range in its application. Selection of the best model is based on the value of the lowest MAPE. Based on the calculation, it is obtained the best model for ARFIMA is ARFIMA (3, d = 0, 63, 0) with MAPE value of 22.95 percent. For SSA with a window length of 53 and 4 group of reconstructed data, resulting MAPE value of 13.57 percent. Based on these results it is concluded that SSA produces better forecasting accuracy.

Inductive reasoning and implicit memory: evidence from intact and impaired memory systems.

PubMed

Girelli, Luisa; Semenza, Carlo; Delazer, Margarete

2004-01-01

In this study, we modified a classic problem solving task, number series completion, in order to explore the contribution of implicit memory to inductive reasoning. Participants were required to complete number series sharing the same underlying algorithm (e.g., +2), differing in both constituent elements (e.g., 2468 versus 57911) and correct answers (e.g., 10 versus 13). In Experiment 1, reliable priming effects emerged, whether primes and targets were separated by four or ten fillers. Experiment 2 provided direct evidence that the observed facilitation arises at central stages of problem solving, namely the identification of the algorithm and its subsequent extrapolation. The observation of analogous priming effects in a severely amnesic patient strongly supports the hypothesis that the facilitation in number series completion was largely determined by implicit memory processes. These findings demonstrate that the influence of implicit processes extends to higher level cognitive domain such as induction reasoning.

What Do We Really Know about Cognitive Inhibition? Task Demands and Inhibitory Effects across a Range of Memory and Behavioural Tasks

PubMed Central

Noreen, Saima; MacLeod, Malcolm D.

2015-01-01

Our study explores inhibitory control across a range of widely recognised memory and behavioural tasks. Eighty-seven never-depressed participants completed a series of tasks designed to measure inhibitory control in memory and behaviour. Specifically, a variant of the selective retrieval-practice and the Think/No-Think tasks were employed as measures of memory inhibition. The Stroop-Colour Naming and the Go/No-Go tasks were used as measures of behavioural inhibition. Participants completed all 4 tasks. Task presentation order was counterbalanced across 3 separate testing sessions for each participant. Standard inhibitory forgetting effects emerged on both memory tasks but the extent of forgetting across these tasks was not correlated. Furthermore, there was no relationship between memory inhibition tasks and either of the main behavioural inhibition measures. At a time when cognitive inhibition continues to gain acceptance as an explanatory mechanism, our study raises fundamental questions about what we actually know about inhibition and how it is affected by the processing demands of particular inhibitory tasks. PMID:26270470

Deconstructing the effect of self-directed study on episodic memory

PubMed Central

Markant, Douglas; DuBrow, Sarah; Davachi, Lila; Gureckis, Todd M.

2014-01-01

Self-directed learning is often associated with better long-term memory retention, however, the mechanisms that underlie this advantage remain poorly understood. This series of experiments was designed to “deconstruct” the notion of self-directed learning in order to better identify the factors most responsible for these improvements to memory. In particular, we isolate the memory advantage that comes from controlling the content of study episodes from the advantage that comes from controlling the timing of those episodes. Across four experiments, self-directed learning significantly enhanced recognition memory relative to passive observation. However, the advantage for self-directed learning was found to be present even under extremely minimal conditions of volitional control (simply pressing a button when ready to advance to the next item). Our results suggest that improvements to memory following self-directed encoding may be related to the ability to coordinate stimulus presentation with the learner’s current preparatory or attentional state, and highlight the need to consider the range of cognitive control processes involved in and influenced by self-directed study. PMID:24941938

Mnemonic convergence in social networks: The emergent properties of cognition at a collective level

PubMed Central

Coman, Alin; Momennejad, Ida; Drach, Rae D.; Geana, Andra

2016-01-01

The development of shared memories, beliefs, and norms is a fundamental characteristic of human communities. These emergent outcomes are thought to occur owing to a dynamic system of information sharing and memory updating, which fundamentally depends on communication. Here we report results on the formation of collective memories in laboratory-created communities. We manipulated conversational network structure in a series of real-time, computer-mediated interactions in fourteen 10-member communities. The results show that mnemonic convergence, measured as the degree of overlap among community members’ memories, is influenced by both individual-level information-processing phenomena and by the conversational social network structure created during conversational recall. By studying laboratory-created social networks, we show how large-scale social phenomena (i.e., collective memory) can emerge out of microlevel local dynamics (i.e., mnemonic reinforcement and suppression effects). The social-interactionist approach proposed herein points to optimal strategies for spreading information in social networks and provides a framework for measuring and forging collective memories in communities of individuals. PMID:27357678

What Do We Really Know about Cognitive Inhibition? Task Demands and Inhibitory Effects across a Range of Memory and Behavioural Tasks.

PubMed

Noreen, Saima; MacLeod, Malcolm D

2015-01-01

Our study explores inhibitory control across a range of widely recognised memory and behavioural tasks. Eighty-seven never-depressed participants completed a series of tasks designed to measure inhibitory control in memory and behaviour. Specifically, a variant of the selective retrieval-practice and the Think/No-Think tasks were employed as measures of memory inhibition. The Stroop-Colour Naming and the Go/No-Go tasks were used as measures of behavioural inhibition. Participants completed all 4 tasks. Task presentation order was counterbalanced across 3 separate testing sessions for each participant. Standard inhibitory forgetting effects emerged on both memory tasks but the extent of forgetting across these tasks was not correlated. Furthermore, there was no relationship between memory inhibition tasks and either of the main behavioural inhibition measures. At a time when cognitive inhibition continues to gain acceptance as an explanatory mechanism, our study raises fundamental questions about what we actually know about inhibition and how it is affected by the processing demands of particular inhibitory tasks.

GPU-accelerated algorithms for many-particle continuous-time quantum walks

NASA Astrophysics Data System (ADS)

Piccinini, Enrico; Benedetti, Claudia; Siloi, Ilaria; Paris, Matteo G. A.; Bordone, Paolo

2017-06-01

Many-particle continuous-time quantum walks (CTQWs) represent a resource for several tasks in quantum technology, including quantum search algorithms and universal quantum computation. In order to design and implement CTQWs in a realistic scenario, one needs effective simulation tools for Hamiltonians that take into account static noise and fluctuations in the lattice, i.e. Hamiltonians containing stochastic terms. To this aim, we suggest a parallel algorithm based on the Taylor series expansion of the evolution operator, and compare its performances with those of algorithms based on the exact diagonalization of the Hamiltonian or a 4th order Runge-Kutta integration. We prove that both Taylor-series expansion and Runge-Kutta algorithms are reliable and have a low computational cost, the Taylor-series expansion showing the additional advantage of a memory allocation not depending on the precision of calculation. Both algorithms are also highly parallelizable within the SIMT paradigm, and are thus suitable for GPGPU computing. In turn, we have benchmarked 4 NVIDIA GPUs and 3 quad-core Intel CPUs for a 2-particle system over lattices of increasing dimension, showing that the speedup provided by GPU computing, with respect to the OPENMP parallelization, lies in the range between 8x and (more than) 20x, depending on the frequency of post-processing. GPU-accelerated codes thus allow one to overcome concerns about the execution time, and make it possible simulations with many interacting particles on large lattices, with the only limit of the memory available on the device.

Optical signal processing using photonic reservoir computing

NASA Astrophysics Data System (ADS)

Salehi, Mohammad Reza; Dehyadegari, Louiza

2014-10-01

As a new approach to recognition and classification problems, photonic reservoir computing has such advantages as parallel information processing, power efficient and high speed. In this paper, a photonic structure has been proposed for reservoir computing which is investigated using a simple, yet, non-partial noisy time series prediction task. This study includes the application of a suitable topology with self-feedbacks in a network of SOA's - which lends the system a strong memory - and leads to adjusting adequate parameters resulting in perfect recognition accuracy (100%) for noise-free time series, which shows a 3% improvement over previous results. For the classification of noisy time series, the rate of accuracy showed a 4% increase and amounted to 96%. Furthermore, an analytical approach was suggested to solve rate equations which led to a substantial decrease in the simulation time, which is an important parameter in classification of large signals such as speech recognition, and better results came up compared with previous works.

Does Active Memory Capacity Change with Age?

ERIC Educational Resources Information Center

Halford, Graeme S.; And Others

A series of experiments, which used the primary memory paradigm of Wickens et al. (1981, 1985) with university students, adults, and 8- and 9-year-old children, found an increase in primary memory capacity with age. Primary memory differs from secondary memory in that the latter is susceptible to proactive interference, whereas the former is not.…

Real-Time State Estimation in a Flight Simulator Using fNIRS

PubMed Central

Gateau, Thibault; Durantin, Gautier; Lancelot, Francois; Scannella, Sebastien; Dehais, Frederic

2015-01-01

Working memory is a key executive function for flying an aircraft. This function is particularly critical when pilots have to recall series of air traffic control instructions. However, working memory limitations may jeopardize flight safety. Since the functional near-infrared spectroscopy (fNIRS) method seems promising for assessing working memory load, our objective is to implement an on-line fNIRS-based inference system that integrates two complementary estimators. The first estimator is a real-time state estimation MACD-based algorithm dedicated to identifying the pilot’s instantaneous mental state (not-on-task vs. on-task). It does not require a calibration process to perform its estimation. The second estimator is an on-line SVM-based classifier that is able to discriminate task difficulty (low working memory load vs. high working memory load). These two estimators were tested with 19 pilots who were placed in a realistic flight simulator and were asked to recall air traffic control instructions. We found that the estimated pilot’s mental state matched significantly better than chance with the pilot’s real state (62% global accuracy, 58% specificity, and 72% sensitivity). The second estimator, dedicated to assessing single trial working memory loads, led to 80% classification accuracy, 72% specificity, and 89% sensitivity. These two estimators establish reusable blocks for further fNIRS-based passive brain computer interface development. PMID:25816347

Statistical regularities in the return intervals of volatility

NASA Astrophysics Data System (ADS)

Wang, F.; Weber, P.; Yamasaki, K.; Havlin, S.; Stanley, H. E.

2007-01-01

We discuss recent results concerning statistical regularities in the return intervals of volatility in financial markets. In particular, we show how the analysis of volatility return intervals, defined as the time between two volatilities larger than a given threshold, can help to get a better understanding of the behavior of financial time series. We find scaling in the distribution of return intervals for thresholds ranging over a factor of 25, from 0.6 to 15 standard deviations, and also for various time windows from one minute up to 390 min (an entire trading day). Moreover, these results are universal for different stocks, commodities, interest rates as well as currencies. We also analyze the memory in the return intervals which relates to the memory in the volatility and find two scaling regimes, ℓ<ℓ* with α1=0.64±0.02 and ℓ> ℓ* with α2=0.92±0.04; these exponent values are similar to results of Liu et al. for the volatility. As an application, we use the scaling and memory properties of the return intervals to suggest a possibly useful method for estimating risk.

Community detection using Kernel Spectral Clustering with memory

NASA Astrophysics Data System (ADS)

Langone, Rocco; Suykens, Johan A. K.

2013-02-01

This work is related to the problem of community detection in dynamic scenarios, which for instance arises in the segmentation of moving objects, clustering of telephone traffic data, time-series micro-array data etc. A desirable feature of a clustering model which has to capture the evolution of communities over time is the temporal smoothness between clusters in successive time-steps. In this way the model is able to track the long-term trend and in the same time it smooths out short-term variation due to noise. We use the Kernel Spectral Clustering with Memory effect (MKSC) which allows to predict cluster memberships of new nodes via out-of-sample extension and has a proper model selection scheme. It is based on a constrained optimization formulation typical of Least Squares Support Vector Machines (LS-SVM), where the objective function is designed to explicitly incorporate temporal smoothness as a valid prior knowledge. The latter, in fact, allows the model to cluster the current data well and to be consistent with the recent history. Here we propose a generalization of the MKSC model with an arbitrary memory, not only one time-step in the past. The experiments conducted on toy problems confirm our expectations: the more memory we add to the model, the smoother over time are the clustering results. We also compare with the Evolutionary Spectral Clustering (ESC) algorithm which is a state-of-the art method, and we obtain comparable or better results.

Long-term memory of hierarchical relationships in free-living greylag geese.

PubMed

Weiss, Brigitte M; Scheiber, Isabella B R

2013-01-01

Animals may memorise spatial and social information for many months and even years. Here, we investigated long-term memory of hierarchically ordered relationships, where the position of a reward depended on the relationship of a stimulus relative to other stimuli in the hierarchy. Seventeen greylag geese (Anser anser) had been trained on discriminations between successive pairs of five or seven implicitly ordered colours, where the higher ranking colour in each pair was rewarded. Geese were re-tested on the task 2, 6 and 12 months after learning the dyadic colour relationships. They chose the correct colour above chance at all three points in time, whereby performance was better in colour pairs at the beginning or end of the colour series. Nonetheless, they also performed above chance on internal colour pairs, which is indicative of long-term memory for quantitative differences in associative strength and/or for relational information. There were no indications for a decline in performance over time, indicating that geese may remember dyadic relationships for at least 6 months and probably well over 1 year. Furthermore, performance in the memory task was unrelated to the individuals' sex and their performance while initially learning the dyadic colour relationships. We discuss possible functions of this long-term memory in the social domain.

Statistical quantifiers of memory for an analysis of human brain and neuro-system diseases

NASA Astrophysics Data System (ADS)

Demin, S. A.; Yulmetyev, R. M.; Panischev, O. Yu.; Hänggi, Peter

2008-03-01

On the basis of a memory function formalism for correlation functions of time series we investigate statistical memory effects by the use of appropriate spectral and relaxation parameters of measured stochastic data for neuro-system diseases. In particular, we study the dynamics of the walk of a patient who suffers from Parkinson's disease (PD), Huntington's disease (HD), amyotrophic lateral sclerosis (ALS), and compare against the data of healthy people (CO - control group). We employ an analytical method which is able to characterize the stochastic properties of stride-to-stride variations of gait cycle timing. Our results allow us to estimate quantitatively a few human locomotion function abnormalities occurring in the human brain and in the central nervous system (CNS). Particularly, the patient's gait dynamics are characterized by an increased memory behavior together with sizable fluctuations as compared with the locomotion dynamics of healthy patients. Moreover, we complement our findings with peculiar features as detected in phase-space portraits and spectral characteristics for the different data sets (PD, HD, ALS and healthy people). The evaluation of statistical quantifiers of the memory function is shown to provide a useful toolkit which can be put to work to identify various abnormalities of locomotion dynamics. Moreover, it allows one to diagnose qualitatively and quantitatively serious brain and central nervous system diseases.

Storage of feature conjunctions in transient auditory memory.

PubMed

Gomes, H; Bernstein, R; Ritter, W; Vaughan, H G; Miller, J

1997-11-01

The purpose of this study was to determine whether feature conjunctions are stored in transient auditory memory. The mismatch negativity (MMN), an event-related potential that is elicited by stimuli that differ from a series of preceding stimuli, was used in this endeavour. A tone that differed from the preceding series of stimuli in the conjunction of two of its features, both present in preceding stimuli but in different combinations, was found to elicit the MMN. The data are interpreted to indicate that information about the conjunction of features is stored in the memory.

A case of Alzheimer's disease in magmatic crystals

NASA Astrophysics Data System (ADS)

Costa Rodriguez, F.; Bouvet de Maisonneuve, C.

2012-12-01

The reequilibration of chemical zoning in crystals from volcanic rocks is increasingly used to determine the duration of the processes involved in their origin, residence and transport. There now exist a good number of determinations of diffusion coefficients in olivine (Fe-Mg, Mn, Ca, Ni, Cr), plagioclase (CaAl-NaSi, Mg, Sr, Ba, REE), pyroxenes (Fe-Mg, Mn, Ca, REE) and quartz (Ti), but most studies have used a single element or component in a single mineral group. Although this is a good approach, it can only access a limited range of time scales, typically the short-term memory of the crystal. In other words, for process durations that are longer than the combination of the diffusivity and diffusion distance (and for a constant boundary), the long-term memory of the crystal might have been lost. This could explain why most time determinations of magmatic processes from volcanic rocks give times of about < 100 years, and why these are shorter than the thousands of years obtained from U-Th series disequilibrium isotopes. We have done a series of numerical calculations and natural observation to determine the time windows that can be accessed with different elements and minerals, and how they may affect the time scales and interpretations of processes that the crystals might be recording. We have looked at two end-members representative of mafic and silicic magmas by changing the temperature and mineral compositions. 3 dimensional calculations of diffusion reequilibration at the center of a 1 x 0.5 x 0.5 mm crystal and using a constant boundary as first case. We find that for mafic magma and olivine, 90 % of equilibration of Fe-Mg, Mn, and Ni occurs in a few decades, but gradients in Ca and Cr persist for a few thousand years. These results can for example explain the large ranges of Ca and Cr contents at a given Fe/Mg of olivine, and why apparently contradictory times can be obtained from elements with different diffusivities in the same crystal. At the same time these findings also highlight that there is a long-term memory of the crystal that is typically not accessed by current studies. However, unraveling this memory is more complex because it seems unrealistic to assume a constant composition at the boundary for hundreds or thousands of years, and because crystals can be growing and dissolving multiple times. Additional models considering growth and a variable boundary show that a significant part of the memory is lost by multiple changes in concentration being superimposed at the crystal rim. Here we also report a case where accessing the older history of the crystals might be possible by a combination of X-Ray element maps plus multiple element zoning traverses (Fe-Mg, Ca, Mn, Ni, Al, P, Cr) in olivine from Llaima volcano (Chile). Element distributions reveal that the crystals had an early history of fast growth. The delicate structures of P zoning have been used to recognize any crystal dissolution. Cr, Fe-Mg, Ni, Mn are zoned but the times obtained from Cr are 4 x longer than those of the other elements. Our interpretation is that the Cr zoning records the older memory of the crystal since eruption but that of Fe-Mg has lost part of the memory due to multiple changes at the rim or complete homogenization of the crystal. Thus using multiple elements and minerals allow accessing the long and short term memory of the crystals and associated magma.

Self-Regulated Reading in Adulthood

PubMed Central

Stine-Morrow, Elizabeth A. L.; Soederberg Miller, Lisa M.; Gagne, Danielle D.; Hertzog, Christopher

2008-01-01

Younger and older adults read a series of passages of three different genres for an immediate assessment of text memory (measured by recall and true-false questions). Word-by-word reading times were measured and decomposed into components reflecting resource allocation to particular linguistic processes using regression. Allocation to word and textbase processes showed some consistency across the three text types and was predictive of memory performance. Older adults allocated more time to word and textbase processes than the young did, but showed enhanced contextual facilitation. Structural equation modeling showed that greater resource allocation to word processes was required among readers with relatively low working memory spans and poorer verbal ability, and that greater resource allocation to textbase processes was engendered by higher verbal ability. Results are discussed in terms of a model of self-regulated language processing suggesting that older readers may compensate for processing deficiencies through greater reliance on discourse context and on increases in resource allocation that are enabled through growth in crystallized ability. PMID:18361662

Social networks: Evolving graphs with memory dependent edges

NASA Astrophysics Data System (ADS)

Grindrod, Peter; Parsons, Mark

2011-10-01

The plethora of digital communication technologies, and their mass take up, has resulted in a wealth of interest in social network data collection and analysis in recent years. Within many such networks the interactions are transient: thus those networks evolve over time. In this paper we introduce a class of models for such networks using evolving graphs with memory dependent edges, which may appear and disappear according to their recent history. We consider time discrete and time continuous variants of the model. We consider the long term asymptotic behaviour as a function of parameters controlling the memory dependence. In particular we show that such networks may continue evolving forever, or else may quench and become static (containing immortal and/or extinct edges). This depends on the existence or otherwise of certain infinite products and series involving age dependent model parameters. We show how to differentiate between the alternatives based on a finite set of observations. To test these ideas we show how model parameters may be calibrated based on limited samples of time dependent data, and we apply these concepts to three real networks: summary data on mobile phone use from a developing region; online social-business network data from China; and disaggregated mobile phone communications data from a reality mining experiment in the US. In each case we show that there is evidence for memory dependent dynamics, such as that embodied within the class of models proposed here.

Comparative analysis of time-scaling properties about water pH in Poyang Lake Inlet and Outlet on the basis of fractal methods.

PubMed

Shi, K; Liu, C Q; Huang, Z W; Zhang, B; Su, Y

2010-01-01

Detrended fluctuation analysis (DFA) and multifractal methods are applied to the time-scaling properties analysis of water pH series in Poyang Lake Inlet and Outlet in China. The results show that these pH series are characterised by long-term memory and multifractal scaling, and these characteristics have obvious differences between the Lake Inlet and Outlet. The comparison results suggest that monofractal and multifractal parameters can be quantitative dynamical indexes reflecting the capability of anti-acidification of Poyang Lake. Furthermore, we investigated the frequency-size distribution of pH series in Poyang Lake Inlet and Outlet. Our findings suggest that water pH is an example of a self-organised criticality (SOC) process. The results show that it is different SOC behaviours that result in the differences of power-law relations between pH series in Poyang Lake Inlet and Outlet. This work can be helpful to improvement of modelling of lake water quality.

Transfer Failure and Proactive Interference in Short-Term Memory

ERIC Educational Resources Information Center

Ellis, John A.

1977-01-01

Two experiments tested the hypothesis that proactive interference over a series of Brown-Peterson trials results from a combination of the subject's failure to transfer information to a permanent memory state and failure to retrieve information from permanent memory. (Editor)

The Development of Metamemory Monitoring during Retrieval: The Case of Memory Strength and Memory Absence

ERIC Educational Resources Information Center

Ghetti, Simona; Lyons, Kristen E.; Lazzarin, Federica; Cornoldi, Cesare

2008-01-01

This research examined the development of the ability to monitor memory strength and memory absence at retrieval. In two experiments, 7-year-olds, 10-year-olds, and adults enacted and imagined enacting a series of bizarre and common actions. Two weeks later, they completed a memory test in which they were asked to determine whether each action had…

TIME-DOMAIN METHODS FOR DIFFUSIVE TRANSPORT IN SOFT MATTER

PubMed Central

Fricks, John; Yao, Lingxing; Elston, Timothy C.; Gregory Forest, And M.

2015-01-01

Passive microrheology [12] utilizes measurements of noisy, entropic fluctuations (i.e., diffusive properties) of micron-scale spheres in soft matter to infer bulk frequency-dependent loss and storage moduli. Here, we are concerned exclusively with diffusion of Brownian particles in viscoelastic media, for which the Mason-Weitz theoretical-experimental protocol is ideal, and the more challenging inference of bulk viscoelastic moduli is decoupled. The diffusive theory begins with a generalized Langevin equation (GLE) with a memory drag law specified by a kernel [7, 16, 22, 23]. We start with a discrete formulation of the GLE as an autoregressive stochastic process governing microbead paths measured by particle tracking. For the inverse problem (recovery of the memory kernel from experimental data) we apply time series analysis (maximum likelihood estimators via the Kalman filter) directly to bead position data, an alternative to formulas based on mean-squared displacement statistics in frequency space. For direct modeling, we present statistically exact GLE algorithms for individual particle paths as well as statistical correlations for displacement and velocity. Our time-domain methods rest upon a generalization of well-known results for a single-mode exponential kernel [1, 7, 22, 23] to an arbitrary M-mode exponential series, for which the GLE is transformed to a vector Ornstein-Uhlenbeck process. PMID:26412904

Generalized time-dependent Schrödinger equation in two dimensions under constraints

NASA Astrophysics Data System (ADS)

Sandev, Trifce; Petreska, Irina; Lenzi, Ervin K.

2018-01-01

We investigate a generalized two-dimensional time-dependent Schrödinger equation on a comb with a memory kernel. A Dirac delta term is introduced in the Schrödinger equation so that the quantum motion along the x-direction is constrained at y = 0. The wave function is analyzed by using Green's function approach for several forms of the memory kernel, which are of particular interest. Closed form solutions for the cases of Dirac delta and power-law memory kernels in terms of Fox H-function, as well as for a distributed order memory kernel, are obtained. Further, a nonlocal term is also introduced and investigated analytically. It is shown that the solution for such a case can be represented in terms of infinite series in Fox H-functions. Green's functions for each of the considered cases are analyzed and plotted for the most representative ones. Anomalous diffusion signatures are evident from the presence of the power-law tails. The normalized Green's functions obtained in this work are of broader interest, as they are an important ingredient for further calculations and analyses of some interesting effects in the transport properties in low-dimensional heterogeneous media.

The architecture of dynamic reservoir in the echo state network

NASA Astrophysics Data System (ADS)

Cui, Hongyan; Liu, Xiang; Li, Lixiang

2012-09-01

Echo state network (ESN) has recently attracted increasing interests because of its superior capability in modeling nonlinear dynamic systems. In the conventional echo state network model, its dynamic reservoir (DR) has a random and sparse topology, which is far from the real biological neural networks from both structural and functional perspectives. We hereby propose three novel types of echo state networks with new dynamic reservoir topologies based on complex network theory, i.e., with a small-world topology, a scale-free topology, and a mixture of small-world and scale-free topologies, respectively. We then analyze the relationship between the dynamic reservoir structure and its prediction capability. We utilize two commonly used time series to evaluate the prediction performance of the three proposed echo state networks and compare them to the conventional model. We also use independent and identically distributed time series to analyze the short-term memory and prediction precision of these echo state networks. Furthermore, we study the ratio of scale-free topology and the small-world topology in the mixed-topology network, and examine its influence on the performance of the echo state networks. Our simulation results show that the proposed echo state network models have better prediction capabilities, a wider spectral radius, but retain almost the same short-term memory capacity as compared to the conventional echo state network model. We also find that the smaller the ratio of the scale-free topology over the small-world topology, the better the memory capacities.

Detection of long term persistence in time series of the Neuquen River (Argentina)

NASA Astrophysics Data System (ADS)

Seoane, Rafael; Paz González, Antonio

2014-05-01

In the Patagonian region (Argentina), previous hydrometeorological studies that have been developed using general circulation models show variations in annual mean flows. Future climate scenarios obtained from high-resolution models indicate decreases in total annual precipitation, and these scenarios are more important in the Neuquén river basin (23000 km2). The aim of this study was the estimation of long term persistence in the Neuquén River basin (Argentina). The detection of variations in the long range dependence term and long memory of time series was evaluated with the Hurst exponent. We applied rescaled adjusted range analysis (R/S) to time series of River discharges measured from 1903 to 2011 and this time series was divided into two subperiods: the first was from 1903 to 1970 and the second from 1970 to 2011. Results show a small increase in persistence for the second period. Our results are consistent with those obtained by Koch and Markovic (2007), who observed and estimated an increase of the H exponent for the period 1960-2000 in the Elbe River (Germany). References Hurst, H. (1951).Long term storage capacities of reservoirs". Trans. Am. Soc. Civil Engrs., 116:776-808. Koch and Markovic (2007). Evidences for Climate Change in Germany over the 20th Century from the Stochastic Analysis of hydro-meteorological Time Series, MODSIM07, International Congress on Modelling and Simulation, Christchurch, New Zealand.

Dynamical analyses of the time series for three foreign exchange rates

NASA Astrophysics Data System (ADS)

Kim, Sehyun; Kim, Soo Yong; Jung, Jae-Won; Kim, Kyungsik

2012-05-01

In this study, we investigate the multifractal properties of three foreign exchange rates (USD-KRW, USD-JPY, and EUR-USD) that are quoted with different economic scales. We estimate and analyze both the generalized Hurst exponent and the autocorrelation function in three foreign exchange rates. The USD-KRW is shown to have the strongest of the Hurst exponents when compared with the other two foreign exchange rates. In particular, the autocorrelation function of the USD-KRW has the largest memory behavior among three foreign exchange rates. It also exhibits a long-memory property in the first quarter, more than those in the other quarters.

Consistency of Handedness, Regardless of Direction, Predicts Baseline Memory Accuracy and Potential for Memory Enhancement

ERIC Educational Resources Information Center

Lyle, Keith B.; Hanaver-Torrez, Shelley D.; Hacklander, Ryan P.; Edlin, James M.

2012-01-01

Research has shown that consistently right-handed individuals have poorer memory than do inconsistently right- or left-handed individuals under baseline conditions but more reliably exhibit enhanced memory retrieval after making a series of saccadic eye movements. From this it could be that consistent versus inconsistent handedness, regardless of…

Is the Binding of Visual Features in Working Memory Resource-Demanding?

ERIC Educational Resources Information Center

Allen, Richard J.; Baddeley, Alan D.; Hitch, Graham J.

2006-01-01

The episodic buffer component of working memory is assumed to play a role in the binding of features into chunks. A series of experiments compared memory for arrays of colors or shapes with memory for bound combinations of these features. Demanding concurrent verbal tasks were used to investigate the role of general attentional processes,…

Estimation of time-dependent Hurst exponents with variational smoothing and application to forecasting foreign exchange rates

NASA Astrophysics Data System (ADS)

Garcin, Matthieu

2017-10-01

Hurst exponents depict the long memory of a time series. For human-dependent phenomena, as in finance, this feature may vary in the time. It justifies modelling dynamics by multifractional Brownian motions, which are consistent with time-dependent Hurst exponents. We improve the existing literature on estimating time-dependent Hurst exponents by proposing a smooth estimate obtained by variational calculus. This method is very general and not restricted to the sole Hurst framework. It is globally more accurate and easier than other existing non-parametric estimation techniques. Besides, in the field of Hurst exponents, it makes it possible to make forecasts based on the estimated multifractional Brownian motion. The application to high-frequency foreign exchange markets (GBP, CHF, SEK, USD, CAD, AUD, JPY, CNY and SGD, all against EUR) shows significantly good forecasts. When the Hurst exponent is higher than 0.5, what depicts a long-memory feature, the accuracy is higher.

Testing a potential alternative to traditional identification procedures: Reaction time-based concealed information test does not work for lineups with cooperative witnesses.

PubMed

Sauerland, Melanie; Wolfs, Andrea C F; Crans, Samantha; Verschuere, Bruno

2017-11-27

Direct eyewitness identification is widely used, but prone to error. We tested the validity of indirect eyewitness identification decisions using the reaction time-based concealed information test (CIT) for assessing cooperative eyewitnesses' face memory as an alternative to traditional lineup procedures. In a series of five experiments, a total of 401 mock eyewitnesses watched one of 11 different stimulus events that depicted a breach of law. Eyewitness identifications in the CIT were derived from longer reaction times as compared to well-matched foil faces not encountered before. Across the five experiments, the weighted mean effect size d was 0.14 (95% CI 0.08-0.19). The reaction time-based CIT seems unsuited for testing cooperative eyewitnesses' memory for faces. The careful matching of the faces required for a fair lineup or the lack of intent to deceive may have hampered the diagnosticity of the reaction time-based CIT.

Long memory and volatility clustering: Is the empirical evidence consistent across stock markets?

NASA Astrophysics Data System (ADS)

Bentes, Sónia R.; Menezes, Rui; Mendes, Diana A.

2008-06-01

Long memory and volatility clustering are two stylized facts frequently related to financial markets. Traditionally, these phenomena have been studied based on conditionally heteroscedastic models like ARCH, GARCH, IGARCH and FIGARCH, inter alia. One advantage of these models is their ability to capture nonlinear dynamics. Another interesting manner to study the volatility phenomenon is by using measures based on the concept of entropy. In this paper we investigate the long memory and volatility clustering for the SP 500, NASDAQ 100 and Stoxx 50 indexes in order to compare the US and European Markets. Additionally, we compare the results from conditionally heteroscedastic models with those from the entropy measures. In the latter, we examine Shannon entropy, Renyi entropy and Tsallis entropy. The results corroborate the previous evidence of nonlinear dynamics in the time series considered.

The selective disruption of spatial working memory by eye movements

PubMed Central

Postle, Bradley R.; Idzikowski, Christopher; Sala, Sergio Della; Logie, Robert H.; Baddeley, Alan D.

2005-01-01

In the late 1970s/early 1980s, Baddeley and colleagues conducted a series of experiments investigating the role of eye movements in visual working memory. Although only described briefly in a book (Baddeley, 1986), these studies have influenced a remarkable number of empirical and theoretical developments in fields ranging from experimental psychology to human neuropsychology to nonhuman primate electrophysiology. This paper presents, in full detail, three critical studies from this series, together with a recently performed study that includes a level of eye movement measurement and control that was not available for the older studies. Together, the results demonstrate several facts about the sensitivity of visuospatial working memory to eye movements. First, it is eye movement control, not movement per se, that produces the disruptive effects. Second, these effects are limited to working memory for locations, and do not generalize to visual working memory for shapes. Third, they can be isolated to the storage/maintenance components of working memory (e.g., to the delay period of the delayed-recognition task). These facts have important implications for models of visual working memory. PMID:16556561

Memory-Efficient Analysis of Dense Functional Connectomes.

PubMed

Loewe, Kristian; Donohue, Sarah E; Schoenfeld, Mircea A; Kruse, Rudolf; Borgelt, Christian

2016-01-01

The functioning of the human brain relies on the interplay and integration of numerous individual units within a complex network. To identify network configurations characteristic of specific cognitive tasks or mental illnesses, functional connectomes can be constructed based on the assessment of synchronous fMRI activity at separate brain sites, and then analyzed using graph-theoretical concepts. In most previous studies, relatively coarse parcellations of the brain were used to define regions as graphical nodes. Such parcellated connectomes are highly dependent on parcellation quality because regional and functional boundaries need to be relatively consistent for the results to be interpretable. In contrast, dense connectomes are not subject to this limitation, since the parcellation inherent to the data is used to define graphical nodes, also allowing for a more detailed spatial mapping of connectivity patterns. However, dense connectomes are associated with considerable computational demands in terms of both time and memory requirements. The memory required to explicitly store dense connectomes in main memory can render their analysis infeasible, especially when considering high-resolution data or analyses across multiple subjects or conditions. Here, we present an object-based matrix representation that achieves a very low memory footprint by computing matrix elements on demand instead of explicitly storing them. In doing so, memory required for a dense connectome is reduced to the amount needed to store the underlying time series data. Based on theoretical considerations and benchmarks, different matrix object implementations and additional programs (based on available Matlab functions and Matlab-based third-party software) are compared with regard to their computational efficiency. The matrix implementation based on on-demand computations has very low memory requirements, thus enabling analyses that would be otherwise infeasible to conduct due to insufficient memory. An open source software package containing the created programs is available for download.

Memory-Efficient Analysis of Dense Functional Connectomes

PubMed Central

Loewe, Kristian; Donohue, Sarah E.; Schoenfeld, Mircea A.; Kruse, Rudolf; Borgelt, Christian

2016-01-01

The functioning of the human brain relies on the interplay and integration of numerous individual units within a complex network. To identify network configurations characteristic of specific cognitive tasks or mental illnesses, functional connectomes can be constructed based on the assessment of synchronous fMRI activity at separate brain sites, and then analyzed using graph-theoretical concepts. In most previous studies, relatively coarse parcellations of the brain were used to define regions as graphical nodes. Such parcellated connectomes are highly dependent on parcellation quality because regional and functional boundaries need to be relatively consistent for the results to be interpretable. In contrast, dense connectomes are not subject to this limitation, since the parcellation inherent to the data is used to define graphical nodes, also allowing for a more detailed spatial mapping of connectivity patterns. However, dense connectomes are associated with considerable computational demands in terms of both time and memory requirements. The memory required to explicitly store dense connectomes in main memory can render their analysis infeasible, especially when considering high-resolution data or analyses across multiple subjects or conditions. Here, we present an object-based matrix representation that achieves a very low memory footprint by computing matrix elements on demand instead of explicitly storing them. In doing so, memory required for a dense connectome is reduced to the amount needed to store the underlying time series data. Based on theoretical considerations and benchmarks, different matrix object implementations and additional programs (based on available Matlab functions and Matlab-based third-party software) are compared with regard to their computational efficiency. The matrix implementation based on on-demand computations has very low memory requirements, thus enabling analyses that would be otherwise infeasible to conduct due to insufficient memory. An open source software package containing the created programs is available for download. PMID:27965565

Perceptual Organization and Operative Thought: A Study of Coherence in Memory.

ERIC Educational Resources Information Center

Heindel, Patricia; Kose, Gary

Examined in three studies were the influence of perceptual organization on children's memory and the relationship between operational thought and memory performance. In the first study, 72 children at 5, 7, and 9 years of age were given a series of Piagetian tasks and a memory task. Subjects were presented with 10 color-shape pairs depicted in…

Short-term Memory as a Processing Shift

ERIC Educational Resources Information Center

Lewis-Smith, Marion Quinn

1975-01-01

The series of experiments described here examined the predictions for free recall from sequential models and the shift formulation, focusing on the roles of short- and long-term memory in the primacy/recency shift and on the effects of expectancies on short- and long-term memory. (Author/RK)

Transition from Target to Gaze Coding in Primate Frontal Eye Field during Memory Delay and Memory–Motor Transformation123

PubMed Central

Sajad, Amirsaman; Sadeh, Morteza; Yan, Xiaogang; Wang, Hongying

2016-01-01

Abstract The frontal eye fields (FEFs) participate in both working memory and sensorimotor transformations for saccades, but their role in integrating these functions through time remains unclear. Here, we tracked FEF spatial codes through time using a novel analytic method applied to the classic memory-delay saccade task. Three-dimensional recordings of head-unrestrained gaze shifts were made in two monkeys trained to make gaze shifts toward briefly flashed targets after a variable delay (450-1500 ms). A preliminary analysis of visual and motor response fields in 74 FEF neurons eliminated most potential models for spatial coding at the neuron population level, as in our previous study (Sajad et al., 2015). We then focused on the spatiotemporal transition from an eye-centered target code (T; preferred in the visual response) to an eye-centered intended gaze position code (G; preferred in the movement response) during the memory delay interval. We treated neural population codes as a continuous spatiotemporal variable by dividing the space spanning T and G into intermediate T–G models and dividing the task into discrete steps through time. We found that FEF delay activity, especially in visuomovement cells, progressively transitions from T through intermediate T–G codes that approach, but do not reach, G. This was followed by a final discrete transition from these intermediate T–G delay codes to a “pure” G code in movement cells without delay activity. These results demonstrate that FEF activity undergoes a series of sensory–memory–motor transformations, including a dynamically evolving spatial memory signal and an imperfect memory-to-motor transformation. PMID:27092335

Malware Memory Analysis for Non-specialists: Investigating Publicly Available Memory Image for the Tigger Trojan Horse

DTIC Science & Technology

2014-06-01

Malware memory analysis for non-specialists Investigating publicly available memory image for the Tigger Trojan horse R...It examines a memory image infected with the Tigger/Syzor Trojan horse . Significance to defence and security Canadian Armed Forces (CAF...additional guidance. The first report written by the author in this series examined the Zeus Trojan horse , found in DRDC Valcartier TM 2013-018 308H[1

The application of computational mechanics to the analysis of natural data: An example in geomagnetism.

NASA Astrophysics Data System (ADS)

Watkins, Nicholas; Clarke, Richard; Freeman, Mervyn

2002-11-01

We discuss how the ideal formalism of Computational Mechanics can be adapted to apply to a non-infinite series of corrupted and correlated data, that is typical of most observed natural time series. Specifically, a simple filter that removes the corruption that creates rare unphysical causal states is demonstrated, and the new concept of effective soficity is introduced. The benefits of these new concepts are demonstrated on simulated time series by (a) the effective elimination of white noise corruption from a periodic signal using the expletive filter and (b) the appearance of an effectively sofic region in the statistical complexity of a biased Poisson switch time series that is insensitive to changes in the word length (memory) used in the analysis. The new algorithm is then applied to analysis of a real geomagnetic time series measured at Halley, Antarctica. Two principal components in the structure are detected that are interpreted as the diurnal variation due to the rotation of the earth-based station under an electrical current pattern that is fixed with respect to the sun-earth axis and the random occurrence of a signature likely to be that of the magnetic substorm. In conclusion, a hypothesis is advanced about model construction in general (see also Clarke et al; arXiv::cond-mat/0110228).

The time to remember: Temporal compression and duration judgements in memory for real-life events.

PubMed

Jeunehomme, Olivier; D'Argembeau, Arnaud

2018-05-01

Recent studies suggest that the continuous flow of information that constitutes daily life events is temporally compressed in episodic memory, yet the characteristics and determinants of this compression mechanism remain unclear. This study examined this question using an experimental paradigm incorporating wearable camera technology. Participants experienced a series of real-life events and were later asked to mentally replay various event sequences that were cued by pictures taken during the original events. Estimates of temporal compression (the ratio of the time needed to mentally re-experience an event to the actual event duration) showed that events were replayed, on average, about eight times faster than the original experiences. This compression mechanism seemed to operate by representing events as a succession of moments or slices of prior experience separated by temporal discontinuities. Importantly, however, rates of temporal compression were not constant and were lower for events involving goal-directed actions. The results also showed that the perceived duration of events increased with the density of recalled moments of prior experience. Taken together, these data extend our understanding of the mechanisms underlying the temporal compression and perceived duration of real-life events in episodic memory.

Selective Postevent Review and Children's Memory for Nonreviewed Materials

ERIC Educational Resources Information Center

Conroy, R.; Salmon, K.

2005-01-01

Two experiments investigated the impact of selective postevent questioning on children's memory for nonreviewed materials. In both experiments, children participated in a series of novel activities. Children in the selective-review condition were subsequently questioned about half of these and comparisons were made to memory in a no-review…

Listeners Remember Music They Like

ERIC Educational Resources Information Center

Stalinski, Stephanie M.; Schellenberg, E. Glenn

2013-01-01

Emotions have important and powerful effects on cognitive processes. Although it is well established that memory influences liking, we sought to document whether liking influences memory. A series of 6 experiments examined whether liking is related to recognition memory for novel music excerpts. In the general method, participants listened to a…

Working Memory and Binding in Sentence Recall

ERIC Educational Resources Information Center

Baddeley, A. D.; Hitch, G. J.; Allen, R. J.

2009-01-01

A series of experiments explored whether chunking in short-term memory for verbal materials depends on attentionally limited executive processes. Secondary tasks were used to disrupt components of working memory and chunking was indexed by the sentence superiority effect, whereby immediate recall is better for sentences than word lists. To…

Memory Analysis of the KBeast Linux Rootkit: Investigating Publicly Available Linux Rootkit Using the Volatility Memory Analysis Framework

DTIC Science & Technology

2015-06-01

examine how a computer forensic investigator/incident handler, without specialised computer memory or software reverse engineering skills , can successfully...memory images and malware, this new series of reports will be directed at those who must analyse Linux malware-infected memory images. The skills ...disable 1287 1000 1000 /usr/lib/policykit-1-gnome/polkit-gnome-authentication- agent-1 1310 1000 1000 /usr/lib/pulseaudio/pulse/gconf- helper 1350

Study of memory effects in international market indices

NASA Astrophysics Data System (ADS)

Mariani, M. C.; Florescu, I.; Beccar Varela, M. P.; Ncheuguim, E.

2010-04-01

Long term memory effects in stock market indices that represent internationally diversified stocks are analyzed in this paper and the results are compared with the S&P 500 index. The Hurst exponent and the Detrended fluctuation analysis (DFA) technique are the tools used for this analysis. The financial time-series data of these indices are tested with the Normalized Truncated Levy Flight to check whether the evolution of these indices is explained by the TLF. Some features that seem to be specific for international indices are discovered and briefly discussed. In particular, a potential investor seems to be faced with new investment opportunities in emerging markets during and especially after a crisis.

Memory is relevant in the symmetric phase of the minority game

NASA Astrophysics Data System (ADS)

Ho, K. H.; Man, W. C.; Chow, F. K.; Chau, H. F.

2005-06-01

Minority game is a simple-mined econophysical model capturing the cooperative behavior among selfish players. Previous investigations, which were based on numerical simulations up to about 100 players for a certain parameter α in the range 0.1≲α≲1 , suggested that memory is irrelevant to the cooperative behavior of the minority game in the so-called symmetric phase. Here using a large scale numerical simulation up to about 3000 players in the parameter range 0.01≲α≲1 , we show that the mean variance of the attendance in the minority game actually depends on the memory in the symmetric phase. We explain such dependence in the framework of crowd-anticrowd theory. Our findings conclude that one should not overlook the feedback mechanism buried under the correlation in the history time series in the study of minority game.

The consentaneous model of the financial markets exhibiting spurious nature of long-range memory

NASA Astrophysics Data System (ADS)

Gontis, V.; Kononovicius, A.

2018-09-01

It is widely accepted that there is strong persistence in the volatility of financial time series. The origin of the observed persistence, or long-range memory, is still an open problem as the observed phenomenon could be a spurious effect. Earlier we have proposed the consentaneous model of the financial markets based on the non-linear stochastic differential equations. The consentaneous model successfully reproduces empirical probability and power spectral densities of volatility. This approach is qualitatively different from models built using fractional Brownian motion. In this contribution we investigate burst and inter-burst duration statistics of volatility in the financial markets employing the consentaneous model. Our analysis provides an evidence that empirical statistical properties of burst and inter-burst duration can be explained by non-linear stochastic differential equations driving the volatility in the financial markets. This serves as an strong argument that long-range memory in finance can have spurious nature.

A phenomenological model for simulating the chemo-responsive shape memory effect in polymers undergoing a permeation transition

NASA Astrophysics Data System (ADS)

Lu, Haibao; Huang, Wei Min; Leng, Jinsong

2014-04-01

We present a phenomenological model for studying the constitutive relations and working mechanism of the chemo-responsive shape memory effect (SME) in shape memory polymers (SMPs). On the basis of the solubility parameter equation, diffusion model and permeation transition model, a phenomenological model is derived for quantitatively identifying the influential factors in the chemically induced SME in SMPs. After this, a permeability parallel model and series model are implemented in order to couple the constitutive relations of the permeability coefficient, stress and relaxation time as a function of stretch, separately. The inductive effect of the permeability transition on the transition temperature is confirmed as the driving force for the chemo-responsive SME. Furthermore, the analytical result from the phenomenological model is compared with the available experimental results and the simulation of a semi-empirical model reported in the literature for verification.

Direct Detection of Hardly Detectable Hidden Chirality of Hydrocarbons and Deuterated Isotopomers by a Helical Polyacetylene through Chiral Amplification and Memory.

PubMed

Maeda, Katsuhiro; Hirose, Daisuke; Okoshi, Natsuki; Shimomura, Kouhei; Wada, Yuya; Ikai, Tomoyuki; Kanoh, Shigeyoshi; Yashima, Eiji

2018-03-07

We report the first direct chirality sensing of a series of chiral hydrocarbons and isotopically chiral compounds (deuterated isotopomers), which are almost impossible to detect by conventional optical spectroscopic methods, by a stereoregular polyacetylene bearing 2,2'-biphenol-derived pendants. The polyacetylene showed a circular dichroism due to a preferred-handed helix formation in response to the hardly detectable hidden chirality of saturated tertiary or chiroptical quaternary hydrocarbons, and deuterated isotopomers. In sharp contrast to the previously reported sensory systems, the chirality detection by the polyacetylene relies on an excess one-handed helix formation induced by the chiral hydrocarbons and deuterated isotopomers via significant amplification of the chirality followed by its static memory, through which chiral information on the minute and hidden chirality can be stored as an excess of a single-handed helix memory for a long time.

Simple Deterministically Constructed Recurrent Neural Networks

NASA Astrophysics Data System (ADS)

Rodan, Ali; Tiňo, Peter

A large number of models for time series processing, forecasting or modeling follows a state-space formulation. Models in the specific class of state-space approaches, referred to as Reservoir Computing, fix their state-transition function. The state space with the associated state transition structure forms a reservoir, which is supposed to be sufficiently complex so as to capture a large number of features of the input stream that can be potentially exploited by the reservoir-to-output readout mapping. The largely "black box" character of reservoirs prevents us from performing a deeper theoretical investigation of the dynamical properties of successful reservoirs. Reservoir construction is largely driven by a series of (more-or-less) ad-hoc randomized model building stages, with both the researchers and practitioners having to rely on a series of trials and errors. We show that a very simple deterministically constructed reservoir with simple cycle topology gives performances comparable to those of the Echo State Network (ESN) on a number of time series benchmarks. Moreover, we argue that the memory capacity of such a model can be made arbitrarily close to the proved theoretical limit.

Fractionating nonword repetition: The contributions of short-term memory and oromotor praxis are different

PubMed Central

Alcock, Katherine J.; Carey, Daniel; Bergström, Lina; Karmiloff-Smith, Annette; Dick, Frederic

2017-01-01

The ability to reproduce novel words is a sensitive marker of language impairment across a variety of developmental disorders. Nonword repetition tasks are thought to reflect phonological short-term memory skills. Yet, when children hear and then utter a word for the first time, they must transform a novel speech signal into a series of coordinated, precisely timed oral movements. Little is known about how children’s oromotor speed, planning and co-ordination abilities might influence their ability to repeat novel nonwords, beyond the influence of higher-level cognitive and linguistic skills. In the present study, we tested 35 typically developing children between the ages of 5−8 years on measures of nonword repetition, digit span, memory for non-verbal sequences, reading fluency, oromotor praxis, and oral diadochokinesis. We found that oromotor praxis uniquely predicted nonword repetition ability in school-age children, and that the variance it accounted for was additional to that of digit span, memory for non-verbal sequences, articulatory rate (measured by oral diadochokinesis) as well as reading fluency. We conclude that the ability to compute and execute novel sensorimotor transformations affects the production of novel words. These results have important implications for understanding motor/language relations in neurodevelopmental disorders. PMID:28704379

Distinct Patterns of Neural Activity during Memory Formation of Nonwords versus Words

PubMed Central

Otten, Leun J.; Sveen, Josefin; Quayle, Angela H.

2008-01-01

Research into the neural underpinnings of memory formation has focused on the encoding of familiar verbal information. Here, we address how the brain supports the encoding of novel information that does not have meaning. Electrical brain activity was recorded from the scalps of healthy young adults while they performed an incidental encoding task (syllable judgments) on separate series of words and ‘nonwords’ (nonsense letter strings that are orthographically legal and pronounceable). Memory for the items was then probed with a recognition memory test. For words as well as nonwords, event-related potentials differed depending on whether an item would subsequently be remembered or forgotten. However, the polarity and timing of the effect varied across item type. For words, subsequently remembered items showed the usually observed positive-going, frontally-distributed modulation from around 600 ms after word onset. For nonwords, by contrast, a negative-going, spatially widespread modulation predicted encoding success from 1000 ms onwards. Nonwords also showed a modulation shortly after item onset. These findings imply that the brain supports the encoding of familiar and unfamiliar letter strings in qualitatively different ways, including the engagement of distinct neural activity at different points in time. The processing of semantic attributes plays an important role in the encoding of words and the associated positive frontal modulation. PMID:17958481

Hydrogen-peroxide-modified egg albumen for transparent and flexible resistive switching memory

NASA Astrophysics Data System (ADS)

Zhou, Guangdong; Yao, Yanqing; Lu, Zhisong; Yang, Xiude; Han, Juanjuan; Wang, Gang; Rao, Xi; Li, Ping; Liu, Qian; Song, Qunliang

2017-10-01

Egg albumen is modified by hydrogen peroxide with concentrations of 5%, 10%, 15% and 30% at room temperature. Compared with devices without modification, a memory cell of Ag/10% H2O2-egg albumen/indium tin oxide exhibits obviously enhanced resistive switching memory behavior with a resistance ratio of 104, self-healing switching endurance for 900 cycles and a prolonged retention time for a 104 s @ 200 mV reading voltage after being bent 103 times. The breakage of massive protein chains occurs followed by the recombination of new protein chain networks due to the oxidation of amidogen and the synthesis of disulfide during the hydrogen peroxide modifying egg albumen. Ions such as Fe3+, Na+, K+, which are surrounded by protein chains, are exposed to the outside of protein chains to generate a series of traps during the egg albumen degeneration process. According to the fitting results of the double logarithm I-V curves and the current-sensing atomic force microscopy (CS-AFM) images of the ON and OFF states, the charge transfer from one trap center to its neighboring trap center is responsible for the resistive switching memory phenomena. The results of our work indicate that hydrogen- peroxide-modified egg albumen could open up a new avenue of biomaterial application in nanoelectronic systems.

Visual feature binding in younger and older adults: encoding and suffix interference effects.

PubMed

Brown, Louise A; Niven, Elaine H; Logie, Robert H; Rhodes, Stephen; Allen, Richard J

2017-02-01

Three experiments investigated younger (18-25 yrs) and older (70-88 yrs) adults' temporary memory for colour-shape combinations (binding). We focused upon estimating the magnitude of the binding cost for each age group across encoding time (Experiment 1; 900/1500 ms), presentation format (Experiment 2; simultaneous/sequential), and interference (Experiment 3; control/suffix) conditions. In Experiment 1, encoding time did not differentially influence binding in the two age groups. In Experiment 2, younger adults exhibited poorer binding performance with sequential relative to simultaneous presentation, and serial position analyses highlighted a particular age-related difficulty remembering the middle item of a series (for all memory conditions). Experiments 1-3 demonstrated small to medium binding effect sizes in older adults across all encoding conditions, with binding less accurate than shape memory. However, younger adults also displayed negative effects of binding (small to large) in two of the experiments. Even when older adults exhibited a greater suffix interference effect in Experiment 3, this was for all memory types, not just binding. We therefore conclude that there is no consistent evidence for a visual binding deficit in healthy older adults. This relative preservation contrasts with the specific and substantial deficits in visual feature binding found in several recent studies of Alzheimer's disease.

The effectiveness of cognitive behavioral therapy with respect to psychological symptoms and recovering autobiographical memory in patients suffering from post-traumatic stress disorder

PubMed Central

Akbarian, Fatemehsadat; Bajoghli, Hafez; Haghighi, Mohammad; Kalak, Nadeem; Holsboer-Trachsler, Edith; Brand, Serge

2015-01-01

Objectives Given the persistence of post-traumatic stress disorder (PTSD) and its major impact on everyday life, it is important to identify effective treatments. In additional to pharmacological treatments, psychotherapeutic treatments are also highly effective. The aim of the present study was to investigate, among a sample of patients suffering from PTSD, the influence of an additional cognitive behavioral therapy (CBT) intervention on their symptoms of PTSD, depression, and anxiety, and on autobiographical memory. Methods A total of 40 patients suffering from PTSD (mean age: 31.64 years; 78.6% female patients) and under psychopharmacological treatment were randomly assigned to an intervention or control condition. The intervention consisted of ten group sessions (one 60–90 minute session per week) of CBT. At baseline and 10 weeks later, a series of self-rating and experts’-rating questionnaires were completed. Results Over time, symptoms of PTSD, depression, and anxiety decreased; however, greater improvement was observed in the experimental than the control condition. Likewise, as a general pattern of results, memory performance improved over time, though again this improvement was greater in the experimental condition. Conclusion Compared to a control condition, additional CBT improves the treatment of PTSD, with respect to both symptoms and autobiographical memory. PMID:25737635

The Effects of Previously Acquired Knowledge on Memory for Textual Information.

ERIC Educational Resources Information Center

Byrd, Mark

1987-01-01

Presented series of biographical passages to young and older adults to examine how semantic memory store of previously acquired knowledge affects ability to retain textual information. Older adults had difficulty in delayed, but not in immediate, recognition condition. Suggests that as older adults' episodic memory deteriorated, they could not…

Children's Eyewitness Memory for Multiple Real-Life Events

ERIC Educational Resources Information Center

Odegard, Timothy N.; Cooper, Crystal M.; Lampinen, James M.; Reyna, Valerie F.; Brainerd, Charles J.

2009-01-01

The present research examined the influence of prior knowledge on children's free recall, cued recall, recognition memory, and source memory judgments for a series of similar real-life events. Forty children (5-12 years old) attended 4 thematic birthday parties and were later interviewed about the events that transpired during the parties using…

Fact Retrieval Processes in Human Memory. Psychology and Education Series Technical Report No. 252.

ERIC Educational Resources Information Center

Wescourt, Keith T.; Atkinson, Richard C.

A major contribution of information-processing theory to the psychology of remembering is the concept of memory or information retrieval. Several theories of the fact retrieval processes of the human memory, which constitute a substrate for any cognitive ability requiring stored information, have drawn heavily on certain data processing…

Tone Series and the Nature of Working Memory Capacity Development

ERIC Educational Resources Information Center

Clark, Katherine M.; Hardman, Kyle O.; Schachtman, Todd R.; Saults, J. Scott; Glass, Bret A.; Cowan, Nelson

2018-01-01

Recent advances in understanding visual working memory, the limited information held in mind for use in ongoing processing, are extended here to examine auditory working memory development. Research with arrays of visual objects has shown how to distinguish the capacity, in terms of the "number" of objects retained, from the…

Declarative Memory Consolidation: Mechanisms Acting during Human Sleep

ERIC Educational Resources Information Center

Gais, Steffen; Born, Jan

2004-01-01

Of late, an increasing number of studies have shown a strong relationship between sleep and memory. Here we summarize a series of our own studies in humans supporting a beneficial influence of slow-wave sleep (SWS) on declarative memory formation, and try to identify some mechanisms that might underlie this influence. Specifically, these…

Individualized Theory of Mind (iToM): When Memory Modulates Empathy

PubMed Central

Ciaramelli, Elisa; Bernardi, Francesco; Moscovitch, Morris

2013-01-01

Functional neuroimaging studies have noted that brain regions supporting theory of mind (ToM) overlap remarkably with those underlying episodic memory, suggesting a link between the two processes. The present study shows that memory for others’ past experiences modulates significantly our appraisal of, and reaction to, what is happening to them currently. Participants read the life story of two characters; one had experienced a long series of love-related failures, the other a long series of work-related failures. In a later faux pas recognition task, participants reported more empathy for the character unlucky in love in love-related faux pas scenarios, and for the character unlucky at work in work-related faux pas scenarios. The memory-based modulation of empathy correlated with the number of details remembered from the characters’ life story. These results suggest that individuals use memory for other people’s past experiences to simulate how they feel in similar situations they are currently facing. The integration of ToM and memory processes allows adjusting mental state inferences to fit unique social targets, constructing an individualized ToM. PMID:23378839

Short-term memory predictions across the lifespan: monitoring span before and after conducting a task.

PubMed

Bertrand, Julie Marilyne; Moulin, Chris John Anthony; Souchay, Céline

2017-05-01

Our objective was to explore metamemory in short-term memory across the lifespan. Five age groups participated in this study: 3 groups of children (4-13 years old), and younger and older adults. We used a three-phase task: prediction-span-postdiction. For prediction and postdiction phases, participants reported with a Yes/No response if they could recall in order a series of images. For the span task, they had to actually recall such series. From 4 years old, children have some ability to monitor their short-term memory and are able to adjust their prediction after experiencing the task. However, accuracy still improves significantly until adolescence. Although the older adults had a lower span, they were as accurate as young adults in their evaluation, suggesting that metamemory is unimpaired for short-term memory tasks in older adults. •We investigate metamemory for short-term memory tasks across the lifespan. •We find younger children cannot accurately predict their span length. •Older adults are accurate in predicting their span length. •People's metamemory accuracy was related to their short-term memory span.

The relationship between processing style, trauma memory processes, and the development of posttraumatic stress symptoms in children and adolescents.

PubMed

McKinnon, Anna; Brewer, Neil; Cameron, Kate; Nixon, Reginald D V

2017-12-01

Data-driven processing, peri-event fear, and trauma memory characteristics are hypothesised to play a core role in the development of Posttraumatic Stress Disorder. We assessed the relationships between these characteristics and Posttraumatic Stress (PTS) symptoms in a sample of youth. Study 1 (N = 36, 7-16 years), involved a sample of children who had undergone a stressful orthopaedic procedure. One week later they answered a series of probed recall questions about the trauma (assessed for accuracy by comparison to a video) and reported on their PTS symptoms. They also rated confidence in their probed recall answers to assess meta-cognitive monitoring of their memory for the trauma. In Study 2, a sample of injured children (N = 57, 7-16 years) were assessed within 1-month of a visit to an Emergency Department, and then at 3-month follow-up. They answered probed recall questions, made confidence ratings, and completed measures of data-driven processing, peri-event fear, PTS and associated psychopathology. Memories were verified using witness accounts. Studies 1 and 2 did not find an association between PTS symptoms and trauma memory accuracy or confidence. In Studies 1 and 2 data-driven processing predicted PTS symptoms. The studies had modest samples sizes and there were ceiling effects for some accuracy and confidence items. Data-driven processing at the time of a trauma was associated with PTS symptoms after accounting for fear at the time of the trauma. Accuracy of recall for trauma memories was not significantly related to PTS symptoms. No decisive conclusion could be drawn regarding the relation between confidence in trauma memories and PTS symptoms. Copyright © 2017 Elsevier Ltd. All rights reserved.

The effect of nabilone on neuropsychological functions related to driving ability: an extended case series.

PubMed

Kurzthaler, Ilsemarie; Bodner, Thomas; Kemmler, Georg; Entner, Tanja; Wissel, Joerg; Berger, Thomas; Fleischhacker, W Wolfgang

2005-06-01

The primary goal of this prospective extended case series was to obtain the first data about the potential influence of nabilone intake on driving ability related neuropsychological functions. Six patients were investigated within a placebo controlled, double-blind crossover study of this synthetic cannabinoid (2 mg/day) in patients with multiple sclerosis and spasticity associated pain. Five neuropsychological functions (reaction time, working memory, divided attention, psychomotor speed and mental flexibility) were assessed. No indication was found of a deterioration of any of the five investigated neuropsychological functions during the 4-week treatment period with nabilone. Copyright 2005 John Wiley & Sons, Ltd.

Working memory capacity and the functional connectome - insights from resting-state fMRI and voxelwise centrality mapping.

PubMed

Markett, Sebastian; Reuter, Martin; Heeren, Behrend; Lachmann, Bernd; Weber, Bernd; Montag, Christian

2018-02-01

The functional connectome represents a comprehensive network map of functional connectivity throughout the human brain. To date, the relationship between the organization of functional connectivity and cognitive performance measures is still poorly understood. In the present study we use resting-state functional magnetic resonance imaging (fMRI) data to explore the link between the functional connectome and working memory capacity in an individual differences design. Working memory capacity, which refers to the maximum amount of context information that an individual can retain in the absence of external stimulation, was assessed outside the MRI scanner and estimated based on behavioral data from a change detection task. Resting-state time series were analyzed by means of voxelwise degree and eigenvector centrality mapping, which are data-driven network analytic approaches for the characterization of functional connectivity. We found working memory capacity to be inversely correlated with both centrality in the right intraparietal sulcus. Exploratory analyses revealed that this relationship was putatively driven by an increase in negative connectivity strength of the structure. This resting-state connectivity finding fits previous task based activation studies that have shown that this area responds to manipulations of working memory load.

Executive function deficits in short-term abstinent cannabis users.

PubMed

McHale, Sue; Hunt, Nigel

2008-07-01

Few cognitive tasks are adequately sensitive to show the small decrements in performance in abstinent chronic cannabis users. In this series of three experiments we set out to demonstrate a variety of tasks that are sufficiently sensitive to show differences in visual memory, verbal memory, everyday memory and executive function between controls and cannabis users. A series of three studies explored cognitive function deficits in cannabis users (phonemic verbal fluency, visual recognition and immediate and delayed recall, and prospective memory) in short-term abstinent cannabis users. Participants were selected using snowball sampling, with cannabis users being compared to a standard control group and a tobacco-use control group. The cannabis users, compared to both control groups, had deficits on verbal fluency, visual recognition, delayed visual recall, and short- and long-interval prospective memory. There were no differences for immediate visual recall. These findings suggest that cannabis use leads to impaired executive function. Further research needs to explore the longer term impact of cannabis use. Copyright 2008 John Wiley & Sons, Ltd.

Network Analyses for Space-Time High Frequency Wind Data

NASA Astrophysics Data System (ADS)

Laib, Mohamed; Kanevski, Mikhail

2017-04-01

Recently, network science has shown an important contribution to the analysis, modelling and visualization of complex time series. Numerous existing methods have been proposed for constructing networks. This work studies spatio-temporal wind data by using networks based on the Granger causality test. Furthermore, a visual comparison is carried out with several frequencies of data and different size of moving window. The main attention is paid to the temporal evolution of connectivity intensity. The Hurst exponent is applied on the provided time series in order to explore if there is a long connectivity memory. The results explore the space time structure of wind data and can be applied to other environmental data. The used dataset presents a challenging case study. It consists of high frequency (10 minutes) wind data from 120 measuring stations in Switzerland, for a time period of 2012-2013. The distribution of stations covers different geomorphological zones and elevation levels. The results are compared with the Person correlation network as well.

Long memory in patterns of mobile phone usage

NASA Astrophysics Data System (ADS)

Owczarczuk, Marcin

2012-02-01

In this article we show that usage of a mobile phone, i.e. daily series of number of calls made by a customer, exhibits long memory. We use a sample of 4502 postpaid users from a Polish mobile operator and study their two-year billing history. We estimate Hurst exponent by nine estimators: aggregated variance method, differencing the variance, absolute values of the aggregated series, Higuchi's method, residuals of regression, the R/S method, periodogram method, modified periodogram method and Whittle estimator. We also analyze empirically relations between estimators. Long memory implies an inertial effect in clients' behavior which may be used by mobile operators to accelerate usage and gain additional profit.

Intrusion errors in visuospatial working memory performance.

PubMed

Cornoldi, Cesare; Mammarella, Nicola

2006-02-01

This study tested the hypothesis that failure in active visuospatial working memory tasks involves a difficulty in avoiding intrusions due to information that is already activated. Two experiments are described, in which participants were required to process several series of locations on a 4 x 4 matrix and then to produce only the final location of each series. Results revealed a higher number of errors due to already activated locations (intrusions) compared with errors due to new locations (inventions). Moreover, when participants were required to pay extra attention to some irrelevant (non-final) locations by tapping on the table, intrusion errors increased. Results are discussed in terms of current models of working memory functioning.

Age-Related Differences in Brain Electrical Activity during Extended Continuous Face Recognition in Younger Children, Older Children and Adults

ERIC Educational Resources Information Center

Van Strien, Jan W.; Glimmerveen, Johanna C.; Franken, Ingmar H. A.; Martens, Vanessa E. G.; de Bruin, Eveline A.

2011-01-01

To examine the development of recognition memory in primary-school children, 36 healthy younger children (8-9 years old) and 36 healthy older children (11-12 years old) participated in an ERP study with an extended continuous face recognition task (Study 1). Each face of a series of 30 faces was shown randomly six times interspersed with…

Auditory and Visual Differences in Time Perception? An Investigation from a Developmental Perspective with Neuropsychological Tests

ERIC Educational Resources Information Center

Zelanti, Pierre S.; Droit-Volet, Sylvie

2012-01-01

Adults and children (5- and 8-year-olds) performed a temporal bisection task with either auditory or visual signals and either a short (0.5-1.0s) or long (4.0-8.0s) duration range. Their working memory and attentional capacities were assessed by a series of neuropsychological tests administered in both the auditory and visual modalities. Results…

Reconsidering plant memory: Intersections between stress recovery, RNA turnover, and epigenetics

PubMed Central

Crisp, Peter A.; Ganguly, Diep; Eichten, Steven R.; Borevitz, Justin O.; Pogson, Barry J.

2016-01-01

Plants grow in dynamic environments where they can be exposed to a multitude of stressful factors, all of which affect their development, yield, and, ultimately, reproductive success. Plants are adept at rapidly acclimating to stressful conditions and are able to further fortify their defenses by retaining memories of stress to enable stronger or more rapid responses should an environmental perturbation recur. Indeed, one mechanism that is often evoked regarding environmental memories is epigenetics. Yet, there are relatively few examples of such memories; neither is there a clear understanding of their duration, considering the plethora of stresses in nature. We propose that this field would benefit from investigations into the processes and mechanisms enabling recovery from stress. An understanding of stress recovery could provide fresh insights into when, how, and why environmental memories are created and regulated. Stress memories may be maladaptive, hindering recovery and affecting development and potential yield. In some circumstances, it may be advantageous for plants to learn to forget. Accordingly, the recovery process entails a balancing act between resetting and memory formation. During recovery, RNA metabolism, posttranscriptional gene silencing, and RNA-directed DNA methylation have the potential to play key roles in resetting the epigenome and transcriptome and in altering memory. Exploration of this emerging area of research is becoming ever more tractable with advances in genomics, phenomics, and high-throughput sequencing methodology that will enable unprecedented profiling of high-resolution stress recovery time series experiments and sampling of large natural populations. PMID:26989783

Final report for the endowment of simulator agents with human-like episodic memory LDRD.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Speed, Ann Elizabeth; Lippitt, Carl Edward; Thomas, Edward Victor

This report documents work undertaken to endow the cognitive framework currently under development at Sandia National Laboratories with a human-like memory for specific life episodes. Capabilities have been demonstrated within the context of three separate problem areas. The first year of the project developed a capability whereby simulated robots were able to utilize a record of shared experience to perform surveillance of a building to detect a source of smoke. The second year focused on simulations of social interactions providing a queriable record of interactions such that a time series of events could be constructed and reconstructed. The third yearmore » addressed tools to promote desktop productivity, creating a capability to query episodic logs in real time allowing the model of a user to build on itself based on observations of the user's behavior.« less

Activation of Imaginal Information on True and False Memories

ERIC Educational Resources Information Center

Chang, Sau Hou; Pierce, Benton H.

2009-01-01

The present study examined the activation of imaginal information on true and false memories. Participants studied a series of concrete objects in pictures or words. The imagery group (n = 96) was instructed to form images and the control group (n = 96) was not instructed to do so. Both groups were then given a standard recognition memory test and…

Scene and Position Specificity in Visual Memory for Objects

ERIC Educational Resources Information Center

Hollingworth, Andrew

2006-01-01

This study investigated whether and how visual representations of individual objects are bound in memory to scene context. Participants viewed a series of naturalistic scenes, and memory for the visual form of a target object in each scene was examined in a 2-alternative forced-choice test, with the distractor object either a different object…

Bilateral Saccadic Eye Movements and Tactile Stimulation, but Not Auditory Stimulation, Enhance Memory Retrieval

ERIC Educational Resources Information Center

Nieuwenhuis, Sander; Elzinga, Bernet M.; Ras, Priscilla H.; Berends, Floris; Duijs, Peter; Samara, Zoe; Slagter, Heleen A.

2013-01-01

Recent research has shown superior memory retrieval when participants make a series of horizontal saccadic eye movements between the memory encoding phase and the retrieval phase compared to participants who do not move their eyes or move their eyes vertically. It has been hypothesized that the rapidly alternating activation of the two hemispheres…

Role of the anterior cingulate cortex in the retrieval of novel object recognition memory after a long delay

PubMed Central

Pezze, Marie A.; Marshall, Hayley J.; Fone, Kevin CF.; Cassaday, Helen J.

2017-01-01

Previous in vivo electrophysiological studies suggest that the anterior cingulate cortex (ACgx) is an important substrate of novel object recognition (NOR) memory. However, intervention studies are needed to confirm this conclusion and permanent lesion studies cannot distinguish effects on encoding and retrieval. The interval between encoding and retrieval tests may also be a critical determinant of the role of the ACgx. The current series of experiments used micro-infusion of the GABAA receptor agonist, muscimol, into ACgx to reversibly inactivate the area and distinguish its role in encoding and retrieval. ACgx infusions of muscimol, before encoding did not alter NOR assessed after a delay of 20 min or 24 h. However, when infused into the ACgx before retrieval muscimol impaired NOR assessed after a delay of 24 h, but not after a 20-min retention test. Together these findings suggest that the ACgx plays a time-dependent role in the retrieval, but not the encoding, of NOR memory, neuronal activation being required for the retrieval of remote (24 h old), but not recent (20 min old) visual memory. PMID:28620078

Programmable Direct-Memory-Access Controller

NASA Technical Reports Server (NTRS)

Hendry, David F.

1990-01-01

Proposed programmable direct-memory-access controller (DMAC) operates with computer systems of 32000 series, which have 32-bit data buses and use addresses of 24 (or potentially 32) bits. Controller functions with or without help of central processing unit (CPU) and starts itself. Includes such advanced features as ability to compare two blocks of memory for equality and to search block of memory for specific value. Made as single very-large-scale integrated-circuit chip.

Voluntary control over prestimulus activity related to encoding

PubMed Central

Gruber, Matthias J.; Otten, Leun J.

2010-01-01

A new development in our understanding of human long-term memory is that effective memory formation relies on neural activity just before an event. It is unknown whether such prestimulus activity is under voluntary control or a reflection of random fluctuations over time. In the present study, we addressed two issues: (i) whether prestimulus activity is influenced by an individual's motivation to encode, and (ii) at what point in time encoding-related activity emerges. Electrical brain activity was recorded while healthy male and female adults memorized series of words. Each word was preceded by a cue, which indicated the monetary reward that would be received if the following word was later remembered. Memory was tested after a short delay with a five-way recognition task to separate different sources of recognition. Electrical activity elicited by the reward cue predicted later memory of a word. Crucially, however, this was only observed when the incentive to memorize a word was high. Encoding-related activity preceded high reward words that were later recollected. This activity started shortly after cue onset and persisted until word onset. Prestimulus activity thus not only signals cue-related processing, but also an ensuing preparatory state. In contrast, reward-related activity was limited to the time period immediately following the reward cue. These findings indicate that engaging neural activity that benefits the encoding of an upcoming event is under voluntary control, reflecting a strategic preparatory state in anticipation of processing an event. PMID:20660262

Acute and Chronic Effects of Alcohol Use on Organizational Processes in Memory

ERIC Educational Resources Information Center

Rosen, Linda J.; Lee, Catherine L.

1976-01-01

Subjects selected on the basis of their drinking histories (alcoholics, heavy drinkers, and social drinkers, N=24) were tested on a series of tasks in order to assess organizational processes in memory. (Editor)

Discrete Dynamics Lab

NASA Astrophysics Data System (ADS)

Wuensche, Andrew

DDLab is interactive graphics software for creating, visualizing, and analyzing many aspects of Cellular Automata, Random Boolean Networks, and Discrete Dynamical Networks in general and studying their behavior, both from the time-series perspective — space-time patterns, and from the state-space perspective — attractor basins. DDLab is relevant to research, applications, and education in the fields of complexity, self-organization, emergent phenomena, chaos, collision-based computing, neural networks, content addressable memory, genetic regulatory networks, dynamical encryption, generative art and music, and the study of the abstract mathematical/physical/dynamical phenomena in their own right.

Low-cost fabrication and polar-dependent switching uniformity of memory devices using alumina interfacial layer and Ag nanoparticle monolayer

NASA Astrophysics Data System (ADS)

Xia, Peng; Li, Luman; Wang, Pengfei; Gan, Ying; Xu, Wei

2017-11-01

A facile and low-cost process was developed for fabricating write-once-read-many-times (WORM) Cu/Ag NPs/Alumina/Al memory devices, where the alumina passivation layer formed naturally in air at room temperature, whereas the Ag nanoparticle monolayer was in situ prepared through thermal annealing of a 4.5 nm Ag film in air at 150°C. The devices exhibit irreversible transition from initial high resistance (OFF) state to low resistance (ON) state, with ON/OFF ratio of 107, indicating the introduction of Ag nanoparticle monolayer greatly improves ON/OFF ratio by four orders of magnitude. The uniformity of threshold voltages exhibits a polar-dependent behavior, and a narrow range of threshold voltages of 0.40 V among individual devices was achieved upon the forward voltage. The memory device can be regarded as two switching units connected in series. The uniform alumina interfacial layer and the non-uniform distribution of local electric fields originated from Ag nanoparticles might be responsible for excellent switching uniformity. Since silver ions in active layer can act as fast ion conductor, a plausible mechanism relating to the formation of filaments sequentially among the two switching units connected in series is suggested for the polar-dependent switching behavior. Furthermore, we demonstrate both alumina layer and Ag NPs monolayer play essential roles in improving switching parameters based on comparative experiments.

Mechanisms of Memory Dysfunction during High Altitude Hypoxia Training in Military Aircrew.

PubMed

Nation, Daniel A; Bondi, Mark W; Gayles, Ellis; Delis, Dean C

2017-01-01

Cognitive dysfunction from high altitude exposure is a major cause of civilian and military air disasters. Pilot training improves recognition of the early symptoms of altitude exposure so that countermeasures may be taken before loss of consciousness. Little is known regarding the nature of cognitive impairments manifesting within this critical window when life-saving measures may still be taken. Prior studies evaluating cognition during high altitude simulation have predominantly focused on measures of reaction time and other basic attention or motor processes. Memory encoding, retention, and retrieval represent critical cognitive functions that may be vulnerable to acute hypoxic/ischemic events and could play a major role in survival of air emergencies, yet these processes have not been studied in the context of high altitude simulation training. In a series of experiments, military aircrew underwent neuropsychological testing before, during, and after brief (15 min) exposure to high altitude simulation (20,000 ft) in a pressure-controlled chamber. Acute exposure to high altitude simulation caused rapid impairment in learning and memory with relative preservation of basic visual and auditory attention. Memory dysfunction was predominantly characterized by deficiencies in memory encoding, as memory for information learned during high altitude exposure did not improve after washout at sea level. Retrieval and retention of memories learned shortly before altitude exposure were also impaired, suggesting further impairment in memory retention. Deficits in memory encoding and retention are rapidly induced upon exposure to high altitude, an effect that could impact life-saving situational awareness and response. (JINS, 2017, 23, 1-10).

Overexpression of the NR2A subunit in the forebrain impairs long-term social recognition and non-social olfactory memory.

PubMed

Jacobs, S A; Tsien, J Z

2014-04-01

Animals must recognize and remember conspecifics and potential mates, and distinguish these animals from potential heterospecific competitors and predators. Despite its necessity, aged animals are known to exhibit impaired social recognition memory. As the brain ages, the ratio of NR2A:NR2B in the brain increases over time and has been postulated to underlie the cognitive decline observed during the aging process. Here, we test the hypothesis that an increased NR2A:NR2B subunit ratio underlies long-term social recognition memory. Using transgenic overexpression of NR2A in the forebrain regions, we investigated the ability of these mice to learn and remember male and female conspecifics, mice of another strain and animals of another rodent species, the rat. Furthermore, due to the importance of olfaction in social recognition, we tested the olfactory memory in the NR2A transgenic mice. Our series of behavioral experiments revealed significant impairments in the NR2A transgenic mice in long-term social memory of both male and female conspecifics. Additionally, the NR2A transgenic mice are unable to recognize mice of another strain or rats. The NR2A transgenic mice also exhibited long-term memory impairments in the olfactory recognition task. Taken together, our results provide evidence that an increased NR2A:NR2B ratio in the forebrain leads to reduced long-term memory function, including the ethologically important memories such as social recognition and olfactory memory.

[Series: Medical Applications of the PHITS Code (2): Acceleration by Parallel Computing].

PubMed

Furuta, Takuya; Sato, Tatsuhiko

2015-01-01

Time-consuming Monte Carlo dose calculation becomes feasible owing to the development of computer technology. However, the recent development is due to emergence of the multi-core high performance computers. Therefore, parallel computing becomes a key to achieve good performance of software programs. A Monte Carlo simulation code PHITS contains two parallel computing functions, the distributed-memory parallelization using protocols of message passing interface (MPI) and the shared-memory parallelization using open multi-processing (OpenMP) directives. Users can choose the two functions according to their needs. This paper gives the explanation of the two functions with their advantages and disadvantages. Some test applications are also provided to show their performance using a typical multi-core high performance workstation.

Age Differences in the Effects of Domain Knowledge on Reading Efficiency

PubMed Central

Miller, Lisa M. Soederberg

2009-01-01

The present study investigated age differences in the effects of knowledge on the efficiency with which information is processed while reading. Individuals between 18 and 85 years of age, with varying levels of cooking knowledge, read and recalled a series of short passages within the domain of cooking. Reading efficiency was operationalized as time spent reading divided by the amount recalled for each passage. Results showed that reading efficiency increased with increasing levels of knowledge among older but not younger adults. Similarly, those with smaller working memory capacities showed increasing efficiency with increasing knowledge. These findings suggest that knowledge promotes a more efficient allocation policy which is particularly helpful in later life, perhaps due to age-related declines in working memory capacity. PMID:19290738

Aggregated Indexing of Biomedical Time Series Data

PubMed Central

Woodbridge, Jonathan; Mortazavi, Bobak; Sarrafzadeh, Majid; Bui, Alex A.T.

2016-01-01

Remote and wearable medical sensing has the potential to create very large and high dimensional datasets. Medical time series databases must be able to efficiently store, index, and mine these datasets to enable medical professionals to effectively analyze data collected from their patients. Conventional high dimensional indexing methods are a two stage process. First, a superset of the true matches is efficiently extracted from the database. Second, supersets are pruned by comparing each of their objects to the query object and rejecting any objects falling outside a predetermined radius. This pruning stage heavily dominates the computational complexity of most conventional search algorithms. Therefore, indexing algorithms can be significantly improved by reducing the amount of pruning. This paper presents an online algorithm to aggregate biomedical times series data to significantly reduce the search space (index size) without compromising the quality of search results. This algorithm is built on the observation that biomedical time series signals are composed of cyclical and often similar patterns. This algorithm takes in a stream of segments and groups them to highly concentrated collections. Locality Sensitive Hashing (LSH) is used to reduce the overall complexity of the algorithm, allowing it to run online. The output of this aggregation is used to populate an index. The proposed algorithm yields logarithmic growth of the index (with respect to the total number of objects) while keeping sensitivity and specificity simultaneously above 98%. Both memory and runtime complexities of time series search are improved when using aggregated indexes. In addition, data mining tasks, such as clustering, exhibit runtimes that are orders of magnitudes faster when run on aggregated indexes. PMID:27617298

Intracarotid amobarbital procedure: I. Prediction of decreased modality-specific memory scores after temporal lobectomy.

PubMed

Wyllie, E; Naugle, R; Awad, I; Chelune, G; Lüders, H; Dinner, D; Skibinski, C; Ahl, J

1991-01-01

To assess predictive value of the intracarotid amobarbital procedure (IAP) for decreased postoperative modality-specific memory, we studied 37 temporal lobectomy patients with intractable partial epilepsy who were selected for operation independent of preoperative IAP findings. When ipsilateral IAP failure was defined by an absolute method as a retention score less than 67%, the results were not associated with decreased modality-specific memory after operation. When ipsilateral IAP failure was defined by a comparative method as a retention score at least 20% lower after ipsilateral than contralateral injection, the results showed greater differences between groups, but differences still did not achieve statistical significance. Four left-resection patients who failed the ipsilateral IAP had a median postoperative change in the Wechsler Memory Scale-Revised (WMS-R) Verbal Memory Index score of -14%, whereas 16 left-resection patients who passed the ipsilateral IAP had a mean postoperative change in the WMS-R Verbal Memory Index score of -7.5% (p = 0.12). These results suggested that the IAP interpreted comparatively may be a helpful adjunctive test in assessment of relative risk for modality-specific memory dysfunction after temporal lobectomy, but larger series of operated patients are needed to confirm this possibility. In this series, complete amnesia was not noted after ipsilateral injection, even in patients with postoperative modality-specific memory decline.

Intrinsic vs. spurious long-range memory in high-frequency records of environmental radioactivity. Critical re-assessment and application to indoor 222Rn concentrations from Coimbra, Portugal

NASA Astrophysics Data System (ADS)

Donner, R. V.; Potirakis, S. M.; Barbosa, S. M.; Matos, J. A. O.; Pereira, A. J. S. C.; Neves, L. J. P. F.

2015-05-01

The presence or absence of long-range correlations in the environmental radioactivity fluctuations has recently attracted considerable interest. Among a multiplicity of practically relevant applications, identifying and disentangling the environmental factors controlling the variable concentrations of the radioactive noble gas radon is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we present a critical re-assessment of a multiplicity of complementary methods that have been previously applied for evaluating the presence of long-range correlations and fractal scaling in environmental radon variations with a particular focus on the specific properties of the underlying time series. As an illustrative case study, we subsequently re-analyze two high-frequency records of indoor radon concentrations from Coimbra, Portugal, each of which spans several weeks of continuous measurements at a high temporal resolution of five minutes.Our results reveal that at the study site, radon concentrations exhibit complex multi-scale dynamics with qualitatively different properties at different time-scales: (i) essentially white noise in the high-frequency part (up to time-scales of about one hour), (ii) spurious indications of a non-stationary, apparently long-range correlated process (at time scales between some hours and one day) arising from marked periodic components, and (iii) low-frequency variability indicating a true long-range dependent process. In the presence of such multi-scale variability, common estimators of long-range memory in time series are prone to fail if applied to the raw data without previous separation of time-scales with qualitatively different dynamics.

Epitaxial Garnets and Hexagonal Ferrites.

DTIC Science & Technology

1983-12-01

operating at frequencies between 1 GHz and 25 GHz. 2. Investigate LPE growth of lithium ferrite with the objective of preparing low-loss, large area films ...and hexagonal ferrites when the series of contracts began in 1975. At that time the liquid phase epitaxy method for growth of magnetic garnet films ...principal interest in epitaxial garnets was for magnetic bubble memories. For this Uapplication the films had to be about 3pm thick with low defect density

Proceedings of the Conference on the Design of Experiments (23rd) S

DTIC Science & Technology

1978-07-01

of Statistics, Carnegie-Mellon University. * [12] Duran , B. S . (1976). A survey of nonparametric tests for scale. Comunications in Statistics A5, 1287...the twenty-third Design of Experiments Conference was the U. S . Army Combat Development Experimentation Command, Fort Ord, California. Excellent...Availability Prof. G. E. P. Box Time Series Modelling University of Wisconsin Dr. Churchill Eisenhart was recipient this year of the Samuel S . Wilks Memorial

From heavy-tailed to exponential distribution of interevent time in cellphone top-up behavior

NASA Astrophysics Data System (ADS)

Wang, Peng; Ma, Qiang

2017-05-01

Cellphone top-up is a kind of activities, to a great extent, driven by individual consumption rather than personal interest and this behavior should be stable in common sense. However, our researches find there are heavy-tails both in interevent time distribution and purchase frequency distribution at the global level. Moreover, we find both memories of interevent time and unit price series are negative, which is different from previous bursty activities. We divide individuals into five groups according to the purchase frequency and the average unit price respectively. Then, the group analysis shows some significant heterogeneity in this behavior. On one hand, we obtain only the individuals with high purchase frequency have the heavy-tailed nature in interevent time distribution. On the contrary, the negative memory is only caused by low purchase-frequency individuals without burstiness. On the other hand, the individuals with different preferential price also have different power-law exponents at the group level and there is no data collapse after rescaling between these distributions. Our findings produce the evidence for the significant heterogeneity of human activity in many aspects.

Complex dynamics of semantic memory access in reading.

PubMed

Baggio, Giosué; Fonseca, André

2012-02-07

Understanding a word in context relies on a cascade of perceptual and conceptual processes, starting with modality-specific input decoding, and leading to the unification of the word's meaning into a discourse model. One critical cognitive event, turning a sensory stimulus into a meaningful linguistic sign, is the access of a semantic representation from memory. Little is known about the changes that activating a word's meaning brings about in cortical dynamics. We recorded the electroencephalogram (EEG) while participants read sentences that could contain a contextually unexpected word, such as 'cold' in 'In July it is very cold outside'. We reconstructed trajectories in phase space from single-trial EEG time series, and we applied three nonlinear measures of predictability and complexity to each side of the semantic access boundary, estimated as the onset time of the N400 effect evoked by critical words. Relative to controls, unexpected words were associated with larger prediction errors preceding the onset of the N400. Accessing the meaning of such words produced a phase transition to lower entropy states, in which cortical processing becomes more predictable and more regular. Our study sheds new light on the dynamics of information flow through interfaces between sensory and memory systems during language processing.

In memory of Natacha Betz

NASA Astrophysics Data System (ADS)

Bouffard, Serge

2018-01-01

Natacha Betz has participated to the creation of the IRAP conference series and co-organized three of them. Unfortunately, ten years ago, she passed away. The organization of IRAP 2016 in France gives us the opportunity to pay a tribute to her memory.

Investigation of Current Spike Phenomena During Heavy Ion Irradiation of NAND Flash Memories

NASA Technical Reports Server (NTRS)

Oldham, Timothy R.; Berg, Melanie; Friendlich, Mark; Wilcox, Ted; Seidleck, Christina; LaBel, Kenneth A.; Irom, Farokh; Buchner, Steven P.; McMorrow, Dale; Mavis, David G.;

On fractality and chaos in Moroccan family business stock returns and volatility

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

2017-05-01

The purpose of this study is to examine existence of fractality and chaos in returns and volatilities of family business companies listed on the Casablanca Stock Exchange (CSE) in Morocco, and also in returns and volatility of the CSE market index. Detrended fluctuation analysis based Hurst exponent and fractionally integrated generalized autoregressive conditional heteroskedasticity (FIGARCH) model are used to quantify fractality in returns and volatility time series respectively. Besides, the largest Lyapunov exponent is employed to quantify chaos in both time series. The empirical results from sixteen family business companies follow. For return series, fractality analysis show that most of family business returns listed on CSE exhibit anti-persistent dynamics, whilst market returns have persistent dynamics. Besides, chaos tests show that business family stock returns are not chaotic while market returns exhibit evidence of chaotic behaviour. For volatility series, fractality analysis shows that most of family business stocks and market index exhibit long memory in volatility. Furthermore, results from chaos tests show that volatility of family business returns is not chaotic, whilst volatility of market index is chaotic. These results may help understanding irregularities patterns in Moroccan family business stock returns and volatility, and how they are different from market dynamics.

Information Memory Processing and Retrieval: Relationships of Learning and Cognition in a Verbal and Visual Task.

ERIC Educational Resources Information Center

Empfield, Chick O.; Moser, Gene W.

One of a series of investigations on the Project on an Information Memory Model, the purpose of this study was to determine the amount and kind of visual information processed and stored in the memory of children using different modalities of observation. Children, aged 5, 9 and 13 years, were randomly assigned to one of three treatment groups.…

FPGA Vision Data Architecture

NASA Technical Reports Server (NTRS)

Morfopoulos, Arin C.; Pham, Thang D.

2013-01-01

JPL has produced a series of FPGA (field programmable gate array) vision algorithms that were written with custom interfaces to get data in and out of each vision module. Each module has unique requirements on the data interface, and further vision modules are continually being developed, each with their own custom interfaces. Each memory module had also been designed for direct access to memory or to another memory module.

Preventing intrusive memories after trauma via a brief intervention involving Tetris computer game play in the emergency department: a proof-of-concept randomized controlled trial

PubMed Central

Iyadurai, L; Blackwell, S E; Meiser-Stedman, R; Watson, P C; Bonsall, M B; Geddes, J R; Nobre, A C; Holmes, E A

2018-01-01

After psychological trauma, recurrent intrusive visual memories may be distressing and disruptive. Preventive interventions post trauma are lacking. Here we test a behavioural intervention after real-life trauma derived from cognitive neuroscience. We hypothesized that intrusive memories would be significantly reduced in number by an intervention involving a computer game with high visuospatial demands (Tetris), via disrupting consolidation of sensory elements of trauma memory. The Tetris-based intervention (trauma memory reminder cue plus c. 20 min game play) vs attention-placebo control (written activity log for same duration) were both delivered in an emergency department within 6 h of a motor vehicle accident. The randomized controlled trial compared the impact on the number of intrusive trauma memories in the subsequent week (primary outcome). Results vindicated the efficacy of the Tetris-based intervention compared with the control condition: there were fewer intrusive memories overall, and time-series analyses showed that intrusion incidence declined more quickly. There were convergent findings on a measure of clinical post-trauma intrusion symptoms at 1 week, but not on other symptom clusters or at 1 month. Results of this proof-of-concept study suggest that a larger trial, powered to detect differences at 1 month, is warranted. Participants found the intervention easy, helpful and minimally distressing. By translating emerging neuroscientific insights and experimental research into the real world, we offer a promising new low-intensity psychiatric intervention that could prevent debilitating intrusive memories following trauma. PMID:28348380

Study of self-compliance behaviors and internal filament characteristics in intrinsic SiO{sub x}-based resistive switching memory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, Yao-Feng, E-mail: yfchang@utexas.edu; Zhou, Fei; Chen, Ying-Chen

2016-01-18

Self-compliance characteristics and reliability optimization are investigated in intrinsic unipolar silicon oxide (SiO{sub x})-based resistive switching (RS) memory using TiW/SiO{sub x}/TiW device structures. The program window (difference between SET voltage and RESET voltage) is dependent on external series resistance, demonstrating that the SET process is due to a voltage-triggered mechanism. The program window has been optimized for program/erase disturbance immunity and reliability for circuit-level applications. The SET and RESET transitions have also been characterized using a dynamic conductivity method, which distinguishes the self-compliance behavior due to an internal series resistance effect (filament) in SiO{sub x}-based RS memory. By using amore » conceptual “filament/resistive gap (GAP)” model of the conductive filament and a proton exchange model with appropriate assumptions, the internal filament resistance and GAP resistance can be estimated for high- and low-resistance states (HRS and LRS), and are found to be independent of external series resistance. Our experimental results not only provide insights into potential reliability issues but also help to clarify the switching mechanisms and device operating characteristics of SiO{sub x}-based RS memory.« less

Whole Brain Radiation-Induced Impairments in Learning and Memory Are Time-Sensitive and Reversible by Systemic Hypoxia

PubMed Central

Warrington, Junie P.; Csiszar, Anna; Mitschelen, Matthew; Lee, Yong Woo; Sonntag, William E.

2012-01-01

Whole brain radiation therapy (WBRT) is commonly used for treatment of primary and metastatic brain tumors; however, cognitive impairment occurs in 40–50% of brain tumor survivors. The etiology of the cognitive impairment following WBRT remains elusive. We recently reported that radiation-induced cerebrovascular rarefaction within hippocampal subregions could be completely reversed by systemic hypoxia. However, the effects of this intervention on learning and memory have not been reported. In this study, we assessed the time-course for WBRT-induced impairments in contextual and spatial learning and the capacity of systemic hypoxia to reverse WBRT-induced deficits in spatial memory. A clinical fractionated series of 4.5Gy WBRT was administered to mice twice weekly for 4 weeks, and after various periods of recovery, behavioral analyses were performed. To study the effects of systemic hypoxia, mice were subjected to 11% (hypoxia) or 21% oxygen (normoxia) for 28 days, initiated 1 month after the completion of WBRT. Our results indicate that WBRT induces a transient deficit in contextual learning, disruption of working memory, and progressive impairment of spatial learning. Additionally, systemic hypoxia completely reversed WBRT-induced impairments in learning and these behavioral effects as well as increased vessel density persisted for at least 2 months following hypoxia treatment. Our results provide critical support for the hypothesis that cerebrovascular rarefaction is a key component of cognitive impairment post-WBRT and indicate that processes of learning and memory, once thought to be permanently impaired after WBRT, can be restored. PMID:22279591

A Spatiotemporal Prediction Framework for Air Pollution Based on Deep RNN

NASA Astrophysics Data System (ADS)

Fan, J.; Li, Q.; Hou, J.; Feng, X.; Karimian, H.; Lin, S.

2017-10-01

Time series data in practical applications always contain missing values due to sensor malfunction, network failure, outliers etc. In order to handle missing values in time series, as well as the lack of considering temporal properties in machine learning models, we propose a spatiotemporal prediction framework based on missing value processing algorithms and deep recurrent neural network (DRNN). By using missing tag and missing interval to represent time series patterns, we implement three different missing value fixing algorithms, which are further incorporated into deep neural network that consists of LSTM (Long Short-term Memory) layers and fully connected layers. Real-world air quality and meteorological datasets (Jingjinji area, China) are used for model training and testing. Deep feed forward neural networks (DFNN) and gradient boosting decision trees (GBDT) are trained as baseline models against the proposed DRNN. Performances of three missing value fixing algorithms, as well as different machine learning models are evaluated and analysed. Experiments show that the proposed DRNN framework outperforms both DFNN and GBDT, therefore validating the capacity of the proposed framework. Our results also provides useful insights for better understanding of different strategies that handle missing values.

Efficient multidimensional regularization for Volterra series estimation

NASA Astrophysics Data System (ADS)

Birpoutsoukis, Georgios; Csurcsia, Péter Zoltán; Schoukens, Johan

2018-05-01

This paper presents an efficient nonparametric time domain nonlinear system identification method. It is shown how truncated Volterra series models can be efficiently estimated without the need of long, transient-free measurements. The method is a novel extension of the regularization methods that have been developed for impulse response estimates of linear time invariant systems. To avoid the excessive memory needs in case of long measurements or large number of estimated parameters, a practical gradient-based estimation method is also provided, leading to the same numerical results as the proposed Volterra estimation method. Moreover, the transient effects in the simulated output are removed by a special regularization method based on the novel ideas of transient removal for Linear Time-Varying (LTV) systems. Combining the proposed methodologies, the nonparametric Volterra models of the cascaded water tanks benchmark are presented in this paper. The results for different scenarios varying from a simple Finite Impulse Response (FIR) model to a 3rd degree Volterra series with and without transient removal are compared and studied. It is clear that the obtained models capture the system dynamics when tested on a validation dataset, and their performance is comparable with the white-box (physical) models.

Discovery of Selective Phosphodiesterase 1 Inhibitors with Memory Enhancing Properties.

PubMed

Dyck, Brian; Branstetter, Bryan; Gharbaoui, Tawfik; Hudson, Andrew R; Breitenbucher, J Guy; Gomez, Laurent; Botrous, Iriny; Marrone, Tami; Barido, Richard; Allerston, Charles K; Cedervall, E Peder; Xu, Rui; Sridhar, Vandana; Barker, Ryan; Aertgeerts, Kathleen; Schmelzer, Kara; Neul, David; Lee, Dong; Massari, Mark Eben; Andersen, Carsten B; Sebring, Kristen; Zhou, Xianbo; Petroski, Robert; Limberis, James; Augustin, Martin; Chun, Lawrence E; Edwards, Thomas E; Peters, Marco; Tabatabaei, Ali

2017-04-27

A series of potent thienotriazolopyrimidinone-based PDE1 inhibitors was discovered. X-ray crystal structures of example compounds from this series in complex with the catalytic domain of PDE1B and PDE10A were determined, allowing optimization of PDE1B potency and PDE selectivity. Reduction of hERG affinity led to greater than a 3000-fold selectivity for PDE1B over hERG. 6-(4-Methoxybenzyl)-9-((tetrahydro-2H-pyran-4-yl)methyl)-8,9,10,11-tetrahydropyrido[4',3':4,5]thieno[3,2-e][1,2,4]triazolo[1,5-c]pyrimidin-5(6H)-one was identified as an orally bioavailable and brain penetrating PDE1B enzyme inhibitor with potent memory-enhancing effects in a rat model of object recognition memory.

Stress, Time Pressure, Strategy Selection and Math Anxiety in Mathematics: A Review of the Literature.

PubMed

Caviola, Sara; Carey, Emma; Mammarella, Irene C; Szucs, Denes

2017-01-01

We review how stress induction, time pressure manipulations and math anxiety can interfere with or modulate selection of problem-solving strategies (henceforth "strategy selection") in arithmetical tasks. Nineteen relevant articles were identified, which contain references to strategy selection and time limit (or time manipulations), with some also discussing emotional aspects in mathematical outcomes. Few of these take cognitive processes such as working memory or executive functions into consideration. We conclude that due to the sparsity of available literature our questions can only be partially answered and currently there is not much evidence of clear associations. We identify major gaps in knowledge and raise a series of open questions to guide further research.

An energy efficient and high speed architecture for convolution computing based on binary resistive random access memory

NASA Astrophysics Data System (ADS)

Liu, Chen; Han, Runze; Zhou, Zheng; Huang, Peng; Liu, Lifeng; Liu, Xiaoyan; Kang, Jinfeng

2018-04-01

In this work we present a novel convolution computing architecture based on metal oxide resistive random access memory (RRAM) to process the image data stored in the RRAM arrays. The proposed image storage architecture shows performances of better speed-device consumption efficiency compared with the previous kernel storage architecture. Further we improve the architecture for a high accuracy and low power computing by utilizing the binary storage and the series resistor. For a 28 × 28 image and 10 kernels with a size of 3 × 3, compared with the previous kernel storage approach, the newly proposed architecture shows excellent performances including: 1) almost 100% accuracy within 20% LRS variation and 90% HRS variation; 2) more than 67 times speed boost; 3) 71.4% energy saving.

Use long short-term memory to enhance Internet of Things for combined sewer overflow monitoring

NASA Astrophysics Data System (ADS)

Zhang, Duo; Lindholm, Geir; Ratnaweera, Harsha

2018-01-01

Combined sewer overflow causes severe water pollution, urban flooding and reduced treatment plant efficiency. Understanding the behavior of CSO structures is vital for urban flooding prevention and overflow control. Neural networks have been extensively applied in water resource related fields. In this study, we collect data from an Internet of Things monitoring CSO structure and build different neural network models for simulating and predicting the water level of the CSO structure. Through a comparison of four different neural networks, namely multilayer perceptron (MLP), wavelet neural network (WNN), long short-term memory (LSTM) and gated recurrent unit (GRU), the LSTM and GRU present superior capabilities for multi-step-ahead time series prediction. Furthermore, GRU achieves prediction performances similar to LSTM with a quicker learning curve.

Blip decomposition of the path integral: exponential acceleration of real-time calculations on quantum dissipative systems.

PubMed

Makri, Nancy

2014-10-07

The real-time path integral representation of the reduced density matrix for a discrete system in contact with a dissipative medium is rewritten in terms of the number of blips, i.e., elementary time intervals over which the forward and backward paths are not identical. For a given set of blips, it is shown that the path sum with respect to the coordinates of all remaining time points is isomorphic to that for the wavefunction of a system subject to an external driving term and thus can be summed by an inexpensive iterative procedure. This exact decomposition reduces the number of terms by a factor that increases exponentially with propagation time. Further, under conditions (moderately high temperature and/or dissipation strength) that lead primarily to incoherent dynamics, the "fully incoherent limit" zero-blip term of the series provides a reasonable approximation to the dynamics, and the blip series converges rapidly to the exact result. Retention of only the blips required for satisfactory convergence leads to speedup of full-memory path integral calculations by many orders of magnitude.

Can We Speculate Running Application With Server Power Consumption Trace?

PubMed

Li, Yuanlong; Hu, Han; Wen, Yonggang; Zhang, Jun

2018-05-01

In this paper, we propose to detect the running applications in a server by classifying the observed power consumption series for the purpose of data center energy consumption monitoring and analysis. Time series classification problem has been extensively studied with various distance measurements developed; also recently the deep learning-based sequence models have been proved to be promising. In this paper, we propose a novel distance measurement and build a time series classification algorithm hybridizing nearest neighbor and long short term memory (LSTM) neural network. More specifically, first we propose a new distance measurement termed as local time warping (LTW), which utilizes a user-specified index set for local warping, and is designed to be noncommutative and nondynamic programming. Second, we hybridize the 1-nearest neighbor (1NN)-LTW and LSTM together. In particular, we combine the prediction probability vector of 1NN-LTW and LSTM to determine the label of the test cases. Finally, using the power consumption data from a real data center, we show that the proposed LTW can improve the classification accuracy of dynamic time warping (DTW) from about 84% to 90%. Our experimental results prove that the proposed LTW is competitive on our data set compared with existed DTW variants and its noncommutative feature is indeed beneficial. We also test a linear version of LTW and find out that it can perform similar to state-of-the-art DTW-based method while it runs as fast as the linear runtime lower bound methods like LB_Keogh for our problem. With the hybrid algorithm, for the power series classification task we achieve an accuracy up to about 93%. Our research can inspire more studies on time series distance measurement and the hybrid of the deep learning models with other traditional models.

Information Memory Processing and Retrieval: Relationships of the Intellect with the Processing of a Learning and Cognition Task.

ERIC Educational Resources Information Center

Moser, Gene W.

Reported is one of a series of investigations of the Project on an Information Memory Model. This study was done to test an information memory model for identifying the unit of information structure involved in task cognitions by humans. Four groups of 30 randomly selected subjects (ages 7, 9, 11 and 15 years) performed a sorting task of 14…

Thermoacoustic tomography for an integro-differential wave equation modeling attenuation

NASA Astrophysics Data System (ADS)

Acosta, Sebastián; Palacios, Benjamín

2018-02-01

In this article we study the inverse problem of thermoacoustic tomography (TAT) on a medium with attenuation represented by a time-convolution (or memory) term, and whose consideration is motivated by the modeling of ultrasound waves in heterogeneous tissue via fractional derivatives with spatially dependent parameters. Under the assumption of being able to measure data on the whole boundary, we prove uniqueness and stability, and propose a convergent reconstruction method for a class of smooth variable sound speeds. By a suitable modification of the time reversal technique, we obtain a Neumann series reconstruction formula.

Iterative blip-summed path integral for quantum dynamics in strongly dissipative environments

NASA Astrophysics Data System (ADS)

Makri, Nancy

2017-04-01

The iterative decomposition of the blip-summed path integral [N. Makri, J. Chem. Phys. 141, 134117 (2014)] is described. The starting point is the expression of the reduced density matrix for a quantum system interacting with a harmonic dissipative bath in the form of a forward-backward path sum, where the effects of the bath enter through the Feynman-Vernon influence functional. The path sum is evaluated iteratively in time by propagating an array that stores blip configurations within the memory interval. Convergence with respect to the number of blips and the memory length yields numerically exact results which are free of statistical error. In situations of strongly dissipative, sluggish baths, the algorithm leads to a dramatic reduction of computational effort in comparison with iterative path integral methods that do not implement the blip decomposition. This gain in efficiency arises from (i) the rapid convergence of the blip series and (ii) circumventing the explicit enumeration of between-blip path segments, whose number grows exponentially with the memory length. Application to an asymmetric dissipative two-level system illustrates the rapid convergence of the algorithm even when the bath memory is extremely long.

Senile dementia: treatment with deanol.

PubMed

Ferris, S H; Sathananthan, G; Gershon, S; Clark, C

1977-06-01

Recent research indicates a possible cholinergic involvement in memory processes and thus the possibility that acetylcholine deficiency may underlie memory impairment in senile dementia. Deanol (2-dimethylaminoethanol), which is assumed to increase brain acetylcholine, was given openly for 4 weeks to 14 senile outpatients, to determine the safety of the drug and whether or not it reduces cognitive impairment. The dosage was gradually increased to 600 mg three times daily during the first two weeks, with no adverse effects. Ten patients improved globally and 4 were unchanged (p less than .01). The total score on the Sandoz Clinical Assessment-Geriatric (SCAG) was lowered by the third week (p less than .01), primarily as a result of reduced depression, irritability and anxiety, and increased motivation-initiative. However, neither the clinical ratings nor an extensive pre- versus post-treatment series of cognitive tests revealed changes in memory or other cognitive functions. Since a similar separate study with a different compound produced no behavioral changes, it is unlikely that the improvement with deanol was due entirely to placebo effects. The results thus suggest that although deanol may not improve memory, it may produce positive behavioral changes in some senile patients.

A Cure for Short Memories.

ERIC Educational Resources Information Center

Instructor, 1983

1983-01-01

This article explains two techniques for helping students develop long-term memory skills and retain information taught in class. One technique relies on mental pictures to keep track of a numbered series of items; the other depends on key words derived from the material that must be memorized. (PP)

Some Prerequisites in Learning to Solve Figural Analogy Problems.

ERIC Educational Resources Information Center

Wagner, James

A series of three experiments was conducted for the purposes of (1) clarifying problems of previous research on the relationship between working memory capacity and performance on figural analogy tasks, and (2) exploring developmental issues concerning executive strategies, working memory capacity, and perceptual processing. Directly manipulating…

Malware Memory Analysis for Non-specialists: Investigating Publicly Available Memory Image 0zapftis (R2D2)

DTIC Science & Technology

2013-10-01

investigators can conduct meaningful memory-based investigations on their own. This technical memorandum examines the 0zapftis (R2D2) Trojan horse , in order...TM 2013-018 and TM 2013-155, examined the Zeus Trojan horse (the former) while the latter examined the Prolaco worm and SpyEye Trojan horse . It is...necessary for a novice to conduct such memory analyses on his own. The first report in this series written by the author examined the Zeus Trojan Horse

Analyzing Snowpack Metrics Over Large Spatial Extents Using Calibrated, Enhanced-Resolution Brightness Temperature Data and Long Short Term Memory Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Norris, W.; J Q Farmer, C.

2017-12-01

Snow water equivalence (SWE) is a difficult metric to measure accurately over large spatial extents; snow-tell sites are too localized, and traditional remotely sensed brightness temperature data is at too coarse of a resolution to capture variation. The new Calibrated Enhanced-Resolution Brightness Temperature (CETB) data from the National Snow and Ice Data Center (NSIDC) offers remotely sensed brightness temperature data at an enhanced resolution of 3.125 km versus the original 25 km, which allows for large spatial extents to be analyzed with reduced uncertainty compared to the 25km product. While the 25km brightness temperature data has proved useful in past research — one group found decreasing trends in SWE outweighed increasing trends three to one in North America; other researchers used the data to incorporate winter conditions, like snow cover, into ecological zoning criterion — with the new 3.125 km data, it is possible to derive more accurate metrics for SWE, since we have far more spatial variability in measurements. Even with higher resolution data, using the 37 - 19 GHz frequencies to estimate SWE distorts the data during times of melt onset and accumulation onset. Past researchers employed statistical splines, while other successful attempts utilized non-parametric curve fitting to smooth out spikes distorting metrics. In this work, rather than using legacy curve fitting techniques, a Long Short Term Memory (LSTM) Artificial Neural Network (ANN) was trained to perform curve fitting on the data. LSTM ANN have shown great promise in modeling time series data, and with almost 40 years of data available — 14,235 days — there is plenty of training data for the ANN. LSTM's are ideal for this type of time series analysis because they allow important trends to persist for long periods of time, but ignore short term fluctuations; since LSTM's have poor mid- to short-term memory, they are ideal for smoothing out the large spikes generated in the melt and accumulation onset seasons, while still capturing the overall trends in the data.

Egr-1: A Candidate Transcription Factor Involved in Molecular Processes Underlying Time-Memory.

PubMed

Shah, Aridni; Jain, Rikesh; Brockmann, Axel

2018-01-01

In honey bees, continuous foraging is accompanied by a sustained up-regulation of the immediate early gene Egr-1 (early growth response protein-1) and candidate downstream genes involved in learning and memory. Here, we present a series of feeder training experiments indicating that Egr-1 expression is highly correlated with the time and duration of training even in the absence of the food reward. Foragers that were trained to visit a feeder over the whole day and then collected on a day without food presentation showed Egr-1 up-regulation over the whole day with a peak expression around 14:00. When exposed to a time-restricted feeder presentation, either 2 h in the morning or 2 h in the evening, Egr-1 expression in the brain was up-regulated only during the hours of training. Foragers that visited a feeder in the morning as well as in the evening showed two peaks of Egr-1 expression. Finally, when we prevented time-trained foragers from leaving the colony using artificial rain, Egr-1 expression in the brains was still slightly but significantly up-regulated around the time of feeder training. In situ hybridization studies showed that active foraging and time-training induced Egr-1 up-regulation occurred in the same brain areas, preferentially the small Kenyon cells of the mushroom bodies and the antennal and optic lobes. Based on these findings we propose that foraging induced Egr-1 expression can get regulated by the circadian clock after time-training over several days and Egr-1 is a candidate transcription factor involved in molecular processes underlying time-memory.

Assessment of vertical excursions and open-sea psychological performance at depths to 250 fsw.

PubMed

Miller, J W; Bachrach, A J; Walsh, J M

1976-12-01

A series of 10 two-man descending vertical excursion dives was carried out in the open sea from an ocean-floor habitat off the coast of Puerto Rico by four aquanauts saturated on a normoxic-nitrogen breathing mixture at a depth of 106 fsw. The purpose of these dives was two-fold: to validate laboratory findings with respect to decompression schedules and to determine whether such excursions would produce evidence of adaptation to nitrogen narcosis. For the latter, tests designed to measure time estimation, short-term memory, and auditory vigilance were used. The validation of experimental excursion tables was carried out without incidence of decompression sickness. Although no signs of nitrogen narcosis were noted during testing, all subjects made significantly longer time estimates in the habitat and during the excursions than on the surface. Variability and incomplete data prevented a statistical analysis of the short-term memory results, and the auditory vigilance proved unusable in the water.

Short-ranged memory model with preferential growth

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Short-ranged memory model with preferential growth.

PubMed

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

2018-02-01

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

Using a Large-scale Neural Model of Cortical Object Processing to Investigate the Neural Substrate for Managing Multiple Items in Short-term Memory.

PubMed

Liu, Qin; Ulloa, Antonio; Horwitz, Barry

2017-11-01

Many cognitive and computational models have been proposed to help understand working memory. In this article, we present a simulation study of cortical processing of visual objects during several working memory tasks using an extended version of a previously constructed large-scale neural model [Tagamets, M. A., & Horwitz, B. Integrating electrophysiological and anatomical experimental data to create a large-scale model that simulates a delayed match-to-sample human brain imaging study. Cerebral Cortex, 8, 310-320, 1998]. The original model consisted of arrays of Wilson-Cowan type of neuronal populations representing primary and secondary visual cortices, inferotemporal (IT) cortex, and pFC. We added a module representing entorhinal cortex, which functions as a gating module. We successfully implemented multiple working memory tasks using the same model and produced neuronal patterns in visual cortex, IT cortex, and pFC that match experimental findings. These working memory tasks can include distractor stimuli or can require that multiple items be retained in mind during a delay period (Sternberg's task). Besides electrophysiology data and behavioral data, we also generated fMRI BOLD time series from our simulation. Our results support the involvement of IT cortex in working memory maintenance and suggest the cortical architecture underlying the neural mechanisms mediating particular working memory tasks. Furthermore, we noticed that, during simulations of memorizing a list of objects, the first and last items in the sequence were recalled best, which may implicate the neural mechanism behind this important psychological effect (i.e., the primacy and recency effect).

Proceedings of the first annual William Pecora Memorial Symposium, October 1975, Sioux Falls, South Dakota

USGS Publications Warehouse

Woll, Priscilla W.; Fischer, William August

1977-01-01

The U.S. Geological Survey agreed to publish the proceeding of the first annual William T. Pecora Memorial Symposium in its Professional Paper series because the subject material is related to the mission of the Survey. The usual standards for this series have been modified to accommodate the variety of styles used by the participants in this symposium. All color illustrations are placed at the front of the book for economy in printing. They are identified by the names of the authors of the papers from which they are extracted.

The Memories of NK Cells: Innate-Adaptive Immune Intrinsic Crosstalk

PubMed Central

Ortolani, Claudio; del Zotto, Genny; Luchetti, Francesca; Canonico, Barbara; Artico, Marco; Papa, Stefano

2016-01-01

Although NK cells are considered part of the innate immune system, a series of evidences has demonstrated that they possess characteristics typical of the adaptive immune system. These NK adaptive features, in particular their memory-like functions, are discussed from an ontogenetic and evolutionary point of view. PMID:28078307

The Memories of NK Cells: Innate-Adaptive Immune Intrinsic Crosstalk.

PubMed

Gabrielli, Sara; Ortolani, Claudio; Del Zotto, Genny; Luchetti, Francesca; Canonico, Barbara; Buccella, Flavia; Artico, Marco; Papa, Stefano; Zamai, Loris

2016-01-01

Although NK cells are considered part of the innate immune system, a series of evidences has demonstrated that they possess characteristics typical of the adaptive immune system. These NK adaptive features, in particular their memory-like functions, are discussed from an ontogenetic and evolutionary point of view.

Multisensory Integration Affects Visuo-Spatial Working Memory

ERIC Educational Resources Information Center

Botta, Fabiano; Santangelo, Valerio; Raffone, Antonino; Sanabria, Daniel; Lupianez, Juan; Belardinelli, Marta Olivetti

2011-01-01

In the present study, we investigate how spatial attention, driven by unisensory and multisensory cues, can bias the access of information into visuo-spatial working memory (VSWM). In a series of four experiments, we compared the effectiveness of spatially-nonpredictive visual, auditory, or audiovisual cues in capturing participants' spatial…

78 FR 23866 - Airworthiness Directives; the Boeing Company

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-23

... operational software in the cabin management system, and loading new software into the mass memory card. The...-200 and -300 series airplanes. The proposed AD would have required installing new operational software in the cabin management system, and loading new software into the mass memory card. Since the...

European Conference on Thermophysical Properties: The First 50 Years (1968 to 2018)

NASA Astrophysics Data System (ADS)

Assael, Marc J.; Righini, Francesco; Maglić, Kosta D.

2018-02-01

This paper presents the story of the initial 50 years of the European Conference on Thermophysical Properties, a successful series of events that started in 1968 and is still going strong. The aim is twofold: to make the story known and to pay gratitude to all those who helped in this endeavor. It also serves as a nice memory of good times for many of us and intends to be a tribute to many colleagues no longer with us.

Dynamic regression modeling of daily nitrate-nitrogen concentrations in a large agricultural watershed.

PubMed

Feng, Zhujing; Schilling, Keith E; Chan, Kung-Sik

2013-06-01

Nitrate-nitrogen concentrations in rivers represent challenges for water supplies that use surface water sources. Nitrate concentrations are often modeled using time-series approaches, but previous efforts have typically relied on monthly time steps. In this study, we developed a dynamic regression model of daily nitrate concentrations in the Raccoon River, Iowa, that incorporated contemporaneous and lags of precipitation and discharge occurring at several locations around the basin. Results suggested that 95 % of the variation in daily nitrate concentrations measured at the outlet of a large agricultural watershed can be explained by time-series patterns of precipitation and discharge occurring in the basin. Discharge was found to be a more important regression variable than precipitation in our model but both regression parameters were strongly correlated with nitrate concentrations. The time-series model was consistent with known patterns of nitrate behavior in the watershed, successfully identifying contemporaneous dilution mechanisms from higher relief and urban areas of the basin while incorporating the delayed contribution of nitrate from tile-drained regions in a lagged response. The first difference of the model errors were modeled as an AR(16) process and suggest that daily nitrate concentration changes remain temporally correlated for more than 2 weeks although temporal correlation was stronger in the first few days before tapering off. Consequently, daily nitrate concentrations are non-stationary, i.e. of strong memory. Using time-series models to reliably forecast daily nitrate concentrations in a river based on patterns of precipitation and discharge occurring in its basin may be of great interest to water suppliers.

Over-Distribution in Source Memory

PubMed Central

Brainerd, C. J.; Reyna, V. F.; Holliday, R. E.; Nakamura, K.

2012-01-01

Semantic false memories are confounded with a second type of error, over-distribution, in which items are attributed to contradictory episodic states. Over-distribution errors have proved to be more common than false memories when the two are disentangled. We investigated whether over-distribution is prevalent in another classic false memory paradigm: source monitoring. It is. Conventional false memory responses (source misattributions) were predominantly over-distribution errors, but unlike semantic false memory, over-distribution also accounted for more than half of true memory responses (correct source attributions). Experimental control of over-distribution was achieved via a series of manipulations that affected either recollection of contextual details or item memory (concreteness, frequency, list-order, number of presentation contexts, and individual differences in verbatim memory). A theoretical model was used to analyze the data (conjoint process dissociation) that predicts that predicts that (a) over-distribution is directly proportional to item memory but inversely proportional to recollection and (b) item memory is not a necessary precondition for recollection of contextual details. The results were consistent with both predictions. PMID:21942494

Can verbal working memory training improve reading?

PubMed

Banales, Erin; Kohnen, Saskia; McArthur, Genevieve

2015-01-01

The aim of the current study was to determine whether poor verbal working memory is associated with poor word reading accuracy because the former causes the latter, or the latter causes the former. To this end, we tested whether (a) verbal working memory training improves poor verbal working memory or poor word reading accuracy, and whether (b) reading training improves poor reading accuracy or verbal working memory in a case series of four children with poor word reading accuracy and verbal working memory. Each child completed 8 weeks of verbal working memory training and 8 weeks of reading training. Verbal working memory training improved verbal working memory in two of the four children, but did not improve their reading accuracy. Similarly, reading training improved word reading accuracy in all children, but did not improve their verbal working memory. These results suggest that the causal links between verbal working memory and reading accuracy may not be as direct as has been assumed.

Fractal scaling analysis of groundwater dynamics in confined aquifers

NASA Astrophysics Data System (ADS)

Tu, Tongbi; Ercan, Ali; Kavvas, M. Levent

2017-10-01

Groundwater closely interacts with surface water and even climate systems in most hydroclimatic settings. Fractal scaling analysis of groundwater dynamics is of significance in modeling hydrological processes by considering potential temporal long-range dependence and scaling crossovers in the groundwater level fluctuations. In this study, it is demonstrated that the groundwater level fluctuations in confined aquifer wells with long observations exhibit site-specific fractal scaling behavior. Detrended fluctuation analysis (DFA) was utilized to quantify the monofractality, and multifractal detrended fluctuation analysis (MF-DFA) and multiscale multifractal analysis (MMA) were employed to examine the multifractal behavior. The DFA results indicated that fractals exist in groundwater level time series, and it was shown that the estimated Hurst exponent is closely dependent on the length and specific time interval of the time series. The MF-DFA and MMA analyses showed that different levels of multifractality exist, which may be partially due to a broad probability density distribution with infinite moments. Furthermore, it is demonstrated that the underlying distribution of groundwater level fluctuations exhibits either non-Gaussian characteristics, which may be fitted by the Lévy stable distribution, or Gaussian characteristics depending on the site characteristics. However, fractional Brownian motion (fBm), which has been identified as an appropriate model to characterize groundwater level fluctuation, is Gaussian with finite moments. Therefore, fBm may be inadequate for the description of physical processes with infinite moments, such as the groundwater level fluctuations in this study. It is concluded that there is a need for generalized governing equations of groundwater flow processes that can model both the long-memory behavior and the Brownian finite-memory behavior.

Torsion and bending properties of shape memory and superelastic nickel-titanium rotary instruments.

PubMed

Ninan, Elizabeth; Berzins, David W

2013-01-01

Recently introduced into the market are shape memory nickel-titanium (NiTi) rotary files. The objective of this study was to investigate the torsion and bending properties of shape memory files (CM Wire, HyFlex CM, and Phoenix Flex) and compare them with conventional (ProFile ISO and K3) and M-Wire (GT Series X and ProFile Vortex) NiTi files. Sizes 20, 30, and 40 (n = 12/size/taper) of 0.02 taper CM Wire, Phoenix Flex, K3, and ProFile ISO and 0.04 taper HyFlex CM, ProFile ISO, GT Series X, and Vortex were tested in torsion and bending per ISO 3630-1 guidelines by using a torsiometer. All data were statistically analyzed by analysis of variance and the Tukey-Kramer test (P = .05) to determine any significant differences between the files. Significant interactions were present among factors of size and file. Variability in maximum torque values was noted among the shape memory files brands, sometimes exhibiting the greatest or least torque depending on brand, size, and taper. In general, the shape memory files showed a high angle of rotation before fracture but were not statistically different from some of the other files. However, the shape memory files were more flexible, as evidenced by significantly lower bending moments (P < .008). Shape memory files show greater flexibility compared with several other NiTi rotary file brands. Copyright © 2013 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

The modality and redundancy effects in multimedia learning in children with dyslexia.

PubMed

Knoop-van Campen, Carolien A N; Segers, Eliane; Verhoeven, Ludo

2018-05-01

The present study aimed to examine the modality and redundancy effects in multimedia learning in children with dyslexia in order to find out whether their learning benefits from written and/or spoken text with pictures. We compared study time and knowledge gain in 26 11-year-old children with dyslexia and 38 typically reading peers in a within-subjects design. All children were presented with a series of user-paced multimedia lessons in 3 conditions: pictorial information presented with (a) written text, (b) audio, or (c) combined text and audio. We also examined whether children's learning outcomes were related to their working memory. With respect to study time, we found modality and reversed redundancy effects. Children with dyslexia spent more time learning in the text condition, compared with the audio condition and the combined text-and-audio condition. Regarding knowledge gain, no modality or redundancy effects were evidenced. Although the groups differed on working memory, it did not influence the modality or redundancy effect on study time or knowledge gain. In multimedia learning, it thus is more efficient to provide children with dyslexia with audio or with auditory support. Copyright © 2018 John Wiley & Sons, Ltd.

Complex dynamics of semantic memory access in reading

PubMed Central

Baggio, Giosué; Fonseca, André

2012-01-01

Understanding a word in context relies on a cascade of perceptual and conceptual processes, starting with modality-specific input decoding, and leading to the unification of the word's meaning into a discourse model. One critical cognitive event, turning a sensory stimulus into a meaningful linguistic sign, is the access of a semantic representation from memory. Little is known about the changes that activating a word's meaning brings about in cortical dynamics. We recorded the electroencephalogram (EEG) while participants read sentences that could contain a contextually unexpected word, such as ‘cold’ in ‘In July it is very cold outside’. We reconstructed trajectories in phase space from single-trial EEG time series, and we applied three nonlinear measures of predictability and complexity to each side of the semantic access boundary, estimated as the onset time of the N400 effect evoked by critical words. Relative to controls, unexpected words were associated with larger prediction errors preceding the onset of the N400. Accessing the meaning of such words produced a phase transition to lower entropy states, in which cortical processing becomes more predictable and more regular. Our study sheds new light on the dynamics of information flow through interfaces between sensory and memory systems during language processing. PMID:21715401

Temporal neural networks and transient analysis of complex engineering systems

NASA Astrophysics Data System (ADS)

Uluyol, Onder

A theory is introduced for a multi-layered Local Output Gamma Feedback (LOGF) neural network within the paradigm of Locally-Recurrent Globally-Feedforward neural networks. It is developed for the identification, prediction, and control tasks of spatio-temporal systems and allows for the presentation of different time scales through incorporation of a gamma memory. It is initially applied to the tasks of sunspot and Mackey-Glass series prediction as benchmarks, then it is extended to the task of power level control of a nuclear reactor at different fuel cycle conditions. The developed LOGF neuron model can also be viewed as a Transformed Input and State (TIS) Gamma memory for neural network architectures for temporal processing. The novel LOGF neuron model extends the static neuron model by incorporating into it a short-term memory structure in the form of a digital gamma filter. A feedforward neural network made up of LOGF neurons can thus be used to model dynamic systems. A learning algorithm based upon the Backpropagation-Through-Time (BTT) approach is derived. It is applicable for training a general L-layer LOGF neural network. The spatial and temporal weights and parameters of the network are iteratively optimized for a given problem using the derived learning algorithm.

Tuning the Electrical Memory Behavior from Nonvolatile to Volatile in Functional Copolyimides Bearing Varied Fluorene and Pyrene Moieties

NASA Astrophysics Data System (ADS)

Jia, Nanfang; Qi, Shengli; Tian, Guofeng; Wang, Xiaodong; Wu, Dezhen

2017-04-01

For producing polymer based electronics with good memory behavior, a series of functional copolyimides were designed and synthesized in this work by copolymerizing 3,3',4,4'-diphenylsulfonetetracarboxylic dianhydride (DSDA) with (9,9'-bis(4-aminophenyl)fluorene) (BAPF) and N, N-bis(4-aminophenyl) aminopyrene (DAPAP) diamines. The synthesized copolyimides DSDA/(DAPAP/BAPF) were denoted as coPI-DAPAP x ( x = 100, 50, 20, 10, 5, 1, 0), where x% represents the molar fraction of the DAPAP unit in the diamines. Characterization results indicate that the coPI-DAPAP x exhibits tunable electrical switching behaviors from write once read many times (WORM, nonvolatile, coPI-DAPAP100, coPI-DAPAP50, coPI-DAPAP20, coPI-DAPAP10) to the static random access memory (SRAM, volatile, coPI-DAPAP5, coPI-DAPAP1) with the variation of the DAPAP content. Optical and electrochemical characterization show gradually decreasing highest occupied molecular orbital levels and enlarged energy gap with the decrease of the DAPAP moiety, suggesting decreasing charge-transfer effect in the copolyimides, which can account for the observed WORM-SRAM memory conversion. Meanwhile, the charge transfer process was elucidated by quantum chemical calculation at B3LYP/6-31G(d) theory level. This work shows the effect of electron donor content on the memory behavior of polymer electronic materials.

Mutual information estimation for irregularly sampled time series

NASA Astrophysics Data System (ADS)

Rehfeld, K.; Marwan, N.; Heitzig, J.; Kurths, J.

2012-04-01

For the automated, objective and joint analysis of time series, similarity measures are crucial. Used in the analysis of climate records, they allow for a complimentary, unbiased view onto sparse datasets. The irregular sampling of many of these time series, however, makes it necessary to either perform signal reconstruction (e.g. interpolation) or to develop and use adapted measures. Standard linear interpolation comes with an inevitable loss of information and bias effects. We have recently developed a Gaussian kernel-based correlation algorithm with which the interpolation error can be substantially lowered, but this would not work should the functional relationship in a bivariate setting be non-linear. We therefore propose an algorithm to estimate lagged auto and cross mutual information from irregularly sampled time series. We have extended the standard and adaptive binning histogram estimators and use Gaussian distributed weights in the estimation of the (joint) probabilities. To test our method we have simulated linear and nonlinear auto-regressive processes with Gamma-distributed inter-sampling intervals. We have then performed a sensitivity analysis for the estimation of actual coupling length, the lag of coupling and the decorrelation time in the synthetic time series and contrast our results to the performance of a signal reconstruction scheme. Finally we applied our estimator to speleothem records. We compare the estimated memory (or decorrelation time) to that from a least-squares estimator based on fitting an auto-regressive process of order 1. The calculated (cross) mutual information results are compared for the different estimators (standard or adaptive binning) and contrasted with results from signal reconstruction. We find that the kernel-based estimator has a significantly lower root mean square error and less systematic sampling bias than the interpolation-based method. It is possible that these encouraging results could be further improved by using non-histogram mutual information estimators, like k-Nearest Neighbor or Kernel-Density estimators, but for short (<1000 points) and irregularly sampled datasets the proposed algorithm is already a great improvement.

Gait performance is not influenced by working memory when walking at a self-selected pace.

PubMed

Grubaugh, Jordan; Rhea, Christopher K

2014-02-01

Gait performance exhibits patterns within the stride-to-stride variability that can be indexed using detrended fluctuation analysis (DFA). Previous work employing DFA has shown that gait patterns can be influenced by constraints, such as natural aging or disease, and they are informative regarding a person's functional ability. Many activities of daily living require concurrent performance in the cognitive and gait domains; specifically working memory is commonly engaged while walking, which is considered dual-tasking. It is unknown if taxing working memory while walking influences gait performance as assessed by DFA. This study used a dual-tasking paradigm to determine if performance decrements are observed in gait or working memory when performed concurrently. Healthy young participants (N = 16) performed a working memory task (automated operation span task) and a gait task (walking at a self-selected speed on a treadmill) in single- and dual-task conditions. A second dual-task condition (reading while walking) was included to control for visual attention, but also introduced a task that taxed working memory over the long term. All trials involving gait lasted at least 10 min. Performance in the working memory task was indexed using five dependent variables (absolute score, partial score, speed error, accuracy error, and math error), while gait performance was indexed by quantifying the mean, standard deviation, and DFA α of the stride interval time series. Two multivariate analyses of variance (one for gait and one for working memory) were used to examine performance in the single- and dual-task conditions. No differences were observed in any of the gait or working memory dependent variables as a function of task condition. The results suggest the locomotor system is adaptive enough to complete a working memory task without compromising gait performance when walking at a self-selected pace.

Constant-torque thermal cycling and two-way shape memory effect in Ni50.3Ti29.7Hf20 torque tubes

NASA Astrophysics Data System (ADS)

Benafan, O.; Gaydosh, D. J.

2018-07-01

Ni-rich Ni50.3Ti29.7Hf20 (at%) high-temperature shape memory alloy tubes were thermomechanically cycled under constant torques. Four loading configurations were examined that consisted of a series of ascending stresses (low-to-high stress from 0 to 500 MPa outer fiber shear stress), a series of descending stresses (high-to-low stress from 500 to 0 MPa), and a series of thermal cycles at a constant stress of 500 MPa, all using an upper cycle temperature (UCT) of 300 °C. The last configuration consisted of another series of ascending stress levels using a lesser UCT of 250 °C. It was found that the descending series trial stabilized the material response in fewer cycles than the other loading paths. Similarly, cycling at a constant stress of 500 MPa for approximately 100 cycles reached near stabilization (<0.05% residual strain accumulation). Transformation shear strains were the highest and most stable when cycled from lower-to-higher stresses (ascending series), reaching 5.78% at 400 MPa. Cycling to lesser UCTs of 250 °C (versus 300 °C) resulted in the highest two-way shape memory effect (TWSME), measuring over 3.25%. This was attributed to the effect of retained martensite and any transformation dislocations that served to stabilize the TWSME at the lower UCT. Results of this study suggest that different training paths might be used, depending on actuator performance requirements, whether the principal need is to maximize transformation strain, maximize the two-way shear strain, or stabilize the response in fewer cycles.

Stress, Time Pressure, Strategy Selection and Math Anxiety in Mathematics: A Review of the Literature

PubMed Central

Caviola, Sara; Carey, Emma; Mammarella, Irene C.; Szucs, Denes

2017-01-01

We review how stress induction, time pressure manipulations and math anxiety can interfere with or modulate selection of problem-solving strategies (henceforth “strategy selection”) in arithmetical tasks. Nineteen relevant articles were identified, which contain references to strategy selection and time limit (or time manipulations), with some also discussing emotional aspects in mathematical outcomes. Few of these take cognitive processes such as working memory or executive functions into consideration. We conclude that due to the sparsity of available literature our questions can only be partially answered and currently there is not much evidence of clear associations. We identify major gaps in knowledge and raise a series of open questions to guide further research. PMID:28919870

Quasi-dynamic Earthquake Cycle Simulation in a Viscoelastic Medium with Memory Variables

NASA Astrophysics Data System (ADS)

Hirahara, K.; Ohtani, M.; Shikakura, Y.

2011-12-01

Earthquake cycle simulations based on rate and state friction laws have successfully reproduced the observed complex earthquake cycles at subduction zones. Most of simulations have assumed elastic media. The lower crust and the upper mantle have, however, viscoelastic properties, which cause postseismic stress relaxation. Hence the slip evolution on the plate interfaces or the faults in long earthquake cycles is different from that in elastic media. Especially, the viscoelasticity plays an important role in the interactive occurrence of inland and great interplate earthquakes. In viscoelastic media, the stress is usually calculated by the temporal convolution of the slip response function matrix and the slip deficit rate vector, which needs the past history of slip rates at all cells. Even if properly truncating the convolution, it requires huge computations. This is why few simulation studies have considered viscoelastic media so far. In this study, we examine the method using memory variables or anelastic functions, which has been developed for the time-domain finite-difference calculation of seismic waves in a dissipative medium (e.g., Emmerich and Korn,1987; Moczo and Kristek, 2005). The procedure for stress calculation with memory variables is as follows. First, we approximate the time-domain slip response function calculated in a viscoelastic medium with a series of relaxation functions with coefficients and relaxation times derived from a generalized Maxell body model. Then we can define the time-domain material-independent memory variable or anelastic function for each relaxation mechanism. Each time-domain memory variable satisfies the first-order differential equation. As a result, we can calculate the stress simply by the product of the unrelaxed modulus and the slip deficit subtracted from the sum of memory variables without temporal convolution. With respect to computational cost, we can summarize as in the followings. Dividing the plate interface into N cells, in elastic media, the stress at all cells is calculated by the product of the slip response function matrix and the slip deficit vector. The computational cost is O(N**2). With H-matrices method, we can reduce this to O(N)-O(NlogN) (Ohtani et al. 2011). The memory size is also reduced from O(N**2) to O(N). In viscoelastic media, the product of the unrelaxed modulus matrix and the vector of the slip deficit subtracted from the sum of memory variables costs O(N) with H-matrices method, which is the same as in elastic ones. If we use m relaxation functions, m x N differential equations are additionally solved at a time. The increase in memory size is (4m+1) x N**2. For approximation of slip response function, we need to estimate coefficients and relaxation times for m relaxation functions non-linearly with constraints. Because it is difficult to execute the non-linear least square estimation with constraints, we consider only m=2 with satisfying constraints. Test calculations in a layered or 3-D heterogeneous viscoelastic structure show this gives the satisfactory approximation. As an example, we report a 2-D earthquake cycle simulation for the 2011 giant Tohoku earthquake in a layered viscoelastic medium.

Flexible Kernel Memory

PubMed Central

Nowicki, Dimitri; Siegelmann, Hava

2010-01-01

This paper introduces a new model of associative memory, capable of both binary and continuous-valued inputs. Based on kernel theory, the memory model is on one hand a generalization of Radial Basis Function networks and, on the other, is in feature space, analogous to a Hopfield network. Attractors can be added, deleted, and updated on-line simply, without harming existing memories, and the number of attractors is independent of input dimension. Input vectors do not have to adhere to a fixed or bounded dimensionality; they can increase and decrease it without relearning previous memories. A memory consolidation process enables the network to generalize concepts and form clusters of input data, which outperforms many unsupervised clustering techniques; this process is demonstrated on handwritten digits from MNIST. Another process, reminiscent of memory reconsolidation is introduced, in which existing memories are refreshed and tuned with new inputs; this process is demonstrated on series of morphed faces. PMID:20552013

Conditional load and store in a shared memory

DOEpatents

Blumrich, Matthias A; Ohmacht, Martin

2015-02-03

A method, system and computer program product for implementing load-reserve and store-conditional instructions in a multi-processor computing system. The computing system includes a multitude of processor units and a shared memory cache, and each of the processor units has access to the memory cache. In one embodiment, the method comprises providing the memory cache with a series of reservation registers, and storing in these registers addresses reserved in the memory cache for the processor units as a result of issuing load-reserve requests. In this embodiment, when one of the processor units makes a request to store data in the memory cache using a store-conditional request, the reservation registers are checked to determine if an address in the memory cache is reserved for that processor unit. If an address in the memory cache is reserved for that processor, the data are stored at this address.

Pharmacologic Induction of CD8+ T Cell Memory: Better Living Through Chemistry

PubMed Central

Gattinoni, Luca; Klebanoff, Christopher A.; Restifo, Nicholas P.

2011-01-01

The generation of a robust population of memory T cells is critical for effective vaccine and cell-based therapies to prevent and treat infectious diseases and cancer. A series of recent papers have established a new, cell-intrinsic approach in which small molecules target key metabolic and developmental pathways to enhance the formation and maintenance of highly functional CD8+ memory T cells. These findings raise the exciting new possibility of using small molecules, many of which are already approved for human use, for the pharmacologic induction of immunologic memory. PMID:20371454

Cross-Linguistic Differences in the Immediate Serial Recall of Consonants versus Vowels

ERIC Educational Resources Information Center

Kissling, Elizabeth M.

2012-01-01

The current study investigated native English and native Arabic speakers' phonological short-term memory for sequences of consonants and vowels. Phonological short-term memory was assessed in immediate serial recall tasks conducted in Arabic and English for both groups. Participants (n = 39) heard series of six consonant-vowel syllables and wrote…

New Methodologies To Evaluate the Memory Strategies of Deaf Individuals.

ERIC Educational Resources Information Center

Clark, Diane

Prior studies have often confounded linguistic and perceptual performance when evaluating deaf subjects' skills, a confusion that may be responsible for results indicating lesser recall ability among the deaf. In this series of studies this linguistic/perceptual confound was investigated in both the iconic and short term memory of deaf…

Investigating the Effects of Veridicality on Age Differences in Verbal Working Memory

ERIC Educational Resources Information Center

Shake, Matthew C.; Perschke, Meghan K.

2013-01-01

In the typical loaded verbal working memory (WM) span task (e.g., Daneman & Carpenter, 1980), participants judge the veridicality of a series of sentences while simultaneously storing the sentence final word for later recall. Performance declines as the number of sentences is increased; aging exacerbates this decline. The present study examined…

An Examination of the Effects of Argument Mapping on Students' Memory and Comprehension Performance

ERIC Educational Resources Information Center

Dwyer, Christopher P.; Hogan, Michael J.; Stewart, Ian

2013-01-01

Argument mapping (AM) is a method of visually diagramming arguments to allow for easy comprehension of core statements and relations. A series of three experiments compared argument map reading and construction with hierarchical outlining, text summarisation, and text reading as learning methods by examining subsequent memory and comprehension…

Prefrontal Cortex: Role in Acquisition of Overlapping Associations and Transitive Inference

ERIC Educational Resources Information Center

DeVito, Loren M.; Lykken, Christine; Kanter, Benjamin R.; Eichenbaum, Howard

2010-01-01

"Transitive inference" refers to the ability to judge from memory the relationships between indirectly related items that compose a hierarchically organized series, and this capacity is considered a fundamental feature of relational memory. Here we explored the role of the prefrontal cortex in transitive inference by examining the performance of…

Centenarians' "holy" memory: is being positive enough?

PubMed

Fairfield, Beth; Mammarella, Nicola; Di Domenico, Alberto

2013-01-01

The authors compared 18 centenarians' (M age = 100.1 years, SD = 1.8 years) recognition memory for emotional (positive, negative, and religious) pictures with 18 older adults (M age = 75.2 years, SD = 6.8 years). Participants observed a series of images that varied in emotional valence and meaning and were later asked to discriminate between old and new images in a series of pictures that included studied images as well as new images. Centenarians showed decreased recognition memory for positive and negative images items compared with older adults, F(1, 34) = 9.82, p < .01. In addition, a significant age by valence interaction was observed highlighting how centenarians remembered religious pictures better while older adults favoured positive information when only positive pictures were taken into consideration. Results are interpreted in terms of possible age-linked changes in meaningful goals that lead centenarians to focus on meaningful religious self-relevant information rather than simply on positive information.

The therapeutic effect of Xueshuan Xinmai tablets on memory injury and brain activity in post-stroke patients: a pilot placebo controlled fMRI study.

PubMed

Wei, Dongfeng; Lv, Chenlong; Zhang, Junying; Peng, Dantao; Hu, Liangping; Zhang, Zhanjun; Wang, Yongyan

2015-01-01

The purpose of this study was to explore the effects of Xueshuan Xinmai tablets (XXMT) for the treatment of cognition, brain activation in the rehabilitation period of ischemic stroke patients. 28 adults patients, aged 50-80 years, in the rehabilitation period of ischemic stroke were divided into XXMT treatment group and placebo control group. Patients received 3 months treatment (oral 0.8 g, 3 times per day). Before and after treatment, all patients were evaluated by a series of neuropsychological tests followed by resting-state functional magnetic resonance imaging (fMRI). In the XXMT treatment group, the patients' episodic memory showed significant improvement. The resting-state fMRI analysis indicated that a significant decline in the fractional amplitude of low-frequency fluctuation value was observed in the bilateral middle cingulate gyrus. Yiqi Huoxue effect under XXMT administration has a favorable mediation on episodic memory, consequently suppresses the activation of the cingulate gyrus in the rehabilitation period of ischemic stroke patients.

Simultaneous estimation of deterministic and fractal stochastic components in non-stationary time series

NASA Astrophysics Data System (ADS)

García, Constantino A.; Otero, Abraham; Félix, Paulo; Presedo, Jesús; Márquez, David G.

2018-07-01

In the past few decades, it has been recognized that 1 / f fluctuations are ubiquitous in nature. The most widely used mathematical models to capture the long-term memory properties of 1 / f fluctuations have been stochastic fractal models. However, physical systems do not usually consist of just stochastic fractal dynamics, but they often also show some degree of deterministic behavior. The present paper proposes a model based on fractal stochastic and deterministic components that can provide a valuable basis for the study of complex systems with long-term correlations. The fractal stochastic component is assumed to be a fractional Brownian motion process and the deterministic component is assumed to be a band-limited signal. We also provide a method that, under the assumptions of this model, is able to characterize the fractal stochastic component and to provide an estimate of the deterministic components present in a given time series. The method is based on a Bayesian wavelet shrinkage procedure that exploits the self-similar properties of the fractal processes in the wavelet domain. This method has been validated over simulated signals and over real signals with economical and biological origin. Real examples illustrate how our model may be useful for exploring the deterministic-stochastic duality of complex systems, and uncovering interesting patterns present in time series.

Single-qubit decoherence under a separable coupling to a random matrix environment

NASA Astrophysics Data System (ADS)

Carrera, M.; Gorin, T.; Seligman, T. H.

2014-08-01

This paper describes the dynamics of a quantum two-level system (qubit) under the influence of an environment modeled by an ensemble of random matrices. In distinction to earlier work, we consider here separable couplings and focus on a regime where the decoherence time is of the same order of magnitude as the environmental Heisenberg time. We derive an analytical expression in the linear response approximation, and study its accuracy by comparison with numerical simulations. We discuss a series of unusual properties, such as purity oscillations, strong signatures of spectral correlations (in the environment Hamiltonian), memory effects, and symmetry-breaking equilibrium states.

Facilitating the use of implicit memory and learning in the physical therapy management of individuals with Alzheimer disease: a case series.

PubMed

White, Laura; Ford, Matthew P; Brown, Cynthia J; Peel, Claire; Triebel, Kristen L

2014-01-01

Physical rehabilitation of individuals with Alzheimer disease (AD) is often complicated by impairments in explicit memory and learning. Rehabilitation strategies that facilitate the use of the preserved implicit memory system may be effective in treating patients with AD. The purpose of this case series is to describe the application of these strategies, including high-repetition practice, errorless learning (EL), and spaced retrieval, to the physical therapy management of individuals with moderate AD. Three women aged 89 to 95 years with moderate AD who resided in an assisted living facility participated in physical therapy to address their mobility limitations. Twelve physical therapy sessions were scheduled over a period of 4 weeks. Interventions were individually designed to address the mobility needs of each patient, and rehabilitation strategies based on implicit learning principles were integrated into the interventions. All patients participated in at least 10 of the 12 physical therapy sessions. Improvements in performance of objective measures of balance were observed in all patients, although only 1 patient's balance score exceeded the minimal detectable change. No significant clinical change was observed in any patients on the Timed Up and Go Test or self-selected gait speed. Principles of implicit learning were integrated into the interventions for these patients with moderate AD. However, the feasibility of applying the EL paradigm was limited. Further research on the effectiveness of EL, spaced retrieval, and other rehabilitation strategies that facilitate implicit learning of mobility skills in patients with AD is needed to promote optimal physical therapy outcomes in this patient population.

A space for mothers: grief as identity construction on memorial websites created by SIDS parents.

PubMed

Finlay, Christopher J; Krueger, Guenther

2011-01-01

In this article we conduct a textual analysis of memorial websites created by mothers who have experienced a loss due to sudden infant death syndrome (SIDS). Using an online Internet ethnographic approach, we reviewed a series of 20 sites in an attempt to analyze the motivations of the site creators as manifested in their online projects. We spent time on the sites, moving through all facets of them, following links, and experiencing them the way a visitor would encounter them. In this virtual exploration we uncovered personal narratives, community building, religious imagery, and numerous examples of social networking. We also analyzed guest books in order to understand who visits these sites and their reasons for doing so. We conclude that development of these sites are a process that helps some mothers in their grief and gives them a focus and activity that is helpful and perhaps healing. More importantly perhaps is the potential for community building and networking that this type of activity allows. As an extension of a real-world memorial such as a gravesite, a virtual mourning space provides more in the way of these types of communications. Our work suggests that memorial websites constructed by SIDS parents help in meaning and identity reconstruction after loss.

Rise of Racetrack Memory! Domain Wall Spin-Orbitronics

NASA Astrophysics Data System (ADS)

Parkin, Stuart

Memory-storage devices based on the current controlled motion of a series of domain walls (DWs) in magnetic racetracks promise performance and reliability beyond that of conventional magnetic disk drives and solid state storage devices (1). Racetracks that are formed from atomically thin, perpendicularly magnetized nano-wires, interfaced with adjacent metal layers with high spin-orbit coupling, give rise to domain walls that exhibit a chiral Néel structure (2). These DWs can be moved very efficiently with current via chiral spin-orbit torques (2,3). Record-breaking current-induced DW speeds exceeding 1,000 m/sec are found in synthetic antiferromagnetic structures (3) in which the net magnetization of the DWs is tuned to almost zero, making them ``invisible''. Based on these recent discoveries, Racetrack Memory devices have the potential to operate on picosecond timescales and at densities more than 100 times greater than other memory technologies. (1) S.S.P. Parkin et al., Science 320, 5873 (2008); S.S.P. Parkin and S.-H. Yang, Nat. Nano. 10, 195 (2015). (2) K.-S. Ryu metal. Nat. Nano. 8, 527 (2013). (3) S.-H. Yang, K.-S. Ryu and S.S.P. Parkin, Nat. Nano. 10, 221 (2015). (4). S.S.P. Parkin, Phys. Rev. Lett. 67, 3598 (1991).

Children's Drawings.

ERIC Educational Resources Information Center

Burgess, Ann W.; Hartman, Carol R.

1993-01-01

This paper reviews the literature on projective drawing tests and child sexual abuse, focusing on children's drawings as an associative tool for memory. The use of the event drawing series, which is a series of seven drawings by a child that graphically present the child's thinking about a specific event, is discussed. (JDD)

Shifting visual perspective during memory retrieval reduces the accuracy of subsequent memories.

PubMed

Marcotti, Petra; St Jacques, Peggy L

2018-03-01

Memories for events can be retrieved from visual perspectives that were never experienced, reflecting the dynamic and reconstructive nature of memories. Characteristics of memories can be altered when shifting from an own eyes perspective, the way most events are initially experienced, to an observer perspective, in which one sees oneself in the memory. Moreover, recent evidence has linked these retrieval-related effects of visual perspective to subsequent changes in memories. Here we examine how shifting visual perspective influences the accuracy of subsequent memories for complex events encoded in the lab. Participants performed a series of mini-events that were experienced from their own eyes, and were later asked to retrieve memories for these events while maintaining the own eyes perspective or shifting to an alternative observer perspective. We then examined how shifting perspective during retrieval modified memories by influencing the accuracy of recall on a final memory test. Across two experiments, we found that shifting visual perspective reduced the accuracy of subsequent memories and that reductions in vividness when shifting visual perspective during retrieval predicted these changes in the accuracy of memories. Our findings suggest that shifting from an own eyes to an observer perspective influences the accuracy of long-term memories.

Scale-free avalanche dynamics in the stock market

NASA Astrophysics Data System (ADS)

Bartolozzi, M.; Leinweber, D. B.; Thomas, A. W.

2006-10-01

Self-organized criticality (SOC) has been claimed to play an important role in many natural and social systems. In the present work we empirically investigate the relevance of this theory to stock-market dynamics. Avalanches in stock-market indices are identified using a multi-scale wavelet-filtering analysis designed to remove Gaussian noise from the index. Here, new methods are developed to identify the optimal filtering parameters which maximize the noise removal. The filtered time series is reconstructed and compared with the original time series. A statistical analysis of both high-frequency Nasdaq E-mini Futures and daily Dow Jones data is performed. The results of this new analysis confirm earlier results revealing a robust power-law behaviour in the probability distribution function of the sizes, duration and laminar times between avalanches. This power-law behaviour holds the potential to be established as a stylized fact of stock market indices in general. While the memory process, implied by the power-law distribution of the laminar times, is not consistent with classical models for SOC, we note that a power-law distribution of the laminar times cannot be used to rule out self-organized critical behaviour.

Verbal short-term memory as an articulatory system: evidence from an alternative paradigm.

PubMed

Cheung, Him; Wooltorton, Lana

2002-01-01

In a series of experiments, the role of articulatory rehearsal in verbal [corrected] short-term memory was examined via a shadowing-plus-recall paradigm. In this paradigm, subjects shadowed a word target presented closely after an auditory memory list before they recalled the list. The phonological relationship between the shadowing target and the final item on the memory list was manipulated. Experiments 1 and 2 demonstrated that targets sounding similar to the list-final memory item generally took longer to shadow than unrelated targets. This inhibitory effect of phonological relatedness was more pronounced with tense- than lax-vowel pseudoword recall lists. The interaction between vowel tenseness and phonological relatedness was replicated in Experiment 3 using shorter lists of real words. In Experiment 4, concurrent articulation was applied during list learning to block rehearsal; consequently, neither the phonological relatedness effect nor its interaction with vowel tenseness emerged. Experiments 5 and 6 manipulated the occurrence frequencies and lexicality of the recall items, respectively, instead of vowel tenseness. Unlike vowel tenseness, these non-articulatory memory factors failed to interact with the phonological relatedness effect. Experiment 7 orthogonally manipulated the vowel tenseness and frequencies of the recall items; slowing in shadowing times due to phonological relatedness was modulated by vowel tenseness but not frequency. Taken together, these results suggest that under the present paradigm, the modifying effect of vowel tenseness on the magnitude of slowing in shadowing due to phonological relatedness is indicative of a prominent articulatory component in verbal short-term retention. The shadowing-plus-recall approach avoids confounding overt recall into internal memory processing, which is an inherent problem of the traditional immediate serial recall and span tasks.

An extract of Salvia (sage) with anticholinesterase properties improves memory and attention in healthy older volunteers.

PubMed

Scholey, Andrew B; Tildesley, Nicola T J; Ballard, Clive G; Wesnes, Keith A; Tasker, Andrea; Perry, Elaine K; Kennedy, David O

2008-05-01

Species of Salvia (sage) have a long-standing reputation in European medical herbalism, including for memory enhancement. In recent controlled trials, administration of sage extracts with established cholinergic properties improved cognitive function in young adults. This randomised, placebo-controlled, double-blind, balanced, five-period crossover study investigated the acute effects on cognitive performance of a standardised extract of Salvia officinalis in older adults. Twenty volunteers (>65 years of age, mean = 72.95) received four active doses of extract (167, 333, 666 and 1332 mg) and a placebo with a 7-day wash-out period between visits. Assessment involved completion of the Cognitive Drug Research computerised assessment battery. On study days, treatments were administered immediately following a baseline assessment with further assessment at 1, 2.5, 4 and 6 h post treatment. Compared with the placebo condition (which exhibited the characteristic performance decline over the day), the 333-mg dose was associated with significant enhancement of secondary memory performance at all testing times. The same measure benefited to a lesser extent from other doses. There also were significant improvements to accuracy of attention following the 333-mg dose. In vitro analysis confirmed cholinesterase inhibiting properties for the extract. The overall pattern of results is consistent with a dose-related benefit to processes involved in efficient stimulus processing and/or memory consolidation rather than retrieval or working memory efficiency. These findings extend those of the memory-enhancing effects of Salvia extracts in younger populations and warrant further investigation in larger series, in other populations and with different dosing regimes.

Memory, Meaning, & Method: A View of Language Teaching. Second Edition.

ERIC Educational Resources Information Center

Stevick, Earl W.

The revised second edition of a 1976 book explores the literature of research on memory, creation of meaning in language learning, and second language teaching methodology, incorporating results of recent work in those areas. Each of the 12 chapters begins with a series of questions to be addressed and ends with further questions. Chapter topics…

Is There a Separate Visual Iconic Memory System? Final Report.

ERIC Educational Resources Information Center

Levie, W. Howard; Levie, Diane D.

The purpose of these studies was to provide evidence to support either the dual-coding hypothesis or the single-system hypothesis of human memory. In one experiment, college subjects were shown a mixed series of words and pictures either while simultaneously engaged in shadowing (repeating aloud) a prose passage presented via earphones or while…

Electrophysiological Correlates of Infant Recognition Memory: The Late Positive Component (LPC).

ERIC Educational Resources Information Center

Nelson, Charles A.

A series of studies has investigated the possibility that human infants performing tasks exhibit something like the P300, a positive-going brain wave associated with task performance and the updating of working memory among adults. Findings indicate that, when infants have the opportunity to form a template against which to compare a previously…

Is the Hippocampus Necessary for Visual and Verbal Binding in Working Memory?

ERIC Educational Resources Information Center

Baddeley, Alan; Allen, Richard; Vargha-Khadem, Faraneh

2010-01-01

A series of experiments test the recent claim that the hippocampus is necessary for the binding of features in working memory. Some potential limitations of studies underlying this claim are discussed, and an attempt is made to further test the hypothesis by studying a case of developmental amnesia whose extensively investigated pathology appears…

The Hippocampus and Memory for "What," "Where," and "When"

ERIC Educational Resources Information Center

Ergorul, Ceren; Eichenbaum, Howard

2004-01-01

Previous studies have indicated that nonhuman animals might have a capacity for episodic-like recall reflected in memory for "what" events that happened "where" and "when". These studies did not identify the brain structures that are critical to this capacity. Here we trained rats to remember single training episodes, each composed of a series of…

Children's Memories of Their Montessori Experience

ERIC Educational Resources Information Center

Tatsch, Joyce

2011-01-01

This article discusses the results of a survey conducted at the Princeton Montessori School (PMS) in New Jersey, a school serving age levels from infants through middle school. The author designed a series of five to six questions about memories of activities, teachers, and friends for all current K-8 students with a minimum of 1 year of…

The Precategorical Nature of Visual Short-Term Memory

ERIC Educational Resources Information Center

Quinlan, Philip T.; Cohen, Dale J.

2016-01-01

We conducted a series of recognition experiments that assessed whether visual short-term memory (VSTM) is sensitive to shared category membership of to-be-remembered (tbr) images of common objects. In Experiment 1 some of the tbr items shared the same basic level category (e.g., hand axe): Such items were no better retained than others. In the…

Providing the Public with Online Access to Large Bibliographic Data Bases.

ERIC Educational Resources Information Center

Firschein, Oscar; Summit, Roger K.

DIALOG, an interactive, computer-based information retrieval language, consists of a series of computer programs designed to make use of direct access memory devices in order to provide the user with a rapid means of identifying records within a specific memory bank. Using the system, a library user can be provided access to sixteen distinct and…

Sex differences in episodic memory: the impact of verbal and visuospatial ability.

PubMed

Herlitz, A; Airaksinen, E; Nordström, E

1999-10-01

The impact of verbal and visuospatial ability on sex differences in episodic memory was investigated. One hundred men and 100 women, 2040 years old, participated in a series of verbal and visuospatial tasks. Episodic memory was assessed in tasks that, to a greater or lesser extent, were verbal or visuospatial in nature. Results showed that women excelled in verbal production tasks and that men performed at a superior level on a mental rotation task. In addition, women tended to perform at a higher level than men on most episodic memory tasks. Taken together, the results demonstrated that (a) women perform at a higher level than men on most verbal episodic memory tasks and on some episodic memory tasks with a visuospatial component, and (b) women's higher performance on episodic memory tasks cannot fully be explained by their superior performance on verbal production tasks.

One bipolar transistor selector - One resistive random access memory device for cross bar memory array

NASA Astrophysics Data System (ADS)

Aluguri, R.; Kumar, D.; Simanjuntak, F. M.; Tseng, T.-Y.

2017-09-01

A bipolar transistor selector was connected in series with a resistive switching memory device to study its memory characteristics for its application in cross bar array memory. The metal oxide based p-n-p bipolar transistor selector indicated good selectivity of about 104 with high retention and long endurance showing its usefulness in cross bar RRAM devices. Zener tunneling is found to be the main conduction phenomena for obtaining high selectivity. 1BT-1R device demonstrated good memory characteristics with non-linearity of 2 orders, selectivity of about 2 orders and long retention characteristics of more than 105 sec. One bit-line pull-up scheme shows that a 650 kb cross bar array made with this 1BT1R devices works well with more than 10 % read margin proving its ability in future memory technology application.

Reconfigurable photonic crystals enabled by pressure-responsive shape-memory polymers

PubMed Central

Fang, Yin; Ni, Yongliang; Leo, Sin-Yen; Taylor, Curtis; Basile, Vito; Jiang, Peng

2015-01-01

Smart shape-memory polymers can memorize and recover their permanent shape in response to an external stimulus (for example, heat). They have been extensively exploited for a wide spectrum of applications ranging from biomedical devices to aerospace morphing structures. However, most of the existing shape-memory polymers are thermoresponsive and their performance is hindered by heat-demanding programming and recovery steps. Although pressure is an easily adjustable process variable such as temperature, pressure-responsive shape-memory polymers are largely unexplored. Here we report a series of shape-memory polymers that enable unusual ‘cold' programming and instantaneous shape recovery triggered by applying a contact pressure at ambient conditions. Moreover, the interdisciplinary integration of scientific principles drawn from two disparate fields—the fast-growing photonic crystal and shape-memory polymer technologies—enables fabrication of reconfigurable photonic crystals and simultaneously provides a simple and sensitive optical technique for investigating the intriguing shape-memory effects at nanoscale. PMID:26074349

Aging and Individual Differences in Binding During Sentence Understanding: Evidence from Temporary and Global Syntactic Attachment Ambiguities

PubMed Central

Payne, Brennan R.; Grison, Sarah; Gao, Xuefei; Christianson, Kiel; Morrow, Daniel G.; Stine-Morrow, Elizabeth A. L.

2013-01-01

We report an investigation of aging and individual differences in binding information during sentence understanding. An age-continuous sample of adults (N = 91), ranging from 18 to 81 years of age, read sentences in which a relative clause could be attached high to a head noun NP1, attached low to its modifying prepositional phrase NP2 (e.g., The son of the princess who scratched himself / herself in public was humiliated), or in which the attachment site of the relative clause was ultimately indeterminate (e.g., The maid of the princess who scratched herself in public was humiliated). Word-by-word reading times and comprehension (e.g., who scratched?) were measured. A series of mixed-effects models were fit to the data, revealing: (1) that, on average, NP1-attached sentences were harder to process and comprehend than NP2-attached sentences; (2) that these average effects were independently moderated by verbal working memory capacity and reading experience, with effects that were most pronounced in the oldest participants and; (3) that readers on average did not allocate extra time to resolve global ambiguities, though older adults with higher working memory span did. Findings are discussed in relation to current models of lifespan cognitive development, working memory, language experience, and the role of prosodic segmentation strategies in reading. Collectively, these data suggest that aging brings differences in sentence understanding, and these differences may depend on independent influences of verbal working memory capacity and reading experience. PMID:24291806

Aging and individual differences in binding during sentence understanding: evidence from temporary and global syntactic attachment ambiguities.

PubMed

Payne, Brennan R; Grison, Sarah; Gao, Xuefei; Christianson, Kiel; Morrow, Daniel G; Stine-Morrow, Elizabeth A L

2014-02-01

We report an investigation of aging and individual differences in binding information during sentence understanding. An age-continuous sample of adults (N=91), ranging from 18 to 81 years of age, read sentences in which a relative clause could be attached high to a head noun NP1, attached low to its modifying prepositional phrase NP2 (e.g., The son of the princess who scratched himself/herself in public was humiliated), or in which the attachment site of the relative clause was ultimately indeterminate (e.g., The maid of the princess who scratched herself in public was humiliated). Word-by-word reading times and comprehension (e.g., who scratched?) were measured. A series of mixed-effects models were fit to the data, revealing: (1) that, on average, NP1-attached sentences were harder to process and comprehend than NP2-attached sentences; (2) that these average effects were independently moderated by verbal working memory capacity and reading experience, with effects that were most pronounced in the oldest participants and; (3) that readers on average did not allocate extra time to resolve global ambiguities, though older adults with higher working memory span did. Findings are discussed in relation to current models of lifespan cognitive development, working memory, language experience, and the role of prosodic segmentation strategies in reading. Collectively, these data suggest that aging brings differences in sentence understanding, and these differences may depend on independent influences of verbal working memory capacity and reading experience. Copyright © 2013 Elsevier B.V. All rights reserved.

Nuclear cardiology apparatus and method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Applegate, R.J.; Ionnou, B.N.; Kearns, D.S.

1981-01-20

A nuclear cardiology system for use with a scintillation camera for evaluating cardiac function by real time measurement of the variation of radiation from the heart of a patient to whom is administered a radioactive tracer. The camera provides data describing the location of individual counts representing radiation events coming from the patient. The system segregates, in real time, counts corresponding to radiation from an electronically defined region of interest describing an investigated part of the heart, such as the left ventricle. Synchronized by the patient's electrocardiogram, time gated memory circuitry divides each heartbeat into a series of subintervals, andmore » stores indications of the respective amounts of radiation events emanating from the region of interest during each of the subintervals. Calculating circuitry scans the stored information and, based on the maximum and minimum respective radiation amounts detected in the subintervals, computes the fraction of blood ejected by the heart in each beat. A strip chart recorder provides a permanent representation of the curve of radiation from the region of interest, as defined by the indicated series of subinterval radiation amounts.« less

A unified nonlinear stochastic time series analysis for climate science

PubMed Central

Moon, Woosok; Wettlaufer, John S.

2017-01-01

Earth’s orbit and axial tilt imprint a strong seasonal cycle on climatological data. Climate variability is typically viewed in terms of fluctuations in the seasonal cycle induced by higher frequency processes. We can interpret this as a competition between the orbitally enforced monthly stability and the fluctuations/noise induced by weather. Here we introduce a new time-series method that determines these contributions from monthly-averaged data. We find that the spatio-temporal distribution of the monthly stability and the magnitude of the noise reveal key fingerprints of several important climate phenomena, including the evolution of the Arctic sea ice cover, the El Nio Southern Oscillation (ENSO), the Atlantic Nio and the Indian Dipole Mode. In analogy with the classical destabilising influence of the ice-albedo feedback on summertime sea ice, we find that during some time interval of the season a destabilising process operates in all of these climate phenomena. The interaction between the destabilisation and the accumulation of noise, which we term the memory effect, underlies phase locking to the seasonal cycle and the statistical nature of seasonal predictability. PMID:28287128

Simulating Responses of Gravitational-Wave Instrumentation

NASA Technical Reports Server (NTRS)

Armstrong, John; Edlund, Jeffrey; Vallisneri. Michele

2006-01-01

Synthetic LISA is a computer program for simulating the responses of the instrumentation of the NASA/ESA Laser Interferometer Space Antenna (LISA) mission, the purpose of which is to detect and study gravitational waves. Synthetic LISA generates synthetic time series of the LISA fundamental noises, as filtered through all the time-delay-interferometry (TDI) observables. (TDI is a method of canceling phase noise in temporally varying unequal-arm interferometers.) Synthetic LISA provides a streamlined module to compute the TDI responses to gravitational waves, according to a full model of TDI (including the motion of the LISA array and the temporal and directional dependence of the arm lengths). Synthetic LISA is written in the C++ programming language as a modular package that accommodates the addition of code for specific gravitational wave sources or for new noise models. In addition, time series for waves and noises can be easily loaded from disk storage or electronic memory. The package includes a Python-language interface for easy, interactive steering and scripting. Through Python, Synthetic LISA can read and write data files in Flexible Image Transport System (FITS), which is a commonly used astronomical data format.

A unified nonlinear stochastic time series analysis for climate science.

PubMed

Moon, Woosok; Wettlaufer, John S

2017-03-13

Earth's orbit and axial tilt imprint a strong seasonal cycle on climatological data. Climate variability is typically viewed in terms of fluctuations in the seasonal cycle induced by higher frequency processes. We can interpret this as a competition between the orbitally enforced monthly stability and the fluctuations/noise induced by weather. Here we introduce a new time-series method that determines these contributions from monthly-averaged data. We find that the spatio-temporal distribution of the monthly stability and the magnitude of the noise reveal key fingerprints of several important climate phenomena, including the evolution of the Arctic sea ice cover, the El Nio Southern Oscillation (ENSO), the Atlantic Nio and the Indian Dipole Mode. In analogy with the classical destabilising influence of the ice-albedo feedback on summertime sea ice, we find that during some time interval of the season a destabilising process operates in all of these climate phenomena. The interaction between the destabilisation and the accumulation of noise, which we term the memory effect, underlies phase locking to the seasonal cycle and the statistical nature of seasonal predictability.

A Series of Computational Neuroscience Labs Increases Comfort with MATLAB.

PubMed

Nichols, David F

2015-01-01

Computational simulations allow for a low-cost, reliable means to demonstrate complex and often times inaccessible concepts to undergraduates. However, students without prior computer programming training may find working with code-based simulations to be intimidating and distracting. A series of computational neuroscience labs involving the Hodgkin-Huxley equations, an Integrate-and-Fire model, and a Hopfield Memory network were used in an undergraduate neuroscience laboratory component of an introductory level course. Using short focused surveys before and after each lab, student comfort levels were shown to increase drastically from a majority of students being uncomfortable or with neutral feelings about working in the MATLAB environment to a vast majority of students being comfortable working in the environment. Though change was reported within each lab, a series of labs was necessary in order to establish a lasting high level of comfort. Comfort working with code is important as a first step in acquiring computational skills that are required to address many questions within neuroscience.

A Series of Computational Neuroscience Labs Increases Comfort with MATLAB

PubMed Central

Nichols, David F.

2015-01-01

Computational simulations allow for a low-cost, reliable means to demonstrate complex and often times inaccessible concepts to undergraduates. However, students without prior computer programming training may find working with code-based simulations to be intimidating and distracting. A series of computational neuroscience labs involving the Hodgkin-Huxley equations, an Integrate-and-Fire model, and a Hopfield Memory network were used in an undergraduate neuroscience laboratory component of an introductory level course. Using short focused surveys before and after each lab, student comfort levels were shown to increase drastically from a majority of students being uncomfortable or with neutral feelings about working in the MATLAB environment to a vast majority of students being comfortable working in the environment. Though change was reported within each lab, a series of labs was necessary in order to establish a lasting high level of comfort. Comfort working with code is important as a first step in acquiring computational skills that are required to address many questions within neuroscience. PMID:26557798

Precision Pointing in Space Using Arrays of Shape Memory Based Linear Actuators

NASA Astrophysics Data System (ADS)

Sonawane, Nikhil

Space systems such as communication satellites, earth observation satellites and telescope require accurate pointing to observe fixed targets over prolonged time. These systems typically use reaction wheels to slew the spacecraft and gimballing systems containing motors to achieve precise pointing. Motor based actuators have limited life as they contain moving parts that require lubrication in space. Alternate methods have utilized piezoelectric actuators. This paper presents Shape memory alloys (SMA) actuators for control of a deployable antenna placed on a satellite. The SMAs are operated as a series of distributed linear actuators. These distributed linear actuators are not prone to single point failures and although each individual actuator is imprecise due to hysteresis and temperature variation, the system as a whole achieves reliable results. The SMAs can be programmed to perform a series of periodic motion and operate as a mechanical guidance system that is not prone to damage from radiation or space weather. Efforts are focused on developing a system that can achieve 1 degree pointing accuracy at first, with an ultimate goal of achieving a few arc seconds accuracy. Bench top model of the actuator system has been developed and working towards testing the system under vacuum. A demonstration flight of the technology is planned aboard a CubeSat.

Resource-sharing between internal maintenance and external selection modulates attentional capture by working memory content.

PubMed

Kiyonaga, Anastasia; Egner, Tobias

2014-01-01

It is unclear why and under what circumstances working memory (WM) and attention interact. Here, we apply the logic of the time-based resource-sharing (TBRS) model of WM (e.g., Barrouillet et al., 2004) to explore the mixed findings of a separate, but related, literature that studies the guidance of visual attention by WM contents. Specifically, we hypothesize that the linkage between WM representations and visual attention is governed by a time-shared cognitive resource that alternately refreshes internal (WM) and selects external (visual attention) information. If this were the case, WM content should guide visual attention (involuntarily), but only when there is time for it to be refreshed in an internal focus of attention. To provide an initial test for this hypothesis, we examined whether the amount of unoccupied time during a WM delay could impact the magnitude of attentional capture by WM contents. Participants were presented with a series of visual search trials while they maintained a WM cue for a delayed-recognition test. WM cues could coincide with the search target, a distracter, or neither. We varied both the number of searches to be performed, and the amount of available time to perform them. Slowing of visual search by a WM matching distracter-and facilitation by a matching target-were curtailed when the delay was filled with fast-paced (refreshing-preventing) search trials, as was subsequent memory probe accuracy. WM content may, therefore, only capture visual attention when it can be refreshed, suggesting that internal (WM) and external attention demands reciprocally impact one another because they share a limited resource. The TBRS rationale can thus be applied in a novel context to explain why WM contents capture attention, and under what conditions that effect should be observed.

Resource-sharing between internal maintenance and external selection modulates attentional capture by working memory content

PubMed Central

Kiyonaga, Anastasia; Egner, Tobias

2014-01-01

It is unclear why and under what circumstances working memory (WM) and attention interact. Here, we apply the logic of the time-based resource-sharing (TBRS) model of WM (e.g., Barrouillet et al., 2004) to explore the mixed findings of a separate, but related, literature that studies the guidance of visual attention by WM contents. Specifically, we hypothesize that the linkage between WM representations and visual attention is governed by a time-shared cognitive resource that alternately refreshes internal (WM) and selects external (visual attention) information. If this were the case, WM content should guide visual attention (involuntarily), but only when there is time for it to be refreshed in an internal focus of attention. To provide an initial test for this hypothesis, we examined whether the amount of unoccupied time during a WM delay could impact the magnitude of attentional capture by WM contents. Participants were presented with a series of visual search trials while they maintained a WM cue for a delayed-recognition test. WM cues could coincide with the search target, a distracter, or neither. We varied both the number of searches to be performed, and the amount of available time to perform them. Slowing of visual search by a WM matching distracter—and facilitation by a matching target—were curtailed when the delay was filled with fast-paced (refreshing-preventing) search trials, as was subsequent memory probe accuracy. WM content may, therefore, only capture visual attention when it can be refreshed, suggesting that internal (WM) and external attention demands reciprocally impact one another because they share a limited resource. The TBRS rationale can thus be applied in a novel context to explain why WM contents capture attention, and under what conditions that effect should be observed. PMID:25221499

A Review of Luminescent Anionic Nano System: d10 Metallocyanide Excimers and Exciplexes in Alkali Halide Hosts

PubMed Central

Li, Xiaobo; Patterson, Howard H.

2013-01-01

Dicyanoaurate, dicyanoargentate, and dicyanocuprate ions in solution and doped in different alkali halide hosts exhibit interesting photophysical and photochemical behavior, such as multiple emission bands, exciplex tuning, optical memory, and thermochromism. This is attributed to the formation of different sizes of nanoclusters in solution and in doped hosts. A series of spectroscopic methods (luminescence, UV-reflectance, IR, and Raman) as well as theoretical calculations have confirmed the existence of excimers and exciplexes. This leads to the tunability of these nano systems over a wide wavelength interval. The population of these nanoclusters varies with temperature and external laser irradiation, which explains the thermochromism and optical memory. DFT calculations indicate an MLCT transition for each nanocluster and the emission energy decreases with increasing cluster size. This is in agreement with the relatively long life-time for the emission peaks and the multiple emission peaks dependence upon cluster concentration. PMID:28811397

Turbulence-induced persistence in laser beam wandering.

PubMed

Zunino, Luciano; Gulich, Damián; Funes, Gustavo; Pérez, Darío G

2015-07-01

We have experimentally confirmed the presence of long-memory correlations in the wandering of a thin Gaussian laser beam over a screen after propagating through a turbulent medium. A laboratory-controlled experiment was conducted in which coordinate fluctuations of the laser beam were recorded at a sufficiently high sampling rate for a wide range of turbulent conditions. Horizontal and vertical displacements of the laser beam centroid were subsequently analyzed by implementing detrended fluctuation analysis. This is a very well-known and widely used methodology to unveil memory effects from time series. Results obtained from this experimental analysis allow us to confirm that both coordinates behave as highly persistent signals for strong turbulent intensities. This finding is relevant for a better comprehension and modeling of the turbulence effects in free-space optical communication systems and other applications related to propagation of optical signals in the atmosphere.

[Synthesis and characterization of polylactide-based thermosetting polyurethanes with shape memory properties].

PubMed

Shi, Shuo; Gu, Lin; Yang, Yihu; Yu, Haibin; Chen, Rui; Xiao, Xianglian; Qiu, Jun

2016-06-25

A series of bio-based thermosetting polyurethanes (Bio-PUs) were synthesized by the crosslinking reaction of polylactide and its copolymers diols with hexamethylene diisocyanate (HDI) trimer. The obtained Bio-PUs were characterized by Fourier Transform Infrared Spectroscopy (FTIR), Differential Scanning Calorimetry (DSC), Thermal Gravimetric Analysis (TGA), universal tensile testing machine and cytotoxicity test. Results indicate that the PLA copolymer (P(LA-co-CL)) diols reduced the glass transition temperature (Tg) of Bio-PUs and improved their thermal stability, compared with PLA diols. The Bio-PUs synthesized from P (LA-co-CL) diols exhibit better mechanical performance and shape memory properties. Especially, Young modulus and elongation at break of the obtained Bio-PUs were 277.7 MPa and 230% respectively; the shape recovery time of the obtained Bio-PUs at body temperature was only 93 s. Furthermore, alamar blue assay results showed that the obtained Bio-PUs had no cell toxicity.

Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks.

PubMed

Vlachas, Pantelis R; Byeon, Wonmin; Wan, Zhong Y; Sapsis, Themistoklis P; Koumoutsakos, Petros

2018-05-01

We introduce a data-driven forecasting method for high-dimensional chaotic systems using long short-term memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high-dimensional dynamical systems in their reduced order space and are shown to be an effective set of nonlinear approximators of their attractor. We demonstrate the forecasting performance of the LSTM and compare it with Gaussian processes (GPs) in time series obtained from the Lorenz 96 system, the Kuramoto-Sivashinsky equation and a prototype climate model. The LSTM networks outperform the GPs in short-term forecasting accuracy in all applications considered. A hybrid architecture, extending the LSTM with a mean stochastic model (MSM-LSTM), is proposed to ensure convergence to the invariant measure. This novel hybrid method is fully data-driven and extends the forecasting capabilities of LSTM networks.

Multigrid Methods: Proceedings of the Copper Mountain Conference on Multigrid Methods (3rd) Held in Copper Mountain, Colorado on April 5-10, 1987

DTIC Science & Technology

1988-08-01

Time Series 53. J. Barros-Neto and R. A. Artino, Hypoelliptic Boundary-Value Problems 54. R. L. Sternberg, A. J. Kalinowski, and J. S. Papadakis... Systems 95. C E. AuL Rings of Continuous Functions 96. R. Chuaqui, Analysis , Geometry, and Probability 97. L. Fuchs and L. Sace, Modules Over...Local Refinements for a Class of Nonshared Memory Systems 449 Hermann Mierendorif Analysis of a Multigrid Method for the Euler Equations of Gas Dynamics

Cognitive load and task condition in event- and time-based prospective memory: an experimental investigation.

PubMed

Khan, Azizuddin; Sharma, Narendra K; Dixit, Shikha

2008-09-01

Prospective memory is memory for the realization of delayed intention. Researchers distinguish 2 kinds of prospective memory: event- and time-based (G. O. Einstein & M. A. McDaniel, 1990). Taking that distinction into account, the present authors explored participants' comparative performance under event- and time-based tasks. In an experimental study of 80 participants, the authors investigated the roles of cognitive load and task condition in prospective memory. Cognitive load (low vs. high) and task condition (event- vs. time-based task) were the independent variables. Accuracy in prospective memory was the dependent variable. Results showed significant differential effects under event- and time-based tasks. However, the effect of cognitive load was more detrimental in time-based prospective memory. Results also revealed that time monitoring is critical in successful performance of time estimation and so in time-based prospective memory. Similarly, participants' better performance on the event-based prospective memory task showed that they acted on the basis of environment cues. Event-based prospective memory was environmentally cued; time-based prospective memory required self-initiation.

Enhanced zinc consumption causes memory deficits and increased brain levels of zinc

USGS Publications Warehouse

Flinn, J.M.; Hunter, D.; Linkous, D.H.; Lanzirotti, A.; Smith, L.N.; Brightwell, J.; Jones, B.F.

2005-01-01

Zinc deficiency has been shown to impair cognitive functioning, but little work has been done on the effects of elevated zinc. This research examined the effect on memory of raising Sprague-Dawley rats on enhanced levels of zinc (10 ppm ZnCO3; 0.153 mM) in the drinking water for periods of 3 or 9 months, both pre- and postnatally. Controls were raised on lab water. Memory was tested in a series of Morris Water Maze (MWM) experiments, and zinc-treated rats were found to have impairments in both reference and working memory. They were significantly slower to find a stationary platform and showed greater thigmotaxicity, a measure of anxiety. On a working memory task, where the platform was moved each day, zinc-treated animals had longer latencies over both trials and days, swam further from the platform, and showed greater thigmotaxicity. On trials using an Atlantis platform, which remained in one place but was lowered on probe trials, the zinc-treated animals had significantly fewer platform crossings, spent less time in the target quadrant, and did not swim as close to the platform position. They had significantly greater latency on nonprobe trials. Microprobe synchrotron X-ray fluorescence (??SXRF) confirmed that brain zinc levels were increased by adding ZnCO 3 to the drinking water. These data show that long-term dietary administration of zinc can lead to impairments in cognitive function. ?? 2004 Elsevier Inc. All rights reserved.

Multi-step prediction for influenza outbreak by an adjusted long short-term memory.

PubMed

Zhang, J; Nawata, K

2018-05-01

Influenza results in approximately 3-5 million annual cases of severe illness and 250 000-500 000 deaths. We urgently need an accurate multi-step-ahead time-series forecasting model to help hospitals to perform dynamical assignments of beds to influenza patients for the annually varied influenza season, and aid pharmaceutical companies to formulate a flexible plan of manufacturing vaccine for the yearly different influenza vaccine. In this study, we utilised four different multi-step prediction algorithms in the long short-term memory (LSTM). The result showed that implementing multiple single-output prediction in a six-layer LSTM structure achieved the best accuracy. The mean absolute percentage errors from two- to 13-step-ahead prediction for the US influenza-like illness rates were all <15%, averagely 12.930%. To the best of our knowledge, it is the first time that LSTM has been applied and refined to perform multi-step-ahead prediction for influenza outbreaks. Hopefully, this modelling methodology can be applied in other countries and therefore help prevent and control influenza worldwide.

Rewarded remembering: dissociations between self-rated motivation and memory performance.

PubMed

Ngaosuvan, Leonard; Mäntylä, Timo

2005-08-01

People often claim that they perform better in memory performance tasks when they are more motivated. However, past research has shown minimal effects of motivation on memory performance when factors contributing to item-specific biases during encoding and retrieval are taken into account. The purpose of the present study was to examine the generality of this apparent dissociation by using more sensitive measures of experienced motivation and memory performance. Extrinsic motivation was manipulated through competition instructions, and subjective ratings of intrinsic and extrinsic motivation were obtained before and after study instructions. Participants studied a series of words, and memory performance was assessed by content recall (Experiment 1) and source recall (Experiment 2). Both experiments showed dissociation between subjective ratings of extrinsic motivation and actual memory performance, so that competition increased self-rated extrinsic motivation but had no effects on memory performance, including source recall. Inconsistent with most people's expectations, the findings suggest that extrinsic motivation has minimal effects on memory performance.

Direct Electrical Stimulation of the Human Entorhinal Region and Hippocampus Impairs Memory.

PubMed

Jacobs, Joshua; Miller, Jonathan; Lee, Sang Ah; Coffey, Tom; Watrous, Andrew J; Sperling, Michael R; Sharan, Ashwini; Worrell, Gregory; Berry, Brent; Lega, Bradley; Jobst, Barbara C; Davis, Kathryn; Gross, Robert E; Sheth, Sameer A; Ezzyat, Youssef; Das, Sandhitsu R; Stein, Joel; Gorniak, Richard; Kahana, Michael J; Rizzuto, Daniel S

2016-12-07

Deep brain stimulation (DBS) has shown promise for treating a range of brain disorders and neurological conditions. One recent study showed that DBS in the entorhinal region improved the accuracy of human spatial memory. Based on this line of work, we performed a series of experiments to more fully characterize the effects of DBS in the medial temporal lobe on human memory. Neurosurgical patients with implanted electrodes performed spatial and verbal-episodic memory tasks. During the encoding periods of both tasks, subjects received electrical stimulation at 50 Hz. In contrast to earlier work, electrical stimulation impaired memory performance significantly in both spatial and verbal tasks. Stimulation in both the entorhinal region and hippocampus caused decreased memory performance. These findings indicate that the entorhinal region and hippocampus are causally involved in human memory and suggest that refined methods are needed to use DBS in these regions to improve memory. Copyright © 2016 Elsevier Inc. All rights reserved.

Consistency of handedness, regardless of direction, predicts baseline memory accuracy and potential for memory enhancement.

PubMed

Lyle, Keith B; Hanaver-Torrez, Shelley D; Hackländer, Ryan P; Edlin, James M

2012-01-01

Research has shown that consistently right-handed individuals have poorer memory than do inconsistently right- or left-handed individuals under baseline conditions but more reliably exhibit enhanced memory retrieval after making a series of saccadic eye movements. From this it could be that consistent versus inconsistent handedness, regardless of left/right direction, is an important individual difference factor in memory. Or, more specifically, it could be the presence or absence of consistent right-handedness that matters for memory. To resolve this ambiguity, we compared consistent and inconsistent left- and right-handers on associative recognition tests taken after saccades or a no-saccades control activity. Consistent-handers exhibited poorer memory than did inconsistent-handers following the control activity, and saccades enhanced retrieval for consistent-handers only. Saccades impaired retrieval for inconsistent-handers. None of these effects depended on left/right direction. Hence, this study establishes handedness consistency, regardless of direction, as an important individual difference factor in memory.

Emotional memory is perceptual.

PubMed

Arntz, Arnoud; de Groot, Corlijn; Kindt, Merel

2005-03-01

In two experiments it was investigated which aspects of memory are influenced by emotion. Using a framework proposed by Roediger (American Psychologist 45 (1990) 1043-1056), two dimensions relevant for memory were distinguished the implicit-explicit distinction, and the perceptual versus conceptual distinction. In week 1, subjects viewed a series of slides accompanied with a spoken story in either of the two versions, a neutral version, or a version with an emotional mid-phase. In week 2, memory performance for the slides and story was assessed unexpectedly. A free recall test revealed superior memory in the emotional condition for the story's mid-phase stimuli as compared to the neutral condition, replicating earlier findings. Furthermore, memory performance was assessed using tests that systematically assessed all combinations of implicit versus explicit and perceptual versus conceptual memory. Subjects who had listened to the emotional story had superior perceptual memory, on both implicit and explicit level, compared to those who had listened to the neutral story. Conceptual memory was not superior in the emotional condition. The results suggest that emotion specifically promotes perceptual memory, probably by better encoding of perceptual aspects of emotional experiences. This might be related to the prominent position of perceptual memories in traumatic memory, manifest in intrusions, nightmares and reliving experiences.

Beneficial effect of commercial Rhodiola extract in rats with scopolamine-induced memory impairment on active avoidance.

PubMed

Vasileva, Liliya V; Getova, Damianka P; Doncheva, Nina D; Marchev, Andrey S; Georgiev, Milen I

2016-12-04

Rhodiola rosea L., family Crassulaceae also known as Golden Root or Arctic root is one of the most widely used medicinal plants with effect on cognitive dysfunction, psychological stress and depression. The aim of the study was to examine the effect of a standardized commercial Rhodiola extract on learning and memory processes in naive rats as well as its effects in rats with scopolamine-induced memory impairment. Sixty male Wistar rats were used in the study. The experiment was conducted in two series - on naive rats and on rats with scopolamine-induced model of impaired memory. The active avoidance test was performed in an automatic conventional shuttle box set-up. The criteria used were the number of conditional stimuli (avoidances), the number of unconditioned stimuli (escapes) as well as the number of intertrial crossings. The chemical fingerprinting of the standardized commercial Rhodiola extract was performed by means of nuclear magnetic resonance (NMR). Naive rats treated with standardized Rhodiola extract increased the number of avoidances during the learning session and memory retention test compared to the controls. Rats with scopolamine-induced memory impairment treated with Rhodiola extract showed an increase in the number of avoidances during the learning session and on the memory tests compared to the scopolamine group. The other two parameters were not changed in rats treated with the extract of Rhodiola in the two series. It was found that the studied Rhodiola extract exerts a beneficial effect on learning and memory processes in naive rats and rats with scopolamine-induced memory impairment. The observed effect is probably due to multiple underlying mechanisms including its modulating effect on acetylcholine levels in the brain and MAO-inhibitory activity leading to stimulation of the monoamines' neurotransmission. In addition the pronounced stress-protective properties of Rhodiola rosea L. could also play a role in the improvement of cognitive functions. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Behavioral and Neural Correlates of Executive Function: Interplay between Inhibition and Updating Processes.

PubMed

Kim, Na Young; Wittenberg, Ellen; Nam, Chang S

2017-01-01

This study investigated the interaction between two executive function processes, inhibition and updating, through analyses of behavioral, neurophysiological, and effective connectivity metrics. Although, many studies have focused on behavioral effects of executive function processes individually, few studies have examined the dynamic causal interactions between these two functions. A total of twenty participants from a local university performed a dual task combing flanker and n-back experimental paradigms, and completed the Operation Span Task designed to measure working memory capacity. We found that both behavioral (accuracy and reaction time) and neurophysiological (P300 amplitude and alpha band power) metrics on the inhibition task (i.e., flanker task) were influenced by the updating load (n-back level) and modulated by working memory capacity. Using independent component analysis, source localization (DIPFIT), and Granger Causality analysis of the EEG time-series data, the present study demonstrated that manipulation of cognitive demand in a dual executive function task influenced the causal neural network. We compared connectivity across three updating loads (n-back levels) and found that experimental manipulation of working memory load enhanced causal connectivity of a large-scale neurocognitive network. This network contains the prefrontal and parietal cortices, which are associated with inhibition and updating executive function processes. This study has potential applications in human performance modeling and assessment of mental workload, such as the design of training materials and interfaces for those performing complex multitasking under stress.

A random access memory immune to single event upset using a T-Resistor

DOEpatents

Ochoa, A. Jr.

1987-10-28

In a random access memory cell, a resistance ''T'' decoupling network in each leg of the cell reduces random errors caused by the interaction of energetic ions with the semiconductor material forming the cell. The cell comprises two parallel legs each containing a series pair of complementary MOS transistors having a common gate connected to the node between the transistors of the opposite leg. The decoupling network in each leg is formed by a series pair of resistors between the transistors together with a third resistor interconnecting the junction between the pair of resistors and the gate of the transistor pair forming the opposite leg of the cell. 4 figs.

Random access memory immune to single event upset using a T-resistor

DOEpatents

Ochoa, Jr., Agustin

1989-01-01

In a random access memory cell, a resistance "T" decoupling network in each leg of the cell reduces random errors caused by the interaction of energetic ions with the semiconductor material forming the cell. The cell comprises two parallel legs each containing a series pair of complementary MOS transistors having a common gate connected to the node between the transistors of the opposite leg. The decoupling network in each leg is formed by a series pair of resistors between the transistors together with a third resistor interconnecting the junction between the pair of resistors and the gate of the transistor pair forming the opposite leg of the cell.

Category Specificity in Normal Episodic Learning: Applications to Object Recognition and Category-Specific Agnosia

ERIC Educational Resources Information Center

Bukach, Cindy M.; Bub, Daniel N.; Masson, Michael E. J.; Lindsay, D. Stephen

2004-01-01

Studies of patients with category-specific agnosia (CSA) have given rise to multiple theories of object recognition, most of which assume the existence of a stable, abstract semantic memory system. We applied an episodic view of memory to questions raised by CSA in a series of studies examining normal observers' recall of newly learned attributes…

Improving Problem Solving in Primary School Students: The Effect of a Training Programme Focusing on Metacognition and Working Memory

ERIC Educational Resources Information Center

Cornoldi, Cesare; Carretti, Barbara; Drusi, Silvia; Tencati, Chiara

2015-01-01

Background: Despite doubts voiced on their efficacy, a series of studies has been carried out on the capacity of training programmes to improve academic and reasoning skills by focusing on underlying cognitive abilities and working memory in particular. No systematic efforts have been made, however, to test training programmes that involve both…

On the Function of Stress Rhythms in Speech: Evidence of a Link with Grouping Effects on Serial Memory

ERIC Educational Resources Information Center

Boucher, Victor J.

2006-01-01

Language learning requires a capacity to recall novel series of speech sounds. Research shows that prosodic marks create grouping effects enhancing serial recall. However, any restriction on memory affecting the reproduction of prosody would limit the set of patterns that could be learned and subsequently used in speech. By implication, grouping…

Errors of Measurement, Theory, and Public Policy. William H. Angoff Memorial Lecture Series

ERIC Educational Resources Information Center

Kane, Michael

2010-01-01

The 12th annual William H. Angoff Memorial Lecture was presented by Dr. Michael T. Kane, ETS's (Educational Testing Service) Samuel J. Messick Chair in Test Validity and the former Director of Research at the National Conference of Bar Examiners. Dr. Kane argues that it is important for policymakers to recognize the impact of errors of measurement…

SciSpark: In-Memory Map-Reduce for Earth Science Algorithms

NASA Astrophysics Data System (ADS)

Ramirez, P.; Wilson, B. D.; Whitehall, K. D.; Palamuttam, R. S.; Mattmann, C. A.; Shah, S.; Goodman, A.; Burke, W.

2016-12-01

We are developing a lightning fast Big Data technology called SciSpark based on ApacheTM Spark under a NASA AIST grant (PI Mattmann). Spark implements the map-reduce paradigm for parallel computing on a cluster, but emphasizes in-memory computation, "spilling" to disk only as needed, and so outperforms the disk-based Apache Hadoop by 100x in memory and by 10x on disk. SciSpark extends Spark to support Earth Science use in three ways: Efficient ingest of N-dimensional geo-located arrays (physical variables) from netCDF3/4, HDF4/5, and/or OPeNDAP URLS; Array operations for dense arrays in scala and Java using the ND4S/ND4J or Breeze libraries; Operations to "split" datasets across a Spark cluster by time or space or both. For example, a decade-long time-series of geo-variables can be split across time to enable parallel "speedups" of analysis by day, month, or season. Similarly, very high-resolution climate grids can be partitioned into spatial tiles for parallel operations across rows, columns, or blocks. In addition, using Spark's gateway into python, PySpark, one can utilize the entire ecosystem of numpy, scipy, etc. Finally, SciSpark Notebooks provide a modern eNotebook technology in which scala, python, or spark-sql codes are entered into cells in the Notebook and executed on the cluster, with results, plots, or graph visualizations displayed in "live widgets". We have exercised SciSpark by implementing three complex Use Cases: discovery and evolution of Mesoscale Convective Complexes (MCCs) in storms, yielding a graph of connected components; PDF Clustering of atmospheric state using parallel K-Means; and statistical "rollups" of geo-variables or model-to-obs. differences (i.e. mean, stddev, skewness, & kurtosis) by day, month, season, year, and multi-year. Geo-variables are ingested and split across the cluster using methods on the sciSparkContext object including netCDFVariables() for spatial decomposition and wholeNetCDFVariables() for time-series. The presentation will cover the architecture of SciSpark, the design of the scientific RDD (sRDD) data structures for N-dim. arrays, results from the three science Use Cases, example Notebooks, lessons learned from the algorithm implementations, and parallel performance metrics.

Synthesis and characterization of shape memory poly (epsilon-caprolactone) polyurethane-ureas

NASA Astrophysics Data System (ADS)

Ren, Hongfeng

Shape memory polymers (SMPs) have attracted significant interest in recent times because of their potential applications in a number of areas, such as medical devices and textiles. However, there are some major drawbacks of SMPs, such as their relatively low moduli resulting in small recovery stresses, and their long response times compared with shape memory alloys (SMAs). A suitable recovery stress which comes from the elastic recovery stress generated in the deformation process is critical in some medical devices. To address some of these shortcomings, the work in this dissertation mainly focuses on the design and synthesis of linear shape memory polymers with higher recovery stress. A series of segmented poly (epsilon-caprolactone) polyurethane-ureas (PCLUUs) were prepared from poly (epsilon-caprolactone) (PCL) diol, different dissociates and chain extenders. NMR and FT-IR were used to identify the structure of the synthesized shape memory polyurethane-ureas. Parameters such as soft segment content (molecular weight and content), chain extender and the rigidity of the main chain were investigated to understand the structure-property relationships of the shape memory polymer systems through DSC, DMA, physical property test, etc. Cyclic thermal mechanic tests were applied to measure the shape memory properties which showed that the recovery stress can be improved above 200% simply by modifying the chain extender. Meanwhile, the synthesis process was optimized to be similar to that of Spandex /LYCRA®. Continuous fibers form shape memory polyurethane-ureas were made from a wet spinning process, which indicated excellent spinnability of the polymer solution. Small angle neutron scattering (SANS) was used to study the morphology of the hard segment at different temperatures and stretch rates and found that the monodisperse rigid cylinder model fit the SANS data quite well. From the cylinder model, the radius of the cylinder increased with increasing hard segment content. The SANS results revealed phase separation of hard and soft segments into nano scale domains. The overall objectives of this dissertation were: ■ To improve the recovery stress of linear shape memory polymers. ■ To study the morphology and structure property relationships of shape memory polymers. Chapter 1 reviews the literature on SMAs and SMPs, especially on linear SMPs. Chapter 2 is devoted to SMPUUs with the aliphatic amine 1, 4-Butanediamine (BDA) as chain extender. Chapter 3 reports the effects of different aliphatic diamines as the chain extenders. Chapter 4 covers the results for shape memory polyurethane-ureas with aromatic diamine 4, 4’-Methylenedianiline (MDA) as the chain extender. The effect of different diisocyanates is covered in Chapter 5. Chapter 6-7 show some synthesized polymer systems with unimproved recovery stress or even no shape memory properties. The overall conclusions of this work are reported in Chapter 8.

Working memory supports inference learning just like classification learning.

PubMed

Craig, Stewart; Lewandowsky, Stephan

2013-08-01

Recent research has found a positive relationship between people's working memory capacity (WMC) and their speed of category learning. To date, only classification-learning tasks have been considered, in which people learn to assign category labels to objects. It is unknown whether learning to make inferences about category features might also be related to WMC. We report data from a study in which 119 participants undertook classification learning and inference learning, and completed a series of WMC tasks. Working memory capacity was positively related to people's classification and inference learning performance.

Biography Today: Profiles of People of Interest to Young Readers. Author Series, Volume 3.

ERIC Educational Resources Information Center

Harris, Laurie Lanzen, Ed.; Abbey, Cherie D., Ed.

This is the third volume of the "Biography Today Author Series." Each volume contains alphabetically arranged sketches. Each entry provides at least one picture of the individual profiled with additional information about the birth, youth, early memories, education, first jobs, marriage and family, career highlights, memorable experiences,…

Biography Today: Profiles of People of Interest to Young Readers. Author Series, Volume 4.

ERIC Educational Resources Information Center

Harris, Laurie Lanzen, Ed.; Abbey, Cherie D., Ed.

This is the fourth volume of the "Biography Today Author Series." Each volume contains alphabetically arranged sketches. Each entry provides at least one picture of the individual profiled with additional information about the birth, youth, early memories, education, first jobs, marriage and family, career highlights, memorable experiences,…

HIV medication adherence and HIV symptom severity: the roles of sleep quality and memory.

PubMed

Babson, Kimberly A; Heinz, Adrienne J; Bonn-Miller, Marcel O

2013-10-01

The purpose of the current study was to examine the extent to which self-reported sleep quality, a clinically malleable factor, is associated with both HIV medication adherence and self-reported HIV symptom severity. In addition, we sought to examine whether sleep quality may explain the association between HIV medication adherence and symptom severity, as well as the role of self-reported memory functioning in terms of the above relations. This study took place from April 2010 to March 2012. Participants were 129 HIV-positive individuals who completed an ART pill count and series of structured clinical interviews and self-report questionnaires on sleep, memory, and HIV symptom severity. A series of regressions were conducted to test study hypotheses. After accounting for covariates (i.e., problematic alcohol, nicotine, and cannabis use, and mood disorder diagnosis), results indicated that self-reported sleep quality was associated with HIV medication adherence and self-reported HIV symptom severity, and that sleep quality partially mediated the relation between medication adherence and self-reported HIV symptom severity. In addition, memory functioning moderated the relation between self-reported sleep quality and HIV symptom severity, such that the interaction of poor sleep quality and relatively good memory functioning was associated with heightened self-reported HIV symptom severity. This study highlights the importance of assessing sleep and memory among HIV-infected individuals as they may represent treatment targets for those experiencing poor medication adherence or particularly severe HIV symptoms. Such information could lead to the inclusion of adjunct brief interventions to target sleep and memory functioning in order to reduce symptom severity among HIV-positive individuals with poor medication adherence.

Memory Applications Using Resonant Tunneling Diodes

NASA Astrophysics Data System (ADS)

Shieh, Ming-Huei

Resonant tunneling diodes (RTDs) producing unique folding current-voltage (I-V) characteristics have attracted considerable research attention due to their promising application in signal processing and multi-valued logic. The negative differential resistance of RTDs renders the operating points self-latching and stable. We have proposed a multiple -dimensional multiple-state RTD-based static random-access memory (SRAM) cell in which the number of stable states can significantly be increased to (N + 1)^ m or more for m number of N-peak RTDs connected in series. The proposed cells take advantage of the hysteresis and folding I-V characteristics of RTD. Several cell designs are presented and evaluated. A two-dimensional nine-state memory cell has been implemented and demonstrated by a breadboard circuit using two 2-peak RTDs. The hysteresis phenomenon in a series of RTDs is also further analyzed. The switch model provided in SPICE 3 can be utilized to simulate the hysteretic I-V characteristics of RTDs. A simple macro-circuit is described to model the hysteretic I-V characteristic of RTD for circuit simulation. A new scheme for storing word-wide multiple-bit information very efficiently in a single memory cell using RTDs is proposed. An efficient and inexpensive periphery circuit to read from and write into the cell is also described. Simulation results on the design of a 3-bit memory cell scheme using one-peak RTDs are also presented. Finally, a binary transistor-less memory cell which is only composed of a pair of RTDs and an ordinary rectifier diode is presented and investigated. A simple means for reading and writing information from or into the memory cell is also discussed.

Exploring heterogeneous market hypothesis using realized volatility

NASA Astrophysics Data System (ADS)

Chin, Wen Cheong; Isa, Zaidi; Mohd Nor, Abu Hassan Shaari

2013-04-01

This study investigates the heterogeneous market hypothesis using high frequency data. The cascaded heterogeneous trading activities with different time durations are modelled by the heterogeneous autoregressive framework. The empirical study indicated the presence of long memory behaviour and predictability elements in the financial time series which supported heterogeneous market hypothesis. Besides the common sum-of-square intraday realized volatility, we also advocated two power variation realized volatilities in forecast evaluation and risk measurement in order to overcome the possible abrupt jumps during the credit crisis. Finally, the empirical results are used in determining the market risk using the value-at-risk approach. The findings of this study have implications for informationally market efficiency analysis, portfolio strategies and risk managements.

Exploring the Effects of Working Memory on Time Perception in Attention Deficit Hyperactivity Disorder.

PubMed

Lee, Hom-Yi; Yang, En-Lin

2018-01-01

Children with attention deficit hyperactivity disorder (ADHD) are often reported to have deficits of time perception. However, there is a strong relation between performance on tasks of working memory and time perception. Thus, it is possible that the poor performance of children with ADHD on time perception results from their deficit of working memory. In this study, the working memory of participants was separately assessed; therefore, we could explore the relationship between working memory and time perception of children with ADHD. Fifty-six children with ADHD and those of healthy controls completed tasks measuring working memory and time perception. The results showed that the time discrimination ability of children with ADHD was poorer than that of controls. However, there was a strong association between time perception and working memory. After controlling working memory and intelligence, the time discrimination ability of children with ADHD was not significantly poorer than that of controls. We suggest that there is an interdependent relationship between time perception and working memory for children with ADHD.

On the Takayanagi principle for the shape memory effect and thermomechanical behaviors in polymers with multi-phases

NASA Astrophysics Data System (ADS)

Lu, Haibao; Yu, Kai; Huang, Wei Min; Leng, Jinsong

2016-12-01

We present an explicit model to study the mechanics and physics of the shape memory effect (SME) in polymers based on the Takayanagi principle. The molecular structural characteristics and elastic behavior of shape memory polymers (SMPs) with multi-phases are investigated in terms of the thermomechanical properties of the individual components, of which the contributions are combined by using Takayanagi’s series-parallel model and parallel-series model, respectively. After that, Boltzmann superposition principle is employed to couple the multi-SME, elastic modulus parameter (E) and temperature parameter (T) in SMPs. Furthermore, the extended Takayanagi model is proposed to separate the plasticizing effect and physical swelling effect on the thermo-/chemo-responsive SME in polymers and then compared with the available experimental data reported in the literature. This study is expected to provide a powerful simulation tool for modeling and experimental substantiation of the mechanics and working mechanism of SME in polymers.

Mindfulness Enhances Episodic Memory Performance: Evidence from a Multimethod Investigation

PubMed Central

Goodman, Robert J.; Ryan, Richard M.; Anālayo, Bhikkhu

2016-01-01

Training in mindfulness, classically described as a receptive attentiveness to present events and experiences, has been shown to improve attention and working memory. Both are key to long-term memory formation, and the present three-study series used multiple methods to examine whether mindfulness would enhance episodic memory, a key form of long-term memory. In Study 1 (N = 143), a self-reported state of mindful attention predicted better recognition performance in the Remember-Know (R-K) paradigm. In Study 2 (N = 93), very brief training in a focused attention form of mindfulness also produced better recognition memory performance on the R-K task relative to a randomized, well-matched active control condition. Study 3 (N = 57) extended these findings by showing that relative to randomized active and inactive control conditions the effect of very brief mindfulness training generalized to free-recall memory performance. This study also found evidence for mediation of the mindfulness training—episodic memory relation by intrinsic motivation. These findings indicate that mindful attention can beneficially impact motivation and episodic memory, with potential implications for educational and occupational performance. PMID:27115491

Mindfulness Enhances Episodic Memory Performance: Evidence from a Multimethod Investigation.

PubMed

Brown, Kirk Warren; Goodman, Robert J; Ryan, Richard M; Anālayo, Bhikkhu

2016-01-01

Training in mindfulness, classically described as a receptive attentiveness to present events and experiences, has been shown to improve attention and working memory. Both are key to long-term memory formation, and the present three-study series used multiple methods to examine whether mindfulness would enhance episodic memory, a key form of long-term memory. In Study 1 (N = 143), a self-reported state of mindful attention predicted better recognition performance in the Remember-Know (R-K) paradigm. In Study 2 (N = 93), very brief training in a focused attention form of mindfulness also produced better recognition memory performance on the R-K task relative to a randomized, well-matched active control condition. Study 3 (N = 57) extended these findings by showing that relative to randomized active and inactive control conditions the effect of very brief mindfulness training generalized to free-recall memory performance. This study also found evidence for mediation of the mindfulness training-episodic memory relation by intrinsic motivation. These findings indicate that mindful attention can beneficially impact motivation and episodic memory, with potential implications for educational and occupational performance.

Primacy of memory linkage in choice among valued objects.

PubMed

Jones, Gregory V; Martin, Maryanne

2006-12-01

Three psychological levels at which an object may be processed have been characterized by Norman (2004) in terms of the object's appearance, its usability, and its capacity to elicit memories. A series of experiments was carried out to investigate participants' choices among valued objects recalled in accordance with these three criteria. It was found consistently that objects selected for their capacity to elicit memories--here termed mnemoactive objects--were valued significantly more than the other objects. Even the financial or social importance of an object was outweighed by the importance of its memory link; possible implications for the economic analysis of subjective well-being are briefly discussed. The same pattern of mnemoactive dominance was found across age and gender. Appropriate choice of objects may allow an individual to exert a degree of indirect voluntary control over the activation of involuntary autobiographical memories, providing a new perspective on Proust's approach to memory.

Piracetam, an AMPAkine drug, facilitates memory consolidation in the day-old chick.

PubMed

Samartgis, Jodi R; Schachte, Leslie; Hazi, Agnes; Crowe, Simon F

2012-12-01

Piracetam is an AMPAkine drug that may have a range of different mechanisms at the cellular level, and which has been shown to facilitate memory, amongst its other effects. This series of experiments demonstrated that a 10mg/kg dose of piracetam facilitated memory consolidation in the day-old chick when injected from immediately until 120min after weak training (i.e. using a 20% v/v concentration of methyl anthranilate) with the passive avoidance learning task. Administration of piracetam immediately after training led to memory facilitation which lasted for up to 24h following training. This dose of the AMPAkine was not shown to facilitate memory reconsolidation. These findings support the contention that application of the AMPAkine piracetam facilitates memory using a weak training task, and extend the range of actions previously noted with NMDA-related agents to those which also facilitate the AMPA receptor. Copyright © 2012 Elsevier Inc. All rights reserved.

Age, gesture span, and dissociations among component subsystems of working memory.

PubMed

Dolman, R; Roy, E A; Dimeck, P T; Hall, C R

2000-01-01

Working memory was examined in old and young adults using a series of span tasks, including the forward versions of the visual-spatial and digit span tasks from the Wechsler Memory Scale-Revised, and comparable hand gesture and visual design span tasks. The observation that the young participants performed significantly better on all the tasks except digit span suggested that aging has an impact on some component subsystems of working memory but not others. Analyses of intercorrelations in span performance supports the dissociation among three component subsystems, one for auditory verbal information (the articulatory loop), one for visual-spatial information (visual-spatial scratch-pad), and one for hand/body postural configuration.

Characteristics of color memory for natural scenes

NASA Astrophysics Data System (ADS)

Amano, Kinjiro; Uchikawa, Keiji; Kuriki, Ichiro

2002-08-01

To study the characteristics of color memory for natural images, a memory-identification task was performed with differing color contrasts; three of the contrasts were defined by chromatic and luminance components of the image, and the others were defined with respect to the categorical colors. After observing a series of pictures successively, subjects identified the pictures using a confidence rating. Detection of increased contrasts tended to be harder than detection of decreased contrasts, suggesting that the chromaticness of pictures is enhanced in memory. Detecting changes within each color category was more difficult than across the categories. A multiple mechanism that processes color differences and categorical colors is briefly considered. 2002 Optical Society of America

Capattery double layer capacitor life performance

NASA Astrophysics Data System (ADS)

Evans, David A.; Clark, Nancy H.; Baca, W. E.; Miller, John R.; Barker, Thomas B.

Double layer capacitors (DLCs) have received increased use in computer memory backup applications for consumer products during the past ten years. Their extraordinarily high capacitance density along with their maintenance-free operation makes them particularly suited for these products. These same features also make DLCs very attractive in military type applications. Unfortunately, lifetime performance data has not been reported in the literature for any DLC component. Our objective in this study was to investigate the effects that voltage and temperature have on the properties and performance of single and series-connected DLCs as a function of time. Evans model RE110474, 0.47-farad, 11.0-volt Capatteries were evaluated. These components have a tantalum package, use welded construction, and contain a glass-to-metal seal, all incorporated to circumvent the typical DLC failure modes of electrolyte loss and container corrosion. A five-level, two-factor Central Composite Design was used in the study. Single and series-connected Capatteries rated at 85 C, 11.0-volts operation were subjected to test temperatures between 25 and 95 C, and voltages between 0 and 12.9 volts (9 test conditions). Measured responses included capacitance, equivalent series resistance, and discharge time. Data were analyzed using a regression analysis to obtain response functions relating DLC properties to their voltage, temperature, and test time history. These results are described and should aid system and component engineers in using DLCs in critical applications.

Case Series Investigations in Cognitive Neuropsychology

PubMed Central

Schwartz, Myrna F.; Dell, Gary S.

2011-01-01

Case series methodology involves the systematic assessment of a sample of related patients, with the goal of understanding how and why they differ from one another. This method has become increasingly important in cognitive neuropsychology, which has long been identified with single-subject research. We review case series studies dealing with impaired semantic memory, reading, and language production, and draw attention to the affinity of this methodology for testing theories that are expressed as computational models and for addressing questions about neuroanatomy. It is concluded that case series methods usefully complement single-subject techniques. PMID:21714756

Archiving and Near Real Time Visualization of USGS Instantaneous Data

NASA Astrophysics Data System (ADS)

Zaslavsky, I.; Ryan, D.; Whitenack, T.; Valentine, D. W.; Rodriguez, M.

2009-12-01

The CUAHSI Hydrologic Information System project has been developing databases, services and online and desktop software applications supporting standards-based publication and access to large volumes of hydrologic data from US federal agencies and academic partners. In particular, the CUAHSI WaterML 1.x schema specification for exchanging hydrologic time series, earlier published as an OGC Discussion Paper (2007), has been adopted by the United States Geological Survey to provide web service access to USGS daily values and instantaneous data. The latter service, making available raw measurements of discharge, gage height and several other parameters for over 10,000 USGS real time measurement points, was announced by USGS, as an experimental WaterML-compliant service, at the end of July 2009. We demonstrate an online application that leverages the new service for nearly continuous harvesting of USGS real time data, and simultaneous visualization and analysis of the data streams. To make this possible, we integrate service components of the CUAHSI software stack with Open Source Data Turbine (OSDT) system, an NSF-supported software environment for robust and scalable assimilation of multimedia data streams (e.g. from sensors), and interfacing with a variety of viewers, databases, archival systems and client applications. Our application continuously queries USGS Instantaneous water data service (which provides access to 15-min measurements updated at USGS every 4 hours), and maps the results for each station-variable combination to a separate "channel", which is used by OSDT to quickly access and manipulate the time series. About 15,000 channels are used, which makes it by far the largest deployment of OSDT. Using RealTime Data Viewer, users can now select one or more stations of interest (e.g. from upstream or downstream from each other), and observe and annotate simultaneous dynamics in the respective discharge and gage height values, using fast forward or backward modes, real-time mode, etc. Memory management, scheduling service-based retrieval from USGS web services, and organizing access to 7,330 selected stations, turned out to be the major challenges in this project. To allow station navigation, they are grouped by state and county in the user interface. Memory footprint has been monitored under different Java VM settings, to find the correct regime. These and other solutions are discussed in the paper, and accompanied with a series of examples of simultaneous visualization of discharge from multiple stations as a component of hydrologic analysis.

TIMESERIESSTREAMING.VI: LabVIEW program for reliable data streaming of large analog time series

NASA Astrophysics Data System (ADS)

Czerwinski, Fabian; Oddershede, Lene B.

2011-02-01

With modern data acquisition devices that work fast and very precise, scientists often face the task of dealing with huge amounts of data. These need to be rapidly processed and stored onto a hard disk. We present a LabVIEW program which reliably streams analog time series of MHz sampling. Its run time has virtually no limitation. We explicitly show how to use the program to extract time series from two experiments: For a photodiode detection system that tracks the position of an optically trapped particle and for a measurement of ionic current through a glass capillary. The program is easy to use and versatile as the input can be any type of analog signal. Also, the data streaming software is simple, highly reliable, and can be easily customized to include, e.g., real-time power spectral analysis and Allan variance noise quantification. Program summaryProgram title: TimeSeriesStreaming.VI Catalogue identifier: AEHT_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHT_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 250 No. of bytes in distributed program, including test data, etc.: 63 259 Distribution format: tar.gz Programming language: LabVIEW ( http://www.ni.com/labview/) Computer: Any machine running LabVIEW 8.6 or higher Operating system: Windows XP and Windows 7 RAM: 60-360 Mbyte Classification: 3 Nature of problem: For numerous scientific and engineering applications, it is highly desirable to have an efficient, reliable, and flexible program to perform data streaming of time series sampled with high frequencies and possibly for long time intervals. This type of data acquisition often produces very large amounts of data not easily streamed onto a computer hard disk using standard methods. Solution method: This LabVIEW program is developed to directly stream any kind of time series onto a hard disk. Due to optimized timing and usage of computational resources, such as multicores and protocols for memory usage, this program provides extremely reliable data acquisition. In particular, the program is optimized to deal with large amounts of data, e.g., taken with high sampling frequencies and over long time intervals. The program can be easily customized for time series analyses. Restrictions: Only tested in Windows-operating LabVIEW environments, must use TDMS format, acquisition cards must be LabVIEW compatible, driver DAQmx installed. Running time: As desirable: microseconds to hours

Resummed memory kernels in generalized system-bath master equations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mavros, Michael G.; Van Voorhis, Troy, E-mail: tvan@mit.edu

2014-08-07

Generalized master equations provide a concise formalism for studying reduced population dynamics. Usually, these master equations require a perturbative expansion of the memory kernels governing the dynamics; in order to prevent divergences, these expansions must be resummed. Resummation techniques of perturbation series are ubiquitous in physics, but they have not been readily studied for the time-dependent memory kernels used in generalized master equations. In this paper, we present a comparison of different resummation techniques for such memory kernels up to fourth order. We study specifically the spin-boson Hamiltonian as a model system bath Hamiltonian, treating the diabatic coupling between themore » two states as a perturbation. A novel derivation of the fourth-order memory kernel for the spin-boson problem is presented; then, the second- and fourth-order kernels are evaluated numerically for a variety of spin-boson parameter regimes. We find that resumming the kernels through fourth order using a Padé approximant results in divergent populations in the strong electronic coupling regime due to a singularity introduced by the nature of the resummation, and thus recommend a non-divergent exponential resummation (the “Landau-Zener resummation” of previous work). The inclusion of fourth-order effects in a Landau-Zener-resummed kernel is shown to improve both the dephasing rate and the obedience of detailed balance over simpler prescriptions like the non-interacting blip approximation, showing a relatively quick convergence on the exact answer. The results suggest that including higher-order contributions to the memory kernel of a generalized master equation and performing an appropriate resummation can provide a numerically-exact solution to system-bath dynamics for a general spectral density, opening the way to a new class of methods for treating system-bath dynamics.« less

Multimaterial 4D Printing with Tailorable Shape Memory Polymers

PubMed Central

Ge, Qi; Sakhaei, Amir Hosein; Lee, Howon; Dunn, Conner K.; Fang, Nicholas X.; Dunn, Martin L.

2016-01-01

We present a new 4D printing approach that can create high resolution (up to a few microns), multimaterial shape memory polymer (SMP) architectures. The approach is based on high resolution projection microstereolithography (PμSL) and uses a family of photo-curable methacrylate based copolymer networks. We designed the constituents and compositions to exhibit desired thermomechanical behavior (including rubbery modulus, glass transition temperature and failure strain which is more than 300% and larger than any existing printable materials) to enable controlled shape memory behavior. We used a high resolution, high contrast digital micro display to ensure high resolution of photo-curing methacrylate based SMPs that requires higher exposure energy than more common acrylate based polymers. An automated material exchange process enables the manufacture of 3D composite architectures from multiple photo-curable SMPs. In order to understand the behavior of the 3D composite microarchitectures, we carry out high fidelity computational simulations of their complex nonlinear, time-dependent behavior and study important design considerations including local deformation, shape fixity and free recovery rate. Simulations are in good agreement with experiments for a series of single and multimaterial components and can be used to facilitate the design of SMP 3D structures. PMID:27499417

Numerical integration of the extended variable generalized Langevin equation with a positive Prony representable memory kernel.

PubMed

Baczewski, Andrew D; Bond, Stephen D

2013-07-28

Generalized Langevin dynamics (GLD) arise in the modeling of a number of systems, ranging from structured fluids that exhibit a viscoelastic mechanical response, to biological systems, and other media that exhibit anomalous diffusive phenomena. Molecular dynamics (MD) simulations that include GLD in conjunction with external and/or pairwise forces require the development of numerical integrators that are efficient, stable, and have known convergence properties. In this article, we derive a family of extended variable integrators for the Generalized Langevin equation with a positive Prony series memory kernel. Using stability and error analysis, we identify a superlative choice of parameters and implement the corresponding numerical algorithm in the LAMMPS MD software package. Salient features of the algorithm include exact conservation of the first and second moments of the equilibrium velocity distribution in some important cases, stable behavior in the limit of conventional Langevin dynamics, and the use of a convolution-free formalism that obviates the need for explicit storage of the time history of particle velocities. Capability is demonstrated with respect to accuracy in numerous canonical examples, stability in certain limits, and an exemplary application in which the effect of a harmonic confining potential is mapped onto a memory kernel.

Using Long-Short-Term-Memory Recurrent Neural Networks to Predict Aviation Engine Vibrations

NASA Astrophysics Data System (ADS)

ElSaid, AbdElRahman Ahmed

This thesis examines building viable Recurrent Neural Networks (RNN) using Long Short Term Memory (LSTM) neurons to predict aircraft engine vibrations. The different networks are trained on a large database of flight data records obtained from an airline containing flights that suffered from excessive vibration. RNNs can provide a more generalizable and robust method for prediction over analytical calculations of engine vibration, as analytical calculations must be solved iteratively based on specific empirical engine parameters, and this database contains multiple types of engines. Further, LSTM RNNs provide a "memory" of the contribution of previous time series data which can further improve predictions of future vibration values. LSTM RNNs were used over traditional RNNs, as those suffer from vanishing/exploding gradients when trained with back propagation. The study managed to predict vibration values for 1, 5, 10, and 20 seconds in the future, with 2.84% 3.3%, 5.51% and 10.19% mean absolute error, respectively. These neural networks provide a promising means for the future development of warning systems so that suitable actions can be taken before the occurrence of excess vibration to avoid unfavorable situations during flight.

Pre-Experimental Familiarization Increases Hippocampal Activity for Both Targets and Lures in Recognition Memory: An fMRI Study

ERIC Educational Resources Information Center

de Zubicaray, Greig I.; McMahon, Katie L.; Hayward, Lydia; Dunn, John C.

2011-01-01

In the present study, items pre-exposed in a familiarization series were included in a list discrimination task to manipulate memory strength. At test, participants were required to discriminate strong targets and strong lures from weak targets and new lures. This resulted in a concordant pattern of increased "old" responses to strong targets and…

Sources of Variability in Working Memory in Early Childhood: A Consideration of Age, Temperament, Language, and Brain Electrical Activity

ERIC Educational Resources Information Center

Wolfe, Christy D.; Bell, Martha Ann

2007-01-01

This study investigated age-related differences in working memory and inhibitory control (WMIC) in 3 1/2-, 4-, and 4 1/2-year-olds and how these differences were associated with differences in regulatory aspects of temperament, language comprehension, and brain electrical activity. A series of cognitive control tasks was administered to measure…

Memory: As It Relates to Children Ages 9 to 12 Years. Skills Essential to Learning Television Project: Working Paper.

ERIC Educational Resources Information Center

Perry, Fred L., Jr.

An overview of theory and research in memory as it relates to developmental differences is offered in this paper, which is intended to provide background information for the staff of the Skills Essential to Learning Television Project (a multi-level series of video and print resources for classroom use). A model for viewing information processing…

IDSP- INTERACTIVE DIGITAL SIGNAL PROCESSOR

NASA Technical Reports Server (NTRS)

Mish, W. H.

1994-01-01

The Interactive Digital Signal Processor, IDSP, consists of a set of time series analysis "operators" based on the various algorithms commonly used for digital signal analysis work. The processing of a digital time series to extract information is usually achieved by the application of a number of fairly standard operations. However, it is often desirable to "experiment" with various operations and combinations of operations to explore their effect on the results. IDSP is designed to provide an interactive and easy-to-use system for this type of digital time series analysis. The IDSP operators can be applied in any sensible order (even recursively), and can be applied to single time series or to simultaneous time series. IDSP is being used extensively to process data obtained from scientific instruments onboard spacecraft. It is also an excellent teaching tool for demonstrating the application of time series operators to artificially-generated signals. IDSP currently includes over 43 standard operators. Processing operators provide for Fourier transformation operations, design and application of digital filters, and Eigenvalue analysis. Additional support operators provide for data editing, display of information, graphical output, and batch operation. User-developed operators can be easily interfaced with the system to provide for expansion and experimentation. Each operator application generates one or more output files from an input file. The processing of a file can involve many operators in a complex application. IDSP maintains historical information as an integral part of each file so that the user can display the operator history of the file at any time during an interactive analysis. IDSP is written in VAX FORTRAN 77 for interactive or batch execution and has been implemented on a DEC VAX-11/780 operating under VMS. The IDSP system generates graphics output for a variety of graphics systems. The program requires the use of Versaplot and Template plotting routines and IMSL Math/Library routines. These software packages are not included in IDSP. The virtual memory requirement for the program is approximately 2.36 MB. The IDSP system was developed in 1982 and was last updated in 1986. Versaplot is a registered trademark of Versatec Inc. Template is a registered trademark of Template Graphics Software Inc. IMSL Math/Library is a registered trademark of IMSL Inc.

Modification of existing human motor memories is enabled by primary cortical processing during memory reactivation.

PubMed

Censor, Nitzan; Dimyan, Michael A; Cohen, Leonardo G

2010-09-14

One of the most challenging tasks of the brain is to constantly update the internal neural representations of existing memories. Animal studies have used invasive methods such as direct microfusion of protein inhibitors to designated brain areas, in order to study the neural mechanisms underlying modification of already existing memories after their reactivation during recall [1-4]. Because such interventions are not possible in humans, it is not known how these neural processes operate in the human brain. In a series of experiments we show here that when an existing human motor memory is reactivated during recall, modification of the memory is blocked by virtual lesion [5] of the related primary cortical human brain area. The virtual lesion was induced by noninvasive repetitive transcranial magnetic stimulation guided by a frameless stereotactic brain navigation system and each subject's brain image. The results demonstrate that primary cortical processing in the human brain interacting with pre-existing reactivated memory traces is critical for successful modification of the existing related memory. Modulation of reactivated memories by noninvasive cortical stimulation may have important implications for human memory research and have far-reaching clinical applications. Copyright © 2010 Elsevier Ltd. All rights reserved.

Traumatic Brain Injury and Hyperbaric Oxygen Therapy Dawn of a New Day

DTIC Science & Technology

2017-09-07

Both used to test for differences between groups • No significant statistical difference between groups, but both groups improved • Relative...George Wolf, Laura M . Baugh, Christine M. Schubert Kabban, Michael F. Richards, Jennifer Prye • Individual test scores • ImPACT: • visual memory and...Stem cells collected prior to series, after 15 exposures. after 30 exposure series, and 6 weel< post series. • 13 subjects from 1.3 ATA air and 15

TBI-ROC Part Seven: Traumatic Brain Injury--Technologies to Support Memory and Cognition

ERIC Educational Resources Information Center

Scherer, Marcia; Elias, Eileen; Weider, Katie

2010-01-01

This article is the seventh of a multi-part series on traumatic brain injury (TBI). The six earlier articles in this series have discussed the individualized nature of TBI and its consequences, the rehabilitation continuum, and interventions at various points along the continuum. As noted throughout the articles, many individuals with TBI…

We should be using nonlinear indices when relating heart-rate dynamics to cognition and mood

PubMed Central

Young, Hayley; Benton, David

2015-01-01

Both heart rate (HR) and brain functioning involve the integrated output of a multitude of regulatory mechanisms, that are not quantified adequately by linear approximations such as means and standard deviations. It was therefore considered whether non-linear measures of HR complexity are more strongly associated with cognition and mood. Whilst resting, the inter-beat (R-R) time series of twenty-one males and twenty-four females were measured for five minutes. The data were summarised using time, frequency and nonlinear complexity measures. Attention, memory, reaction times, mood and cortisol levels were assessed. Nonlinear HR indices captured additional information, enabling a greater percentage of the variance in behaviour to be explained. On occasions non-linear indices were related to aspects for behaviour, for example focused attention and cortisol production, when time or frequency indices were not. These effects were sexually dimorphic with HR complexity being more strongly associated with the behaviour of females. It was concluded that nonlinear rather than linear methods of summarizing the HR times series offers a novel way of relating brain functioning and behaviour. It should be considered whether non-linear measures of HR complexity can be used as a biomarker of the integrated functioning of the brain. PMID:26565560

Some stylized facts of the Bitcoin market

NASA Astrophysics Data System (ADS)

Bariviera, Aurelio F.; Basgall, María José; Hasperué, Waldo; Naiouf, Marcelo

2017-10-01

In recent years a new type of tradable assets appeared, generically known as cryptocurrencies. Among them, the most widespread is Bitcoin. Given its novelty, this paper investigates some statistical properties of the Bitcoin market. This study compares Bitcoin and standard currencies dynamics and focuses on the analysis of returns at different time scales. We test the presence of long memory in return time series from 2011 to 2017, using transaction data from one Bitcoin platform. We compute the Hurst exponent by means of the Detrended Fluctuation Analysis method, using a sliding window in order to measure long range dependence. We detect that Hurst exponents changes significantly during the first years of existence of Bitcoin, tending to stabilize in recent times. Additionally, multiscale analysis shows a similar behavior of the Hurst exponent, implying a self-similar process.

Comparison of Intraoperative Portable CT Scanners in Skull Base and Endoscopic Sinus Surgery: Single Center Case Series

PubMed Central

Conley, David B.; Tan, Bruce; Bendok, Bernard R.; Batjer, H. Hunt; Chandra, Rakesh; Sidle, Douglas; Rahme, Rudy J.; Adel, Joseph G.; Fishman, Andrew J.

2011-01-01

Precise and safe management of complex skull base lesions can be enhanced by intraoperative computed tomography (CT) scanning. Surgery in these areas requires real-time feedback of anatomic landmarks. Several portable CT scanners are currently available. We present a comparison of our clinical experience with three portable scanners in skull base and craniofacial surgery. We present clinical case series and the participants were from the Northwestern Memorial Hospital. Three scanners are studied: one conventional multidetector CT (MDCT), two digital flat panel cone-beam CT (CBCT) devices. Technical considerations, ease of use, image characteristics, and integration with image guidance are presented for each device. All three scanners provide good quality images. Intraoperative scanning can be used to update the image guidance system in real time. The conventional MDCT is unique in its ability to resolve soft tissue. The flat panel CBCT scanners generally emit lower levels of radiation and have less metal artifact effect. In this series, intraoperative CT scanning was technically feasible and deemed useful in surgical decision-making in 75% of patients. Intraoperative portable CT scanning has significant utility in complex skull base surgery. This technology informs the surgeon of the precise extent of dissection and updates intraoperative stereotactic navigation. PMID:22470270

Item-location binding in working memory: is it hippocampus-dependent?

PubMed

Allen, Richard J; Vargha-Khadem, Faraneh; Baddeley, Alan D

2014-07-01

A general consensus is emerging that the hippocampus has an important and active role in the creation of new long-term memory representations of associations or bindings between elements. However, it is less clear whether this contribution can be extended to the creation of temporary bound representations in working memory, involving the retention of small numbers of items over short delays. We examined this by administering a series of recognition and recall tests of working memory for colour-location binding and object-location binding to a patient with highly selective hippocampal damage (Jon), and groups of control participants. Jon achieved high levels of accuracy in all working memory tests of recognition and recall binding across retention intervals of up to 10s. In contrast, Jon performed at chance on an unexpected delayed test of the same object-location binding information. These findings indicate a clear dissociation between working memory and long-term memory, with no evidence for a critical hippocampal contribution to item-location binding in working memory. Copyright © 2014 Elsevier Ltd. All rights reserved.

The effect of Twitter exposure on false memory formation.

PubMed

Fenn, Kimberly M; Griffin, Nicholas R; Uitvlugt, Mitchell G; Ravizza, Susan M

2014-12-01

Social media sites such as Facebook and Twitter have increased drastically in popularity. However, information on these sites is not verified and may contain inaccuracies. It is well-established that false information encountered after an event can lead to memory distortion. Therefore, social media may be particularly harmful for autobiographical memory. Here, we tested the effect of Twitter on false memory. We presented participants with a series of images that depicted a story and then presented false information about the images in a scrolling feed that bore either a low or high resemblance to a Twitter feed. Confidence for correct information was similar across the groups, but confidence for suggested information was significantly lower when false information was presented in a Twitter format. We propose that individuals take into account the medium of the message when integrating information into memory.

Modeling the stylized facts in finance through simple nonlinear adaptive systems

PubMed Central

Hommes, Cars H.

2002-01-01

Recent work on adaptive systems for modeling financial markets is discussed. Financial markets are viewed as evolutionary systems between different, competing trading strategies. Agents are boundedly rational in the sense that they tend to follow strategies that have performed well, according to realized profits or accumulated wealth, in the recent past. Simple technical trading rules may survive evolutionary competition in a heterogeneous world where prices and beliefs co-evolve over time. Evolutionary models can explain important stylized facts, such as fat tails, clustered volatility, and long memory, of real financial series. PMID:12011401

Automatic construction of a recurrent neural network based classifier for vehicle passage detection

NASA Astrophysics Data System (ADS)

Burnaev, Evgeny; Koptelov, Ivan; Novikov, German; Khanipov, Timur

2017-03-01

Recurrent Neural Networks (RNNs) are extensively used for time-series modeling and prediction. We propose an approach for automatic construction of a binary classifier based on Long Short-Term Memory RNNs (LSTM-RNNs) for detection of a vehicle passage through a checkpoint. As an input to the classifier we use multidimensional signals of various sensors that are installed on the checkpoint. Obtained results demonstrate that the previous approach to handcrafting a classifier, consisting of a set of deterministic rules, can be successfully replaced by an automatic RNN training on an appropriately labelled data.

Programs for Testing Processor-in-Memory Computing Systems

NASA Technical Reports Server (NTRS)

Katz, Daniel S.

2006-01-01

The Multithreaded Microbenchmarks for Processor-In-Memory (PIM) Compilers, Simulators, and Hardware are computer programs arranged in a series for use in testing the performances of PIM computing systems, including compilers, simulators, and hardware. The programs at the beginning of the series test basic functionality; the programs at subsequent positions in the series test increasingly complex functionality. The programs are intended to be used while designing a PIM system, and can be used to verify that compilers, simulators, and hardware work correctly. The programs can also be used to enable designers of these system components to examine tradeoffs in implementation. Finally, these programs can be run on non-PIM hardware (either single-threaded or multithreaded) using the POSIX pthreads standard to verify that the benchmarks themselves operate correctly. [POSIX (Portable Operating System Interface for UNIX) is a set of standards that define how programs and operating systems interact with each other. pthreads is a library of pre-emptive thread routines that comply with one of the POSIX standards.

The Development of Time-Based Prospective Memory in Childhood: The Role of Working Memory Updating

ERIC Educational Resources Information Center

Voigt, Babett; Mahy, Caitlin E. V.; Ellis, Judi; Schnitzspahn, Katharina; Krause, Ivonne; Altgassen, Mareike; Kliegel, Matthias

2014-01-01

This large-scale study examined the development of time-based prospective memory (PM) across childhood and the roles that working memory updating and time monitoring play in driving age effects in PM performance. One hundred and ninety-seven children aged 5 to 14 years completed a time-based PM task where working memory updating load was…

Revisiting the Effect of Reminders on Infants' Media Memories: Does the Encoding Format Matter?

ERIC Educational Resources Information Center

Barr, Rachel; Brito, Natalie; Simcock, Gabrielle

2013-01-01

With the present research, the authors examined whether reminders could maintain 18-month-olds' memories generated from picture books and videos. Infants (N = 98) were shown a series of target actions in a picture book or on video. Either 24 hr or 2 weeks prior to a 4-week deferred imitation test, they were exposed to a reminder, a partial…

On the function of stress rhythms in speech: evidence of a link with grouping effects on serial memory.

PubMed

Boucher, Victor J

2006-01-01

Language learning requires a capacity to recall novel series of speech sounds. Research shows that prosodic marks create grouping effects enhancing serial recall. However, any restriction on memory affecting the reproduction of prosody would limit the set of patterns that could be learned and subsequently used in speech. By implication, grouping effects of prosody would also be limited to reproducible patterns. This view of the role of prosody and the contribution of memory processes in the organization of prosodic patterns is examined by evaluating the correspondence between a reported tendency to restrict stress intervals in speech and size limits on stress-grouping effects. French speech is used where stress defines the endpoints of groups. In Experiment 1, 40 speakers recalled novel series of syllables containing stress-groups of varying size. Recall was not enhanced by groupings exceeding four syllables, which corresponded to a restriction on the reproducibility of stress-groups. In Experiment 2, the subjects produced given sentences containing phrases of differing length. The results show a strong tendency to insert stress within phrases that exceed four syllables. Since prosody can arise in the recall of syntactically unstructured lists, the results offer initial support for viewing memory processes as a factor of stress-rhythm organization.

Fluctuation behaviors of financial return volatility duration

NASA Astrophysics Data System (ADS)

Niu, Hongli; Wang, Jun; Lu, Yunfan

2016-04-01

It is of significantly crucial to understand the return volatility of financial markets because it helps to quantify the investment risk, optimize the portfolio, and provide a key input of option pricing models. The characteristics of isolated high volatility events above certain threshold in price fluctuations and the distributions of return intervals between these events arouse great interest in financial research. In the present work, we introduce a new concept of daily return volatility duration, which is defined as the shortest passage time when the future volatility intensity is above or below the current volatility intensity (without predefining a threshold). The statistical properties of the daily return volatility durations for seven representative stock indices from the world financial markets are investigated. Some useful and interesting empirical results of these volatility duration series about the probability distributions, memory effects and multifractal properties are obtained. These results also show that the proposed stock volatility series analysis is a meaningful and beneficial trial.

Accelerating execution of the integrated TIGER series Monte Carlo radiation transport codes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, L.M.; Hochstedler, R.D.

1997-02-01

Execution of the integrated TIGER series (ITS) of coupled electron/photon Monte Carlo radiation transport codes has been accelerated by modifying the FORTRAN source code for more efficient computation. Each member code of ITS was benchmarked and profiled with a specific test case that directed the acceleration effort toward the most computationally intensive subroutines. Techniques for accelerating these subroutines included replacing linear search algorithms with binary versions, replacing the pseudo-random number generator, reducing program memory allocation, and proofing the input files for geometrical redundancies. All techniques produced identical or statistically similar results to the original code. Final benchmark timing of themore » accelerated code resulted in speed-up factors of 2.00 for TIGER (the one-dimensional slab geometry code), 1.74 for CYLTRAN (the two-dimensional cylindrical geometry code), and 1.90 for ACCEPT (the arbitrary three-dimensional geometry code).« less

The dynamic nature of systems consolidation: Stress during learning as a switch guiding the rate of the hippocampal dependency and memory quality.

PubMed

Pedraza, Lizeth K; Sierra, Rodrigo O; Boos, Flávia Z; Haubrich, Josué; Quillfeldt, Jorge A; Alvares, Lucas de Oliveira

2016-03-01

Memory fades over time, becoming more schematic or abstract. The loss of contextual detail in memory may reflect a time-dependent change in the brain structures supporting memory. It has been well established that contextual fear memory relies on the hippocampus for expression shortly after learning, but it becomes hippocampus-independent at a later time point, a process called systems consolidation. This time-dependent process correlates with the loss of memory precision. Here, we investigated whether training intensity predicts the gradual decay of hippocampal dependency to retrieve memory, and the quality of the contextual memory representation over time. We have found that training intensity modulates the progressive decay of hippocampal dependency and memory precision. Strong training intensity accelerates systems consolidation and memory generalization in a remarkable timeframe match. The mechanisms underpinning such process are triggered by glucocorticoid and noradrenaline released during training. These results suggest that the stress levels during emotional learning act as a switch, determining the fate of memory quality. Moderate stress will create a detailed memory, whereas a highly stressful training will develop a generic gist-like memory. © 2015 Wiley Periodicals, Inc.

Psychogenic amnesia: syndromes, outcome, and patterns of retrograde amnesia.

PubMed

Harrison, Neil A; Johnston, Kate; Corno, Federica; Casey, Sarah J; Friedner, Kimberley; Humphreys, Kate; Jaldow, Eli J; Pitkanen, Mervi; Kopelman, Michael D

2017-09-01

There are very few case series of patients with acute psychogenic memory loss (also known as dissociative/functional amnesia), and still fewer studies of outcome, or comparisons with neurological memory-disordered patients. Consequently, the literature on psychogenic amnesia is somewhat fragmented and offers little prognostic value for individual patients. In the present study, we reviewed the case records and neuropsychological findings in 53 psychogenic amnesia cases (ratio of 3:1, males:females), in comparison with 21 consecutively recruited neurological memory-disordered patients and 14 healthy control subjects. In particular, we examined the pattern of retrograde amnesia on an assessment of autobiographical memory (the Autobiographical Memory Interview). We found that our patients with psychogenic memory loss fell into four distinct groups, which we categorized as: (i) fugue state; (ii) fugue-to-focal retrograde amnesia; (iii) psychogenic focal retrograde amnesia following a minor neurological episode; and (iv) patients with gaps in their memories. While neurological cases were characterized by relevant neurological symptoms, a history of a past head injury was actually more common in our psychogenic cases (P = 0.012), perhaps reflecting a 'learning episode' predisposing to later psychological amnesia. As anticipated, loss of the sense of personal identity was confined to the psychogenic group. However, clinical depression, family/relationship problems, financial/employment problems, and failure to recognize the family were also statistically more common in that group. The pattern of autobiographical memory loss differed between the psychogenic groups: fugue cases showed a severe and uniform loss of memories for both facts and events across all time periods, whereas the two focal retrograde amnesia groups showed a 'reversed' temporal gradient with relative sparing of recent memories. After 3-6 months, the fugue patients had improved to normal scores for facts and near-normal scores for events. By contrast, the two focal retrograde amnesia groups showed less improvement and continued to show a reversed temporal gradient. In conclusion, the outcome in psychogenic amnesia, particularly those characterized by fugue, is better than generally supposed. Findings are interpreted in terms of Markowitsch's and Kopelman's models of psychogenic amnesia, and with respect to Anderson's neuroimaging findings in memory inhibition. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Neural Correlates of Direct and Indirect Suppression of Autobiographical Memories

PubMed Central

Noreen, Saima; O’Connor, Akira R.; MacLeod, Malcolm D.

2016-01-01

Research indicates that there are two possible mechanisms by which particular target memories can be intentionally forgotten. Direct suppression, which involves the suppression of the unwanted memory directly, and is dependent on a fronto-hippocampal modulatory process, and, memory substitution, which includes directing one’s attention to an alternative memory in order to prevent the unwanted memory from coming to mind, and involves engaging the caudal prefrontal cortex (cPFC) and the mid-ventrolateral prefrontal cortex (VLPFC) regions. Research to date, however, has investigated the neural basis of memory suppression of relatively simple information. The aim of the current study was to use fMRI to identify the neural mechanisms associated with the suppression of autobiographical memories. In the present study, 22 participants generated memories in response to a series of cue words. In a second session, participants learnt these cue-memory pairings, and were subsequently presented with a cue word and asked either to recall (think) or to suppress (no-think) the associated memory, or to think of an alternative memory in order to suppress the original memory (memory-substitution). Our findings demonstrated successful forgetting effects in the no-think and memory substitution conditions. Although we found no activation in the dorsolateral prefrontal cortex, there was reduced hippocampal activation during direct suppression. In the memory substitution condition, however, we failed to find increased activation in the cPFC and VLPFC regions. Our findings suggest that the suppression of autobiographical memories may rely on different neural mechanisms to those established for other types of material in memory. PMID:27047412

Neural Correlates of Direct and Indirect Suppression of Autobiographical Memories.

PubMed

Noreen, Saima; O'Connor, Akira R; MacLeod, Malcolm D

2016-01-01

Research indicates that there are two possible mechanisms by which particular target memories can be intentionally forgotten. Direct suppression, which involves the suppression of the unwanted memory directly, and is dependent on a fronto-hippocampal modulatory process, and, memory substitution, which includes directing one's attention to an alternative memory in order to prevent the unwanted memory from coming to mind, and involves engaging the caudal prefrontal cortex (cPFC) and the mid-ventrolateral prefrontal cortex (VLPFC) regions. Research to date, however, has investigated the neural basis of memory suppression of relatively simple information. The aim of the current study was to use fMRI to identify the neural mechanisms associated with the suppression of autobiographical memories. In the present study, 22 participants generated memories in response to a series of cue words. In a second session, participants learnt these cue-memory pairings, and were subsequently presented with a cue word and asked either to recall (think) or to suppress (no-think) the associated memory, or to think of an alternative memory in order to suppress the original memory (memory-substitution). Our findings demonstrated successful forgetting effects in the no-think and memory substitution conditions. Although we found no activation in the dorsolateral prefrontal cortex, there was reduced hippocampal activation during direct suppression. In the memory substitution condition, however, we failed to find increased activation in the cPFC and VLPFC regions. Our findings suggest that the suppression of autobiographical memories may rely on different neural mechanisms to those established for other types of material in memory.

The memory of the accreting plate boundary and the continuity of fracture zones

USGS Publications Warehouse

Schouten, Hans; Klitgord, Kim D.

1982-01-01

A detailed aeromagnetic anomaly map of the Mesozoic seafloor-spreading lineations southwest of Bermuda reveals the dominant magnetic grain of the oceanic crust and the character of the accreting boundary at the time of crustal formation. The magnetic anomaly pattern is that of a series of elongate lobes perpendicular to the fracture zone (flowline) trends. The linear sets of magnetic anomaly peaks and troughs have narrow regions of reduced amplitude anomalies associated with the fracture zones. During the period of Mesozoic geomagnetic polarity reversals (when 1200 km of central North Atlantic seafloor formed), the Atlantic accreting boundary consisted of stationary, elongate, spreading center cells that maintained their independence even though sometimes only minor spatial offsets existed between cells. Normal oceanic crustal structure was formed in the spreading center cells, but structural anomalies and discontinuities characteristic of fracture zones were formed at their boundaries, which parallel flowlines of Mesozoic relative plate motion in the central North Atlantic. We suggest that the memory for a stationary pattern of independent spreading center cells resides in the young brittle lithosphere at the accreting boundary where the lithosphere is weakest; here, each spreading center cell independently goes through its cylce of stress buildup, stress release, and crustal accretion, after which its memory is refreshed. The temporal offset between the peaks of the accretionary activity that takes place within each cell may provide the mechanism for maintaining the independence of adjacent spreading center cells through times when no spatial offset between the cells exists.

Fast prediction of pulsed nonlinear acoustic fields from clinically relevant sources using Time-Averaged Wave Envelope approach: comparison of numerical simulations and experimental results

PubMed Central

Wójcik, J.; Kujawska, T.; Nowicki, A.; Lewin, P.A.

2008-01-01

The primary goal of this work was to verify experimentally the applicability of the recently introduced Time-Averaged Wave Envelope (TAWE) method [1] as a tool for fast prediction of four dimensional (4D) pulsed nonlinear pressure fields from arbitrarily shaped acoustic sources in attenuating media. The experiments were performed in water at the fundamental frequency of 2.8 MHz for spherically focused (focal length F = 80 mm) square (20 × 20 mm) and rectangular (10 × 25 mm) sources similar to those used in the design of 1D linear arrays operating with ultrasonic imaging systems. The experimental results obtained with 10-cycle tone bursts at three different excitation levels corresponding to linear, moderately nonlinear and highly nonlinear propagation conditions (0.045, 0.225 and 0.45 MPa on-source pressure amplitude, respectively) were compared with those yielded using the TAWE approach [1]. The comparison of the experimental results and numerical simulations has shown that the TAWE approach is well suited to predict (to within ± 1 dB) both the spatial-temporal and spatial-spectral pressure variations in the pulsed nonlinear acoustic beams. The obtained results indicated that implementation of the TAWE approach enabled shortening of computation time in comparison with the time needed for prediction of the full 4D pulsed nonlinear acoustic fields using a conventional (Fourier-series) approach [2]. The reduction in computation time depends on several parameters, including the source geometry, dimensions, fundamental resonance frequency, excitation level as well as the strength of the medium nonlinearity. For the non-axisymmetric focused transducers mentioned above and excited by a tone burst corresponding to moderately nonlinear and highly nonlinear conditions the execution time of computations was 3 and 12 hours, respectively, when using a 1.5 GHz clock frequency, 32-bit processor PC laptop with 2 GB RAM memory, only. Such prediction of the full 4D pulsed field is not possible when using conventional, Fourier-series scheme as it would require increasing the RAM memory by at least 2 orders of magnitude. PMID:18474387

Biography Today: Sports Series. Profiles of People of Interest to Young Readers, Volume 4.

ERIC Educational Resources Information Center

Harris, Laurie Lanzen, Ed.; Abbey, Cherie D., Ed.

This book is the fourth in a series of biographies on today's sports figures designed for students age 9 years and older. It contains alphabetically arranged sketches of the sports figures. Each entry provides at least one picture of the individual profiled. Bold faced rubrics lead the reader to information on birth, youth, early memories,…

Biography Today: Profiles of People of Interest to Young Readers. Sports Series, Volume 9.

ERIC Educational Resources Information Center

Abbey, Cherie D., Ed.

This ninth volume of the "Biography Today Sports" series is intended to appeal to young readers in a format they can enjoy reading and readily understand. Each alphabetically-arranged sketch provides at least one picture of the individual profiled, and bold-faced rubrics lead the reader to information on birth, youth, early memories,…

Low-complexity camera digital signal imaging for video document projection system

NASA Astrophysics Data System (ADS)

Hsia, Shih-Chang; Tsai, Po-Shien

2011-04-01

We present high-performance and low-complexity algorithms for real-time camera imaging applications. The main functions of the proposed camera digital signal processing (DSP) involve color interpolation, white balance, adaptive binary processing, auto gain control, and edge and color enhancement for video projection systems. A series of simulations demonstrate that the proposed method can achieve good image quality while keeping computation cost and memory requirements low. On the basis of the proposed algorithms, the cost-effective hardware core is developed using Verilog HDL. The prototype chip has been verified with one low-cost programmable device. The real-time camera system can achieve 1270 × 792 resolution with the combination of extra components and can demonstrate each DSP function.

A unified nonlinear stochastic time series analysis for climate science

NASA Astrophysics Data System (ADS)

Moon, Woosok; Wettlaufer, John

2017-04-01

Earth's orbit and axial tilt imprint a strong seasonal cycle on climatological data. Climate variability is typically viewed in terms of fluctuations in the seasonal cycle induced by higher frequency processes. We can interpret this as a competition between the orbitally enforced monthly stability and the fluctuations/noise induced by weather. Here we introduce a new time-series method that determines these contributions from monthly-averaged data. We find that the spatio-temporal distribution of the monthly stability and the magnitude of the noise reveal key fingerprints of several important climate phenomena, including the evolution of the Arctic sea ice cover, the El Niño Southern Oscillation (ENSO), the Atlantic Niño and the Indian Dipole Mode. In analogy with the classical destabilising influence of the ice-albedo feedback on summertime sea ice, we find that during some period of the season a destabilising process operates in all of these climate phenomena. The interaction between the destabilisation and the accumulation of noise, which we term the memory effect, underlies phase locking to the seasonal cycle and the statistical nature of seasonal predictability.

Memory retrieval and the passage of time: from reconsolidation and strengthening to extinction

PubMed Central

Inda, Maria Carmen; Muravieva, Elizaveta V.; Alberini, Cristina M.

2011-01-01

An established memory can be made transiently labile if retrieved or reactivated. Over time, it becomes again resistant to disruption and this process that renders the memory stable is termed reconsolidation. The reasons why a memory becomes labile after retrieval and reconsolidates still remains debated. Here, using inhibitory avoidance (IA) learning in rats, we provide evidence that retrievals of a young memory, which are accompanied by its reconsolidation, result in memory strengthening and contribute to its overall consolidation. This function associated to reconsolidation is temporally limited. With the passage of time, the stored memory undergoes important changes, as revealed by the behavioral outcomes of its retrieval. Over time, without explicit retrievals, memory first strengthens and becomes refractory to both retrieval-dependent interference and strengthening. At later times, the same retrievals that lead to reconsolidation of a young memory extinguish an older memory. We conclude that the storage of information is very dynamic and that its temporal evolution regulates behavioral outcomes. These results are important for potential clinical applications. PMID:21289172

Time course of effects of emotion on item memory and source memory for Chinese words.

PubMed

Wang, Bo; Fu, Xiaolan

2011-05-01

Although many studies have investigated the effect of emotion on memory, it is unclear whether the effect of emotion extends to all aspects of an event. In addition, it is poorly understood how effects of emotion on item memory and source memory change over time. This study examined the time course of effects of emotion on item memory and source memory. Participants learned intentionally a list of neutral, positive, and negative Chinese words, which were presented twice, and then took test of free recall, followed by recognition and source memory tests, at one of eight delayed points of time. The main findings are (within the time frame of 2 weeks): (1) Negative emotion enhances free recall, whereas there is only a trend that positive emotion enhances free recall. In addition, negative and positive emotions have different points of time at which their effects on free recall reach the greatest magnitude. (2) Negative emotion reduces recognition, whereas positive emotion has no effect on recognition. (3) Neither positive nor negative emotion has any effect on source memory. The above findings indicate that effect of emotion does not necessarily extend to all aspects of an event and that valence is a critical modulating factor in effect of emotion on item memory. Furthermore, emotion does not affect the time course of item memory and source memory, at least with a time frame of 2 weeks. This study has implications for establishing the theoretical model regarding the effect of emotion on memory. Copyright © 2011 Elsevier Inc. All rights reserved.

Moderate hypoglycaemia after learning does not affect memory consolidation and brain activation during recognition in non-diabetic adults.

PubMed

Warren, Roderick E; Sommerfield, Andrew J; Greve, Andrea; Allen, Kate V; Deary, Ian J; Frier, Brian M

2008-01-01

Some aspects of memory performance are impaired during acute hypoglycaemia. The hippocampus is critical to formation of long-term memory, and may be particularly sensitive to hypoglycaemia. This study examined whether moderate hypoglycaemia occurring after learning would disrupt the consolidation process, and used functional magnetic resonance imaging (fMRI) to identify accompanying changes in brain activation. Sixteen non-diabetic subjects each underwent two glucose clamp studies. During euglycaemia (4.5 mmol/L), subjects tried to memorize a series of words and a series of pictures of faces. Then, either hypoglycaemia (2.5 mmol/L) was induced for one hour, or euglycaemia was maintained. During subsequent uncontrolled euglycaemia, subjects' recognition of the word and face stimuli was tested, with simultaneous fMRI to measure brain activation during recognition. Face identification scores were 67.2% after euglycaemia and 66.9% after hypoglycaemia (p = 0.895). Word identification scores were 78.0 and 77.1% respectively (p = 0.701). Analysis of the fMRI identified two foci where activation was altered after hypoglycaemia compared with euglycaemia, but these were not in regions associated with memory, and were probably statistical artefacts. One hour of hypoglycaemia at 2.5 mmol/L induced 20-40 min after learning did not disrupt memory consolidation. fMRI did not show evidence of altered brain activation after hypoglycaemia. Consolidation may be relatively resistant to hypoglycaemia, or may have been complete before hypoglycaemia was induced. The study was powered to detect a large effect, and provides some reassurance that moderate hypoglycaemia does not cause major disruption of previously learned memories in people with insulin-treated diabetes. Copyright (c) 2008 John Wiley & Sons, Ltd.

Accelerating 3D Elastic Wave Equations on Knights Landing based Intel Xeon Phi processors

NASA Astrophysics Data System (ADS)

Sourouri, Mohammed; Birger Raknes, Espen

2017-04-01

In advanced imaging methods like reverse-time migration (RTM) and full waveform inversion (FWI) the elastic wave equation (EWE) is numerically solved many times to create the seismic image or the elastic parameter model update. Thus, it is essential to optimize the solution time for solving the EWE as this will have a major impact on the total computational cost in running RTM or FWI. From a computational point of view applications implementing EWEs are associated with two major challenges. The first challenge is the amount of memory-bound computations involved, while the second challenge is the execution of such computations over very large datasets. So far, multi-core processors have not been able to tackle these two challenges, which eventually led to the adoption of accelerators such as Graphics Processing Units (GPUs). Compared to conventional CPUs, GPUs are densely populated with many floating-point units and fast memory, a type of architecture that has proven to map well to many scientific computations. Despite its architectural advantages, full-scale adoption of accelerators has yet to materialize. First, accelerators require a significant programming effort imposed by programming models such as CUDA or OpenCL. Second, accelerators come with a limited amount of memory, which also require explicit data transfers between the CPU and the accelerator over the slow PCI bus. The second generation of the Xeon Phi processor based on the Knights Landing (KNL) architecture, promises the computational capabilities of an accelerator but require the same programming effort as traditional multi-core processors. The high computational performance is realized through many integrated cores (number of cores and tiles and memory varies with the model) organized in tiles that are connected via a 2D mesh based interconnect. In contrary to accelerators, KNL is a self-hosted system, meaning explicit data transfers over the PCI bus are no longer required. However, like most accelerators, KNL sports a memory subsystem consisting of low-level caches and 16GB of high-bandwidth MCDRAM memory. For capacity computing, up to 400GB of conventional DDR4 memory is provided. Such a strict hierarchical memory layout means that data locality is imperative if the true potential of this product is to be harnessed. In this work, we study a series of optimizations specifically targeting KNL for our EWE based application to reduce the time-to-solution time for the following 3D model sizes in grid points: 1283, 2563 and 5123. We compare the results with an optimized version for multi-core CPUs running on a dual-socket Xeon E5 2680v3 system using OpenMP. Our initial naive implementation on the KNL is roughly 20% faster than the multi-core version, but by using only one thread per core and careful memory placement using the memkind library, we could achieve higher speedups. Additionally, by using the MCDRAM as cache for problem sizes that are smaller than 16 GB further performance improvements were unlocked. Depending on the problem size, our overall results indicate that the KNL based system is approximately 2.2x faster than the 24-core Xeon E5 2680v3 system, with only modest changes to the code.

A Time and Place for Everything: Developmental Differences in the Building Blocks of Episodic Memory

PubMed Central

Lee, Joshua K.; Wendelken, J. Carter; Bunge, Silvia A.; Ghetti, Simona

2015-01-01

This research investigated whether episodic memory development can be explained by improvements in relational binding processes, involved in forming novel associations between events and the context in which they occurred. Memory for item-space, item-time, and item-item relations was assessed in an ethnically diverse sample of 151 children aged 7 to 11 years and 28 young adults. Item-space memory reached adult performance by 9½ years, whereas item-time and item-item memory improved into adulthood. In path analysis, item-space, but not item-time best explained item-item memory. Across age groups, relational binding related to source memory and performance on standardized memory assessments. In conclusion, relational binding development depends on relation type, but relational binding overall supports episodic memory development. PMID:26493950

Phenotypic and Functional Alterations in Circulating Memory CD8 T Cells with Time after Primary Infection.

PubMed

Martin, Matthew D; Kim, Marie T; Shan, Qiang; Sompallae, Ramakrishna; Xue, Hai-Hui; Harty, John T; Badovinac, Vladimir P

2015-10-01

Memory CD8 T cells confer increased protection to immune hosts upon secondary viral, bacterial, and parasitic infections. The level of protection provided depends on the numbers, quality (functional ability), and location of memory CD8 T cells present at the time of infection. While primary memory CD8 T cells can be maintained for the life of the host, the full extent of phenotypic and functional changes that occur over time after initial antigen encounter remains poorly characterized. Here we show that critical properties of circulating primary memory CD8 T cells, including location, phenotype, cytokine production, maintenance, secondary proliferation, secondary memory generation potential, and mitochondrial function change with time after infection. Interestingly, phenotypic and functional alterations in the memory population are not due solely to shifts in the ratio of effector (CD62Llo) and central memory (CD62Lhi) cells, but also occur within defined CD62Lhi memory CD8 T cell subsets. CD62Lhi memory cells retain the ability to efficiently produce cytokines with time after infection. However, while it is was not formally tested whether changes in CD62Lhi memory CD8 T cells over time occur in a cell intrinsic manner or are due to selective death and/or survival, the gene expression profiles of CD62Lhi memory CD8 T cells change, phenotypic heterogeneity decreases, and mitochondrial function and proliferative capacity in either a lymphopenic environment or in response to antigen re-encounter increase with time. Importantly, and in accordance with their enhanced proliferative and metabolic capabilities, protection provided against chronic LCMV clone-13 infection increases over time for both circulating memory CD8 T cell populations and for CD62Lhi memory cells. Taken together, the data in this study reveal that memory CD8 T cells continue to change with time after infection and suggest that the outcome of vaccination strategies designed to elicit protective memory CD8 T cells using single or prime-boost immunizations depends upon the timing between antigen encounters.

The influence of the glycaemic load of breakfast on the behaviour of children in school.

PubMed

Benton, David; Maconie, Alys; Williams, Claire

2007-11-23

The impact of breakfasts of different glycaemic loads on the performance of nineteen children, aged six to seven years, was explored. Over a four week period, children attended a school breakfast club each day and ate one of three meals. Each meal offered a similar amount of energy but differed in their glycaemic load. When working individually, the behaviour of a child was rated in the classroom every ten seconds for 30 min to produce a measure of time spent on task. Memory was assessed by asking for the recall of a series of objects. The ability to sustain attention was measured by asking for a response after various delays. The incidence of negative behaviour was recorded when playing a video game that was too difficult to allow success. Two to three hours after a low glycaemic load breakfast had been consumed, performance on the tests of memory and the ability to sustain attention were better, fewer signs of frustration were displayed and initially more time was spent on task when working individually in class. The importance of the results was discussed in the context of the wide range of factors that influence behaviour in school.

Evidence for modality-independent order coding in working memory.

PubMed

Depoorter, Ann; Vandierendonck, André

2009-03-01

The aim of the present study was to investigate the representation of serial order in working memory, more specifically whether serial order is coded by means of a modality-dependent or a modality-independent order code. This was investigated by means of a series of four experiments based on a dual-task methodology in which one short-term memory task was embedded between the presentation and recall of another short-term memory task. Two aspects were varied in these memory tasks--namely, the modality of the stimulus materials (verbal or visuo-spatial) and the presence of an order component in the task (an order or an item memory task). The results of this study showed impaired primary-task recognition performance when both the primary and the embedded task included an order component, irrespective of the modality of the stimulus materials. If one or both of the tasks did not contain an order component, less interference was found. The results of this study support the existence of a modality-independent order code.

Multi-shape memory polymers achieved by the spatio-assembly of 3D printable thermoplastic building blocks.

PubMed

Li, Hongze; Gao, Xiang; Luo, Yingwu

2016-04-07

Multi-shape memory polymers were prepared by the macroscale spatio-assembly of building blocks in this work. The building blocks were methyl acrylate-co-styrene (MA-co-St) copolymers, which have the St-block-(St-random-MA)-block-St tri-block chain sequence. This design ensures that their transition temperatures can be adjusted over a wide range by varying the composition of the middle block. The two St blocks at the chain ends can generate a crosslink network in the final device to achieve strong bonding force between building blocks and the shape memory capacity. Due to their thermoplastic properties, 3D printing was employed for the spatio-assembly to build devices. This method is capable of introducing many transition phases into one device and preparing complicated shapes via 3D printing. The device can perform a complex action via a series of shape changes. Besides, this method can avoid the difficult programing of a series of temporary shapes. The control of intermediate temporary shapes was realized via programing the shapes and locations of building blocks in the final device.

Time domain nonlinear SMA damper force identification approach and its numerical validation

NASA Astrophysics Data System (ADS)

Xin, Lulu; Xu, Bin; He, Jia

2012-04-01

Most of the currently available vibration-based identification approaches for structural damage detection are based on eigenvalues and/or eigenvectors extracted from vibration measurements and, strictly speaking, are only suitable for linear system. However, the initiation and development of damage in engineering structures under severe dynamic loadings are typical nonlinear procedure. Studies on the identification of restoring force which is a direct indicator of the extent of the nonlinearity have received increasing attention in recent years. In this study, a date-based time domain identification approach for general nonlinear system was developed. The applied excitation and the corresponding response time series of the structure were used for identification by means of standard least-square techniques and a power series polynomial model (PSPM) which was utilized to model the nonlinear restoring force (NRF). The feasibility and robustness of the proposed approach was verified by a 2 degree-of-freedoms (DOFs) lumped mass numerical model equipped with a shape memory ally (SMA) damper mimicking nonlinear behavior. The results show that the proposed data-based time domain method is capable of identifying the NRF in engineering structures without any assumptions on the mass distribution and the topology of the structure, and provides a promising way for damage detection in the presence of structural nonlinearities.

Phenomenological analysis of medical time series with regular and stochastic components

NASA Astrophysics Data System (ADS)

Timashev, Serge F.; Polyakov, Yuriy S.

2007-06-01

Flicker-Noise Spectroscopy (FNS), a general approach to the extraction and parameterization of resonant and stochastic components contained in medical time series, is presented. The basic idea of FNS is to treat the correlation links present in sequences of different irregularities, such as spikes, "jumps", and discontinuities in derivatives of different orders, on all levels of the spatiotemporal hierarchy of the system under study as main information carriers. The tools to extract and analyze the information are power spectra and difference moments (structural functions), which complement the information of each other. The structural function stochastic component is formed exclusively by "jumps" of the dynamic variable while the power spectrum stochastic component is formed by both spikes and "jumps" on every level of the hierarchy. The information "passport" characteristics that are determined by fitting the derived expressions to the experimental variations for the stochastic components of power spectra and structural functions are interpreted as the correlation times and parameters that describe the rate of "memory loss" on these correlation time intervals for different irregularities. The number of the extracted parameters is determined by the requirements of the problem under study. Application of this approach to the analysis of tremor velocity signals for a Parkinsonian patient is discussed.

Immunologic considerations for generating memory CD8 T cells through vaccination.

PubMed

Butler, Noah S; Nolz, Jeffrey C; Harty, John T

2011-07-01

Following infection or vaccination, naïve CD8 T cells that receive the appropriate integration of antigenic, co-stimulatory and inflammatory signals undergo a programmed series of biological changes that ultimately results in the generation of memory cells. Memory CD8 T cells, in contrast to naïve cells, more effectively limit or prevent pathogen re-infection because of both qualitative and quantitative changes that occur following their induction. Unlike vaccination strategies aimed at generating antibody production, the ability to generate protective memory CD8 T cells has proven more complicated and problematic. However, recent experimental results have revealed important principles regarding the molecular and genetic basis for memory CD8 T cell formation, as well as identified ways to manipulate their development through vaccination, resulting in potential new avenues to enhance protective immunity. © 2011 Blackwell Publishing Ltd.

Marijuana effects on long-term memory assessment and retrieval.

PubMed

Darley, C F; Tinklenberg, J R; Roth, W T; Vernon, S; Kopell, B S

1977-05-09

The ability of 16 college-educated male subjects to recall from long-term memory a series of common facts was tested during intoxication with marijuana extract calibrated to 0.3 mg/kg delta-9-tetrahydrocannabinol and during placebo conditions. The subjects' ability to assess their memory capabilities was then determined by measuring how certain they were about the accuracy of their recall performance and by having them predict their performance on a subsequent recognition test involving the same recall items. Marijuana had no effect on recall or recognition performance. These results do not support the view that marijuana provides access to facts in long-term storage which are inaccessible during non-intoxication. During both marijuana and placebo conditions, subjects could accurately predict their recognition memory performance. Hence, marijuana did not alter the subjects' ability to accurately assess what information resides in long-term memory even though they did not have complete access to that information.

Shape Memory Properties and Enzymatic Degradability of Poly(ε-caprolactone)-Based Polyurethane Urea Containing Phenylalanine-Derived Chain Extender.

PubMed

Wang, Rong; Zhang, Fanjun; Lin, Weiwei; Liu, Wenkai; Li, Jiehua; Luo, Feng; Wang, Yaning; Tan, Hong

2018-06-01

Biodegradable shape memory polymers are promising biomaterials for minimally invasive surgical procedures. Herein, a series of linear biodegradable shape memory poly(ε-caprolactone) (PCL)-based polyurethane ureas (PUUs) containing a novel phenylalanine-derived chain extender is synthesized. The phenylalanine-derived chain extender, phenylalanine-hexamethylenediamine-phenylalanine (PHP), contains two chymotrypsin cleaving sites to enhance the enzymatic degradation of PUUs. The degradation rate, the crystallinity, and mechanical properties of PUUs are tailored by the content of PHP. Meanwhile, semicrystalline PCL is not only hydrolytically degradable but also vital for shape memory. Good shape memory ability under body temperature is achieved for PUUs due to the strong interactions in hard segments for permanent crosslinking and the crystallization-melt transition of PCL to switch temporary shape. The PUUs would have a great potential in application as implanting stent. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Electrical Characterization of the RCA CDP1822SD Random Access Memory, Volume 1, Appendix a

NASA Technical Reports Server (NTRS)

Klute, A.

1979-01-01

Electrical characteristization tests were performed on 35 RCA CDP1822SD, 256-by-4-bit, CMOS, random access memories. The tests included three functional tests, AC and DC parametric tests, a series of schmoo plots, rise/fall time screening, and a data retention test. All tests were performed on an automated IC test system with temperatures controlled by a thermal airstream unit. All the functional tests, the data retention test, and the AC and DC parametric tests were performed at ambient temperatures of 25 C, -20 C, -55 C, 85 C, and 125 C. The schmoo plots were performed at ambient temperatures of 25 C, -55 C, and 125 C. The data retention test was performed at 25 C. Five devices failed one or more functional tests and four of these devices failed to meet the expected limits of a number of AC parametric tests. Some of the schmoo plots indicated a small degree of interaction between parameters.

Electrical Evaluation of RCA MWS5001D Random Access Memory, Volume 1

NASA Technical Reports Server (NTRS)

Klute, A.

1979-01-01

Electrical characterization and qualification tests were performed on the RCA MWS5001D, 1024 by 1-bit, CMOS, random access memory. Characterization tests were performed on five devices. The tests included functional tests, AC parametric worst case pattern selection test, determination of worst-case transition for setup and hold times and a series of schmoo plots. The qualification tests were performed on 32 devices and included a 2000 hour burn in with electrical tests performed at 0 hours and after 168, 1000, and 2000 hours of burn in. The tests performed included functional tests and AC and DC parametric tests. All of the tests in the characterization phase, with the exception of the worst-case transition test, were performed at ambient temperatures of 25, -55 and 125 C. The worst-case transition test was performed at 25 C. The preburn in electrical tests were performed at 25, -55, and 125 C. All burn in endpoint tests were performed at 25, -40, -55, 85, and 125 C.

Genetic algorithms with memory- and elitism-based immigrants in dynamic environments.

PubMed

Yang, Shengxiang

2008-01-01

In recent years the genetic algorithm community has shown a growing interest in studying dynamic optimization problems. Several approaches have been devised. The random immigrants and memory schemes are two major ones. The random immigrants scheme addresses dynamic environments by maintaining the population diversity while the memory scheme aims to adapt genetic algorithms quickly to new environments by reusing historical information. This paper investigates a hybrid memory and random immigrants scheme, called memory-based immigrants, and a hybrid elitism and random immigrants scheme, called elitism-based immigrants, for genetic algorithms in dynamic environments. In these schemes, the best individual from memory or the elite from the previous generation is retrieved as the base to create immigrants into the population by mutation. This way, not only can diversity be maintained but it is done more efficiently to adapt genetic algorithms to the current environment. Based on a series of systematically constructed dynamic problems, experiments are carried out to compare genetic algorithms with the memory-based and elitism-based immigrants schemes against genetic algorithms with traditional memory and random immigrants schemes and a hybrid memory and multi-population scheme. The sensitivity analysis regarding some key parameters is also carried out. Experimental results show that the memory-based and elitism-based immigrants schemes efficiently improve the performance of genetic algorithms in dynamic environments.

Parallel effects of memory set activation and search on timing and working memory capacity.

PubMed

Schweickert, Richard; Fortin, Claudette; Xi, Zhuangzhuang; Viau-Quesnel, Charles

2014-01-01

Accurately estimating a time interval is required in everyday activities such as driving or cooking. Estimating time is relatively easy, provided a person attends to it. But a brief shift of attention to another task usually interferes with timing. Most processes carried out concurrently with timing interfere with it. Curiously, some do not. Literature on a few processes suggests a general proposition, the Timing and Complex-Span Hypothesis: A process interferes with concurrent timing if and only if process performance is related to complex span. Complex-span is the number of items correctly recalled in order, when each item presented for study is followed by a brief activity. Literature on task switching, visual search, memory search, word generation and mental time travel supports the hypothesis. Previous work found that another process, activation of a memory set in long term memory, is not related to complex-span. If the Timing and Complex-Span Hypothesis is true, activation should not interfere with concurrent timing in dual-task conditions. We tested such activation in single-task memory search task conditions and in dual-task conditions where memory search was executed with concurrent timing. In Experiment 1, activating a memory set increased reaction time, with no significant effect on time production. In Experiment 2, set size and memory set activation were manipulated. Activation and set size had a puzzling interaction for time productions, perhaps due to difficult conditions, leading us to use a related but easier task in Experiment 3. In Experiment 3 increasing set size lengthened time production, but memory activation had no significant effect. Results here and in previous literature on the whole support the Timing and Complex-Span Hypotheses. Results also support a sequential organization of activation and search of memory. This organization predicts activation and set size have additive effects on reaction time and multiplicative effects on percent correct, which was found.

The Empty Schoolhouse: Memories of One-Room Texas Schools. The Centennial Series of the Association of Former Students, Texas A&M University, Number 68.

ERIC Educational Resources Information Center

Clegg, Luther Bryan, Ed.

This book relates the experiences of students and teachers who spent their days in one- and two-room schoolhouses in West Texas during the first half of the 20th century. The book is based on interviews with 77 people and is divided into two sections: student recollections and teachers' memories. Former students reflect on school facilities, the…

Episodic Memory Does Not Add Up: Verbatim-Gist Superposition Predicts Violations of the Additive Law of Probability

PubMed Central

Brainerd, C. J.; Wang, Zheng; Reyna, Valerie. F.; Nakamura, K.

2015-01-01

Fuzzy-trace theory’s assumptions about memory representation are cognitive examples of the familiar superposition property of physical quantum systems. When those assumptions are implemented in a formal quantum model (QEMc), they predict that episodic memory will violate the additive law of probability: If memory is tested for a partition of an item’s possible episodic states, the individual probabilities of remembering the item as belonging to each state must sum to more than 1. We detected this phenomenon using two standard designs, item false memory and source false memory. The quantum implementation of fuzzy-trace theory also predicts that violations of the additive law will vary in strength as a function of reliance on gist memory. That prediction, too, was confirmed via a series of manipulations (e.g., semantic relatedness, testing delay) that are thought to increase gist reliance. Surprisingly, an analysis of the underlying structure of violations of the additive law revealed that as a general rule, increases in remembering correct episodic states do not produce commensurate reductions in remembering incorrect states. PMID:26236091

Shared processing in multiple object tracking and visual working memory in the absence of response order and task order confounds

PubMed Central

Howe, Piers D. L.

2017-01-01

To understand how the visual system represents multiple moving objects and how those representations contribute to tracking, it is essential that we understand how the processes of attention and working memory interact. In the work described here we present an investigation of that interaction via a series of tracking and working memory dual-task experiments. Previously, it has been argued that tracking is resistant to disruption by a concurrent working memory task and that any apparent disruption is in fact due to observers making a response to the working memory task, rather than due to competition for shared resources. Contrary to this, in our experiments we find that when task order and response order confounds are avoided, all participants show a similar decrease in both tracking and working memory performance. However, if task and response order confounds are not adequately controlled for we find substantial individual differences, which could explain the previous conflicting reports on this topic. Our results provide clear evidence that tracking and working memory tasks share processing resources. PMID:28410383

Interactions of cognitive and auditory abilities in congenitally blind individuals.

PubMed

Rokem, Ariel; Ahissar, Merav

2009-02-01

Congenitally blind individuals have been found to show superior performance in perceptual and memory tasks. In the present study, we asked whether superior stimulus encoding could account for performance in memory tasks. We characterized the performance of a group of congenitally blind individuals on a series of auditory, memory and executive cognitive tasks and compared their performance to that of sighted controls matched for age, education and musical training. As expected, we found superior verbal spans among congenitally blind individuals. Moreover, we found superior speech perception, measured by resilience to noise, and superior auditory frequency discrimination. However, when memory span was measured under conditions of equivalent speech perception, by adjusting the signal to noise ratio for each individual to the same level of perceptual difficulty (80% correct), the advantage in memory span was completely eliminated. Moreover, blind individuals did not possess any advantage in cognitive executive functions, such as manipulation of items in memory and math abilities. We propose that the short-term memory advantage of blind individuals results from better stimulus encoding, rather than from superiority at subsequent processing stages.

Shared processing in multiple object tracking and visual working memory in the absence of response order and task order confounds.

PubMed

Lapierre, Mark D; Cropper, Simon J; Howe, Piers D L

2017-01-01

To understand how the visual system represents multiple moving objects and how those representations contribute to tracking, it is essential that we understand how the processes of attention and working memory interact. In the work described here we present an investigation of that interaction via a series of tracking and working memory dual-task experiments. Previously, it has been argued that tracking is resistant to disruption by a concurrent working memory task and that any apparent disruption is in fact due to observers making a response to the working memory task, rather than due to competition for shared resources. Contrary to this, in our experiments we find that when task order and response order confounds are avoided, all participants show a similar decrease in both tracking and working memory performance. However, if task and response order confounds are not adequately controlled for we find substantial individual differences, which could explain the previous conflicting reports on this topic. Our results provide clear evidence that tracking and working memory tasks share processing resources.

Identification of 5-(1-Methyl-5-(trifluoromethyl)-1H-pyrazol-3-yl)thiophene-2-Carboxamides as Novel and Selective Monoamine Oxidase B Inhibitors Used to Improve Memory and Cognition.

PubMed

Kaplan, Alan P; Keenan, Terence; Scott, Roderick; Zhou, Xianbo; Bourchouladze, Rusiko; McRiner, Andrew J; Wilson, Mark E; Romashko, Darlene; Miller, Regina; Bletsch, Matthew; Anderson, Gary; Stanley, Jennifer; Zhang, Adia; Lee, Dong; Nikpur, John

2017-12-20

Initial work in Drosophila and mice demonstrated that the transcription factor cyclic adenosine monophosphate (cAMP) response element binding protein (CREB) is a master control gene for memory formation. The relationship between CREB and memory has also been found to be true in other species, including aplysia and rats. It is thus well-established that CREB activation plays a central role in memory enhancement and that CREB is activated during memory formation. On the basis of these findings, a phenotypic high-throughput screening campaign utilizing a CRE-luciferase (CRE-Luci) SK-N-MC cell line was performed to identify compounds that enhance transcriptional activation of the CRE promoter with a suboptimal dose of forskolin. A number of small-molecule hits of unknown mechanisms of action were identified in the screening campaign, including HT-0411. Follow-up studies suggested that the CREB activation by HT-0411 is attributed to its specific and selective inhibition of monoamine oxidase B (MAO-B). Further, HT-0411 was shown to improve 24 h memory in rodents in a contextual fear conditioning model. This report describes the lead optimization of a series of 5-(1-methyl-5-(trifluoromethyl)-1H-pyrazol-3-yl) thiophene-2-carboxamides that were identified as novel, potent, and selective inhibitors of MAO-B. Extensive SAR studies and in vivo behavioral evaluations of this and other related analogue series identified a number of potential clinical development candidates; ultimately, compound 8f was identified as a candidate molecule with high selectivity toward MAO-B (29-56 nM) over MAO-A (19% inhibition at a screening concentration of 50 μM), an excellent profile against a panel of other enzymes and receptors, good pharmacokinetic properties in rodents and dogs, and efficacy in multiple rodent memory models.

Assessing predictability of a hydrological stochastic-dynamical system

NASA Astrophysics Data System (ADS)

Gelfan, Alexander

2014-05-01

The water cycle includes the processes with different memory that creates potential for predictability of hydrological system based on separating its long and short memory components and conditioning long-term prediction on slower evolving components (similar to approaches in climate prediction). In the face of the Panta Rhei IAHS Decade questions, it is important to find a conceptual approach to classify hydrological system components with respect to their predictability, define predictable/unpredictable patterns, extend lead-time and improve reliability of hydrological predictions based on the predictable patterns. Representation of hydrological systems as the dynamical systems subjected to the effect of noise (stochastic-dynamical systems) provides possible tool for such conceptualization. A method has been proposed for assessing predictability of hydrological system caused by its sensitivity to both initial and boundary conditions. The predictability is defined through a procedure of convergence of pre-assigned probabilistic measure (e.g. variance) of the system state to stable value. The time interval of the convergence, that is the time interval during which the system losses memory about its initial state, defines limit of the system predictability. The proposed method was applied to assess predictability of soil moisture dynamics in the Nizhnedevitskaya experimental station (51.516N; 38.383E) located in the agricultural zone of the central European Russia. A stochastic-dynamical model combining a deterministic one-dimensional model of hydrothermal regime of soil with a stochastic model of meteorological inputs was developed. The deterministic model describes processes of coupled heat and moisture transfer through unfrozen/frozen soil and accounts for the influence of phase changes on water flow. The stochastic model produces time series of daily meteorological variables (precipitation, air temperature and humidity), whose statistical properties are similar to those of the corresponding series of the actual data measured at the station. Beginning from the initial conditions and being forced by Monte-Carlo generated synthetic meteorological series, the model simulated diverging trajectories of soil moisture characteristics (water content of soil column, moisture of different soil layers, etc.). Limit of predictability of the specific characteristic was determined through time of stabilization of variance of the characteristic between the trajectories, as they move away from the initial state. Numerical experiments were carried out with the stochastic-dynamical model to analyze sensitivity of the soil moisture predictability assessments to uncertainty in the initial conditions, to determine effects of the soil hydraulic properties and processes of soil freezing on the predictability. It was found, particularly, that soil water content predictability is sensitive to errors in the initial conditions and strongly depends on the hydraulic properties of soil under both unfrozen and frozen conditions. Even if the initial conditions are "well-established", the assessed predictability of water content of unfrozen soil does not exceed 30-40 days, while for frozen conditions it may be as long as 3-4 months. The latter creates opportunity for utilizing the autumn water content of soil as the predictor for spring snowmelt runoff in the region under consideration.

Automated quantitative muscle biopsy analysis system

NASA Technical Reports Server (NTRS)

Castleman, Kenneth R. (Inventor)

1980-01-01

An automated system to aid the diagnosis of neuromuscular diseases by producing fiber size histograms utilizing histochemically stained muscle biopsy tissue. Televised images of the microscopic fibers are processed electronically by a multi-microprocessor computer, which isolates, measures, and classifies the fibers and displays the fiber size distribution. The architecture of the multi-microprocessor computer, which is iterated to any required degree of complexity, features a series of individual microprocessors P.sub.n each receiving data from a shared memory M.sub.n-1 and outputing processed data to a separate shared memory M.sub.n+1 under control of a program stored in dedicated memory M.sub.n.

Designing shape-memory Heusler alloys from first-principles

NASA Astrophysics Data System (ADS)

Siewert, M.; Gruner, M. E.; Dannenberg, A.; Chakrabarti, A.; Herper, H. C.; Wuttig, M.; Barman, S. R.; Singh, S.; Al-Zubi, A.; Hickel, T.; Neugebauer, J.; Gillessen, M.; Dronskowski, R.; Entel, P.

2011-11-01

The phase diagrams of magnetic shape-memory Heusler alloys, in particular, ternary Ni-Mn-Z and quarternary (Pt, Ni)-Mn-Z alloys with Z = Ga, Sn, have been addressed by density functional theory and Monte Carlo simulations. Finite temperature free energy calculations show that the phonon contribution stabilizes the high-temperature austenite structure while at low temperatures magnetism and the band Jahn-Teller effect favor the modulated monoclinic 14M or the nonmodulated tetragonal structure. The substitution of Ni by Pt leads to a series of magnetic shape-memory alloys with very similar properties to Ni-Mn-Ga but with a maximal eigenstrain of 14%.

Effects of complete monocular deprivation in visuo-spatial memory.

PubMed

Cattaneo, Zaira; Merabet, Lotfi B; Bhatt, Ela; Vecchi, Tomaso

2008-09-30

Monocular deprivation has been associated with both specific deficits and enhancements in visual perception and processing. In this study, performance on a visuo-spatial memory task was compared in congenitally monocular individuals and sighted control individuals viewing monocularly (i.e., patched) and binocularly. The task required the individuals to view and memorize a series of target locations on two-dimensional matrices. Overall, congenitally monocular individuals performed worse than sighted individuals (with a specific deficit in simultaneously maintaining distinct spatial representations in memory), indicating that the lack of binocular visual experience affects the way visual information is represented in visuo-spatial memory. No difference was observed between the monocular and binocular viewing control groups, suggesting that early monocular deprivation affects the development of cortical mechanisms mediating visuo-spatial cognition.

Memory for staged events: Supporting older and younger adults' memory with SenseCam.

PubMed

Mair, Ali; Poirier, Marie; Conway, Martin A

2018-03-01

Two experiments measured the effect of retrieval support provided by a wearable camera, SenseCam, on older and younger adults' memory for a recently experienced complex staged event. In each experiment, participants completed a series of tasks in groups, and the events were recalled 2 weeks later, after viewing SenseCam images (experimental condition) or thinking about the event (control condition). When IQ and education were matched, young adults recalled more event details than older adults, demonstrating an age-related deficit for novel autobiographical material. Reviewing SenseCam images increased the number of details recalled by older and younger adults, and the effect was similar for both groups. These results suggest that memory can be supported by the use of SenseCam, but the age-related deficit is not eliminated.

Comparing different types of source memory attributes in dementia of Alzheimer's type.

PubMed

Mammarella, Nicola; Fairfield, Beth; Di Domenico, Alberto

2012-04-01

Source monitoring (SM) refers to our ability to discriminate between memories from different sources. Twenty healthy high-cognitive functioning older adults, 20 healthy low-cognitive functioning older adults, and 20 older adults with dementia of Alzheimer's type (DAT) were asked to perform a series of SM tasks that varied in terms of the to-be-remembered source attribute (perceptual, spatial, temporal, semantic, social, and affective details). Results indicated that older DAT adults had greater difficulty in SM compared to the healthy control groups, especially with spatial and semantic details. Data are discussed in terms of the SM framework and suggest that poor memory for some types of source information may be considered as an important indicator of clinical memory function when assessing for the presence and severity of dementia.

Narrative organisation at encoding facilitated children's long-term episodic memory.

PubMed

Wang, Qi; Bui, Van-Kim; Song, Qingfang

2015-01-01

This study examined the effect of narrative organisation at encoding on long-term episodic memory in a sample of five- to seven-year-old children (N = 113). At an initial interview, children were asked to narrate a story from a picture book. Six months later, they were interviewed again and asked to recall the story and answer a series of direct questions about the story. Children who initially encoded more information in narrative and produced more complete, complex, cohesive and coherent narratives remembered the story in greater detail and accuracy following the six-month interval, independent of age and verbal skills. The relation between narrative organisation and memory was consistent across culture and gender. These findings provide new insight into the critical role of narrative in episodic memory.

Olfactory imprinting is correlated with changes in gene expression in the olfactory epithelia of the zebrafish.

PubMed

Harden, Maegan V; Newton, Lucy A; Lloyd, Russell C; Whitlock, Kathleen E

2006-11-01

Odors experienced as juveniles can have significant effects on the behavior of mature organisms. A dramatic example of this occurs in salmon, where the odors experienced by developing fish determine the river to which they return as adults. Further examples of olfactory memories are found in many animals including vertebrates and invertebrates. Yet, the cellular and molecular bases underlying the formation of olfactory memory are poorly understood. We have devised a series of experiments to determine whether zebrafish can form olfactory memories much like those observed in salmonids. Here we show for the first time that zebrafish form and retain olfactory memories of an artificial odorant, phenylethyl alcohol (PEA), experienced as juveniles. Furthermore, we demonstrate that exposure to PEA results in changes in gene expression within the olfactory sensory system. These changes are evident by in situ hybridization in the olfactory epithelium of the developing zebrafish. Strikingly, our analysis by in situ hybridization demonstrates that the transcription factor, otx2, is up regulated in the olfactory sensory epithelia in response to PEA. This increase is evident at 2-3 days postfertilization and is maintained in the adult animals. We propose that the changes in otx2 gene expression are manifest as an increase in the number of neuronal precursors in the cells olfactory epithelium of the odor-exposed fish. Thus, our results reveal a role for the environment in controlling gene expression in the developing peripheral nervous system. Copyright 2006 Wiley Periodicals, Inc.

Working memory performance and neural activity in prefrontal cortex of peripubertal monkeys

PubMed Central

Zhou, Xin; Zhu, Dantong; Qi, Xue-Lian; Lees, Cynthia J.; Bennett, Allyson J.; Salinas, Emilio; Stanford, Terrence R.

2013-01-01

The dorsolateral prefrontal cortex matures late into adolescence or early adulthood. This pattern of maturation mirrors working memory abilities, which continue to improve into adulthood. However, the nature of the changes that prefrontal neuronal activity undergoes during this process is poorly understood. We investigated behavioral performance and neural activity in working memory tasks around the time of puberty, a developmental event associated with the release of sex hormones and significant neurological change. The developmental stages of male rhesus monkeys were evaluated with a series of morphometric, hormonal, and radiographic measures. Peripubertal monkeys were trained to perform an oculomotor delayed response task and a variation of this task involving a distractor stimulus. We found that the peripubertal monkeys tended to abort a relatively large fraction of trials, and these were associated with low levels of task-related neuronal activity. However, for completed trials, accuracy in the delayed saccade task was high and the appearance of a distractor stimulus did not impact performance significantly. In correct trials delay period activity was robust and was not eliminated by the presentation of a distracting stimulus, whereas in trials that resulted in errors the sustained cue-related activity was significantly weaker. Our results show that in peripubertal monkeys the prefrontal cortex is capable of generating robust persistent activity in the delay periods of working memory tasks, although in general it may be more prone to stochastic failure than in adults. PMID:24047904

Move to learn: Integrating spatial information from multiple viewpoints.

PubMed

Holmes, Corinne A; Newcombe, Nora S; Shipley, Thomas F

2018-05-11

Recalling a spatial layout from multiple orientations - spatial flexibility - is challenging, even when the global configuration can be viewed from a single vantage point, but more so when it must be viewed piecemeal. In the current study, we examined whether experiencing the transition between multiple viewpoints enhances spatial memory and flexible recall for a spatial configuration viewed simultaneously (Exp. 1) and sequentially (Exp. 2), whether the type of transition matters, and whether action provides an additional advantage over passive experience. In Experiment 1, participants viewed an array of dollhouse furniture from four viewpoints, but with all furniture simultaneously visible. In Experiment 2, participants viewed the same array piecemeal, from four partitioned viewpoints that allowed for viewing only a segment at a time. The transition between viewpoints involved rotation of the array or participant movement around it. Rotation and participant movement were passively experienced or actively generated. The control condition presented the dollhouse as a series of static views. Across both experiments, participant movement significantly enhanced spatial memory relative to array rotation or static views. However, in Exp. 2, there was a further advantage for actively walking around the array compared to being passively pushed. These findings suggest that movement around a stable environment is key to spatial memory and flexible recall, with action providing an additional boost to the integration of temporally segmented spatial events. Thus, spatial memory may be more flexible than prior data indicate, when studied under more natural acquisition conditions. Copyright © 2018 Elsevier B.V. All rights reserved.

No Clear Association between Impaired Short-Term or Working Memory Storage and Time Reproduction Capacity in Adult ADHD Patients.

PubMed

Mette, Christian; Grabemann, Marco; Zimmermann, Marco; Strunz, Laura; Scherbaum, Norbert; Wiltfang, Jens; Kis, Bernhard

2015-01-01

Altered time reproduction is exhibited by patients with adult attention deficit hyperactivity disorder (ADHD). It remains unclear whether memory capacity influences the ability of adults with ADHD to reproduce time intervals. We conducted a behavioral study on 30 ADHD patients who were medicated with methylphenidate, 29 unmedicated adult ADHD patients and 32 healthy controls (HCs). We assessed time reproduction using six time intervals (1 s, 4 s, 6 s, 10 s, 24 s and 60 s) and assessed memory performance using the Wechsler memory scale. The patients with ADHD exhibited lower memory performance scores than the HCs. No significant differences in the raw scores for any of the time intervals (p > .05), with the exception of the variability at the short time intervals (1 s, 4 s and 6 s) (p < .01), were found between the groups. The overall analyses failed to reveal any significant correlations between time reproduction at any of the time intervals examined in the time reproduction task and working memory performance (p > .05). We detected no findings indicating that working memory might influence time reproduction in adult patients with ADHD. Therefore, further studies concerning time reproduction and memory capacity among adult patients with ADHD must be performed to verify and replicate the present findings.

Spatial memory in foraging games.

PubMed

Kerster, Bryan E; Rhodes, Theo; Kello, Christopher T

2016-03-01

Foraging and foraging-like processes are found in spatial navigation, memory, visual search, and many other search functions in human cognition and behavior. Foraging is commonly theorized using either random or correlated movements based on Lévy walks, or a series of decisions to remain or leave proximal areas known as "patches". Neither class of model makes use of spatial memory, but search performance may be enhanced when information about searched and unsearched locations is encoded. A video game was developed to test the role of human spatial memory in a canonical foraging task. Analyses of search trajectories from over 2000 human players yielded evidence that foraging movements were inherently clustered, and that clustering was facilitated by spatial memory cues and influenced by memory for spatial locations of targets found. A simple foraging model is presented in which spatial memory is used to integrate aspects of Lévy-based and patch-based foraging theories to perform a kind of area-restricted search, and thereby enhance performance as search unfolds. Using only two free parameters, the model accounts for a variety of findings that individually support competing theories, but together they argue for the integration of spatial memory into theories of foraging. Copyright © 2015 Elsevier B.V. All rights reserved.

When green is positive and red is negative: Aging and the influence of color on emotional memories.

PubMed

Mammarella, Nicola; Di Domenico, Alberto; Palumbo, Rocco; Fairfield, Beth

2016-12-01

Numerous studies have reported age-related differences in memory for emotional information. One explanation places emphasis on an emotion processing preference in older adults that reflects their socioemotional self-relevant goals. Here, we evaluate the degree to which this preference in memory may be modulated by color. In 2 experiments, younger and older adults were asked to study a series of affective words (Experiment 1) or affective pictures (Experiment 2) and then presented with an immediate yes/no memory recognition task. In particular, words and pictures were colored according to the following valence-color associations: positive-green, negative-red, and neutral-blue. Each study condition included both congruent (e.g., positive-green) and incongruent associations (e.g., positive-red). For both experiments, participants showed an advantage for congruent associations compared with other types of valence-color pairings that emphasized a robust joint effect of color and affective valence in memory. More specifically, older adults' memory was sensitive to positive-green stimuli only. We discussed results in line with mechanisms underlying positivity effects in memory and the effect of color on emotional memory encoding. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Memory-induced acceleration and slowdown of barrier crossing

NASA Astrophysics Data System (ADS)

Kappler, Julian; Daldrop, Jan O.; Brünig, Florian N.; Boehle, Moritz D.; Netz, Roland R.

2018-01-01

We study the mean first-passage time τMFP for the barrier crossing of a single massive particle with non-Markovian memory by Langevin simulations in one dimension. In the Markovian limit of short memory time τΓ, the expected Kramers turnover between the overdamped (high-friction) and the inertial (low-friction) limits is recovered. Compared to the Markovian case, we find barrier crossing to be accelerated for intermediate memory time, while for long memory time, barrier crossing is slowed down and τMFP increases with τΓ as a power law τM F P˜τΓ2. Both effects are derived from an asymptotic propagator analysis: while barrier crossing acceleration at intermediate memory can be understood as an effective particle mass reduction, slowing down for long memory is caused by the slow kinetics of energy diffusion. A simple and globally accurate heuristic formula for τMFP in terms of all relevant time scales of the system is presented and used to establish a scaling diagram featuring the Markovian overdamped and the Markovian inertial regimes, as well as the non-Markovian intermediate memory time regime where barrier crossing is accelerated and the non-Markovian long memory time regime where barrier crossing is slowed down.

Scaling properties in time-varying networks with memory

NASA Astrophysics Data System (ADS)

Kim, Hyewon; Ha, Meesoon; Jeong, Hawoong

2015-12-01

The formation of network structure is mainly influenced by an individual node's activity and its memory, where activity can usually be interpreted as the individual inherent property and memory can be represented by the interaction strength between nodes. In our study, we define the activity through the appearance pattern in the time-aggregated network representation, and quantify the memory through the contact pattern of empirical temporal networks. To address the role of activity and memory in epidemics on time-varying networks, we propose temporal-pattern coarsening of activity-driven growing networks with memory. In particular, we focus on the relation between time-scale coarsening and spreading dynamics in the context of dynamic scaling and finite-size scaling. Finally, we discuss the universality issue of spreading dynamics on time-varying networks for various memory-causality tests.

Time-based and event-based prospective memory in autism spectrum disorder: the roles of executive function and theory of mind, and time-estimation.

PubMed

Williams, David; Boucher, Jill; Lind, Sophie; Jarrold, Christopher

2013-07-01

Prospective memory (remembering to carry out an action in the future) has been studied relatively little in ASD. We explored time-based (carry out an action at a pre-specified time) and event-based (carry out an action upon the occurrence of a pre-specified event) prospective memory, as well as possible cognitive correlates, among 21 intellectually high-functioning children with ASD, and 21 age- and IQ-matched neurotypical comparison children. We found impaired time-based, but undiminished event-based, prospective memory among children with ASD. In the ASD group, time-based prospective memory performance was associated significantly with diminished theory of mind, but not with diminished cognitive flexibility. There was no evidence that time-estimation ability contributed to time-based prospective memory impairment in ASD.

Influence of metal electrode on the performance of ZnO based resistance switching memories

NASA Astrophysics Data System (ADS)

Wang, Xueting; Qian, Haolei; Guan, Liao; Wang, Wei; Xing, Boran; Yan, Xiaoyuan; Zhang, Shucheng; Sha, Jian; Wang, Yewu

2017-10-01

Resistance random access memory (RRAM) is considered a promising candidate for the next generation of non-volatile memory. In this work, we fabricate metal (Ag, Ti, or Pt)/ZnO/Pt RRAM cells and then systematically investigate the effects of different top electrodes and their performance. With the formation and rupture of Ag-bridge and the shapeless oxygen vacancy filaments under a series of positive and negative bias, the set and reset processes have been successfully conducted in the Ag/ZnO/Pt device with very low work voltage, high on-off ratio, and good endurance. When applying the voltage bias to the Ti/ZnO/Pt device, the interfacial oxygen ions' migration causes the redox reaction of the conducting filament's oxygen vacancies, leading to the formation and rupture of the conducting filaments but in a relatively poor endurance. At the same time, for the Pt/ZnO/Pt device, once the filaments in the functional layer consisting of oxygen vacancies are formed, it is difficult to disrupt, resulting in the permanent low resistance state after a forming-like process. The results demonstrated that the devices with a metallic conductive bridge mechanism show much better switching behaviors than those with an oxygen ion/vacancy filament mechanism.

Jordan recurrent neural network versus IHACRES in modelling daily streamflows

NASA Astrophysics Data System (ADS)

Carcano, Elena Carla; Bartolini, Paolo; Muselli, Marco; Piroddi, Luigi

2008-12-01

SummaryA study of possible scenarios for modelling streamflow data from daily time series, using artificial neural networks (ANNs), is presented. Particular emphasis is devoted to the reconstruction of drought periods where water resource management and control are most critical. This paper considers two connectionist models: a feedforward multilayer perceptron (MLP) and a Jordan recurrent neural network (JNN), comparing network performance on real world data from two small catchments (192 and 69 km 2 in size) with irregular and torrential regimes. Several network configurations are tested to ensure a good combination of input features (rainfall and previous streamflow data) that capture the variability of the physical processes at work. Tapped delayed line (TDL) and memory effect techniques are introduced to recognize and reproduce temporal dependence. Results show a poor agreement when using TDL only, but a remarkable improvement can be obtained with JNN and its memory effect procedures, which are able to reproduce the system memory over a catchment in a more effective way. Furthermore, the IHACRES conceptual model, which relies on both rainfall and temperature input data, is introduced for comparative study. The results suggest that when good input data is unavailable, metric models perform better than conceptual ones and, in general, it is difficult to justify substantial conceptualization of complex processes.

Sequential Self-Folding Structures by 3D Printed Digital Shape Memory Polymers

NASA Astrophysics Data System (ADS)

Mao, Yiqi; Yu, Kai; Isakov, Michael S.; Wu, Jiangtao; Dunn, Martin L.; Jerry Qi, H.

2015-09-01

Folding is ubiquitous in nature with examples ranging from the formation of cellular components to winged insects. It finds technological applications including packaging of solar cells and space structures, deployable biomedical devices, and self-assembling robots and airbags. Here we demonstrate sequential self-folding structures realized by thermal activation of spatially-variable patterns that are 3D printed with digital shape memory polymers, which are digital materials with different shape memory behaviors. The time-dependent behavior of each polymer allows the temporal sequencing of activation when the structure is subjected to a uniform temperature. This is demonstrated via a series of 3D printed structures that respond rapidly to a thermal stimulus, and self-fold to specified shapes in controlled shape changing sequences. Measurements of the spatial and temporal nature of self-folding structures are in good agreement with the companion finite element simulations. A simplified reduced-order model is also developed to rapidly and accurately describe the self-folding physics. An important aspect of self-folding is the management of self-collisions, where different portions of the folding structure contact and then block further folding. A metric is developed to predict collisions and is used together with the reduced-order model to design self-folding structures that lock themselves into stable desired configurations.

The Role of Working Memory in the Probabilistic Inference of Future Sensory Events.

PubMed

Cashdollar, Nathan; Ruhnau, Philipp; Weisz, Nathan; Hasson, Uri

2017-05-01

The ability to represent the emerging regularity of sensory information from the external environment has been thought to allow one to probabilistically infer future sensory occurrences and thus optimize behavior. However, the underlying neural implementation of this process is still not comprehensively understood. Through a convergence of behavioral and neurophysiological evidence, we establish that the probabilistic inference of future events is critically linked to people's ability to maintain the recent past in working memory. Magnetoencephalography recordings demonstrated that when visual stimuli occurring over an extended time series had a greater statistical regularity, individuals with higher working-memory capacity (WMC) displayed enhanced slow-wave neural oscillations in the θ frequency band (4-8 Hz.) prior to, but not during stimulus appearance. This prestimulus neural activity was specifically linked to contexts where information could be anticipated and influenced the preferential sensory processing for this visual information after its appearance. A separate behavioral study demonstrated that this process intrinsically emerges during continuous perception and underpins a realistic advantage for efficient behavioral responses. In this way, WMC optimizes the anticipation of higher level semantic concepts expected to occur in the near future. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Continuous Timescale Long-Short Term Memory Neural Network for Human Intent Understanding

PubMed Central

Yu, Zhibin; Moirangthem, Dennis S.; Lee, Minho

2017-01-01

Understanding of human intention by observing a series of human actions has been a challenging task. In order to do so, we need to analyze longer sequences of human actions related with intentions and extract the context from the dynamic features. The multiple timescales recurrent neural network (MTRNN) model, which is believed to be a kind of solution, is a useful tool for recording and regenerating a continuous signal for dynamic tasks. However, the conventional MTRNN suffers from the vanishing gradient problem which renders it impossible to be used for longer sequence understanding. To address this problem, we propose a new model named Continuous Timescale Long-Short Term Memory (CTLSTM) in which we inherit the multiple timescales concept into the Long-Short Term Memory (LSTM) recurrent neural network (RNN) that addresses the vanishing gradient problem. We design an additional recurrent connection in the LSTM cell outputs to produce a time-delay in order to capture the slow context. Our experiments show that the proposed model exhibits better context modeling ability and captures the dynamic features on multiple large dataset classification tasks. The results illustrate that the multiple timescales concept enhances the ability of our model to handle longer sequences related with human intentions and hence proving to be more suitable for complex tasks, such as intention recognition. PMID:28878646

Scaling behaviors of precipitation over China

NASA Astrophysics Data System (ADS)

Jiang, Lei; Li, Nana; Zhao, Xia

2017-04-01

Scaling behaviors in the precipitation time series derived from 1951 to 2009 over China are investigated by detrended fluctuation analysis (DFA) method. The results show that there exists long-term memory for the precipitation time series in some stations, where the values of the scaling exponent α are less than 0.62, implying weak persistence characteristics. The values of scaling exponent in other stations indicate random behaviors. In addition, the scaling exponent α in precipitation records varies from station to station over China. A numerical test is made to verify the significance in DFA exponents by shuffling the data records many times. We think it is significant when the values of scaling exponent before shuffled precipitation records are larger than the interval threshold for 95 % confidence level after shuffling precipitation records many times. By comparison, the daily precipitation records exhibit weak positively long-range correlation in a power law fashion mainly at the stations taking on zonal distributions in south China, upper and middle reaches of the Yellow River, northern part of northeast China. This may be related to the subtropical high. Furthermore, the values of scaling exponent which cannot pass the significance test do not show a clear distribution pattern. It seems that the stations are mainly distributed in coastal areas, southwest China, and southern part of north China. In fact, many complicated factors may affect the scaling behaviors of precipitation such as the system of the east and south Asian monsoon, the interaction between sea and land, and the big landform of the Tibetan Plateau. These results may provide a better prerequisite to long-term predictor of precipitation time series for different regions over China.

Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time.

PubMed

Limongi, Roberto; Silva, Angélica M

2016-11-01

The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production - where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

Does targeted cognitive training reduce educational disparities in cognitive function among cognitively normal older adults?

PubMed

Clark, Daniel O; Xu, Huiping; Unverzagt, Frederick W; Hendrie, Hugh

2016-07-01

The aim of this study was to investigate educational differences in treatment responses to memory, reasoning, and speed of processing cognitive training relative to no-contact control. Secondary analyses of the Advanced Cognitive Training for Independent and Vital Elderly trial were conducted. Two thousand eight hundred older adults were randomized to memory, reasoning, or speed of processing training or no-contact control. A repeated-measures mixed-effects model was used to investigate immediate post-training and 1-year outcomes with sensitivity analyses out to 10 years. Outcomes were as follows: (1) memory composite of Hopkins Verbal Learning Test, Rey Auditory Verbal Learning Test, and Rivermead Behavioral Memory Test; (2) reasoning composite of letter series, letter sets, and word series; and (3) speed of processing measured using three trials of useful field of view and the digit symbol substitution test. The effects of reasoning and memory training did not differ by educational attainment. The effect of speed of processing training did. Those with fewer than 12 years of education experienced a 50% greater effect on the useful field of view test compared with those with 16 or more years of education. The training advantage for those with fewer than 12 years of education was maintained to 3 years post-training. Older adults with less than a secondary education are at elevated risk of dementia, including Alzheimer's disease. The analyses here indicate that speed of processing training is effective in older adults with low educational attainment. Copyright © 2015 John Wiley & Sons, Ltd.

The Mark III Hypercube-Ensemble Computers

NASA Technical Reports Server (NTRS)

Peterson, John C.; Tuazon, Jesus O.; Lieberman, Don; Pniel, Moshe

1988-01-01

Mark III Hypercube concept applied in development of series of increasingly powerful computers. Processor of each node of Mark III Hypercube ensemble is specialized computer containing three subprocessors and shared main memory. Solves problem quickly by simultaneously processing part of problem at each such node and passing combined results to host computer. Disciplines benefitting from speed and memory capacity include astrophysics, geophysics, chemistry, weather, high-energy physics, applied mechanics, image processing, oil exploration, aircraft design, and microcircuit design.

Short-term memory and critical clusterization in brain neurons spike series

NASA Astrophysics Data System (ADS)

Bershadskii, A.; Dremencov, E.; Yadid, G.

2003-06-01

A new phenomenon: critical clusterization, is observed in the neuron firing of a genetically defined rat model of depression. The critical clusterization is studied using a multiscaling analysis of the data obtained from the neurons belonging to the Red Nucleus area of the depressive brains. It is suggested that this critical phenomenon can be partially responsible for the observed ill behavior of the depressive brains: loss of short-term motor memory and slow motor reaction.

Time-dependent effects of cortisol on the contextualization of emotional memories.

PubMed

van Ast, Vanessa A; Cornelisse, Sandra; Meeter, Martijn; Joëls, Marian; Kindt, Merel

2013-12-01

The inability to store fearful memories into their original encoding context is considered to be an important vulnerability factor for the development of anxiety disorders like posttraumatic stress disorder. Altered memory contextualization most likely involves effects of the stress hormone cortisol, acting via receptors located in the memory neurocircuitry. Cortisol via these receptors induces rapid nongenomic effects followed by slower genomic effects, which are thought to modulate cognitive function in opposite, complementary ways. Here, we targeted these time-dependent effects of cortisol during memory encoding and tested subsequent contextualization of emotional and neutral memories. In a double-blind, placebo-controlled design, 64 men were randomly assigned to one of three groups: 1) received 10 mg hydrocortisone 30 minutes (rapid cortisol effects) before a memory encoding task; 2) received 10 mg hydrocortisone 210 minutes (slow cortisol) before a memory encoding task; or 3) received placebo at both times. During encoding, participants were presented with neutral and emotional words in unique background pictures. Approximately 24 hours later, context dependency of their memories was assessed. Recognition data revealed that cortisol's rapid effects impair emotional memory contextualization, while cortisol's slow effects enhance it. Neutral memory contextualization remained unaltered by cortisol, irrespective of the timing of the drug. This study shows distinct time-dependent effects of cortisol on the contextualization of specifically emotional memories. The results suggest that rapid effects of cortisol may lead to impaired emotional memory contextualization, while slow effects of cortisol may confer protection against emotional memory generalization. © 2013 Society of Biological Psychiatry.

Hold it! Memory affects attentional dwell time.

PubMed

Parks, Emily L; Hopfinger, Joseph B

2008-12-01

The allocation of attention, including the initial orienting and the subsequent dwell time, is affected by several bottom-up and top-down factors. How item memory affects these processes, however, remains unclear. Here, we investigated whether item memory affects attentional dwell time by using a modified version of the attentional blink (AB) paradigm. Across four experiments, our results revealed that the AB was significantly affected by memory status (novel vs. old), but critically, this effect depended on the ongoing memory context. Specifically, items that were unique in terms of memory status demanded more resources, as measured by a protracted AB. The present findings suggest that a more comprehensive understanding of memory's effects on attention can be obtained by accounting for an item's memorial context, as well as its individual item memory strength. Our results provide new evidence that item memory and memory context play a significant role in the temporal allocation of attention.

SPA- STATISTICAL PACKAGE FOR TIME AND FREQUENCY DOMAIN ANALYSIS

NASA Technical Reports Server (NTRS)

Brownlow, J. D.

1994-01-01

The need for statistical analysis often arises when data is in the form of a time series. This type of data is usually a collection of numerical observations made at specified time intervals. Two kinds of analysis may be performed on the data. First, the time series may be treated as a set of independent observations using a time domain analysis to derive the usual statistical properties including the mean, variance, and distribution form. Secondly, the order and time intervals of the observations may be used in a frequency domain analysis to examine the time series for periodicities. In almost all practical applications, the collected data is actually a mixture of the desired signal and a noise signal which is collected over a finite time period with a finite precision. Therefore, any statistical calculations and analyses are actually estimates. The Spectrum Analysis (SPA) program was developed to perform a wide range of statistical estimation functions. SPA can provide the data analyst with a rigorous tool for performing time and frequency domain studies. In a time domain statistical analysis the SPA program will compute the mean variance, standard deviation, mean square, and root mean square. It also lists the data maximum, data minimum, and the number of observations included in the sample. In addition, a histogram of the time domain data is generated, a normal curve is fit to the histogram, and a goodness-of-fit test is performed. These time domain calculations may be performed on both raw and filtered data. For a frequency domain statistical analysis the SPA program computes the power spectrum, cross spectrum, coherence, phase angle, amplitude ratio, and transfer function. The estimates of the frequency domain parameters may be smoothed with the use of Hann-Tukey, Hamming, Barlett, or moving average windows. Various digital filters are available to isolate data frequency components. Frequency components with periods longer than the data collection interval are removed by least-squares detrending. As many as ten channels of data may be analyzed at one time. Both tabular and plotted output may be generated by the SPA program. This program is written in FORTRAN IV and has been implemented on a CDC 6000 series computer with a central memory requirement of approximately 142K (octal) of 60 bit words. This core requirement can be reduced by segmentation of the program. The SPA program was developed in 1978.

The many faces of amnesia.

PubMed

Gold, Paul E

2006-01-01

Results from studies of retrograde amnesia provide much of the evidence for theories of memory consolidation. Retrograde amnesia gradients are often interpreted as revealing the time needed for the formation of long-term memories. The rapid forgetting observed after many amnestic treatments, including protein synthesis inhibitors, and the parallel decay seen in long-term potentiation experiments are presumed to reveal the duration of short-term memory processing. However, there is clear and consistent evidence that the time courses obtained in these amnesia experiments are highly variable within and across experiments and treatments. The evidence is inconsistent with identification of basic temporal properties of memory consolidation. Alternative views include modulation of memory and emphasize the roles that hormones and neurotransmitters have in regulating memory formation. Of related interest, converging lines of evidence suggest that inhibitors of protein synthesis and of other biochemical processes act on modulators of memory formation rather than on mechanisms of memory formation. Based on these findings, memory consolidation and reconsolidation studies might better be identified as memory modulation and "remodulation" studies. Beyond a missing and perhaps unattainable time constant of memory consolidation, some current views of memory consolidation assume that memories, once formed, are generally unmodifiable. It is this perspective that appears to have led to the recent interest in memory reconsolidation. But the view adopted here is that memories are continually malleable, being updated by new experiences and, at the same time, altering the memories of later experiences. Studies of memory remodulation offer promise of understanding the neurobiological bases by which new memories are altered by prior experiences and by which old memories are altered by new experiences.

Relational memory and self-efficacy measures reveal distinct profiles of subjective memory concerns in older adults.

PubMed

Lucas, Heather D; Monti, Jim M; McAuley, Edward; Watson, Patrick D; Kramer, Arthur F; Cohen, Neal J

2016-07-01

Subjective memory concerns (SMCs) in healthy older adults are associated with future decline and can indicate preclinical dementia. However, SMCs may be multiply determined, and often correlate with affective or psychosocial variables rather than with performance on memory tests. Our objective was to identify sensitive and selective methods to disentangle the underlying causes of SMCs. Because preclinical dementia pathology targets the hippocampus, we hypothesized that performance on hippocampally dependent relational memory tests would correlate with SMCs. We thus administered a series of memory tasks with varying dependence on relational memory processing to 91 older adults, along with questionnaires assessing depression, anxiety, and memory self-efficacy. We used correlational, regression, and mediation analyses to compare the variance in SMCs accounted for by these measures. Performance on the task most dependent on relational memory processing showed a stronger negative association with SMCs than did other memory performance metrics. SMCs were also negatively associated with memory self-efficacy. These 2 measures, along with age and education, accounted for 40% of the variance in SMCs. Self-efficacy and relational memory were uncorrelated and independent predictors of SMCs. Moreover, self-efficacy statistically mediated the relationship between SMCs and depression and anxiety, which can be detrimental to cognitive aging. These data identify multiple mechanisms that can contribute to SMCs, and suggest that SMCs can both cause and be caused by age-related cognitive decline. Relational memory measures may be effective assays of objective memory difficulties, while assessing self-efficacy could identify detrimental affective responses to cognitive aging. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

V.A.Robsman: Nonlinear Testing and Building Industry

NASA Astrophysics Data System (ADS)

Rudenko, Oleg V.

2006-05-01

This talk is devoted to the memory of outstanding scientist and engineer Vadim A. Robsman who died in January 2005. Dr.Robsman was the Honored Builder of Russia. He developed and applied new methods of nondestructive testing of buildings, bridges, power plants and other building units. At the same time, he published works on fundamental problems of acoustics and nonlinear dynamics. In particular, he suggested a new equation of the 4-th order continuing the series of basic equations of nonlinear wave theory (Burgers Eq.: 2-nd order, Korteveg - de Vries Eq.: 3-rd order) and found exact solutions for high-intensity waves in scattering media.

The influence of liquidity on informational efficiency: The case of the Thai Stock Market

NASA Astrophysics Data System (ADS)

Bariviera, Aurelio Fernández

2011-11-01

The presence of long-range memory in financial time series is a puzzling fact that challenges the established financial theory. We study the effect of liquidity on the efficiency (measured by the Hurst’s exponent) of the Thai Stock Market. According to our study, we find that: (i) the R/S method could generate spurious long-range dependence, giving the DFA method more reliable estimates of the Hurst’s exponent and (ii) there is a weak relationship between market capitalization and the efficiency of the market, and that the latter is not significantly affected by the presence of foreign investors.

No Clear Association between Impaired Short-Term or Working Memory Storage and Time Reproduction Capacity in Adult ADHD Patients

PubMed Central

Mette, Christian; Grabemann, Marco; Zimmermann, Marco; Strunz, Laura; Scherbaum, Norbert; Wiltfang, Jens; Kis, Bernhard

2015-01-01

Objective Altered time reproduction is exhibited by patients with adult attention deficit hyperactivity disorder (ADHD). It remains unclear whether memory capacity influences the ability of adults with ADHD to reproduce time intervals. Method We conducted a behavioral study on 30 ADHD patients who were medicated with methylphenidate, 29 unmedicated adult ADHD patients and 32 healthy controls (HCs). We assessed time reproduction using six time intervals (1 s, 4 s, 6 s, 10 s, 24 s and 60 s) and assessed memory performance using the Wechsler memory scale. Results The patients with ADHD exhibited lower memory performance scores than the HCs. No significant differences in the raw scores for any of the time intervals (p > .05), with the exception of the variability at the short time intervals (1 s, 4 s and 6 s) (p < .01), were found between the groups. The overall analyses failed to reveal any significant correlations between time reproduction at any of the time intervals examined in the time reproduction task and working memory performance (p > .05). Conclusion We detected no findings indicating that working memory might influence time reproduction in adult patients with ADHD. Therefore, further studies concerning time reproduction and memory capacity among adult patients with ADHD must be performed to verify and replicate the present findings. PMID:26221955

B.Gregory Lecture

ScienceCinema

None

2018-05-18

Third series of "Gregory lectures" on the memory of B. Gregory (1919-1977), DG from 1965 to 1970. The first conference B. Gregory is presented by Professor V. Weisskopf, his predecessor. Chriss Greeg from Berkeley also speaks.

Memory--a century of consolidation.

PubMed

McGaugh, J L

2000-01-14

The memory consolidation hypothesis proposed 100 years ago by Müller and Pilzecker continues to guide memory research. The hypothesis that new memories consolidate slowly over time has stimulated studies revealing the hormonal and neural influences regulating memory consolidation, as well as molecular and cellular mechanisms. This review examines the progress made over the century in understanding the time-dependent processes that create our lasting memories.

Time series analysis of temporal networks

NASA Astrophysics Data System (ADS)

Sikdar, Sandipan; Ganguly, Niloy; Mukherjee, Animesh

2016-01-01

A common but an important feature of all real-world networks is that they are temporal in nature, i.e., the network structure changes over time. Due to this dynamic nature, it becomes difficult to propose suitable growth models that can explain the various important characteristic properties of these networks. In fact, in many application oriented studies only knowing these properties is sufficient. For instance, if one wishes to launch a targeted attack on a network, this can be done even without the knowledge of the full network structure; rather an estimate of some of the properties is sufficient enough to launch the attack. We, in this paper show that even if the network structure at a future time point is not available one can still manage to estimate its properties. We propose a novel method to map a temporal network to a set of time series instances, analyze them and using a standard forecast model of time series, try to predict the properties of a temporal network at a later time instance. To our aim, we consider eight properties such as number of active nodes, average degree, clustering coefficient etc. and apply our prediction framework on them. We mainly focus on the temporal network of human face-to-face contacts and observe that it represents a stochastic process with memory that can be modeled as Auto-Regressive-Integrated-Moving-Average (ARIMA). We use cross validation techniques to find the percentage accuracy of our predictions. An important observation is that the frequency domain properties of the time series obtained from spectrogram analysis could be used to refine the prediction framework by identifying beforehand the cases where the error in prediction is likely to be high. This leads to an improvement of 7.96% (for error level ≤20%) in prediction accuracy on an average across all datasets. As an application we show how such prediction scheme can be used to launch targeted attacks on temporal networks. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.

Predictors of Time-Based Prospective Memory in Children

ERIC Educational Resources Information Center

Mackinlay, Rachael J.; Kliegel, Matthias; Mantyla, Timo

2009-01-01

This study identified age differences in time-based prospective memory performance in school-aged children and explored possible cognitive correlates of age-related performance. A total of 56 7- to 12-year-olds performed a prospective memory task in which prospective memory accuracy, ongoing task performance, and time monitoring were assessed.…

How Semantic and Episodic Memory Contribute to Autobiographical Memory. Commentary on Burt

ERIC Educational Resources Information Center

Tendolkar, Indira

2008-01-01

In his article, Chris Burt focuses on the relationship between time and autobiographical memory. The question Burt puts forward is whether temporal markers in reports on autobiographic memories reflect specific temporal information or result from rather complex cognitive processing of time-relevant knowledge. The aspect of time is inherent to the…

Gaze movements and spatial working memory in collision avoidance: a traffic intersection task

PubMed Central

Hardiess, Gregor; Hansmann-Roth, Sabrina; Mallot, Hanspeter A.

2013-01-01

Street crossing under traffic is an everyday activity including collision detection as well as avoidance of objects in the path of motion. Such tasks demand extraction and representation of spatio-temporal information about relevant obstacles in an optimized format. Relevant task information is extracted visually by the use of gaze movements and represented in spatial working memory. In a virtual reality traffic intersection task, subjects are confronted with a two-lane intersection where cars are appearing with different frequencies, corresponding to high and low traffic densities. Under free observation and exploration of the scenery (using unrestricted eye and head movements) the overall task for the subjects was to predict the potential-of-collision (POC) of the cars or to adjust an adequate driving speed in order to cross the intersection without collision (i.e., to find the free space for crossing). In a series of experiments, gaze movement parameters, task performance, and the representation of car positions within working memory at distinct time points were assessed in normal subjects as well as in neurological patients suffering from homonymous hemianopia. In the following, we review the findings of these experiments together with other studies and provide a new perspective of the role of gaze behavior and spatial memory in collision detection and avoidance, focusing on the following questions: (1) which sensory variables can be identified supporting adequate collision detection? (2) How do gaze movements and working memory contribute to collision avoidance when multiple moving objects are present and (3) how do they correlate with task performance? (4) How do patients with homonymous visual field defects (HVFDs) use gaze movements and working memory to compensate for visual field loss? In conclusion, we extend the theory of collision detection and avoidance in the case of multiple moving objects and provide a new perspective on the combined operation of external (bottom-up) and internal (top-down) cues in a traffic intersection task. PMID:23760667

The beneficial role of memory reactivation for language learning during sleep: A review.

PubMed

Schreiner, Thomas; Rasch, Björn

2017-04-01

Sleep is essential for diverse aspects of language learning. According to a prominent concept these beneficial effects of sleep rely on spontaneous reactivation processes. A series of recent studies demonstrated that inducing such reactivation processes by re-exposure to memory cues during sleep enhances foreign vocabulary learning. Building upon these findings, the present article reviews recent models and empirical findings concerning the beneficial effects of sleep on language learning. Consequently, the memory function of sleep, its neural underpinnings and the role of the sleeping brain in language learning will be summarized. Finally, we will propose a working model concerning the oscillatory requirements for successful reactivation processes and future research questions to advance our understanding of the role of sleep on language learning and memory processes in general. Copyright © 2016 Elsevier Inc. All rights reserved.

Comparative Analysis of VaR Estimation of Double Long-Memory GARCH Models: Empirical Analysis of China's Stock Market

NASA Astrophysics Data System (ADS)

Cao, Guangxi; Guo, Jianping; Xu, Lin

GARCH models are widely used to model the volatility of financial assets and measure VaR. Based on the characteristics of long-memory and lepkurtosis and fat tail of stock market return series, we compared the ability of double long-memory GARCH models with skewed student-t-distribution to compute VaR, through the empirical analysis of Shanghai Composite Index (SHCI) and Shenzhen Component Index (SZCI). The results show that the ARFIMA-HYGARCH model performance better than others, and at less than or equal to 2.5 percent of the level of VaR, double long-memory GARCH models have stronger ability to evaluate in-sample VaRs in long position than in short position while there is a diametrically opposite conclusion for ability of out-of-sample VaR forecast.

Runtime support for parallelizing data mining algorithms

NASA Astrophysics Data System (ADS)

Jin, Ruoming; Agrawal, Gagan

2002-03-01

With recent technological advances, shared memory parallel machines have become more scalable, and offer large main memories and high bus bandwidths. They are emerging as good platforms for data warehousing and data mining. In this paper, we focus on shared memory parallelization of data mining algorithms. We have developed a series of techniques for parallelization of data mining algorithms, including full replication, full locking, fixed locking, optimized full locking, and cache-sensitive locking. Unlike previous work on shared memory parallelization of specific data mining algorithms, all of our techniques apply to a large number of common data mining algorithms. In addition, we propose a reduction-object based interface for specifying a data mining algorithm. We show how our runtime system can apply any of the technique we have developed starting from a common specification of the algorithm.

Is there differences in cognitive and motor functioning between hemodialysis and peritoneal dialysis patients?

PubMed

Radić, Josipa; Ljutić, Dragan; Radić, Mislav; Kovačić, Vedran; Sain, Milenka; Dodig-Ćurković, Katarina

2011-01-01

Change in cognitive function is one of the well-known consequences of the end-stage renal disease (ESRD). The aim of this study was to determine the effect of hemodialysis (HD) and continuous ambulatory peritoneal dialysis (CAPD) on cognitive and motor functions. In this cross-sectional study, cognitive and motor functions were investigated in a selected population of 42 patients with ESRD (22 patients on chronic HD and 20 patients on CAPD, aged 50.31 ± 11.07 years). Assessment of cognitive and motor functions was performed by Symbol Digit Modalities Test (SDMT) and Complex Reactiometer Drenovac (CRD-series), a battery of computer-generated psychological tests to measure simple visual discrimination of signal location, short-term memory, simple convergent visual orientation, and convergent thinking. The statistically significant difference in cognitive-motor functions between HD and CAPD patients was not found in any of the time-related parameters in all CRD-series tests or SDMT score. Higher serum levels of albumin, creatinine, and calcium were correlated with better cognitive-motor performance among all patients regardless of dialysis modality. The significant correlation between ultrafiltration rate per HD and short-term memory actualization test score (CRD-324 MT) among HD patients was found (r = 0.434, p = 0.025). This study has demonstrated that well-nourished and medically stable HD and CAPD patients without clinical signs of dementia or cognitive impairment and without significant difference in age and level of education performed all tests of cognitive-motor abilities without statistically significant difference.

Memories of unethical actions become obfuscated over time

PubMed Central

Kouchaki, Maryam; Gino, Francesca

2016-01-01

Despite our optimistic belief that we would behave honestly when facing the temptation to act unethically, we often cross ethical boundaries. This paper explores one possibility of why people engage in unethical behavior over time by suggesting that their memory for their past unethical actions is impaired. We propose that, after engaging in unethical behavior, individuals’ memories of their actions become more obfuscated over time because of the psychological distress and discomfort such misdeeds cause. In nine studies (n = 2,109), we show that engaging in unethical behavior produces changes in memory so that memories of unethical actions gradually become less clear and vivid than memories of ethical actions or other types of actions that are either positive or negative in valence. We term this memory obfuscation of one’s unethical acts over time “unethical amnesia.” Because of unethical amnesia, people are more likely to act dishonestly repeatedly over time. PMID:27185941

Memories of unethical actions become obfuscated over time.

PubMed

Kouchaki, Maryam; Gino, Francesca

2016-05-31

Despite our optimistic belief that we would behave honestly when facing the temptation to act unethically, we often cross ethical boundaries. This paper explores one possibility of why people engage in unethical behavior over time by suggesting that their memory for their past unethical actions is impaired. We propose that, after engaging in unethical behavior, individuals' memories of their actions become more obfuscated over time because of the psychological distress and discomfort such misdeeds cause. In nine studies (n = 2,109), we show that engaging in unethical behavior produces changes in memory so that memories of unethical actions gradually become less clear and vivid than memories of ethical actions or other types of actions that are either positive or negative in valence. We term this memory obfuscation of one's unethical acts over time "unethical amnesia." Because of unethical amnesia, people are more likely to act dishonestly repeatedly over time.

HPA Axis Function Alters Development of Working Memory in Boys with FXS

PubMed Central

Scherr, Jessica F.; Hahn, Laura J.; Hooper, Stephen R.; Hatton, Deborah; Roberts, Jane E.

2016-01-01

The present study examines verbal working memory over time in boys with fragile X syndrome (FXS) compared to nonverbal mental-age (NVMA) matched, typically developing (TD) boys. Concomitantly, the relationship between cortisol—a physiological marker for stress—and verbal working memory performance over time is examined to understand the role of physiological mechanisms in cognitive development in FXS. Participants were assessed between one and three times over a 2-year time frame using two verbal working memory tests that differ in complexity: memory for words and auditory working memory with salivary cortisol collected at the beginning and end of each assessment. Multilevel modeling results indicate specific deficits over time on the memory for words task in boys with FXS compared to TD controls that is exacerbated by elevated baseline cortisol. Similar increasing rates of growth over time were observed for boys with FXS and TD controls on the more complex auditory working memory task, but only boys with FXS displayed an association of increased baseline cortisol and lower performance. This study highlights the benefit of investigations of how dynamic biological and cognitive factors interact and influence cognitive development over time. PMID:26760450

EBLAST: an efficient high-compression image transformation 3. application to Internet image and video transmission

NASA Astrophysics Data System (ADS)

Schmalz, Mark S.; Ritter, Gerhard X.; Caimi, Frank M.

2001-12-01

A wide variety of digital image compression transforms developed for still imaging and broadcast video transmission are unsuitable for Internet video applications due to insufficient compression ratio, poor reconstruction fidelity, or excessive computational requirements. Examples include hierarchical transforms that require all, or large portion of, a source image to reside in memory at one time, transforms that induce significant locking effect at operationally salient compression ratios, and algorithms that require large amounts of floating-point computation. The latter constraint holds especially for video compression by small mobile imaging devices for transmission to, and compression on, platforms such as palmtop computers or personal digital assistants (PDAs). As Internet video requirements for frame rate and resolution increase to produce more detailed, less discontinuous motion sequences, a new class of compression transforms will be needed, especially for small memory models and displays such as those found on PDAs. In this, the third series of papers, we discuss the EBLAST compression transform and its application to Internet communication. Leading transforms for compression of Internet video and still imagery are reviewed and analyzed, including GIF, JPEG, AWIC (wavelet-based), wavelet packets, and SPIHT, whose performance is compared with EBLAST. Performance analysis criteria include time and space complexity and quality of the decompressed image. The latter is determined by rate-distortion data obtained from a database of realistic test images. Discussion also includes issues such as robustness of the compressed format to channel noise. EBLAST has been shown to perform superiorly to JPEG and, unlike current wavelet compression transforms, supports fast implementation on embedded processors with small memory models.

A generalized memory test algorithm

NASA Technical Reports Server (NTRS)

Milner, E. J.

1982-01-01

A general algorithm for testing digital computer memory is presented. The test checks that (1) every bit can be cleared and set in each memory work, and (2) bits are not erroneously cleared and/or set elsewhere in memory at the same time. The algorithm can be applied to any size memory block and any size memory word. It is concise and efficient, requiring the very few cycles through memory. For example, a test of 16-bit-word-size memory requries only 384 cycles through memory. Approximately 15 seconds were required to test a 32K block of such memory, using a microcomputer having a cycle time of 133 nanoseconds.

Nonverbal working memory of humans and monkeys: rehearsal in the sketchpad?

NASA Technical Reports Server (NTRS)

Washburn, D. A.; Astur, R. S.; Rumbaugh, D. M. (Principal Investigator)

1998-01-01

Investigations of working memory tend to focus on the retention of verbal information. The present experiments were designed to characterize the active maintenance rehearsal process used in the retention of visuospatial information. Rhesus monkeys (Macaca mulatta; N = 6) were tested as well as humans (total N = 90) because these nonhuman primates have excellent visual working memory but, unlike humans, cannot verbally recode the stimuli to employ verbal rehearsal mechanisms. A series of experiments was conducted using a distractor-task paradigm, a directed forgetting procedure, and a dual-task paradigm. No evidence was found for an active maintenance process for either species. Rather, it appears that information is maintained in the visuospatial sketchpad without active rehearsal.

Potential High-Temperature Shape-Memory Alloys Identified in the Ti(Ni,Pt) System

NASA Technical Reports Server (NTRS)

Noebe, Ronald D.; Biles, Tiffany A.; Garg, Anita; Nathal, Michael V.

2004-01-01

"Shape memory" is a unique property of certain alloys that, when deformed (within certain strain limits) at low temperatures, will remember and recover to their original predeformed shape upon heating. It occurs when an alloy is deformed in the low-temperature martensitic phase and is then heated above its transformation temperature back to an austenitic state. As the material passes through this solid-state phase transformation on heating, it also recovers its original shape. This behavior is widely exploited, near room temperature, in commercially available NiTi alloys for connectors, couplings, valves, actuators, stents, and other medical and dental devices. In addition, there are limitless applications in the aerospace, automotive, chemical processing, and many other industries for materials that exhibit this type of shape-memory behavior at higher temperatures. But for high temperatures, there are currently no commercial shape-memory alloys. Although there are significant challenges to the development of high-temperature shape-memory alloys, at the NASA Glenn Research Center we have identified a series of alloy compositions in the Ti-Ni-Pt system that show great promise as potential high-temperature shape-memory materials.

Dissociations in cognitive memory: the syndrome of developmental amnesia.

PubMed

Vargha-Khadem, F; Gadian, D G; Mishkin, M

2001-09-29

The dearth of studies on amnesia in children has led to the assumption that when damage to the medial temporal lobe system occurs early in life, the compensatory capacity of the immature brain rescues memory functions. An alternative view is that such damage so interferes with the development of learning and memory that it results not in selective cognitive impairments but in general mental retardation. Data will be presented to counter both of these arguments. Results obtained from a series of 11 amnesic patients with a history of hypoxic ischaemic damage sustained perinatally or during childhood indicate that regardless of age at onset of hippocampal pathology, there is a pronounced dissociation between episodic memory, which is severely impaired, and semantic memory, which is relatively preserved. A second dissociation is characterized by markedly impaired recall and relatively spared recognition leading to a distinction between recollection-based versus familiarity-based judgements. These findings are discussed in terms of the locus and extent of neuropathology associated with hypoxic ischaemic damage, the neural basis of 'remembering' versus 'knowing', and a hierarchical model of cognitive memory.

Video Game Training Enhances Visuospatial Working Memory and Episodic Memory in Older Adults

PubMed Central

Toril, Pilar; Reales, José M.; Mayas, Julia; Ballesteros, Soledad

2016-01-01

In this longitudinal intervention study with experimental and control groups, we investigated the effects of video game training on the visuospatial working memory (WM) and episodic memory of healthy older adults. Participants were 19 volunteer older adults, who received 15 1-h video game training sessions with a series of video games selected from a commercial package (Lumosity), and a control group of 20 healthy older adults. The results showed that the performance of the trainees improved significantly in all the practiced video games. Most importantly, we found significant enhancements after training in the trained group and no change in the control group in two computerized tasks designed to assess visuospatial WM, namely the Corsi blocks task and the Jigsaw puzzle task. The episodic memory and short-term memory of the trainees also improved. Gains in some WM and episodic memory tasks were maintained during a 3-month follow-up period. These results suggest that the aging brain still retains some degree of plasticity, and that video game training might be an effective intervention tool to improve WM and other cognitive functions in older adults. PMID:27199723

Remembering President Barack Obama's inauguration and the landing of US Airways Flight 1549: a comparison of the predictors of autobiographical and event memory.

PubMed

Koppel, Jonathan; Brown, Adam D; Stone, Charles B; Coman, Alin; Hirst, William

2013-01-01

We examined and compared the predictors of autobiographical memory (AM) consistency and event memory accuracy across two publicly documented yet disparate public events: the inauguration of Barack Obama as the 44th president of the United States on January 20th 2009, and the emergency landing of US Airways Flight 1549, off the coast of Manhattan, on January 15th 2009. We tracked autobiographical and event memories for both events, with assessments taking place within 2½ weeks of both events (Survey 1), and again between 3½ and 4 months after both events (Survey 2). In a series of stepwise regressions we found that the psychological variables of recalled emotional intensity and personal importance/centrality predicted AM consistency and event memory accuracy for the inauguration. Conversely, the rehearsal variables of covert rehearsal and media attention predicted, respectively, AM consistency and event memory accuracy for the plane landing. We conclude from these findings that different factors may underlie autobiographical and event memory for personally and culturally significant events (e.g., the inauguration), relative to noteworthy, yet less culturally significant, events (e.g., the plane landing).

MRI-leukoaraiosis thresholds and the phenotypic expression of dementia

PubMed Central

Mitchell, Sandra M.; Brumback, Babette; Tanner, Jared J.; Schmalfuss, Ilona; Lamar, Melissa; Giovannetti, Tania; Heilman, Kenneth M.; Libon, David J.

2012-01-01

Objective: To examine the concept of leukoaraiosis thresholds on working memory, visuoconstruction, memory, and language in dementia. Methods: A consecutive series of 83 individuals with insidious onset/progressive dementia clinically diagnosed with Alzheimer disease (AD) or small vessel vascular dementia (VaD) completed neuropsychological measures assessing working memory, visuoconstruction, episodic memory, and language. A clinical MRI scan was used to quantify leukoaraiosis, total white matter, hippocampus, lacune, and intracranial volume. We performed analyses to detect the lowest level of leukoaraiosis associated with impairment on the neuropsychological measures. Results: Leukoaraiosis ranged from 0.63% to 23.74% of participants' white matter. Leukoaraiosis explained a significant amount of variance in working memory performance when it involved 3% or more of the white matter with curve estimations showing the relationship to be nonlinear in nature. Greater leukoaraiosis (13%) was implicated for impairment in visuoconstruction. Relationships between leukoaraiosis, episodic memory, and language measures were linear or flat. Conclusions: Leukoaraiosis involves specific threshold points for working memory and visuoconstructional tests in AD/VaD spectrum dementia. These data underscore the need to better understand the threshold at which leukoaraiosis affects and alters the phenotypic expression in insidious onset dementia syndromes. PMID:22843264

Tunable Solid-State Quantum Memory Using Rare-Earth-Ion-Doped Crystal, Nd(3+):GaN

DTIC Science & Technology

2017-04-01

by plasma-assisted molecular beam epitaxy in a modular Gen II reactor using liquid gallium, solid Nd, and a nitrogen plasma. The photoluminescence (PL...provide a tunable memory. To vary the applied field, we designed and grew a series of Nd-doped GaN p-i-n structures, strain- balanced superlattice...27 Fig. 23 Electric field vs. GaN well/ AlxGa(1-x)N barrier thickness for strain- balanced superlattice (SBSL) structures with

The mitigating effect of repeated memory reactivations on forgetting

NASA Astrophysics Data System (ADS)

MacLeod, Sydney; Reynolds, Michael G.; Lehmann, Hugo

2018-12-01

Memory reactivation is a process whereby cueing or recalling a long-term memory makes it enter a new active and labile state. Substantial evidence suggests that during this state the memory can be updated (e.g., adding information) and can become more vulnerable to disruption (e.g., brain insult). Memory reactivations can also prevent memory decay or forgetting. However, it is unclear whether cueing recall of a feature or component of the memory can benefit retention similarly to promoting recall of the entire memory. We examined this possibility by having participants view a series of neutral images and then randomly assigning them to one of four reactivation groups: control (no reactivation), distractor (reactivation of experimental procedures), component (image category reactivation), and descriptive (effortful description of the images). The experiment also included three retention intervals: 1 h, 9 days, and 28 days. Importantly, the participants received three reactivations equally spaced within their respective retention interval. At the end of the interval, all the participants were given an in-lab free-recall test in which they were asked to write down each image they remembered with as many details as possible. The data revealed that both the participants in the descriptive reactivation and component reactivation groups remembered significantly more than the participants in the control groups, with the effect being most pronounced in the 28-day retention interval condition. These findings suggest that memory reactivation, even component reactivation of a memory, makes memories more resistant to decay.

Real Time Large Memory Optical Pattern Recognition.

DTIC Science & Technology

1984-06-01

AD-Ri58 023 REAL TIME LARGE MEMORY OPTICAL PATTERN RECOGNITION(U) - h ARMY MISSILE COMMAND REDSTONE ARSENAL AL RESEARCH DIRECTORATE D A GREGORY JUN...TECHNICAL REPORT RR-84-9 Ln REAL TIME LARGE MEMORY OPTICAL PATTERN RECOGNITION Don A. Gregory Research Directorate US Army Missile Laboratory JUNE 1984 L...RR-84-9 , ___/_ _ __ _ __ _ __ _ __"__ _ 4. TITLE (and Subtitle) S. TYPE OF REPORT & PERIOD COVERED Real Time Large Memory Optical Pattern Technical

Dispersion entropy for the analysis of resting-state MEG regularity in Alzheimer's disease.

PubMed

Azami, Hamed; Rostaghi, Mostafa; Fernandez, Alberto; Escudero, Javier

2016-08-01

Alzheimer's disease (AD) is a progressive degenerative brain disorder affecting memory, thinking, behaviour and emotion. It is the most common form of dementia and a big social problem in western societies. The analysis of brain activity may help to diagnose this disease. Changes in entropy methods have been reported useful in research studies to characterize AD. We have recently proposed dispersion entropy (DisEn) as a very fast and powerful tool to quantify the irregularity of time series. The aim of this paper is to evaluate the ability of DisEn, in comparison with fuzzy entropy (FuzEn), sample entropy (SampEn), and permutation entropy (PerEn), to discriminate 36 AD patients from 26 elderly control subjects using resting-state magnetoencephalogram (MEG) signals. The results obtained by DisEn, FuzEn, and SampEn, unlike PerEn, show that the AD patients' signals are more regular than controls' time series. The p-values obtained by DisEn, FuzEn, SampEn, and PerEn based methods demonstrate the superiority of DisEn over PerEn, SampEn, and PerEn. Moreover, the computation time for the newly proposed DisEn-based method is noticeably less than for the FuzEn, SampEn, and PerEn based approaches.

Episodic Autobiographical Memories over the Course of Time: Cognitive, Neuropsychological and Neuroimaging Findings

ERIC Educational Resources Information Center

Piolino, Pascale; Desgranges, Beatrice; Eustache, Francis

2009-01-01

The critical attributes of episodic memory are self, autonoetic consciousness and subjectively sensed time. The aim of this paper is to present a theoretical overview of our already published researches into the nature of episodic memory over the course of time. We have developed a new method of assessing "autobiographical" memory (TEMPau task),…

Recovering and preventing loss of detailed memory: differential rates of forgetting for detail types in episodic memory

PubMed Central

Bonasia, Kyra; St-Laurent, Marie; Pishdadian, Sara; Winocur, Gordon; Grady, Cheryl; Moscovitch, Morris

2016-01-01

Episodic memories undergo qualitative changes with time, but little is known about how different aspects of memory are affected. Different types of information in a memory, such as perceptual detail, and central themes, may be lost at different rates. In patients with medial temporal lobe damage, memory for perceptual details is severely impaired, while memory for central details is relatively spared. Given the sensitivity of memory to loss of details, the present study sought to investigate factors that mediate the forgetting of different types of information from naturalistic episodic memories in young healthy adults. The study investigated (1) time-dependent loss of “central” and “peripheral” details from episodic memories, (2) the effectiveness of cuing with reminders to reinstate memory details, and (3) the role of retrieval in preventing forgetting. Over the course of 7 d, memory for naturalistic events (film clips) underwent a time-dependent loss of peripheral details, while memory for central details (the core or gist of events) showed significantly less loss. Giving brief reminders of the clips just before retrieval reinstated memory for peripheral details, suggesting that loss of details is not always permanent, and may reflect both a storage and retrieval deficit. Furthermore, retrieving a memory shortly after it was encoded prevented loss of both central and peripheral details, thereby promoting retention over time. We consider the implications of these results for behavioral and neurobiological models of retention and forgetting. PMID:26773100