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

Mittal, Sparsh; Zhang, Zhao

With each CMOS technology generation, leakage energy consumption has been dramatically increasing and hence, managing leakage power consumption of large last-level caches (LLCs) has become a critical issue in modern processor design. In this paper, we present EnCache, a novel software-based technique which uses dynamic profiling-based cache reconfiguration for saving cache leakage energy. EnCache uses a simple hardware component called profiling cache, which dynamically predicts energy efficiency of an application for 32 possible cache configurations. Using these estimates, system software reconfigures the cache to the most energy efficient configuration. EnCache uses dynamic cache reconfiguration and hence, it does not requiremore » offline profiling or tuning the parameter for each application. Furthermore, EnCache optimizes directly for the overall memory subsystem (LLC and main memory) energy efficiency instead of the LLC energy efficiency alone. The experiments performed with an x86-64 simulator and workloads from SPEC2006 suite confirm that EnCache provides larger energy saving than a conventional energy saving scheme. For single core and dual-core system configurations, the average savings in memory subsystem energy over a shared baseline configuration are 30.0% and 27.3%, respectively.« less

Template Based Low Data Rate Speech Encoder

DTIC Science & Technology

1993-09-30

Nasality Distinguishes In/ from d/ 95.6 96.9 1m/ from /b/, etc. Sustention Distinguishes /f/ from /p/, $7.5 88.3 ibi from N/, Al from /0 8. etc. Sibilation...processor performs mainly Processor Workstation input/output (I/O) operations. The dynamic random access memory (DRAM) has 16 million bytes of...storage capacity. To execute the 800-b/s voice algorithm, the following amount of memory is needed: 5 MB for tables, 1.5 MB for it "program, and 30 KB for

Concept of dynamic memory in economics

NASA Astrophysics Data System (ADS)

Tarasova, Valentina V.; Tarasov, Vasily E.

2018-02-01

In this paper we discuss a concept of dynamic memory and an application of fractional calculus to describe the dynamic memory. The concept of memory is considered from the standpoint of economic models in the framework of continuous time approach based on fractional calculus. We also describe some general restrictions that can be imposed on the structure and properties of dynamic memory. These restrictions include the following three principles: (a) the principle of fading memory; (b) the principle of memory homogeneity on time (the principle of non-aging memory); (c) the principle of memory reversibility (the principle of memory recovery). Examples of different memory functions are suggested by using the fractional calculus. To illustrate an application of the concept of dynamic memory in economics we consider a generalization of the Harrod-Domar model, where the power-law memory is taken into account.

Distributed cable sensors with memory feature for post-disaster damage assessment

NASA Astrophysics Data System (ADS)

Chen, Genda; McDaniel, Ryan D.; Pommerenke, David J.; Sun, Shishuang

2005-05-01

A new design of distributed crack sensors is presented for the condition assessment of reinforced concrete (RC) structures during and immediately after an earthquake event. This study is mainly focused on the performance of cable sensors under dynamic loading, particularly their ability to memorize the crack history of an RC member. This unique memory feature enables the post-earthquake condition assessment of structural members such as RC columns, in which the earthquake-induced cracks are closed immediately after an earthquake event due to gravity loads and they are visually undetectable. Factors affecting the onset of the memory feature were investigated experimentally with small-scale RC beams under cyclic loading. Test results indicated that both crack width and the number of loading cycles were instrumental in the onset of the memory feature of cable sensors. Practical issues related to dynamic acquisition with the sensors were discussed. The sensors were proven to be fatigue resistant from the shake table tests of RC columns. They continued to show useful signal after the columns can no longer support additional loads.

Enabling the High Level Synthesis of Data Analytics Accelerators

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

Minutoli, Marco; Castellana, Vito G.; Tumeo, Antonino

Conventional High Level Synthesis (HLS) tools mainly tar- get compute intensive kernels typical of digital signal pro- cessing applications. We are developing techniques and ar- chitectural templates to enable HLS of data analytics appli- cations. These applications are memory intensive, present fine-grained, unpredictable data accesses, and irregular, dy- namic task parallelism. We discuss an architectural tem- plate based around a distributed controller to efficiently ex- ploit thread level parallelism. We present a memory in- terface that supports parallel memory subsystems and en- ables implementing atomic memory operations. We intro- duce a dynamic task scheduling approach to efficiently ex- ecute heavilymore » unbalanced workload. The templates are val- idated by synthesizing queries from the Lehigh University Benchmark (LUBM), a well know SPARQL benchmark.« less

Sparse distributed memory: Principles and operation

NASA Technical Reports Server (NTRS)

Flynn, M. J.; Kanerva, P.; Bhadkamkar, N.

1989-01-01

Sparse distributed memory is a generalized random access memory (RAM) for long (1000 bit) binary words. Such words can be written into and read from the memory, and they can also be used to address the memory. The main attribute of the memory is sensitivity to similarity, meaning that a word can be read back not only by giving the original write address but also by giving one close to it as measured by the Hamming distance between addresses. Large memories of this kind are expected to have wide use in speech recognition and scene analysis, in signal detection and verification, and in adaptive control of automated equipment, in general, in dealing with real world information in real time. The memory can be realized as a simple, massively parallel computer. Digital technology has reached a point where building large memories is becoming practical. Major design issues were resolved which were faced in building the memories. The design is described of a prototype memory with 256 bit addresses and from 8 to 128 K locations for 256 bit words. A key aspect of the design is extensive use of dynamic RAM and other standard components.

Design and Implementation of High-Performance GIS Dynamic Objects Rendering Engine

NASA Astrophysics Data System (ADS)

Zhong, Y.; Wang, S.; Li, R.; Yun, W.; Song, G.

2017-12-01

Spatio-temporal dynamic visualization is more vivid than static visualization. It important to use dynamic visualization techniques to reveal the variation process and trend vividly and comprehensively for the geographical phenomenon. To deal with challenges caused by dynamic visualization of both 2D and 3D spatial dynamic targets, especially for different spatial data types require high-performance GIS dynamic objects rendering engine. The main approach for improving the rendering engine with vast dynamic targets relies on key technologies of high-performance GIS, including memory computing, parallel computing, GPU computing and high-performance algorisms. In this study, high-performance GIS dynamic objects rendering engine is designed and implemented for solving the problem based on hybrid accelerative techniques. The high-performance GIS rendering engine contains GPU computing, OpenGL technology, and high-performance algorism with the advantage of 64-bit memory computing. It processes 2D, 3D dynamic target data efficiently and runs smoothly with vast dynamic target data. The prototype system of high-performance GIS dynamic objects rendering engine is developed based SuperMap GIS iObjects. The experiments are designed for large-scale spatial data visualization, the results showed that the high-performance GIS dynamic objects rendering engine have the advantage of high performance. Rendering two-dimensional and three-dimensional dynamic objects achieve 20 times faster on GPU than on CPU.

76 FR 73676 - Certain Dynamic Random Access Memory Devices, and Products Containing Same; Receipt of Complaint...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-29

... INTERNATIONAL TRADE COMMISSION [DN 2859] Certain Dynamic Random Access Memory Devices, and.... International Trade Commission has received a complaint entitled In Re Certain Dynamic Random Access Memory... certain dynamic random access memory devices, and products containing same. The complaint names Elpida...

75 FR 16507 - In the Matter of Certain Semiconductor Chips Having Synchronous Dynamic Random Access Memory...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-01

... Semiconductor Chips Having Synchronous Dynamic Random Access Memory Controllers and Products Containing Same... synchronous dynamic random access memory controllers and products containing same by reason of infringement of... semiconductor chips having synchronous dynamic random access memory controllers and products containing same...

H∞ memory feedback control with input limitation minimization for offshore jacket platform stabilization

NASA Astrophysics Data System (ADS)

Yang, Jia Sheng

2018-06-01

In this paper, we investigate a H∞ memory controller with input limitation minimization (HMCIM) for offshore jacket platforms stabilization. The main objective of this study is to reduce the control consumption as well as protect the actuator when satisfying the requirement of the system performance. First, we introduce a dynamic model of offshore platform with low order main modes based on mode reduction method in numerical analysis. Then, based on H∞ control theory and matrix inequality techniques, we develop a novel H∞ memory controller with input limitation. Furthermore, a non-convex optimization model to minimize input energy consumption is proposed. Since it is difficult to solve this non-convex optimization model by optimization algorithm, we use a relaxation method with matrix operations to transform this non-convex optimization model to be a convex optimization model. Thus, it could be solved by a standard convex optimization solver in MATLAB or CPLEX. Finally, several numerical examples are given to validate the proposed models and methods.

76 FR 80964 - Certain Dynamic Random Access Memory Devices, and Products Containing Same; Institution of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-27

... INTERNATIONAL TRADE COMMISSION [Investigation No. 337-TA-821] Certain Dynamic Random Access Memory... importation, and the sale within the United States after importation of certain dynamic random access memory... certain dynamic random access memory devices, and products containing same that infringe one or more of...

Remembering the dynamic changes in pain intensity and unpleasantness: a psychophysical study.

PubMed

Khoshnejad, Mina; Fortin, Marie C; Rohani, Farzan; Duncan, Gary H; Rainville, Pierre

2014-03-01

This study investigated the short-term memory of dynamic changes in acute pain using psychophysical methods. Pain intensity or unpleasantness induced by painful contact-heat stimuli of 8, 9, or 10s was rated continuously during the stimulus or after a 14-s delay using an electronic visual analog scale in 10 healthy volunteers. Because the continuous visual analog scale time courses contained large amounts of redundant information, a principal component analysis was applied to characterize the main features inherent to both the concurrent rating and retrospective evaluations. Three components explained about 90% of the total variance across all trials and subjects, with the first component reflecting the global perceptual profile, and the second and third components explaining finer perceptual aspects (eg, changes in slope at onset and offset and shifts in peak latency). We postulate that these 3 principal components may provide some information about the structure of the mental representations of what one perceives, stores, and remembers during the course of few seconds. Analysis performed on the components confirmed significant memory distortions and revealed that the discriminative information about pain dimensions in concurrent ratings was partly or completely lost in retrospective ratings. Importantly, our results highlight individual differences affecting these memory processes. These results provide further evidence of the important transformations underlying the processing of pain in explicit memory and raise fundamental questions about the conversion of dynamic nociceptive signals into a mental representation of pain in perception and memory. Copyright © 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Short-Term Plasticity and Long-Term Potentiation in Magnetic Tunnel Junctions: Towards Volatile Synapses

NASA Astrophysics Data System (ADS)

Sengupta, Abhronil; Roy, Kaushik

2016-02-01

Synaptic memory is considered to be the main element responsible for learning and cognition in humans. Although traditionally nonvolatile long-term plasticity changes are implemented in nanoelectronic synapses for neuromorphic applications, recent studies in neuroscience reveal that biological synapses undergo metastable volatile strengthening followed by a long-term strengthening provided that the frequency of the input stimulus is sufficiently high. Such "memory strengthening" and "memory decay" functionalities can potentially lead to adaptive neuromorphic architectures. In this paper, we demonstrate the close resemblance of the magnetization dynamics of a magnetic tunnel junction (MTJ) to short-term plasticity and long-term potentiation observed in biological synapses. We illustrate that, in addition to the magnitude and duration of the input stimulus, the frequency of the stimulus plays a critical role in determining long-term potentiation of the MTJ. Such MTJ synaptic memory arrays can be utilized to create compact, ultrafast, and low-power intelligent neural systems.

Network-wide reorganization of procedural memory during NREM sleep revealed by fMRI

PubMed Central

Vahdat, Shahabeddin; Fogel, Stuart; Benali, Habib; Doyon, Julien

2017-01-01

Sleep is necessary for the optimal consolidation of newly acquired procedural memories. However, the mechanisms by which motor memory traces develop during sleep remain controversial in humans, as this process has been mainly investigated indirectly by comparing pre- and post-sleep conditions. Here, we used functional magnetic resonance imaging and electroencephalography during sleep following motor sequence learning to investigate how newly-formed memory traces evolve dynamically over time. We provide direct evidence for transient reactivation followed by downscaling of functional connectivity in a cortically-dominant pattern formed during learning, as well as gradual reorganization of this representation toward a subcortically-dominant consolidated trace during non-rapid eye movement (NREM) sleep. Importantly, the putamen functional connectivity within the consolidated network during NREM sleep was related to overnight behavioral gains. Our results demonstrate that NREM sleep is necessary for two complementary processes: the restoration and reorganization of newly-learned information during sleep, which underlie human motor memory consolidation. DOI: http://dx.doi.org/10.7554/eLife.24987.001 PMID:28892464

Dynamic intersectoral models with power-law memory

NASA Astrophysics Data System (ADS)

Tarasova, Valentina V.; Tarasov, Vasily E.

2018-01-01

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

Exciton versus free carrier photogeneration in organometal trihalide perovskites probed by broadband ultrafast polarization memory dynamics.

PubMed

Sheng, ChuanXiang; Zhang, Chuang; Zhai, Yaxin; Mielczarek, Kamil; Wang, Weiwei; Ma, Wanli; Zakhidov, Anvar; Vardeny, Z Valy

2015-03-20

We studied the ultrafast transient response of photoexcitations in two hybrid organic-inorganic perovskite films used for high efficiency photovoltaic cells, namely, CH(3)NH(3)PbI(3) and CH(3)NH(3)PbI(1.1)Br(1.9) using polarized broadband pump-probe spectroscopy in the spectral range of 0.3-2.7 eV with 300 fs time resolution. For CH(3)NH(3)PbI(3) with above-gap excitation we found both photogenerated carriers and excitons, but only carriers are photogenerated with below-gap excitation. In contrast, mainly excitons are photogenerated in CH(3)NH(3)PbI(1.1)Br(1.9). Surprisingly, we also discovered in CH(3)NH(3)PbI(3), but not in CH(3)NH(3)PbI(1.1)Br(1.9), transient photoinduced polarization memory for both excitons and photocarriers, which is also reflected in the steady state photoluminescence. From the polarization memory dynamics we obtained the excitons diffusion constant in CH(3)NH(3)PbI(3), D≈0.01  cm(2) s(-1).

Exciton versus Free Carrier Photogeneration in Organometal Trihalide Perovskites Probed by Broadband Ultrafast Polarization Memory Dynamics

NASA Astrophysics Data System (ADS)

Sheng, ChuanXiang; Zhang, Chuang; Zhai, Yaxin; Mielczarek, Kamil; Wang, Weiwei; Ma, Wanli; Zakhidov, Anvar; Vardeny, Z. Valy

2015-03-01

We studied the ultrafast transient response of photoexcitations in two hybrid organic-inorganic perovskite films used for high efficiency photovoltaic cells, namely, CH3NH3PbI3 and CH3NH3PbI1.1Br1.9 using polarized broadband pump-probe spectroscopy in the spectral range of 0.3-2.7 eV with 300 fs time resolution. For CH3NH3PbI3 with above-gap excitation we found both photogenerated carriers and excitons, but only carriers are photogenerated with below-gap excitation. In contrast, mainly excitons are photogenerated in CH3NH3PbI1.1Br1.9 . Surprisingly, we also discovered in CH3NH3PbI3 , but not in CH3NH3PbI1.1Br1.9 , transient photoinduced polarization memory for both excitons and photocarriers, which is also reflected in the steady state photoluminescence. From the polarization memory dynamics we obtained the excitons diffusion constant in CH3NH3PbI3 , D ≈0.01 cm2 s-1 .

Dynamic relation between working memory capacity and speech recognition in noise during the first 6 months of hearing aid use.

PubMed

Ng, Elaine H N; Classon, Elisabet; Larsby, Birgitta; Arlinger, Stig; Lunner, Thomas; Rudner, Mary; Rönnberg, Jerker

2014-11-23

The present study aimed to investigate the changing relationship between aided speech recognition and cognitive function during the first 6 months of hearing aid use. Twenty-seven first-time hearing aid users with symmetrical mild to moderate sensorineural hearing loss were recruited. Aided speech recognition thresholds in noise were obtained in the hearing aid fitting session as well as at 3 and 6 months postfitting. Cognitive abilities were assessed using a reading span test, which is a measure of working memory capacity, and a cognitive test battery. Results showed a significant correlation between reading span and speech reception threshold during the hearing aid fitting session. This relation was significantly weakened over the first 6 months of hearing aid use. Multiple regression analysis showed that reading span was the main predictor of speech recognition thresholds in noise when hearing aids were first fitted, but that the pure-tone average hearing threshold was the main predictor 6 months later. One way of explaining the results is that working memory capacity plays a more important role in speech recognition in noise initially rather than after 6 months of use. We propose that new hearing aid users engage working memory capacity to recognize unfamiliar processed speech signals because the phonological form of these signals cannot be automatically matched to phonological representations in long-term memory. As familiarization proceeds, the mismatch effect is alleviated, and the engagement of working memory capacity is reduced. © The Author(s) 2014.

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.

Memory effects in nanoparticle dynamics and transport

NASA Astrophysics Data System (ADS)

Sanghi, Tarun; Bhadauria, Ravi; Aluru, N. R.

2016-10-01

In this work, we use the generalized Langevin equation (GLE) to characterize and understand memory effects in nanoparticle dynamics and transport. Using the GLE formulation, we compute the memory function and investigate its scaling with the mass, shape, and size of the nanoparticle. It is observed that changing the mass of the nanoparticle leads to a rescaling of the memory function with the reduced mass of the system. Further, we show that for different mass nanoparticles it is the initial value of the memory function and not its relaxation time that determines the "memory" or "memoryless" dynamics. The size and the shape of the nanoparticle are found to influence both the functional-form and the initial value of the memory function. For a fixed mass nanoparticle, increasing its size enhances the memory effects. Using GLE simulations we also investigate and highlight the role of memory in nanoparticle dynamics and transport.

Temporal Expectations Guide Dynamic Prioritization in Visual Working Memory through Attenuated α Oscillations.

PubMed

van Ede, Freek; Niklaus, Marcel; Nobre, Anna C

2017-01-11

Although working memory is generally considered a highly dynamic mnemonic store, popular laboratory tasks used to understand its psychological and neural mechanisms (such as change detection and continuous reproduction) often remain relatively "static," involving the retention of a set number of items throughout a shared delay interval. In the current study, we investigated visual working memory in a more dynamic setting, and assessed the following: (1) whether internally guided temporal expectations can dynamically and reversibly prioritize individual mnemonic items at specific times at which they are deemed most relevant; and (2) the neural substrates that support such dynamic prioritization. Participants encoded two differently colored oriented bars into visual working memory to retrieve the orientation of one bar with a precision judgment when subsequently probed. To test for the flexible temporal control to access and retrieve remembered items, we manipulated the probability for each of the two bars to be probed over time, and recorded EEG in healthy human volunteers. Temporal expectations had a profound influence on working memory performance, leading to faster access times as well as more accurate orientation reproductions for items that were probed at expected times. Furthermore, this dynamic prioritization was associated with the temporally specific attenuation of contralateral α (8-14 Hz) oscillations that, moreover, predicted working memory access times on a trial-by-trial basis. We conclude that attentional prioritization in working memory can be dynamically steered by internally guided temporal expectations, and is supported by the attenuation of α oscillations in task-relevant sensory brain areas. In dynamic, everyday-like, environments, flexible goal-directed behavior requires that mental representations that are kept in an active (working memory) store are dynamic, too. We investigated working memory in a more dynamic setting than is conventional, and demonstrate that expectations about when mnemonic items are most relevant can dynamically and reversibly prioritize these items in time. Moreover, we uncover a neural substrate of such dynamic prioritization in contralateral visual brain areas and show that this substrate predicts working memory retrieval times on a trial-by-trial basis. This places the experimental study of working memory, and its neuronal underpinnings, in a more dynamic and ecologically valid context, and provides new insights into the neural implementation of attentional prioritization within working memory. Copyright © 2017 van Ede et al.

[Physiopathology of autobiographical memory in aging: episodic and semantic distinction, clinical findings and neuroimaging studies].

PubMed

Piolino, Pascale; Martinelli, Pénélope; Viard, Armelle; Noulhiane, Marion; Eustache, Francis; Desgranges, Béatrice

2010-01-01

From an early age, autobiographical memory models our feeling of identity and continuity. It grows throughout lifetime with our experiences and is built up from general self-knowledge and specific memories. The study of autobiographical memory depicts the dynamic and reconstructive features of this type of long-term memory, combining both semantic and episodic aspects, its strength and fragility. In this article, we propose to illustrate the properties of autobiographical memory from the field of cognitive psychology, neuropsychology and neuroimaging research through the analysis of the mechanisms of disturbance in normal and Alzheimer's disease. We show that the cognitive and neural bases of autobiographical memory are distinct in both cases. In normal aging, autobiographical memory retrieval is mainly dependent on frontal/executive function and on sense of reexperiencing specific context connected to hippocampal regions regardless of memory remoteness. In Alzheimer's disease, autobiographical memory deficit, characterized by a Ribot's temporal gradient, is connected to different regions according to memory remoteness. Our functional neuroimaging results suggest that patients at the early stage can compensate for their massive deficit of episodic recent memories correlated to hippocampal alteration with over general remote memories related to prefrontal regions. On the whole, the research findings allowed initiating new autobiographical memory studies by comparing normal and pathological aging and developing cognitive methods of memory rehabilitation in patients based on preserved personal semantic capacity. © Société de Biologie, 2010.

Stable and Dynamic Coding for Working Memory in Primate Prefrontal Cortex

PubMed Central

Watanabe, Kei; Funahashi, Shintaro; Stokes, Mark G.

2017-01-01

Working memory (WM) provides the stability necessary for high-level cognition. Influential theories typically assume that WM depends on the persistence of stable neural representations, yet increasing evidence suggests that neural states are highly dynamic. Here we apply multivariate pattern analysis to explore the population dynamics in primate lateral prefrontal cortex (PFC) during three variants of the classic memory-guided saccade task (recorded in four animals). We observed the hallmark of dynamic population coding across key phases of a working memory task: sensory processing, memory encoding, and response execution. Throughout both these dynamic epochs and the memory delay period, however, the neural representational geometry remained stable. We identified two characteristics that jointly explain these dynamics: (1) time-varying changes in the subpopulation of neurons coding for task variables (i.e., dynamic subpopulations); and (2) time-varying selectivity within neurons (i.e., dynamic selectivity). These results indicate that even in a very simple memory-guided saccade task, PFC neurons display complex dynamics to support stable representations for WM. SIGNIFICANCE STATEMENT Flexible, intelligent behavior requires the maintenance and manipulation of incoming information over various time spans. For short time spans, this faculty is labeled “working memory” (WM). Dominant models propose that WM is maintained by stable, persistent patterns of neural activity in prefrontal cortex (PFC). However, recent evidence suggests that neural activity in PFC is dynamic, even while the contents of WM remain stably represented. Here, we explored the neural dynamics in PFC during a memory-guided saccade task. We found evidence for dynamic population coding in various task epochs, despite striking stability in the neural representational geometry of WM. Furthermore, we identified two distinct cellular mechanisms that contribute to dynamic population coding. PMID:28559375

Modeling Coevolution between Language and Memory Capacity during Language Origin

PubMed Central

Gong, Tao; Shuai, Lan

2015-01-01

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

Modeling Coevolution between Language and Memory Capacity during Language Origin.

PubMed

Gong, Tao; Shuai, Lan

2015-01-01

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

The Dynamics of Memory: Context-Dependent Updating

ERIC Educational Resources Information Center

Hupbach, Almut; Hardt, Oliver; Gomez, Rebecca; Nadel, Lynn

2008-01-01

Understanding the dynamics of memory change is one of the current challenges facing cognitive neuroscience. Recent animal work on memory reconsolidation shows that memories can be altered long after acquisition. When reactivated, memories can be modified and require a restabilization (reconsolidation) process. We recently extended this finding to…

76 FR 2336 - Dynamic Random Access Memory Semiconductors From the Republic of Korea: Final Results of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-13

... DEPARTMENT OF COMMERCE International Trade Administration [C-580-851] Dynamic Random Access Memory... administrative review of the countervailing duty order on dynamic random access memory semiconductors from the... following events have occurred since the publication of the preliminary results of this review. See Dynamic...

76 FR 55417 - In the Matter of Certain Dynamic Random Access Memory and Nand Flash Memory Devices and Products...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-07

... Access Memory and Nand Flash Memory Devices and Products Containing Same; Notice of Institution of... importation, and the sale within the United States after importation of certain dynamic random access memory and NAND flash memory devices and products containing same by reason of infringement of certain claims...

All-memristive neuromorphic computing with level-tuned neurons

NASA Astrophysics Data System (ADS)

Pantazi, Angeliki; Woźniak, Stanisław; Tuma, Tomas; Eleftheriou, Evangelos

2016-09-01

In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from many sources. Brain-inspired neuromorphic computing systems increasingly attract research interest as an alternative to the classical von Neumann processor architecture, mainly because of the coexistence of memory and processing units. In these systems, the basic components are neurons interconnected by synapses. The neurons, based on their nonlinear dynamics, generate spikes that provide the main communication mechanism. The computational tasks are distributed across the neural network, where synapses implement both the memory and the computational units, by means of learning mechanisms such as spike-timing-dependent plasticity. In this work, we present an all-memristive neuromorphic architecture comprising neurons and synapses realized by using the physical properties and state dynamics of phase-change memristors. The architecture employs a novel concept of interconnecting the neurons in the same layer, resulting in level-tuned neuronal characteristics that preferentially process input information. We demonstrate the proposed architecture in the tasks of unsupervised learning and detection of multiple temporal correlations in parallel input streams. The efficiency of the neuromorphic architecture along with the homogenous neuro-synaptic dynamics implemented with nanoscale phase-change memristors represent a significant step towards the development of ultrahigh-density neuromorphic co-processors.

All-memristive neuromorphic computing with level-tuned neurons.

PubMed

Pantazi, Angeliki; Woźniak, Stanisław; Tuma, Tomas; Eleftheriou, Evangelos

2016-09-02

In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from many sources. Brain-inspired neuromorphic computing systems increasingly attract research interest as an alternative to the classical von Neumann processor architecture, mainly because of the coexistence of memory and processing units. In these systems, the basic components are neurons interconnected by synapses. The neurons, based on their nonlinear dynamics, generate spikes that provide the main communication mechanism. The computational tasks are distributed across the neural network, where synapses implement both the memory and the computational units, by means of learning mechanisms such as spike-timing-dependent plasticity. In this work, we present an all-memristive neuromorphic architecture comprising neurons and synapses realized by using the physical properties and state dynamics of phase-change memristors. The architecture employs a novel concept of interconnecting the neurons in the same layer, resulting in level-tuned neuronal characteristics that preferentially process input information. We demonstrate the proposed architecture in the tasks of unsupervised learning and detection of multiple temporal correlations in parallel input streams. The efficiency of the neuromorphic architecture along with the homogenous neuro-synaptic dynamics implemented with nanoscale phase-change memristors represent a significant step towards the development of ultrahigh-density neuromorphic co-processors.

CMOS integration of high-k/metal gate transistors in diffusion and gate replacement (D&GR) scheme for dynamic random access memory peripheral circuits

NASA Astrophysics Data System (ADS)

Dentoni Litta, Eugenio; Ritzenthaler, Romain; Schram, Tom; Spessot, Alessio; O’Sullivan, Barry; Machkaoutsan, Vladimir; Fazan, Pierre; Ji, Yunhyuck; Mannaert, Geert; Lorant, Christophe; Sebaai, Farid; Thiam, Arame; Ercken, Monique; Demuynck, Steven; Horiguchi, Naoto

2018-04-01

Integration of high-k/metal gate stacks in peripheral transistors is a major candidate to ensure continued scaling of dynamic random access memory (DRAM) technology. In this paper, the CMOS integration of diffusion and gate replacement (D&GR) high-k/metal gate stacks is investigated, evaluating four different approaches for the critical patterning step of removing the N-type field effect transistor (NFET) effective work function (eWF) shifter stack from the P-type field effect transistor (PFET) area. The effect of plasma exposure during the patterning step is investigated in detail and found to have a strong impact on threshold voltage tunability. A CMOS integration scheme based on an experimental wet-compatible photoresist is developed and the fulfillment of the main device metrics [equivalent oxide thickness (EOT), eWF, gate leakage current density, on/off currents, short channel control] is demonstrated.

Memory-induced nonlinear dynamics of excitation in cardiac diseases.

PubMed

Landaw, Julian; Qu, Zhilin

2018-04-01

Excitable cells, such as cardiac myocytes, exhibit short-term memory, i.e., the state of the cell depends on its history of excitation. Memory can originate from slow recovery of membrane ion channels or from accumulation of intracellular ion concentrations, such as calcium ion or sodium ion concentration accumulation. Here we examine the effects of memory on excitation dynamics in cardiac myocytes under two diseased conditions, early repolarization and reduced repolarization reserve, each with memory from two different sources: slow recovery of a potassium ion channel and slow accumulation of the intracellular calcium ion concentration. We first carry out computer simulations of action potential models described by differential equations to demonstrate complex excitation dynamics, such as chaos. We then develop iterated map models that incorporate memory, which accurately capture the complex excitation dynamics and bifurcations of the action potential models. Finally, we carry out theoretical analyses of the iterated map models to reveal the underlying mechanisms of memory-induced nonlinear dynamics. Our study demonstrates that the memory effect can be unmasked or greatly exacerbated under certain diseased conditions, which promotes complex excitation dynamics, such as chaos. The iterated map models reveal that memory converts a monotonic iterated map function into a nonmonotonic one to promote the bifurcations leading to high periodicity and chaos.

Memory-induced nonlinear dynamics of excitation in cardiac diseases

NASA Astrophysics Data System (ADS)

Landaw, Julian; Qu, Zhilin

2018-04-01

Excitable cells, such as cardiac myocytes, exhibit short-term memory, i.e., the state of the cell depends on its history of excitation. Memory can originate from slow recovery of membrane ion channels or from accumulation of intracellular ion concentrations, such as calcium ion or sodium ion concentration accumulation. Here we examine the effects of memory on excitation dynamics in cardiac myocytes under two diseased conditions, early repolarization and reduced repolarization reserve, each with memory from two different sources: slow recovery of a potassium ion channel and slow accumulation of the intracellular calcium ion concentration. We first carry out computer simulations of action potential models described by differential equations to demonstrate complex excitation dynamics, such as chaos. We then develop iterated map models that incorporate memory, which accurately capture the complex excitation dynamics and bifurcations of the action potential models. Finally, we carry out theoretical analyses of the iterated map models to reveal the underlying mechanisms of memory-induced nonlinear dynamics. Our study demonstrates that the memory effect can be unmasked or greatly exacerbated under certain diseased conditions, which promotes complex excitation dynamics, such as chaos. The iterated map models reveal that memory converts a monotonic iterated map function into a nonmonotonic one to promote the bifurcations leading to high periodicity and chaos.

Dynamic data distributions in Vienna Fortran

NASA Technical Reports Server (NTRS)

Chapman, Barbara; Mehrotra, Piyush; Moritsch, Hans; Zima, Hans

1993-01-01

Vienna Fortran is a machine-independent language extension of Fortran, which is based upon the Single-Program-Multiple-Data (SPMD) paradigm and allows the user to write programs for distributed-memory systems using global addresses. The language features focus mainly on the issue of distributing data across virtual processor structures. Those features of Vienna Fortran that allow the data distributions of arrays to change dynamically, depending on runtime conditions are discussed. The relevant language features are discussed, their implementation is outlined, and how they may be used in applications is described.

75 FR 14467 - In the Matter of: Certain Dynamic Random Access Memory Semiconductors and Products Containing...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-25

... Access Memory Semiconductors and Products Containing Same, Including Memory Modules; Notice of... the sale within the United States after importation of certain dynamic random access memory semiconductors and products containing same, including memory modules, by reason of infringement of certain...

Sleep and memory in the making. Are current concepts sufficient in children?

PubMed

Peigneux, P

2014-01-01

Memory consolidation is an active process wired in brain plasticity. How plasticity mechanisms develop and are modulated after learning is at the core of current models of sleep-dependent memory consolidation. Nowadays, two main classes of sleep-related memory consolidation theories are proposed, namely system consolidation and synaptic homeostasis. However, novel models of consolidation emerge, that might better account for the highly dynamic and interactive processes of encoding and memory consolidation. Processing steps can take place at various temporal phases and be modulated by interactions with prior experiences and ongoing events. In this perspective, sleep might support (or not) memory consolidation processes under specific neurophysiological and environmental circumstances leading to enduring representations in long-term memory stores. We outline here a discussion about how current and emergent models account for the complexity and apparent inconsistency of empirical data. Additionally, models aimed at understanding neurophysiological and/or cognitive processes should not only provide a satisfactory explanation for the phenomena at stake, but also account for their ontogeny and the conditions that disrupt their organisation. Looking at the available literature, this developmental condition appears to remain unfulfilled when trying to understand the relationships between sleep, learning and memory consolidation processes, both in healthy children and in children with pathological conditions.

Neural Dynamics Associated with Semantic and Episodic Memory for Faces: Evidence from Multiple Frequency Bands

ERIC Educational Resources Information Center

Zion-Golumbic, Elana; Kutas, Marta; Bentin, Shlomo

2010-01-01

Prior semantic knowledge facilitates episodic recognition memory for faces. To examine the neural manifestation of the interplay between semantic and episodic memory, we investigated neuroelectric dynamics during the creation (study) and the retrieval (test) of episodic memories for famous and nonfamous faces. Episodic memory effects were evident…

The Science of Computing: Virtual Memory

NASA Technical Reports Server (NTRS)

Denning, Peter J.

1986-01-01

In the March-April issue, I described how a computer's storage system is organized as a hierarchy consisting of cache, main memory, and secondary memory (e.g., disk). The cache and main memory form a subsystem that functions like main memory but attains speeds approaching cache. What happens if a program and its data are too large for the main memory? This is not a frivolous question. Every generation of computer users has been frustrated by insufficient memory. A new line of computers may have sufficient storage for the computations of its predecessor, but new programs will soon exhaust its capacity. In 1960, a longrange planning committee at MIT dared to dream of a computer with 1 million words of main memory. In 1985, the Cray-2 was delivered with 256 million words. Computational physicists dream of computers with 1 billion words. Computer architects have done an outstanding job of enlarging main memories yet they have never kept up with demand. Only the shortsighted believe they can.

Endocannabinoid signaling and memory dynamics: A synaptic perspective.

PubMed

Drumond, Ana; Madeira, Natália; Fonseca, Rosalina

2017-02-01

Memory acquisition is a key brain feature in which our human nature relies on. Memories evolve over time. Initially after learning, memories are labile and sensitive to disruption by the interference of concurrent events. Later on, after consolidation, memories are resistant to disruption. However, reactivation of previously consolidated memories renders them again in an unstable state and therefore susceptible to perturbation. Additionally, and depending on the characteristics of the stimuli, a parallel process may be initiated which ultimately leads to the extinction of the previously acquired response. This dynamic aspect of memory maintenance opens the possibility for an updating of previously acquired memories but it also creates several conceptual challenges. What is the time window for memory updating? What determines whether reconsolidation or extinction is triggered? In this review, we tried to re-examine the relationship between consolidation, reconsolidation and extinction, aiming for a unifying view of memory dynamics. Since cellular models of memory share common principles, we present the evidence that similar rules apply to the maintenance of synaptic plasticity. Recently, a new function of the endocannabinoid (eCB) signaling system has been described for associative forms of synaptic plasticity in amygdala synapses. The eCB system has emerged as a key modulator of memory dynamics by adjusting the outcome to stimuli intensity. We propose a key function of eCB in discriminative forms of learning by restricting associative plasticity in amygdala synapses. Since many neuropsychiatric disorders are associated with a dysregulation in memory dynamics, understanding the rules underlying memory maintenance paves the path to better clinical interventions. Copyright © 2016 Elsevier Inc. All rights reserved.

How Does the Sparse Memory “Engram” Neurons Encode the Memory of a Spatial–Temporal Event?

PubMed Central

Guan, Ji-Song; Jiang, Jun; Xie, Hong; Liu, Kai-Yuan

2016-01-01

Episodic memory in human brain is not a fixed 2-D picture but a highly dynamic movie serial, integrating information at both the temporal and the spatial domains. Recent studies in neuroscience reveal that memory storage and recall are closely related to the activities in discrete memory engram (trace) neurons within the dentate gyrus region of hippocampus and the layer 2/3 of neocortex. More strikingly, optogenetic reactivation of those memory trace neurons is able to trigger the recall of naturally encoded memory. It is still unknown how the discrete memory traces encode and reactivate the memory. Considering a particular memory normally represents a natural event, which consists of information at both the temporal and spatial domains, it is unknown how the discrete trace neurons could reconstitute such enriched information in the brain. Furthermore, as the optogenetic-stimuli induced recall of memory did not depend on firing pattern of the memory traces, it is most likely that the spatial activation pattern, but not the temporal activation pattern of the discrete memory trace neurons encodes the memory in the brain. How does the neural circuit convert the activities in the spatial domain into the temporal domain to reconstitute memory of a natural event? By reviewing the literature, here we present how the memory engram (trace) neurons are selected and consolidated in the brain. Then, we will discuss the main challenges in the memory trace theory. In the end, we will provide a plausible model of memory trace cell network, underlying the conversion of neural activities between the spatial domain and the temporal domain. We will also discuss on how the activation of sparse memory trace neurons might trigger the replay of neural activities in specific temporal patterns. PMID:27601979

How Does the Sparse Memory "Engram" Neurons Encode the Memory of a Spatial-Temporal Event?

PubMed

Guan, Ji-Song; Jiang, Jun; Xie, Hong; Liu, Kai-Yuan

2016-01-01

Episodic memory in human brain is not a fixed 2-D picture but a highly dynamic movie serial, integrating information at both the temporal and the spatial domains. Recent studies in neuroscience reveal that memory storage and recall are closely related to the activities in discrete memory engram (trace) neurons within the dentate gyrus region of hippocampus and the layer 2/3 of neocortex. More strikingly, optogenetic reactivation of those memory trace neurons is able to trigger the recall of naturally encoded memory. It is still unknown how the discrete memory traces encode and reactivate the memory. Considering a particular memory normally represents a natural event, which consists of information at both the temporal and spatial domains, it is unknown how the discrete trace neurons could reconstitute such enriched information in the brain. Furthermore, as the optogenetic-stimuli induced recall of memory did not depend on firing pattern of the memory traces, it is most likely that the spatial activation pattern, but not the temporal activation pattern of the discrete memory trace neurons encodes the memory in the brain. How does the neural circuit convert the activities in the spatial domain into the temporal domain to reconstitute memory of a natural event? By reviewing the literature, here we present how the memory engram (trace) neurons are selected and consolidated in the brain. Then, we will discuss the main challenges in the memory trace theory. In the end, we will provide a plausible model of memory trace cell network, underlying the conversion of neural activities between the spatial domain and the temporal domain. We will also discuss on how the activation of sparse memory trace neurons might trigger the replay of neural activities in specific temporal patterns.

From network heterogeneities to familiarity detection and hippocampal memory management

PubMed Central

Wang, Jane X.; Poe, Gina; Zochowski, Michal

2009-01-01

Hippocampal-neocortical interactions are key to the rapid formation of novel associative memories in the hippocampus and consolidation to long term storage sites in the neocortex. We investigated the role of network correlates during information processing in hippocampal-cortical networks. We found that changes in the intrinsic network dynamics due to the formation of structural network heterogeneities alone act as a dynamical and regulatory mechanism for stimulus novelty and familiarity detection, thereby controlling memory management in the context of memory consolidation. This network dynamic, coupled with an anatomically established feedback between the hippocampus and the neocortex, recovered heretofore unexplained properties of neural activity patterns during memory management tasks which we observed during sleep in multiunit recordings from behaving animals. Our simple dynamical mechanism shows an experimentally matched progressive shift of memory activation from the hippocampus to the neocortex and thus provides the means to achieve an autonomous off-line progression of memory consolidation. PMID:18999453

75 FR 44283 - In the Matter of Certain Dynamic Random Access Memory Semiconductors and Products Containing Same...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-28

... Random Access Memory Semiconductors and Products Containing Same, Including Memory Modules; Notice of a... importation of certain dynamic random access memory semiconductors and products containing same, including memory modules, by reason of infringement of certain claims of U.S. Patent Nos. 5,480,051; 5,422,309; 5...

Cell-assembly coding in several memory processes.

PubMed

Sakurai, Y

1998-01-01

The present paper discusses why the cell assembly, i.e., an ensemble population of neurons with flexible functional connections, is a tenable view of the basic code for information processes in the brain. The main properties indicating the reality of cell-assembly coding are neurons overlaps among different assemblies and connection dynamics within and among the assemblies. The former can be detected as multiple functions of individual neurons in processing different kinds of information. Individual neurons appear to be involved in multiple information processes. The latter can be detected as changes of functional synaptic connections in processing different kinds of information. Correlations of activity among some of the recorded neurons appear to change in multiple information processes. Recent experiments have compared several different memory processes (tasks) and detected these two main properties, indicating cell-assembly coding of memory in the working brain. The first experiment compared different types of processing of identical stimuli, i.e., working memory and reference memory of auditory stimuli. The second experiment compared identical processes of different types of stimuli, i.e., discriminations of simple auditory, simple visual, and configural auditory-visual stimuli. The third experiment compared identical processes of different types of stimuli with or without temporal processing of stimuli, i.e., discriminations of elemental auditory, configural auditory-visual, and sequential auditory-visual stimuli. Some possible features of the cell-assembly coding, especially "dual coding" by individual neurons and cell assemblies, are discussed for future experimental approaches. Copyright 1998 Academic Press.

On Connection Between Topology and Memory Loss in Sheared Granular Materials

NASA Astrophysics Data System (ADS)

Kovalcinova, Lenka; Kramar, Miro; Mischaikow, Konstantin; Kondic, Lou

We present combined results of discrete element simulations and topological data analysis that allows us to characterize the geometrical properties of force networks. Our numerical setup consists of the system of cylindrical particles placed inside rectangular box with periodic boundary conditions along the horizontal direction. System dynamics is driven by constant shearing speed of the top and bottom walls (in the opposite directions) and pressure applied on the top wall in a dense flow regime. Our study reveals the origin of memory loss in granular systems through local rapid changes in force networks. To understand these rapid events we analyze the evolution of the largest Lyapunov exponent in a simpler case of granular system without inter-particle friction and explore a correlation with topological measures. Surprisingly, our results suggest that the memory loss is driven mainly by pressure even in the case of fixed inertial number. We conclude that the interplay between physical properties of the granular system and force network geometry is a key to understand the dynamics of the sheared systems. This research was supported by NSF Grant No. DMS-1521717 and DARPA No. HR0011-16-2-0033.

Stochastic modeling for dynamics of HIV-1 infection using cellular automata: A review.

PubMed

Precharattana, Monamorn

2016-02-01

Recently, the description of immune response by discrete models has emerged to play an important role to study the problems in the area of human immunodeficiency virus type 1 (HIV-1) infection, leading to AIDS. As infection of target immune cells by HIV-1 mainly takes place in the lymphoid tissue, cellular automata (CA) models thus represent a significant step in understanding when the infected population is dispersed. Motivated by these, the studies of the dynamics of HIV-1 infection using CA in memory have been presented to recognize how CA have been developed for HIV-1 dynamics, which issues have been studied already and which issues still are objectives in future studies.

Theta synchronization networks emerge during human object-place memory encoding.

PubMed

Sato, Naoyuki; Yamaguchi, Yoko

2007-03-26

Recent rodent hippocampus studies have suggested that theta rhythm-dependent neural dynamics ('theta phase precession') is essential for an on-line memory formation. A computational study indicated that the phase precession enables a human object-place association memory with voluntary eye movements, although it is still an open question whether the human brain uses the dynamics. Here we elucidated subsequent memory-correlated activities in human scalp electroencephalography in an object-place association memory designed according the former computational study. Our results successfully demonstrated that subsequent memory recall is characterized by an increase in theta power and coherence, and further, that multiple theta synchronization networks emerge. These findings suggest the human theta dynamics in common with rodents in episodic memory formation.

Dynamic Photorefractive Memory and its Application for Opto-Electronic Neural Networks.

NASA Astrophysics Data System (ADS)

Sasaki, Hironori

This dissertation describes the analysis of the photorefractive crystal dynamics and its application for opto-electronic neural network systems. The realization of the dynamic photorefractive memory is investigated in terms of the following aspects: fast memory update, uniform grating multiplexing schedules and the prevention of the partial erasure of existing gratings. The fast memory update is realized by the selective erasure process that superimposes a new grating on the original one with an appropriate phase shift. The dynamics of the selective erasure process is analyzed using the first-order photorefractive material equations and experimentally confirmed. The effects of beam coupling and fringe bending on the selective erasure dynamics are also analyzed by numerically solving a combination of coupled wave equations and the photorefractive material equation. Incremental recording technique is proposed as a uniform grating multiplexing schedule and compared with the conventional scheduled recording technique in terms of phase distribution in the presence of an external dc electric field, as well as the image gray scale dependence. The theoretical analysis and experimental results proved the superiority of the incremental recording technique over the scheduled recording. Novel recirculating information memory architecture is proposed and experimentally demonstrated to prevent partial degradation of the existing gratings by accessing the memory. Gratings are circulated through a memory feed back loop based on the incremental recording dynamics and demonstrate robust read/write/erase capabilities. The dynamic photorefractive memory is applied to opto-electronic neural network systems. Module architecture based on the page-oriented dynamic photorefractive memory is proposed. This module architecture can implement two complementary interconnection organizations, fan-in and fan-out. The module system scalability and the learning capabilities are theoretically investigated using the photorefractive dynamics described in previous chapters of the dissertation. The implementation of the feed-forward image compression network with 900 input and 9 output neurons with 6-bit interconnection accuracy is experimentally demonstrated. Learning of the Perceptron network that determines sex based on input face images of 900 pixels is also successfully demonstrated.

Elements of the cellular metabolic structure

PubMed Central

De la Fuente, Ildefonso M.

2015-01-01

A large number of studies have demonstrated the existence of metabolic covalent modifications in different molecular structures, which are able to store biochemical information that is not encoded by DNA. Some of these covalent mark patterns can be transmitted across generations (epigenetic changes). Recently, the emergence of Hopfield-like attractor dynamics has been observed in self-organized enzymatic networks, which have the capacity to store functional catalytic patterns that can be correctly recovered by specific input stimuli. Hopfield-like metabolic dynamics are stable and can be maintained as a long-term biochemical memory. In addition, specific molecular information can be transferred from the functional dynamics of the metabolic networks to the enzymatic activity involved in covalent post-translational modulation, so that determined functional memory can be embedded in multiple stable molecular marks. The metabolic dynamics governed by Hopfield-type attractors (functional processes), as well as the enzymatic covalent modifications of specific molecules (structural dynamic processes) seem to represent the two stages of the dynamical memory of cellular metabolism (metabolic memory). Epigenetic processes appear to be the structural manifestation of this cellular metabolic memory. Here, a new framework for molecular information storage in the cell is presented, which is characterized by two functionally and molecularly interrelated systems: a dynamic, flexible and adaptive system (metabolic memory) and an essentially conservative system (genetic memory). The molecular information of both systems seems to coordinate the physiological development of the whole cell. PMID:25988183

LOD-based clustering techniques for efficient large-scale terrain storage and visualization

NASA Astrophysics Data System (ADS)

Bao, Xiaohong; Pajarola, Renato

2003-05-01

Large multi-resolution terrain data sets are usually stored out-of-core. To visualize terrain data at interactive frame rates, the data needs to be organized on disk, loaded into main memory part by part, then rendered efficiently. Many main-memory algorithms have been proposed for efficient vertex selection and mesh construction. Organization of terrain data on disk is quite difficult because the error, the triangulation dependency and the spatial location of each vertex all need to be considered. Previous terrain clustering algorithms did not consider the per-vertex approximation error of individual terrain data sets. Therefore, the vertex sequences on disk are exactly the same for any terrain. In this paper, we propose a novel clustering algorithm which introduces the level-of-detail (LOD) information to terrain data organization to map multi-resolution terrain data to external memory. In our approach the LOD parameters of the terrain elevation points are reflected during clustering. The experiments show that dynamic loading and paging of terrain data at varying LOD is very efficient and minimizes page faults. Additionally, the preprocessing of this algorithm is very fast and works from out-of-core.

Memory and betweenness preference in temporal networks induced from time series

NASA Astrophysics Data System (ADS)

Weng, Tongfeng; Zhang, Jie; Small, Michael; Zheng, Rui; Hui, Pan

2017-02-01

We construct temporal networks from time series via unfolding the temporal information into an additional topological dimension of the networks. Thus, we are able to introduce memory entropy analysis to unravel the memory effect within the considered signal. We find distinct patterns in the entropy growth rate of the aggregate network at different memory scales for time series with different dynamics ranging from white noise, 1/f noise, autoregressive process, periodic to chaotic dynamics. Interestingly, for a chaotic time series, an exponential scaling emerges in the memory entropy analysis. We demonstrate that the memory exponent can successfully characterize bifurcation phenomenon, and differentiate the human cardiac system in healthy and pathological states. Moreover, we show that the betweenness preference analysis of these temporal networks can further characterize dynamical systems and separate distinct electrocardiogram recordings. Our work explores the memory effect and betweenness preference in temporal networks constructed from time series data, providing a new perspective to understand the underlying dynamical systems.

Statistical Computations Underlying the Dynamics of Memory Updating

PubMed Central

Gershman, Samuel J.; Radulescu, Angela; Norman, Kenneth A.; Niv, Yael

2014-01-01

Psychophysical and neurophysiological studies have suggested that memory is not simply a carbon copy of our experience: Memories are modified or new memories are formed depending on the dynamic structure of our experience, and specifically, on how gradually or abruptly the world changes. We present a statistical theory of memory formation in a dynamic environment, based on a nonparametric generalization of the switching Kalman filter. We show that this theory can qualitatively account for several psychophysical and neural phenomena, and present results of a new visual memory experiment aimed at testing the theory directly. Our experimental findings suggest that humans can use temporal discontinuities in the structure of the environment to determine when to form new memory traces. The statistical perspective we offer provides a coherent account of the conditions under which new experience is integrated into an old memory versus forming a new memory, and shows that memory formation depends on inferences about the underlying structure of our experience. PMID:25375816

Non-Markovian Complexity in the Quantum-to-Classical Transition

PubMed Central

Xiong, Heng-Na; Lo, Ping-Yuan; Zhang, Wei-Min; Feng, Da Hsuan; Nori, Franco

2015-01-01

The quantum-to-classical transition is due to environment-induced decoherence, and it depicts how classical dynamics emerges from quantum systems. Previously, the quantum-to-classical transition has mainly been described with memory-less (Markovian) quantum processes. Here we study the complexity of the quantum-to-classical transition through general non-Markovian memory processes. That is, the influence of various reservoirs results in a given initial quantum state evolving into one of the following four scenarios: thermal state, thermal-like state, quantum steady state, or oscillating quantum nonstationary state. In the latter two scenarios, the system maintains partial or full quantum coherence due to the strong non-Markovian memory effect, so that in these cases, the quantum-to-classical transition never occurs. This unexpected new feature provides a new avenue for the development of future quantum technologies because the remaining quantum oscillations in steady states are decoherence-free. PMID:26303002

The Dynamic Multiprocess Framework: Evidence from Prospective Memory with Contextual Variability

PubMed Central

Scullin, Michael K.; McDaniel, Mark A.; Shelton, Jill Talley

2013-01-01

The ability to remember to execute delayed intentions is referred to as prospective memory. Previous theoretical and empirical work has focused on isolating whether a particular prospective memory task is supported either by effortful monitoring processes or by cue-driven spontaneous processes. In the present work, we advance the Dynamic Multiprocess Framework, which contends that both monitoring and spontaneous retrieval may be utilized dynamically to support prospective remembering. To capture the dynamic interplay between monitoring and spontaneous retrieval we had participants perform many ongoing tasks and told them that their prospective memory cue may occur in any context. Following either a 20-min or a 12-hr retention interval, the prospective memory cues were presented infrequently across three separate ongoing tasks. The monitoring patterns (measured as ongoing task cost relative to a between-subjects control condition) were consistent and robust across the three contexts. There was no evidence for monitoring prior to the initial prospective memory cue; however, individuals who successfully spontaneously retrieved the prospective memory intention, thereby realizing that prospective memory cues could be expected within that context, subsequently monitored. These data support the Dynamic Multiprocess Framework, which contends that individuals will engage monitoring when prospective memory cues are expected, disengage monitoring when cues are not expected, and that when monitoring is disengaged, a probabilistic spontaneous retrieval mechanism can support prospective remembering. PMID:23916951

Episodic memory deficits slow down the dynamics of cognitive procedural learning in normal ageing

PubMed Central

Beaunieux, Hélène; Hubert, Valérie; Pitel, Anne Lise; Desgranges, Béatrice; Eustache, Francis

2009-01-01

Cognitive procedural learning is characterized by three phases, each involving distinct processes. Considering the implication of the episodic memory in the first cognitive stage, the impairment of this memory system might be responsible for a slowing down of the cognitive procedural learning dynamics in the course of aging. Performances of massed cognitive procedural learning were evaluated in older and younger participants using the Tower of Toronto task. Nonverbal intelligence and psychomotor abilities were used to analyze procedural dynamics, while episodic memory and working memory were assessed to measure their respective contributions to learning strategies. This experiment showed that older participants did not spontaneously invoke episodic memory and presented a slowdown in the cognitive procedural learning associated with a late involvement of working memory. These findings suggest that the slowdown in the cognitive procedural learning may be linked with the implementation of different learning strategies less involving episodic memory in older subjects. PMID:18654928

Working Memory and Dynamic Measures of Analogical Reasoning as Predictors of Children's Math and Reading Achievement

ERIC Educational Resources Information Center

Stevenson, Claire E.; Bergwerff, Catharina E.; Heiser, Willem J.; Resing, Wilma C. M.

2014-01-01

Working memory and inductive reasoning ability each appear related to children's achievement in math and reading. Dynamic measures of reasoning, based on an assessment procedure including feedback, may provide additional predictive value. The aim of this study was to investigate whether working memory and dynamic measures of analogical…

A dynamic evolution model of human opinion as affected by advertising

NASA Astrophysics Data System (ADS)

Luo, Gui-Xun; Liu, Yun; Zeng, Qing-An; Diao, Su-Meng; Xiong, Fei

2014-11-01

We propose a new model to investigate the dynamics of human opinion as affected by advertising, based on the main idea of the CODA model and taking into account two practical factors: one is that the marginal influence of an additional friend will decrease with an increasing number of friends; the other is the decline of memory over time. Simulations show several significant conclusions for both advertising agencies and the general public. A small difference of advertising’s influence on individuals or advertising coverage will result in significantly different advertising effectiveness within a certain interval of value. Compared to the value of advertising’s influence on individuals, the advertising coverage plays a more important role due to the exponential decay of memory. Meanwhile, some of the obtained results are in accordance with people’s daily cognition about advertising. The real key factor in determining the success of advertising is the intensity of exchanging opinions, and people’s external actions always follow their internal opinions. Negative opinions also play an important role.

The Construction of Semantic Memory: Grammar-Based Representations Learned from Relational Episodic Information

PubMed Central

Battaglia, Francesco P.; Pennartz, Cyriel M. A.

2011-01-01

After acquisition, memories underlie a process of consolidation, making them more resistant to interference and brain injury. Memory consolidation involves systems-level interactions, most importantly between the hippocampus and associated structures, which takes part in the initial encoding of memory, and the neocortex, which supports long-term storage. This dichotomy parallels the contrast between episodic memory (tied to the hippocampal formation), collecting an autobiographical stream of experiences, and semantic memory, a repertoire of facts and statistical regularities about the world, involving the neocortex at large. Experimental evidence points to a gradual transformation of memories, following encoding, from an episodic to a semantic character. This may require an exchange of information between different memory modules during inactive periods. We propose a theory for such interactions and for the formation of semantic memory, in which episodic memory is encoded as relational data. Semantic memory is modeled as a modified stochastic grammar, which learns to parse episodic configurations expressed as an association matrix. The grammar produces tree-like representations of episodes, describing the relationships between its main constituents at multiple levels of categorization, based on its current knowledge of world regularities. These regularities are learned by the grammar from episodic memory information, through an expectation-maximization procedure, analogous to the inside–outside algorithm for stochastic context-free grammars. We propose that a Monte-Carlo sampling version of this algorithm can be mapped on the dynamics of “sleep replay” of previously acquired information in the hippocampus and neocortex. We propose that the model can reproduce several properties of semantic memory such as decontextualization, top-down processing, and creation of schemata. PMID:21887143

Unraveling Network-induced Memory Contention: Deeper Insights with Machine Learning

DOE PAGES

Groves, Taylor Liles; Grant, Ryan; Gonzales, Aaron; ...

2017-11-21

Remote Direct Memory Access (RDMA) is expected to be an integral communication mechanism for future exascale systems enabling asynchronous data transfers, so that applications may fully utilize CPU resources while simultaneously sharing data amongst remote nodes. We examine Network-induced Memory Contention (NiMC) on Infiniband networks. We expose the interactions between RDMA, main-memory and cache, when applications and out-of-band services compete for memory resources. We then explore NiMCs resulting impact on application-level performance. For a range of hardware technologies and HPC workloads, we quantify NiMC and show that NiMCs impact grows with scale resulting in up to 3X performance degradation atmore » scales as small as 8K processes even in applications that previously have been shown to be performance resilient in the presence of noise. In addition, this work examines the problem of predicting NiMC's impact on applications by leveraging machine learning and easily accessible performance counters. This approach provides additional insights about the root cause of NiMC and facilitates dynamic selection of potential solutions. Finally, we evaluated three potential techniques to reduce NiMCs impact, namely hardware offloading, core reservation and network throttling.« less

Unraveling Network-induced Memory Contention: Deeper Insights with Machine Learning

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

Groves, Taylor Liles; Grant, Ryan; Gonzales, Aaron

Remote Direct Memory Access (RDMA) is expected to be an integral communication mechanism for future exascale systems enabling asynchronous data transfers, so that applications may fully utilize CPU resources while simultaneously sharing data amongst remote nodes. We examine Network-induced Memory Contention (NiMC) on Infiniband networks. We expose the interactions between RDMA, main-memory and cache, when applications and out-of-band services compete for memory resources. We then explore NiMCs resulting impact on application-level performance. For a range of hardware technologies and HPC workloads, we quantify NiMC and show that NiMCs impact grows with scale resulting in up to 3X performance degradation atmore » scales as small as 8K processes even in applications that previously have been shown to be performance resilient in the presence of noise. In addition, this work examines the problem of predicting NiMC's impact on applications by leveraging machine learning and easily accessible performance counters. This approach provides additional insights about the root cause of NiMC and facilitates dynamic selection of potential solutions. Finally, we evaluated three potential techniques to reduce NiMCs impact, namely hardware offloading, core reservation and network throttling.« less

Including Memory Friction in Single- and Two-State Quantum Dynamics Simulations.

PubMed

Brown, Paul A; Messina, Michael

2016-03-03

We present a simple computational algorithm that allows for the inclusion of memory friction in a quantum dynamics simulation of a small, quantum, primary system coupled to many atoms in the surroundings. We show how including a memory friction operator, F̂, in the primary quantum system's Hamiltonian operator builds memory friction into the dynamics of the primary quantum system. We show that, in the harmonic, semi-classical limit, this friction operator causes the classical phase-space centers of a wavepacket to evolve exactly as if it were a classical particle experiencing memory friction. We also show that this friction operator can be used to include memory friction in the quantum dynamics of an anharmonic primary system. We then generalize the algorithm so that it can be used to treat a primary quantum system that is evolving, non-adiabatically on two coupled potential energy surfaces, i.e., a model that can be used to model H atom transfer, for example. We demonstrate this approach's computational ease and flexibility by showing numerical results for both harmonic and anharmonic primary quantum systems in the single surface case. Finally, we present numerical results for a model of non-adiabatic H atom transfer between a reactant and product state that includes memory friction on one or both of the non-adiabatic potential energy surfaces and uncover some interesting dynamical effects of non-memory friction on the H atom transfer process.

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.

Numerical analysis of dynamic behavior of pre-stressed shape memory alloy concrete beam-column joints

NASA Astrophysics Data System (ADS)

Yan, S.; Xiao, Z. F.; Lin, M. Y.; Niu, J.

2018-04-01

Beam-column joints are important parts of a main frame structure. Mechanical properties of beam-column joints have a great influence on dynamic performances of the frame structure. Shape memory alloy (SMA) as a new type of intelligent metal materials has wide applications in civil engineering. The paper aims at proposing a novel beam-column joint reinforced with pre-stressed SMA tendons to increase its dynamic performance. Based on the finite element analysis (FEA) software ABAQUS, a numerical simulation for 6 beam-column scaled models considering different SMA reinforcement ratios and pre-stress levels was performed, focusing on bearing capacities, energy-dissipation and self-centering capacities, etc. These models were numerically tested under a pseudo-static load on the beam end, companying a constant vertical compressive load on the top of the column. The numerical results show that the proposed SMA-reinforced joint has a significantly increased bearing capacity and a good self-centering capability after unloading even though the energy-dissipation capacity becomes smaller due the less residual deformation. The concept and mechanism of the novel joint can be used as an important reference for civil engineering applications.

CDW fluctuations and the pseudogap in the single-particle conductivity of quasi-1D Peierls CDW systems: II.

PubMed

Kupčić, I; Rukelj, Z; Barišić, S

2014-05-14

The current-dipole Kubo formula for the dynamical conductivity of interacting multiband electronic systems derived in Kupčić et al (2013 J. Phys.: Condens. Matter 25 145602) is illustrated on the Peierls model for quasi-one-dimensional systems with the charge-density-wave (CDW) instability. Using the microscopic representation of the Peierls model, it is shown in which way the scattering of conduction electrons by CDW fluctuations affects the dynamical conductivity at temperatures above and well below the CDW transition temperature. The generalized Drude formula for the intraband conductivity is derived in the ordered CDW state well below the transition temperature. The natural extension of this formula to the case where the intraband memory function is dependent on frequency and wave vectors is also presented. It is shown that the main adventage of such a memory-function conductivity model is that it can be easily extended to study the dynamical conductivity and the electronic Raman scattering in more complicated multiband electronic systems in a way consistent with the law of conservation of energy. The incoherent interband conductivity in the CDW pseudogap state is briefly discussed as well.

Programming and memory dynamics of innate leukocytes during tissue homeostasis and inflammation.

PubMed

Lee, Christina; Geng, Shuo; Zhang, Yao; Rahtes, Allison; Li, Liwu

2017-09-01

The field of innate immunity is witnessing a paradigm shift regarding "memory" and "programming" dynamics. Past studies of innate leukocytes characterized them as first responders to danger signals with no memory. However, recent findings suggest that innate leukocytes, such as monocytes and neutrophils, are capable of "memorizing" not only the chemical nature but also the history and dosages of external stimulants. As a consequence, innate leukocytes can be dynamically programmed or reprogrammed into complex inflammatory memory states. Key examples of innate leukocyte memory dynamics include the development of primed and tolerant monocytes when "programmed" with a variety of inflammatory stimulants at varying signal strengths. The development of innate leukocyte memory may have far-reaching translational implications, as programmed innate leukocytes may affect the pathogenesis of both acute and chronic inflammatory diseases. This review intends to critically discuss some of the recent studies that address this emerging concept and its implication in the pathogenesis of inflammatory diseases. © Society for Leukocyte Biology.

Non-volatile main memory management methods based on a file system.

PubMed

Oikawa, Shuichi

2014-01-01

There are upcoming non-volatile (NV) memory technologies that provide byte addressability and high performance. PCM, MRAM, and STT-RAM are such examples. Such NV memory can be used as storage because of its data persistency without power supply while it can be used as main memory because of its high performance that matches up with DRAM. There are a number of researches that investigated its uses for main memory and storage. They were, however, conducted independently. This paper presents the methods that enables the integration of the main memory and file system management for NV memory. Such integration makes NV memory simultaneously utilized as both main memory and storage. The presented methods use a file system as their basis for the NV memory management. We implemented the proposed methods in the Linux kernel, and performed the evaluation on the QEMU system emulator. The evaluation results show that 1) the proposed methods can perform comparably to the existing DRAM memory allocator and significantly better than the page swapping, 2) their performance is affected by the internal data structures of a file system, and 3) the data structures appropriate for traditional hard disk drives do not always work effectively for byte addressable NV memory. We also performed the evaluation of the effects caused by the longer access latency of NV memory by cycle-accurate full-system simulation. The results show that the effect on page allocation cost is limited if the increase of latency is moderate.

Stress in the zoo: Tracking the impact of stress on memory formation over time.

PubMed

Vogel, Susanne; Schwabe, Lars

2016-09-01

Although stress is well known to modulate human memory, precisely how memory formation is altered by a stressful encounter remains unclear. Stress effects on cognition are mainly mediated by the rapidly acting sympathetic nervous system, resulting in the release of catecholamines, and the slower acting hypothalamus-pituitary-adrenal axis secreting cortisol, which induces its effects on cognition through fast, non-genomic actions and delayed, genomic actions. Importantly, these different waves of the physiological stress response are thought to dynamically alter neural processing in brain regions important for memory such as the amygdala and the hippocampus. However, the precise time course of stress effects on memory formation is still unclear. To track the development of stress effects on memory over time, we tested individuals who underwent a stressful experience or a control procedure before a 2-h walk through a zoo, while an automatic camera continuously photographed the events they encoded. In a recognition memory test one week later, participants were presented with target photographs of their own zoo tour and lure photographs from an alternate tour. Stressed participants showed better memory for the experimental treatment than control participants, and this memory enhancement for the stressful encounter itself was directly linked to the sympathetic stress response. Moreover, stress enhanced memory for events encoded 41-65min after stressor onset, which was associated with the cortisol stress response, most likely arising from non-genomic cortisol actions. However, memory for events encoded long after the stressor, when genomic cortisol actions had most likely developed, remained unchanged. Our findings provide novel insights into how stress effects on memory formation develop over time, depending on the activity of major physiological stress response systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

OFF, Open source Finite volume Fluid dynamics code: A free, high-order solver based on parallel, modular, object-oriented Fortran API

NASA Astrophysics Data System (ADS)

Zaghi, S.

2014-07-01

OFF, an open source (free software) code for performing fluid dynamics simulations, is presented. The aim of OFF is to solve, numerically, the unsteady (and steady) compressible Navier-Stokes equations of fluid dynamics by means of finite volume techniques: the research background is mainly focused on high-order (WENO) schemes for multi-fluids, multi-phase flows over complex geometries. To this purpose a highly modular, object-oriented application program interface (API) has been developed. In particular, the concepts of data encapsulation and inheritance available within Fortran language (from standard 2003) have been stressed in order to represent each fluid dynamics "entity" (e.g. the conservative variables of a finite volume, its geometry, etc…) by a single object so that a large variety of computational libraries can be easily (and efficiently) developed upon these objects. The main features of OFF can be summarized as follows: Programming LanguageOFF is written in standard (compliant) Fortran 2003; its design is highly modular in order to enhance simplicity of use and maintenance without compromising the efficiency; Parallel Frameworks Supported the development of OFF has been also targeted to maximize the computational efficiency: the code is designed to run on shared-memory multi-cores workstations and distributed-memory clusters of shared-memory nodes (supercomputers); the code's parallelization is based on Open Multiprocessing (OpenMP) and Message Passing Interface (MPI) paradigms; Usability, Maintenance and Enhancement in order to improve the usability, maintenance and enhancement of the code also the documentation has been carefully taken into account; the documentation is built upon comprehensive comments placed directly into the source files (no external documentation files needed): these comments are parsed by means of doxygen free software producing high quality html and latex documentation pages; the distributed versioning system referred as git has been adopted in order to facilitate the collaborative maintenance and improvement of the code; CopyrightsOFF is a free software that anyone can use, copy, distribute, study, change and improve under the GNU Public License version 3. The present paper is a manifesto of OFF code and presents the currently implemented features and ongoing developments. This work is focused on the computational techniques adopted and a detailed description of the main API characteristics is reported. OFF capabilities are demonstrated by means of one and two dimensional examples and a three dimensional real application.

Convergence dynamics and pseudo almost periodicity of a class of nonautonomous RFDEs with applications

NASA Astrophysics Data System (ADS)

Fan, Meng; Ye, Dan

2005-09-01

This paper studies the dynamics of a system of retarded functional differential equations (i.e., RF=Es), which generalize the Hopfield neural network models, the bidirectional associative memory neural networks, the hybrid network models of the cellular neural network type, and some population growth model. Sufficient criteria are established for the globally exponential stability and the existence and uniqueness of pseudo almost periodic solution. The approaches are based on constructing suitable Lyapunov functionals and the well-known Banach contraction mapping principle. The paper ends with some applications of the main results to some neural network models and population growth models and numerical simulations.

Robust sequential working memory recall in heterogeneous cognitive networks

PubMed Central

Rabinovich, Mikhail I.; Sokolov, Yury; Kozma, Robert

2014-01-01

Psychiatric disorders are often caused by partial heterogeneous disinhibition in cognitive networks, controlling sequential and spatial working memory (SWM). Such dynamic connectivity changes suggest that the normal relationship between the neuronal components within the network deteriorates. As a result, competitive network dynamics is qualitatively altered. This dynamics defines the robust recall of the sequential information from memory and, thus, the SWM capacity. To understand pathological and non-pathological bifurcations of the sequential memory dynamics, here we investigate the model of recurrent inhibitory-excitatory networks with heterogeneous inhibition. We consider the ensemble of units with all-to-all inhibitory connections, in which the connection strengths are monotonically distributed at some interval. Based on computer experiments and studying the Lyapunov exponents, we observed and analyzed the new phenomenon—clustered sequential dynamics. The results are interpreted in the context of the winnerless competition principle. Accordingly, clustered sequential dynamics is represented in the phase space of the model by two weakly interacting quasi-attractors. One of them is similar to the sequential heteroclinic chain—the regular image of SWM, while the other is a quasi-chaotic attractor. Coexistence of these quasi-attractors means that the recall of the normal information sequence is intermittently interrupted by episodes with chaotic dynamics. We indicate potential dynamic ways for augmenting damaged working memory and other cognitive functions. PMID:25452717

Automatic multi-banking of memory for microprocessors

NASA Technical Reports Server (NTRS)

Wiker, G. A. (Inventor)

1984-01-01

A microprocessor system is provided with added memories to expand its address spaces beyond its address word length capacity by using indirect addressing instructions of a type having a detectable operations code and dedicating designated address spaces of memory to each of the added memories, one space to a memory. By decoding each operations code of instructions read from main memory into a decoder to identify indirect addressing instructions of the specified type, and then decoding the address that follows in a decoder to determine which added memory is associated therewith, the associated added memory is selectively enabled through a unit while the main memory is disabled to permit the instruction to be executed on the location to which the effective address of the indirect address instruction points, either before the indirect address is read from main memory or afterwards, depending on how the system is arranged by a switch.

Exploiting short-term memory in soft body dynamics as a computational resource

PubMed Central

Nakajima, K.; Li, T.; Hauser, H.; Pfeifer, R.

2014-01-01

Soft materials are not only highly deformable, but they also possess rich and diverse body dynamics. Soft body dynamics exhibit a variety of properties, including nonlinearity, elasticity and potentially infinitely many degrees of freedom. Here, we demonstrate that such soft body dynamics can be employed to conduct certain types of computation. Using body dynamics generated from a soft silicone arm, we show that they can be exploited to emulate functions that require memory and to embed robust closed-loop control into the arm. Our results suggest that soft body dynamics have a short-term memory and can serve as a computational resource. This finding paves the way towards exploiting passive body dynamics for control of a large class of underactuated systems. PMID:25185579

Optimal Foraging in Semantic Memory

ERIC Educational Resources Information Center

Hills, Thomas T.; Jones, Michael N.; Todd, Peter M.

2012-01-01

Do humans search in memory using dynamic local-to-global search strategies similar to those that animals use to forage between patches in space? If so, do their dynamic memory search policies correspond to optimal foraging strategies seen for spatial foraging? Results from a number of fields suggest these possibilities, including the shared…

The Response Dynamics of Recognition Memory: Sensitivity and Bias

ERIC Educational Resources Information Center

Koop, Gregory J.; Criss, Amy H.

2016-01-01

Advances in theories of memory are hampered by insufficient metrics for measuring memory. The goal of this paper is to further the development of model-independent, sensitive empirical measures of the recognition decision process. We evaluate whether metrics from continuous mouse tracking, or response dynamics, uniquely identify response bias and…

FFTs in external or hierarchical memory

NASA Technical Reports Server (NTRS)

Bailey, David H.

1989-01-01

A description is given of advanced techniques for computing an ordered FFT on a computer with external or hierarchical memory. These algorithms (1) require as few as two passes through the external data set, (2) use strictly unit stride, long vector transfers between main memory and external storage, (3) require only a modest amount of scratch space in main memory, and (4) are well suited for vector and parallel computation. Performance figures are included for implementations of some of these algorithms on Cray supercomputers. Of interest is the fact that a main memory version outperforms the current Cray library FFT routines on the Cray-2, the Cray X-MP, and the Cray Y-MP systems. Using all eight processors on the Cray Y-MP, this main memory routine runs at nearly 2 Gflops.

Reconfigurable and Reprocessable Thermoset Shape Memory Polymer with Synergetic Triple Dynamic Covalent Bonds.

PubMed

Wang, Yongwei; Pan, Yi; Zheng, Zhaohui; Ding, Xiaobin

2018-04-20

Degradable shape memory polymers (SMPs), especially for polyurethane-based SMPs, have shown great potential for biomedical applications. How to reasonably fabricate SMPs with the ideal combination of degradability, shape reconfigurability, and reprocessability is a critical issue and remains a challenge for medical disposable materials. Herein, a shape memory poly(urethane-urea) with synergetic triple dynamic covalent bonds is reported via embedding polycaprolactone unit into poly(urethane-urea) with the hindered urea dynamic bond. The single polymer network is biodegradable, thermadapt, and reprocessable, without sacrificing the outstanding shape memory performance. Such a shape memory network with plasticity and reprocessability is expected to have significant and positive impact on the medical device industry. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dynamic visual noise affects visual short-term memory for surface color, but not spatial location.

PubMed

Dent, Kevin

2010-01-01

In two experiments participants retained a single color or a set of four spatial locations in memory. During a 5 s retention interval participants viewed either flickering dynamic visual noise or a static matrix pattern. In Experiment 1 memory was assessed using a recognition procedure, in which participants indicated if a particular test stimulus matched the memorized stimulus or not. In Experiment 2 participants attempted to either reproduce the locations or they picked the color from a whole range of possibilities. Both experiments revealed effects of dynamic visual noise (DVN) on memory for colors but not for locations. The implications of the results for theories of working memory and the methodological prospects for DVN as an experimental tool are discussed.

Is random access memory random?

NASA Technical Reports Server (NTRS)

Denning, P. J.

1986-01-01

Most software is contructed on the assumption that the programs and data are stored in random access memory (RAM). Physical limitations on the relative speeds of processor and memory elements lead to a variety of memory organizations that match processor addressing rate with memory service rate. These include interleaved and cached memory. A very high fraction of a processor's address requests can be satified from the cache without reference to the main memory. The cache requests information from main memory in blocks that can be transferred at the full memory speed. Programmers who organize algorithms for locality can realize the highest performance from these computers.

Dynamic Search and Working Memory in Social Recall

ERIC Educational Resources Information Center

Hills, Thomas T.; Pachur, Thorsten

2012-01-01

What are the mechanisms underlying search in social memory (e.g., remembering the people one knows)? Do the search mechanisms involve dynamic local-to-global transitions similar to semantic search, and are these transitions governed by the general control of attention, associated with working memory span? To find out, we asked participants to…

The Dynamics of Access to Groups in Working Memory

ERIC Educational Resources Information Center

Farrell, Simon; Lelievre, Anna

2012-01-01

The finding that participants leave a pause between groups when attempting serial recall of temporally grouped lists has been taken to indicate access to a hierarchical representation of the list in working memory. An alternative explanation is that the dynamics of serial recall solely reflect output (rather than memorial) processes, with the…

75 FR 20564 - Dynamic Random Access Memory Semiconductors from the Republic of Korea: Extension of Time Limit...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-20

... DEPARTMENT OF COMMERCE International Trade Administration [C-580-851] Dynamic Random Access Memory Semiconductors from the Republic of Korea: Extension of Time Limit for Preliminary Results of Countervailing Duty... access memory semiconductors from the Republic of Korea, covering the period January 1, 2008 through...

Effect of memory in non-Markovian Boolean networks illustrated with a case study: A cell cycling process

NASA Astrophysics Data System (ADS)

Ebadi, H.; Saeedian, M.; Ausloos, M.; Jafari, G. R.

2016-11-01

The Boolean network is one successful model to investigate discrete complex systems such as the gene interacting phenomenon. The dynamics of a Boolean network, controlled with Boolean functions, is usually considered to be a Markovian (memory-less) process. However, both self-organizing features of biological phenomena and their intelligent nature should raise some doubt about ignoring the history of their time evolution. Here, we extend the Boolean network Markovian approach: we involve the effect of memory on the dynamics. This can be explored by modifying Boolean functions into non-Markovian functions, for example, by investigating the usual non-Markovian threshold function —one of the most applied Boolean functions. By applying the non-Markovian threshold function on the dynamical process of the yeast cell cycle network, we discover a power-law-like memory with a more robust dynamics than the Markovian dynamics.

Implementation of Parallel Dynamic Simulation on Shared-Memory vs. Distributed-Memory Environments

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

Jin, Shuangshuang; Chen, Yousu; Wu, Di

2015-12-09

Power system dynamic simulation computes the system response to a sequence of large disturbance, such as sudden changes in generation or load, or a network short circuit followed by protective branch switching operation. It consists of a large set of differential and algebraic equations, which is computational intensive and challenging to solve using single-processor based dynamic simulation solution. High-performance computing (HPC) based parallel computing is a very promising technology to speed up the computation and facilitate the simulation process. This paper presents two different parallel implementations of power grid dynamic simulation using Open Multi-processing (OpenMP) on shared-memory platform, and Messagemore » Passing Interface (MPI) on distributed-memory clusters, respectively. The difference of the parallel simulation algorithms and architectures of the two HPC technologies are illustrated, and their performances for running parallel dynamic simulation are compared and demonstrated.« less

Two semiconductor ring lasers coupled by a single-waveguide for optical memory operation

NASA Astrophysics Data System (ADS)

Van der Sande, Guy; Coomans, Werner; Gelens, Lendert

2014-05-01

Semiconductor ring lasers are semiconductor lasers where the laser cavity consists of a ring-shaped waveguide. SRLs are highly integrable and scalable, making them ideal candidates for key components in photonic integrated circuits. SRLs can generate light in two counterpropagating directions between which bistability has been demonstrated. Hence, information can be coded into the emission direction. This bistable operation allows SRLs to be used in systems for all-optical switching and as all-optical memories. For the demonstration of fast optical flip-flop operation, Hill et al. [Nature 432, 206 (2004)] fabricated two SRLs coupled by a single waveguide, rather than a solitary SRL. Nevertheless, the literature shows that a single SRL can also function perfectly as an all-optical memory. In our recent paper [W. Coomans et al., Phys. Rev. A 88, 033813, (2013)], we have raised the question whether coupling two SRLs to realize a single optical memory has any advantage over using a solitary SRL, taking into account the obvious disadvantage of a doubled footprint and power consumption. To provide the answer, we have presented in that paper a numerical study of the dynamical behavior of semiconductor ring lasers coupled by a single bus waveguide, both when weakly coupled and when strongly coupled. We have provided a detailed analysis of the multistable landscape in the coupled system, analyzed the stability of all solutions and related the internal dynamics in the individual lasers to the field effectively measured at the output of the waveguide. We have shown which coupling phases generally promote instabilities and therefore need to be avoided in the design. Regarding all-optical memory operation, we have demonstrated that there is no real advantage for bistable memory operation compared to using a solitary SRL. An increased power suppression ratio has been found to be mainly due to the destructive interference of the SRL fields at the low power port. Also, multistability between several modal configurations has been shown to remain unavoidable.

Mouse Cognition-Related Behavior in the Open-Field: Emergence of Places of Attraction

PubMed Central

Dvorkin, Anna; Benjamini, Yoav; Golani, Ilan

2008-01-01

Spatial memory is often studied in the Morris Water Maze, where the animal's spatial orientation has been shown to be mainly shaped by distal visual cues. Cognition-related behavior has also been described along “well-trodden paths”—spatial habits established by animals in the wild and in captivity reflecting a form of spatial memory. In the present study we combine the study of Open Field behavior with the study of behavior on well-trodden paths, revealing a form of locational memory that appears to correlate with spatial memory. The tracked path of the mouse is used to examine the dynamics of visiting behavior to locations. A visit is defined as either progressing through a location or stopping there, where progressing and stopping are computationally defined. We then estimate the probability of stopping at a location as a function of the number of previous visits to that location, i.e., we measure the effect of visiting history to a location on stopping in it. This can be regarded as an estimate of the familiarity of the mouse with locations. The recently wild-derived inbred strain CZECHII shows the highest effect of visiting history on stopping, C57 inbred mice show a lower effect, and DBA mice show no effect. We employ a rarely used, bottom-to-top computational approach, starting from simple kinematics of movement and gradually building our way up until we end with (emergent) locational memory. The effect of visiting history to a location on stopping in it can be regarded as an estimate of the familiarity of the mouse with locations, implying memory of these locations. We show that the magnitude of this estimate is strain-specific, implying a genetic influence. The dynamics of this process reveal that locations along the mouse's trodden path gradually become places of attraction, where the mouse stops habitually. PMID:18463701

Simple model of epidemics with pathogen mutation.

PubMed

Girvan, Michelle; Callaway, Duncan S; Newman, M E J; Strogatz, Steven H

2002-03-01

We study how the interplay between the memory immune response and pathogen mutation affects epidemic dynamics in two related models. The first explicitly models pathogen mutation and individual memory immune responses, with contacted individuals becoming infected only if they are exposed to strains that are significantly different from other strains in their memory repertoire. The second model is a reduction of the first to a system of difference equations. In this case, individuals spend a fixed amount of time in a generalized immune class. In both models, we observe four fundamentally different types of behavior, depending on parameters: (1) pathogen extinction due to lack of contact between individuals; (2) endemic infection; (3) periodic epidemic outbreaks; and (4) one or more outbreaks followed by extinction of the epidemic due to extremely low minima in the oscillations. We analyze both models to determine the location of each transition. Our main result is that pathogens in highly connected populations must mutate rapidly in order to remain viable.

Dynamic search and working memory in social recall.

PubMed

Hills, Thomas T; Pachur, Thorsten

2012-01-01

What are the mechanisms underlying search in social memory (e.g., remembering the people one knows)? Do the search mechanisms involve dynamic local-to-global transitions similar to semantic search, and are these transitions governed by the general control of attention, associated with working memory span? To find out, we asked participants to recall individuals from their personal social networks and measured each participant's working memory capacity. Additionally, participants provided social-category and contact-frequency information about the recalled individuals as well as information about the social proximity among the recalled individuals. On the basis of these data, we tested various computational models of memory search regarding their ability to account for the patterns in which participants recalled from social memory. Although recall patterns showed clustering based on social categories, models assuming dynamic transitions between representations cued by social proximity and frequency information predicted participants' recall patterns best-no additional explanatory power was gained from social-category information. Moreover, individual differences in the time between transitions were positively correlated with differences in working memory capacity. These results highlight the role of social proximity in structuring social memory and elucidate the role of working memory for maintaining search criteria during search within that structure.

A self-learning rule base for command following in dynamical systems

NASA Technical Reports Server (NTRS)

Tsai, Wei K.; Lee, Hon-Mun; Parlos, Alexander

1992-01-01

In this paper, a self-learning Rule Base for command following in dynamical systems is presented. The learning is accomplished though reinforcement learning using an associative memory called SAM. The main advantage of SAM is that it is a function approximator with explicit storage of training samples. A learning algorithm patterned after the dynamic programming is proposed. Two artificially created, unstable dynamical systems are used for testing, and the Rule Base was used to generate a feedback control to improve the command following ability of the otherwise uncontrolled systems. The numerical results are very encouraging. The controlled systems exhibit a more stable behavior and a better capability to follow reference commands. The rules resulting from the reinforcement learning are explicitly stored and they can be modified or augmented by human experts. Due to overlapping storage scheme of SAM, the stored rules are similar to fuzzy rules.

Faithful Solid State Optical Memory with Dynamically Decoupled Spin Wave Storage

NASA Astrophysics Data System (ADS)

Lovrić, Marko; Suter, Dieter; Ferrier, Alban; Goldner, Philippe

2013-07-01

We report a high fidelity optical memory in which dynamical decoupling is used to extend the storage time. This is demonstrated in a rare-earth doped crystal in which optical coherences were transferred to nuclear spin coherences and then protected against environmental noise by dynamical decoupling, leading to storage times of up to 4.2 ms. An interference experiment shows that relative phases of input pulses are preserved through the whole storage and retrieval process with a visibility ≈1, demonstrating the usefulness of dynamical decoupling for extending the storage time of quantum memories. We also show that dynamical decoupling sequences insensitive to initial spin coherence increase retrieval efficiency.

Faithful solid state optical memory with dynamically decoupled spin wave storage.

PubMed

Lovrić, Marko; Suter, Dieter; Ferrier, Alban; Goldner, Philippe

2013-07-12

We report a high fidelity optical memory in which dynamical decoupling is used to extend the storage time. This is demonstrated in a rare-earth doped crystal in which optical coherences were transferred to nuclear spin coherences and then protected against environmental noise by dynamical decoupling, leading to storage times of up to 4.2 ms. An interference experiment shows that relative phases of input pulses are preserved through the whole storage and retrieval process with a visibility ≈1, demonstrating the usefulness of dynamical decoupling for extending the storage time of quantum memories. We also show that dynamical decoupling sequences insensitive to initial spin coherence increase retrieval efficiency.

Dynamic Forest: An Efficient Index Structure for NAND Flash Memory

NASA Astrophysics Data System (ADS)

Yang, Chul-Woong; Yong Lee, Ki; Ho Kim, Myoung; Lee, Yoon-Joon

In this paper, we present an efficient index structure for NAND flash memory, called the Dynamic Forest (D-Forest). Since write operations incur high overhead on NAND flash memory, D-Forest is designed to minimize write operations for index updates. The experimental results show that D-Forest significantly reduces write operations compared to the conventional B+-tree.

GABA[subscript A] Receptors Determine the Temporal Dynamics of Memory Retention

ERIC Educational Resources Information Center

McNally, Gavan P.; Augustyn, Katarzyna A.; Richardson, Rick

2008-01-01

Four experiments studied the role of GABA[subscript A] receptors in the temporal dynamics of memory retention. Memory for an active avoidance response was a nonmonotonic function of the retention interval. When rats were tested shortly (2 min) or some time (24 h) after training, retention was excellent, but when they were tested at intermediate…

Myosin II Motor Activity in the Lateral Amygdala Is Required for Fear Memory Consolidation

ERIC Educational Resources Information Center

Gavin, Cristin F.; Rubio, Maria D.; Young, Erica; Miller, Courtney; Rumbaugh, Gavin

2012-01-01

Learning induces dynamic changes to the actin cytoskeleton that are required to support memory formation. However, the molecular mechanisms that mediate filamentous actin (F-actin) dynamics during learning and memory are poorly understood. Myosin II motors are highly expressed in actin-rich growth structures including dendritic spines, and we have…

Dynamic effects of memory in a cobweb model with competing technologies

NASA Astrophysics Data System (ADS)

Agliari, Anna; Naimzada, Ahmad; Pecora, Nicolò

2017-02-01

We analyze a simple model based on the cobweb demand-supply framework with costly innovators and free imitators and study the endogenous dynamics of price and firms' fractions in a homogeneous good market. The evolutionary selection between technologies depends on a performance measure in which a memory parameter is introduced. The resulting dynamics is then described by a two-dimensional map. In addition to the locally stabilizing effect due to the presence of memory, we show the existence of a double stability threshold which entails for different dynamic scenarios occurring when the memory parameter takes extreme values (i.e. when consideration of the last profit realization prevails or it is too much neglected). The eventuality of different coexisting attractors as well as the structure of the basins of attraction that characterizes the path dependence property of the model with memory is shown. In particular, through global analysis we also illustrate particular bifurcations sequences that may increase the complexity of the related basins of attraction.

Fast Entanglement Establishment via Local Dynamics for Quantum Repeater Networks

NASA Astrophysics Data System (ADS)

Gyongyosi, Laszlo; Imre, Sandor

Quantum entanglement is a necessity for future quantum communication networks, quantum internet, and long-distance quantum key distribution. The current approaches of entanglement distribution require high-delay entanglement transmission, entanglement swapping to extend the range of entanglement, high-cost entanglement purification, and long-lived quantum memories. We introduce a fundamental protocol for establishing entanglement in quantum communication networks. The proposed scheme does not require entanglement transmission between the nodes, high-cost entanglement swapping, entanglement purification, or long-lived quantum memories. The protocol reliably establishes a maximally entangled system between the remote nodes via dynamics generated by local Hamiltonians. The method eliminates the main drawbacks of current schemes allowing fast entanglement establishment with a minimized delay. Our solution provides a fundamental method for future long-distance quantum key distribution, quantum repeater networks, quantum internet, and quantum-networking protocols. This work was partially supported by the GOP-1.1.1-11-2012-0092 project sponsored by the EU and European Structural Fund, by the Hungarian Scientific Research Fund - OTKA K-112125, and by the COST Action MP1006.

Memory dynamics under stress.

PubMed

Quaedflieg, Conny W E M; Schwabe, Lars

2018-03-01

Stressful events have a major impact on memory. They modulate memory formation in a time-dependent manner, closely linked to the temporal profile of action of major stress mediators, in particular catecholamines and glucocorticoids. Shortly after stressor onset, rapidly acting catecholamines and fast, non-genomic glucocorticoid actions direct cognitive resources to the processing and consolidation of the ongoing threat. In parallel, control of memory is biased towards rather rigid systems, promoting habitual forms of memory allowing efficient processing under stress, at the expense of "cognitive" systems supporting memory flexibility and specificity. In this review, we discuss the implications of this shift in the balance of multiple memory systems for the dynamics of the memory trace. Specifically, stress appears to hinder the incorporation of contextual details into the memory trace, to impede the integration of new information into existing knowledge structures, to impair the flexible generalisation across past experiences, and to hamper the modification of memories in light of new information. Delayed, genomic glucocorticoid actions might reverse the control of memory, thus restoring homeostasis and "cognitive" control of memory again.

Dynamics of aircraft antiskid braking systems. [conducted at the Langley aircraft landing loads and traction facility

NASA Technical Reports Server (NTRS)

Tanner, J. A.; Stubbs, S. M.; Dreher, R. C.; Smith, E. G.

1982-01-01

A computer study was performed to assess the accuracy of three brake pressure-torque mathematical models. The investigation utilized one main gear wheel, brake, and tire assembly of a McDonnell Douglas DC-9 series 10 airplane. The investigation indicates that the performance of aircraft antiskid braking systems is strongly influenced by tire characteristics, dynamic response of the antiskid control valve, and pressure-torque response of the brake. The computer study employed an average torque error criterion to assess the accuracy of the models. The results indicate that a variable nonlinear spring with hysteresis memory function models the pressure-torque response of the brake more accurately than currently used models.

Mapping virtual addresses to different physical addresses for value disambiguation for thread memory access requests

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

Gala, Alan; Ohmacht, Martin

A multiprocessor system includes nodes. Each node includes a data path that includes a core, a TLB, and a first level cache implementing disambiguation. The system also includes at least one second level cache and a main memory. For thread memory access requests, the core uses an address associated with an instruction format of the core. The first level cache uses an address format related to the size of the main memory plus an offset corresponding to hardware thread meta data. The second level cache uses a physical main memory address plus software thread meta data to store the memorymore » access request. The second level cache accesses the main memory using the physical address with neither the offset nor the thread meta data after resolving speculation. In short, this system includes mapping of a virtual address to a different physical addresses for value disambiguation for different threads.« less

Exploiting short-term memory in soft body dynamics as a computational resource.

PubMed

Nakajima, K; Li, T; Hauser, H; Pfeifer, R

2014-11-06

Soft materials are not only highly deformable, but they also possess rich and diverse body dynamics. Soft body dynamics exhibit a variety of properties, including nonlinearity, elasticity and potentially infinitely many degrees of freedom. Here, we demonstrate that such soft body dynamics can be employed to conduct certain types of computation. Using body dynamics generated from a soft silicone arm, we show that they can be exploited to emulate functions that require memory and to embed robust closed-loop control into the arm. Our results suggest that soft body dynamics have a short-term memory and can serve as a computational resource. This finding paves the way towards exploiting passive body dynamics for control of a large class of underactuated systems. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

The importance of hippocampal dynamic connectivity in explaining memory function in multiple sclerosis.

PubMed

van Geest, Quinten; Hulst, Hanneke E; Meijer, Kim A; Hoyng, Lieke; Geurts, Jeroen J G; Douw, Linda

2018-05-01

Brain dynamics (i.e., variable strength of communication between areas), even at the scale of seconds, are thought to underlie complex human behavior, such as learning and memory. In multiple sclerosis (MS), memory problems occur often and have so far only been related to "stationary" brain measures (e.g., atrophy, lesions, activation and stationary (s) functional connectivity (FC) over an entire functional scanning session). However, dynamics in FC (dFC) between the hippocampus and the (neo)cortex may be another important neurobiological substrate of memory impairment in MS that has not yet been explored. Therefore, we investigated hippocampal dFC during a functional (f) magnetic resonance imaging (MRI) episodic memory task and its relationship with verbal and visuospatial memory performance outside the MR scanner. Thirty-eight MS patients and 29 healthy controls underwent neuropsychological tests to assess memory function. Imaging (1.5T) was obtained during performance of a memory task. We assessed hippocampal volume, functional activation, and sFC (i.e., FC of the hippocampus with the rest of the brain averaged over the entire scan, using an atlas-based approach). Dynamic FC of the hippocampus was calculated using a sliding window approach. No group differences were found in hippocampal activation, sFC, and dFC. However, stepwise forward regression analyses in patients revealed that lower dFC of the left hippocampus (standardized β = -0.30; p  =   .021) could explain an additional 7% of variance (53% in total) in verbal memory, in addition to female sex and larger left hippocampal volume. For visuospatial memory, lower dFC of the right hippocampus (standardized β = -0.38; p  =   .013) could explain an additional 13% of variance (24% in total) in addition to higher sFC of the right hippocampus. Low hippocampal dFC is an important indicator for maintained memory performance in MS, in addition to other hippocampal imaging measures. Hence, brain dynamics may offer new insights into the neurobiological mechanisms underlying memory (dys)function.

Large-scale hydropower system optimization using dynamic programming and object-oriented programming: the case of the Northeast China Power Grid.

PubMed

Li, Ji-Qing; Zhang, Yu-Shan; Ji, Chang-Ming; Wang, Ai-Jing; Lund, Jay R

2013-01-01

This paper examines long-term optimal operation using dynamic programming for a large hydropower system of 10 reservoirs in Northeast China. Besides considering flow and hydraulic head, the optimization explicitly includes time-varying electricity market prices to maximize benefit. Two techniques are used to reduce the 'curse of dimensionality' of dynamic programming with many reservoirs. Discrete differential dynamic programming (DDDP) reduces the search space and computer memory needed. Object-oriented programming (OOP) and the ability to dynamically allocate and release memory with the C++ language greatly reduces the cumulative effect of computer memory for solving multi-dimensional dynamic programming models. The case study shows that the model can reduce the 'curse of dimensionality' and achieve satisfactory results.

Modeling soil moisture memory in savanna ecosystems

NASA Astrophysics Data System (ADS)

Gou, S.; Miller, G. R.

2011-12-01

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

Mind-to-mind heteroclinic coordination: Model of sequential episodic memory initiation.

PubMed

Afraimovich, V S; Zaks, M A; Rabinovich, M I

2018-05-01

Retrieval of episodic memory is a dynamical process in the large scale brain networks. In social groups, the neural patterns, associated with specific events directly experienced by single members, are encoded, recalled, and shared by all participants. Here, we construct and study the dynamical model for the formation and maintaining of episodic memory in small ensembles of interacting minds. We prove that the unconventional dynamical attractor of this process-the nonsmooth heteroclinic torus-is structurally stable within the Lotka-Volterra-like sets of equations. Dynamics on this torus combines the absence of chaos with asymptotic instability of every separate trajectory; its adequate quantitative characteristics are length-related Lyapunov exponents. Variation of the coupling strength between the participants results in different types of sequential switching between metastable states; we interpret them as stages in formation and modification of the episodic memory.

Mind-to-mind heteroclinic coordination: Model of sequential episodic memory initiation

NASA Astrophysics Data System (ADS)

Afraimovich, V. S.; Zaks, M. A.; Rabinovich, M. I.

2018-05-01

Retrieval of episodic memory is a dynamical process in the large scale brain networks. In social groups, the neural patterns, associated with specific events directly experienced by single members, are encoded, recalled, and shared by all participants. Here, we construct and study the dynamical model for the formation and maintaining of episodic memory in small ensembles of interacting minds. We prove that the unconventional dynamical attractor of this process—the nonsmooth heteroclinic torus—is structurally stable within the Lotka-Volterra-like sets of equations. Dynamics on this torus combines the absence of chaos with asymptotic instability of every separate trajectory; its adequate quantitative characteristics are length-related Lyapunov exponents. Variation of the coupling strength between the participants results in different types of sequential switching between metastable states; we interpret them as stages in formation and modification of the episodic memory.

Driving working memory with frequency-tuned noninvasive brain stimulation.

PubMed

Albouy, Philippe; Baillet, Sylvain; Zatorre, Robert J

2018-04-29

Frequency-tuned noninvasive brain stimulation is a recent approach in cognitive neuroscience that involves matching the frequency of transcranially applied electromagnetic fields to that of specific oscillatory components of the underlying neurophysiology. The objective of this method is to modulate ongoing/intrinsic brain oscillations, which correspond to rhythmic fluctuations of neural excitability, to causally change behavior. We review the impact of frequency-tuned noninvasive brain stimulation on the research field of human working memory. We argue that this is a powerful method to probe and understand the mechanisms of memory functions, targeting specifically task-related oscillatory dynamics, neuronal representations, and brain networks. We report the main behavioral and neurophysiological outcomes published to date, in particular, how functionally relevant oscillatory signatures in signal power and interregional connectivity yield causal changes of working memory abilities. We also present recent developments of the technique that aim to modulate cross-frequency coupling in polyrhythmic neural activity. Overall, the method has led to significant advances in our understanding of the mechanisms of systems neuroscience, and the role of brain oscillations in cognition and behavior. We also emphasize the translational impact of noninvasive brain stimulation techniques in the development of therapeutic approaches. © 2018 New York Academy of Sciences.

Temperature and leakage aware techniques to improve cache reliability

NASA Astrophysics Data System (ADS)

Akaaboune, Adil

Decreasing power consumption in small devices such as handhelds, cell phones and high-performance processors is now one of the most critical design concerns. On-chip cache memories dominate the chip area in microprocessors and thus arises the need for power efficient cache memories. Cache is the simplest cost effective method to attain high speed memory hierarchy and, its performance is extremely critical for high speed computers. Cache is used by the microprocessor for channeling the performance gap between processor and main memory (RAM) hence the memory bandwidth is frequently a bottleneck which can affect the peak throughput significantly. In the design of any cache system, the tradeoffs of area/cost, performance, power consumption, and thermal management must be taken into consideration. Previous work has mainly concentrated on performance and area/cost constraints. More recent works have focused on low power design especially for portable devices and media-processing systems, however fewer research has been done on the relationship between heat management, Leakage power and cost per die. Lately, the focus of power dissipation in the new generations of microprocessors has shifted from dynamic power to idle power, a previously underestimated form of power loss that causes battery charge to drain and shutdown too early due the waste of energy. The problem has been aggravated by the aggressive scaling of process; device level method used originally by designers to enhance performance, conserve dissipation and reduces the sizes of digital circuits that are increasingly condensed. This dissertation studies the impact of hotspots, in the cache memory, on leakage consumption and microprocessor reliability and durability. The work will first prove that by eliminating hotspots in the cache memory, leakage power will be reduced and therefore, the reliability will be improved. The second technique studied is data quality management that improves the quality of the data stored in the cache to reduce power consumption. The initial work done on this subject focuses on the type of data that increases leakage consumption and ways to manage without impacting the performance of the microprocessor. The second phase of the project focuses on managing the data storage in different blocks of the cache to smooth the leakage power as well as dynamic power consumption. The last technique is a voltage controlled cache to reduce the leakage consumption of the cache while in execution and even in idle state. Two blocks of the 4-way set associative cache go through a voltage regulator before getting to the voltage well, and the other two are directly connected to the voltage well. The idea behind this technique is to use the replacement algorithm information to increase or decrease voltage of the two blocks depending on the need of the information stored on them.

Cellular dynamical mechanisms for encoding the time and place of events along spatiotemporal trajectories in episodic memory.

PubMed

Hasselmo, Michael E; Giocomo, Lisa M; Brandon, Mark P; Yoshida, Motoharu

2010-12-31

Understanding the mechanisms of episodic memory requires linking behavioral data and lesion effects to data on the dynamics of cellular membrane potentials and population interactions within brain regions. Linking behavior to specific membrane channels and neurochemicals has implications for therapeutic applications. Lesions of the hippocampus, entorhinal cortex and subcortical nuclei impair episodic memory function in humans and animals, and unit recording data from these regions in behaving animals indicate episodic memory processes. Intracellular recording in these regions demonstrates specific cellular properties including resonance, membrane potential oscillations and bistable persistent spiking that could underlie the encoding and retrieval of episodic trajectories. A model presented here shows how intrinsic dynamical properties of neurons could mediate the encoding of episodic memories as complex spatiotemporal trajectories. The dynamics of neurons allow encoding and retrieval of unique episodic trajectories in multiple continuous dimensions including temporal intervals, personal location, the spatial coordinates and sensory features of perceived objects and generated actions, and associations between these elements. The model also addresses how cellular dynamics could underlie unit firing data suggesting mechanisms for coding continuous dimensions of space, time, sensation and action. Copyright © 2010 Elsevier B.V. All rights reserved.

Cellular dynamical mechanisms for encoding the time and place of events along spatiotemporal trajectories in episodic memory

PubMed Central

Hasselmo, Michael E.; Giocomo, Lisa M.; Yoshida, Motoharu

2010-01-01

Understanding the mechanisms of episodic memory requires linking behavioural data and lesion effects to data on the dynamics of cellular membrane potentials and population interactions within these brain regions. Linking behavior to specific membrane channels and neurochemicals has implications for therapeutic applications. Lesions of the hippocampus, entorhinal cortex and subcortical nuclei impair episodic memory function in humans and animals, and unit recording data from these regions in behaving animals indicate episodic memory processes. Intracellular recording in these regions demonstrates specific cellular properties including resonance, membrane potential oscillations and bistable persistent spiking that could underlie the encoding and retrieval of episodic trajectories. A model presented here shows how intrinsic dynamical properties of neurons could mediate the encoding of episodic memories as complex spatiotemporal trajectories. The dynamics of neurons allow encoding and retrieval of unique episodic trajectories in multiple continuous dimensions including temporal intervals, personal location, the spatial coordinates and sensory features of perceived objects and generated actions, and associations between these elements. The model also addresses how cellular dynamics could underlie unit firing data suggesting mechanisms for coding continuous dimensions of space, time, sensation and action. PMID:20018213

Memory Dynamics in Cross-linked Actin Networks

NASA Astrophysics Data System (ADS)

Scheff, Danielle; Majumdar, Sayantan; Gardel, Margaret

Cells demonstrate the remarkable ability to adapt to mechanical stimuli through rearrangement of the actin cytoskeleton, a cross-linked network of actin filaments. In addition to its importance in cell biology, understanding this mechanical response provides strategies for creation of novel materials. A recent study has demonstrated that applied stress can encode mechanical memory in these networks through changes in network geometry, which gives rise to anisotropic shear response. Under later shear, the network is stiffer in the direction of the previously applied stress. However, the dynamics behind the encoding of this memory are unknown. To address this question, we explore the effect of varying either the rigidity of the cross-linkers or the length of actin filament on the time scales required for both memory encoding and over which it later decays. While previous experiments saw only a long-lived memory, initial results suggest another mechanism where memories relax relatively quickly. Overall, our study is crucial for understanding the process by which an external stress can impact network arrangement and thus the dynamics of memory formation.

Protocols for Molecular Dynamics Simulations of RNA Nanostructures.

PubMed

Kim, Taejin; Kasprzak, Wojciech K; Shapiro, Bruce A

2017-01-01

Molecular dynamics (MD) simulations have been used as one of the main research tools to study a wide range of biological systems and bridge the gap between X-ray crystallography or NMR structures and biological mechanism. In the field of RNA nanostructures, MD simulations have been used to fix steric clashes in computationally designed RNA nanostructures, characterize the dynamics, and investigate the interaction between RNA and other biomolecules such as delivery agents and membranes.In this chapter we present examples of computational protocols for molecular dynamics simulations in explicit and implicit solvent using the Amber Molecular Dynamics Package. We also show examples of post-simulation analysis steps and briefly mention selected tools beyond the Amber package. Limitations of the methods, tools, and protocols are also discussed. Most of the examples are illustrated for a small RNA duplex (helix), but the protocols are applicable to any nucleic acid structure, subject only to the computational speed and memory limitations of the hardware available to the user.

Data Movement Dominates: Final Report

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

Jacob, Bruce L.

Over the past three years in this project, what we have observed is that the primary reason for data movement in large-scale systems is that the per-node capacity is not large enough—i.e., one of the solutions to the data-movement problem (certainly not the only solution that is required, but a significant one nonetheless) is to increase per-node capacity so that inter-node traffic is reduced. This unfortunately is not as simple as it sounds. Today’s main memory systems for datacenters, enterprise computing systems, and supercomputers, fail to provide high per-socket capacity [Dirik & Jacob 2009; Cooper-Balis et al. 2012], except atmore » extremely high price points (factors of 10–100x the cost/bit of consumer main-memory systems) [Stokes 2008]. The reason is that our choice of technology for today’s main memory systems—i.e., DRAM, which we have used as a main-memory technology since the 1970s [Jacob et al. 2007]—can no longer keep up with our needs for density and price per bit. Main memory systems have always been built from the cheapest, densest, lowest-power memory technology available, and DRAM is no longer the cheapest, the densest, nor the lowest-power storage technology out there. It is now time for DRAM to go the way that SRAM went: move out of the way for a cheaper, slower, denser storage technology, and become a cache instead. This inflection point has happened before, in the context of SRAM yielding to DRAM. There was once a time that SRAM was the storage technology of choice for all main memories [Tomasulo 1967; Thornton 1970; Kidder 1981]. However, once DRAM hit volume production in the 1970s and 80s, it supplanted SRAM as a main memory technology because it was cheaper, and it was denser. It also happened to be lower power, but that was not the primary consideration of the day. At the time, it was recognized that DRAM was much slower than SRAM, but it was only at the supercomputer level (For instance the Cray X-MP in the 1980s and its follow-on, the Cray Y-MP, in the 1990s) that could one afford to build ever- larger main memories out of SRAM—the reasoning for moving to DRAM was that an appropriately designed memory hierarchy, built of DRAM as main memory and SRAM as a cache, would approach the performance of SRAM, at the price-per-bit of DRAM [Mashey 1999]. Today it is quite clear that, were one to build an entire multi-gigabyte main memory out of SRAM instead of DRAM, one could improve the performance of almost any computer system by up to an order of magnitude—but this option is not even considered, because to build that system would be prohibitively expensive. It is now time to revisit the same design choice in the context of modern technologies and modern systems. For reasons both technical and economic, we can no longer afford to build ever-larger main memory systems out of DRAM. Flash memory, on the other hand, is significantly cheaper and denser than DRAM and therefore should take its place. While it is true that flash is significantly slower than DRAM, one can afford to build much larger main memories out of flash than out of DRAM, and we show that an appropriately designed memory hierarchy, built of flash as main memory and DRAM as a cache, will approach the performance of DRAM, at the price-per-bit of flash. In our studies as part of this project, we have investigated Non-Volatile Main Memory (NVMM), a new main-memory architecture for large-scale computing systems, one that is specifically designed to address the weaknesses described previously. In particular, it provides the following features: non-volatility: The bulk of the storage is comprised of NAND flash, and in this organization DRAM is used only as a cache, not as main memory. Furthermore, the flash is journaled, which means that operations such as checkpoint/restore are already built into the system. 1+ terabytes of storage per socket: SSDs and DRAM DIMMs have roughly the same form factor (several square inches of PCB surface area), and terabyte SSDs are now commonplace. performance approaching that of DRAM: DRAM is used as a cache to the flash system. price-per-bit approaching that of NAND: Flash is currently well under $0.50 per gigabyte; DDR3 SDRAM is currently just over $10 per gigabyte [Newegg 2014]. Even today, one can build an easily affordable main memory system with a terabyte or more of NAND storage per CPU socket (which would be extremely expensive were one to use DRAM), and our cycle- accurate, full-system experiments show that this can be done at a performance point that lies within a factor of two of DRAM.« less

The default mode network and the working memory network are not anti-correlated during all phases of a working memory task.

PubMed

Piccoli, Tommaso; Valente, Giancarlo; Linden, David E J; Re, Marta; Esposito, Fabrizio; Sack, Alexander T; Di Salle, Francesco

2015-01-01

The default mode network and the working memory network are known to be anti-correlated during sustained cognitive processing, in a load-dependent manner. We hypothesized that functional connectivity among nodes of the two networks could be dynamically modulated by task phases across time. To address the dynamic links between default mode network and the working memory network, we used a delayed visuo-spatial working memory paradigm, which allowed us to separate three different phases of working memory (encoding, maintenance, and retrieval), and analyzed the functional connectivity during each phase within and between the default mode network and the working memory network networks. We found that the two networks are anti-correlated only during the maintenance phase of working memory, i.e. when attention is focused on a memorized stimulus in the absence of external input. Conversely, during the encoding and retrieval phases, when the external stimulation is present, the default mode network is positively coupled with the working memory network, suggesting the existence of a dynamically switching of functional connectivity between "task-positive" and "task-negative" brain networks. Our results demonstrate that the well-established dichotomy of the human brain (anti-correlated networks during rest and balanced activation-deactivation during cognition) has a more nuanced organization than previously thought and engages in different patterns of correlation and anti-correlation during specific sub-phases of a cognitive task. This nuanced organization reinforces the hypothesis of a direct involvement of the default mode network in cognitive functions, as represented by a dynamic rather than static interaction with specific task-positive networks, such as the working memory network.

The Default Mode Network and the Working Memory Network Are Not Anti-Correlated during All Phases of a Working Memory Task

PubMed Central

Piccoli, Tommaso; Valente, Giancarlo; Linden, David E. J.; Re, Marta; Esposito, Fabrizio; Sack, Alexander T.; Salle, Francesco Di

2015-01-01

Introduction The default mode network and the working memory network are known to be anti-correlated during sustained cognitive processing, in a load-dependent manner. We hypothesized that functional connectivity among nodes of the two networks could be dynamically modulated by task phases across time. Methods To address the dynamic links between default mode network and the working memory network, we used a delayed visuo-spatial working memory paradigm, which allowed us to separate three different phases of working memory (encoding, maintenance, and retrieval), and analyzed the functional connectivity during each phase within and between the default mode network and the working memory network networks. Results We found that the two networks are anti-correlated only during the maintenance phase of working memory, i.e. when attention is focused on a memorized stimulus in the absence of external input. Conversely, during the encoding and retrieval phases, when the external stimulation is present, the default mode network is positively coupled with the working memory network, suggesting the existence of a dynamically switching of functional connectivity between “task-positive” and “task-negative” brain networks. Conclusions Our results demonstrate that the well-established dichotomy of the human brain (anti-correlated networks during rest and balanced activation-deactivation during cognition) has a more nuanced organization than previously thought and engages in different patterns of correlation and anti-correlation during specific sub-phases of a cognitive task. This nuanced organization reinforces the hypothesis of a direct involvement of the default mode network in cognitive functions, as represented by a dynamic rather than static interaction with specific task-positive networks, such as the working memory network. PMID:25848951

Cholinergic modulation of cognitive processing: insights drawn from computational models

PubMed Central

Newman, Ehren L.; Gupta, Kishan; Climer, Jason R.; Monaghan, Caitlin K.; Hasselmo, Michael E.

2012-01-01

Acetylcholine plays an important role in cognitive function, as shown by pharmacological manipulations that impact working memory, attention, episodic memory, and spatial memory function. Acetylcholine also shows striking modulatory influences on the cellular physiology of hippocampal and cortical neurons. Modeling of neural circuits provides a framework for understanding how the cognitive functions may arise from the influence of acetylcholine on neural and network dynamics. We review the influences of cholinergic manipulations on behavioral performance in working memory, attention, episodic memory, and spatial memory tasks, the physiological effects of acetylcholine on neural and circuit dynamics, and the computational models that provide insight into the functional relationships between the physiology and behavior. Specifically, we discuss the important role of acetylcholine in governing mechanisms of active maintenance in working memory tasks and in regulating network dynamics important for effective processing of stimuli in attention and episodic memory tasks. We also propose that theta rhythm plays a crucial role as an intermediary between the physiological influences of acetylcholine and behavior in episodic and spatial memory tasks. We conclude with a synthesis of the existing modeling work and highlight future directions that are likely to be rewarding given the existing state of the literature for both empiricists and modelers. PMID:22707936

Incorporation of memory effects in coarse-grained modeling via the Mori-Zwanzig formalism

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

Li, Zhen; Bian, Xin; Karniadakis, George Em, E-mail: george-karniadakis@brown.edu

2015-12-28

The Mori-Zwanzig formalism for coarse-graining a complex dynamical system typically introduces memory effects. The Markovian assumption of delta-correlated fluctuating forces is often employed to simplify the formulation of coarse-grained (CG) models and numerical implementations. However, when the time scales of a system are not clearly separated, the memory effects become strong and the Markovian assumption becomes inaccurate. To this end, we incorporate memory effects into CG modeling by preserving non-Markovian interactions between CG variables, and the memory kernel is evaluated directly from microscopic dynamics. For a specific example, molecular dynamics (MD) simulations of star polymer melts are performed while themore » corresponding CG system is defined by grouping many bonded atoms into single clusters. Then, the effective interactions between CG clusters as well as the memory kernel are obtained from the MD simulations. The constructed CG force field with a memory kernel leads to a non-Markovian dissipative particle dynamics (NM-DPD). Quantitative comparisons between the CG models with Markovian and non-Markovian approximations indicate that including the memory effects using NM-DPD yields similar results as the Markovian-based DPD if the system has clear time scale separation. However, for systems with small separation of time scales, NM-DPD can reproduce correct short-time properties that are related to how the system responds to high-frequency disturbances, which cannot be captured by the Markovian-based DPD model.« less

HIV dynamics linked to memory CD4+ T cell homeostasis.

PubMed

Murray, John M; Zaunders, John; Emery, Sean; Cooper, David A; Hey-Nguyen, William J; Koelsch, Kersten K; Kelleher, Anthony D

2017-01-01

The dynamics of latent HIV is linked to infection and clearance of resting memory CD4+ T cells. Infection also resides within activated, non-dividing memory cells and can be impacted by antigen-driven and homeostatic proliferation despite suppressive antiretroviral therapy (ART). We investigated whether plasma viral level (pVL) and HIV DNA dynamics could be explained by HIV's impact on memory CD4+ T cell homeostasis. Median total, 2-LTR and integrated HIV DNA levels per μL of peripheral blood, for 8 primary (PHI) and 8 chronic HIV infected (CHI) individuals enrolled on a raltegravir (RAL) based regimen, exhibited greatest changes over the 1st year of ART. Dynamics slowed over the following 2 years so that total HIV DNA levels were equivalent to reported values for individuals after 10 years of ART. The mathematical model reproduced the multiphasic dynamics of pVL, and levels of total, 2-LTR and integrated HIV DNA in both PHI and CHI over 3 years of ART. Under these simulations, residual viremia originated from reactivated latently infected cells where most of these cells arose from clonal expansion within the resting phenotype. Since virion production from clonally expanded cells will not be affected by antiretroviral drugs, simulations of ART intensification had little impact on pVL. HIV DNA decay over the first year of ART followed the loss of activated memory cells (120 day half-life) while the 5.9 year half-life of total HIV DNA after this point mirrored the slower decay of resting memory cells. Simulations had difficulty reproducing the fast early HIV DNA dynamics, including 2-LTR levels peaking at week 12, and the later slow loss of total and 2-LTR HIV DNA, suggesting some ongoing infection. In summary, our modelling indicates that much of the dynamical behavior of HIV can be explained by its impact on memory CD4+ T cell homeostasis.

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…

The Temporal Signature of Memories: Identification of a General Mechanism for Dynamic Memory Replay in Humans

PubMed Central

Michelmann, Sebastian; Bowman, Howard; Hanslmayr, Simon

2016-01-01

Reinstatement of dynamic memories requires the replay of neural patterns that unfold over time in a similar manner as during perception. However, little is known about the mechanisms that guide such a temporally structured replay in humans, because previous studies used either unsuitable methods or paradigms to address this question. Here, we overcome these limitations by developing a new analysis method to detect the replay of temporal patterns in a paradigm that requires participants to mentally replay short sound or video clips. We show that memory reinstatement is accompanied by a decrease of low-frequency (8 Hz) power, which carries a temporal phase signature of the replayed stimulus. These replay effects were evident in the visual as well as in the auditory domain and were localized to sensory-specific regions. These results suggest low-frequency phase to be a domain-general mechanism that orchestrates dynamic memory replay in humans. PMID:27494601

Memory effects on mechanically stimulated electric signal; diversification of stimuli impact on material memory and comments on the observed features

NASA Astrophysics Data System (ADS)

Kyriazis, Panagiotis; Stavrakas, Ilias; Anastasiadis, Cimon; Triantis, Dimos; Stonham, John

2010-05-01

Memory is defined as the ability of marble and generally of brittle geomaterials to retain 'imprints' from previous treatments and to reproduce information about these treatments under certain conditions, by analogy to the memory of human beings. Memory effects have been observed in the evolution of a variety of physical properties like the acoustic emissions of brittle materials during fracture. The existence of memory effects for the mechanically stimulated electric signal, either by Pressure (PSC) or by Bending (BSC), is examined in this work, alongside with an attempt to distinguish between the two different manifestations of 'memory' based on the electrification mechanism that is triggered at different levels of externally applied load on samples. Having identified two main mechanisms (i.e. the dynamic and the cracking) and following the human memory model, we suggest the separation of memory of a material specimen into two levels i.e. the short or temporary and long or permanent memory. For the observation and analysis of the short memory of brittle materials we have conducted experiments using the PSC technique in marble specimens. The materials are imposed to cyclic stepwise loading of the same level, scheme and direction (axial stress - unchanged position of material) in order to comply with the conditions that are proposed as suitable for memory effects study by other researchers. We have also conducted experimental tests of cyclic high level stepwise loading on amphibolite rock specimens in order to verify and study the existence of permanent memory effects. Modelling the signal recordings and studying the effects of memory on the signals, we have identified certain trends manifestation for the two types of memory that are summarised to the following points. (a) Both types of memory influence the PSC peaks evolution (exponential decrease) in cyclic loadings of the same level. (b) Permanent memory cannot be erased and affects PSC signal permanently and severely. (c) The short memory has temporary influence on the PSC signal and the impacts on the signal are milder. The main properties of the PSC signal, which are affected by the existence of memory, converge to an inertial attitude of the material to the same stimuli and they are quite common with the properties of other fracture induced signals (i.e. AE). Namely, they are the following: (a) The PSC peak evolution over loading cycles is a changing signal property either in the case of permanent or of temporary memory, with respect to the time interval between events, especially in the latter case. (b) The decrease of the dissipated electric energy during cyclic loading tests. (c) The PSC slower relaxation in each loading, quantified by the relaxation process parameters evolution. (d) The PSC signal response delay in each loading cycle increase The existence of memory effects on the mechanically stimulated electric signal is an indication that information about the deformation history (paleostresses) of the material reside inside the material. Under certain conditions such information can be revealed by analysis of the PSC signal response to specific external mechanical triggering.

Dynamic modulation of innate immunity programming and memory.

PubMed

Yuan, Ruoxi; Li, Liwu

2016-01-01

Recent progress harkens back to the old theme of immune memory, except this time in the area of innate immunity, to which traditional paradigm only prescribes a rudimentary first-line defense function with no memory. However, both in vitro and in vivo studies reveal that innate leukocytes may adopt distinct activation states such as priming, tolerance, and exhaustion, depending upon the history of prior challenges. The dynamic programming and potential memory of innate leukocytes may have far-reaching consequences in health and disease. This review aims to provide some salient features of innate programing and memory, patho-physiological consequences, underlying mechanisms, and current pressing issues.

Neural basis for dynamic updating of object representation in visual working memory.

PubMed

Takahama, Sachiko; Miyauchi, Satoru; Saiki, Jun

2010-02-15

In real world, objects have multiple features and change dynamically. Thus, object representations must satisfy dynamic updating and feature binding. Previous studies have investigated the neural activity of dynamic updating or feature binding alone, but not both simultaneously. We investigated the neural basis of feature-bound object representation in a dynamically updating situation by conducting a multiple object permanence tracking task, which required observers to simultaneously process both the maintenance and dynamic updating of feature-bound objects. Using an event-related design, we separated activities during memory maintenance and change detection. In the search for regions showing selective activation in dynamic updating of feature-bound objects, we identified a network during memory maintenance that was comprised of the inferior precentral sulcus, superior parietal lobule, and middle frontal gyrus. In the change detection period, various prefrontal regions, including the anterior prefrontal cortex, were activated. In updating object representation of dynamically moving objects, the inferior precentral sulcus closely cooperates with a so-called "frontoparietal network", and subregions of the frontoparietal network can be decomposed into those sensitive to spatial updating and feature binding. The anterior prefrontal cortex identifies changes in object representation by comparing memory and perceptual representations rather than maintaining object representations per se, as previously suggested. Copyright 2009 Elsevier Inc. All rights reserved.

Extending the Memory of Microcomputers

NASA Technical Reports Server (NTRS)

Wiker, G. A.

1984-01-01

Memory increased while retaining real-time capabilities. Extra memory capacity added to microprocessor without increasing memory address length and special transfer instructions by dedicating block of space in main memory to hold addresses of locations in extra memory.

Working-Memory Load and Temporal Myopia in Dynamic Decision Making

ERIC Educational Resources Information Center

Worthy, Darrell A.; Otto, A. Ross; Maddox, W. Todd

2012-01-01

We examined the role of working memory (WM) in dynamic decision making by having participants perform decision-making tasks under single-task or dual-task conditions. In 2 experiments participants performed dynamic decision-making tasks in which they chose 1 of 2 options on each trial. The decreasing option always gave a larger immediate reward…

Neuronal DNA Methyltransferases: Epigenetic Mediators between Synaptic Activity and Gene Expression?

PubMed Central

Bayraktar, Gonca; Kreutz, Michael R.

2017-01-01

DNMT3A and 3B are the main de novo DNA methyltransferases (DNMTs) in the brain that introduce new methylation marks to non-methylated DNA in postmitotic neurons. DNA methylation is a key epigenetic mark that is known to regulate important cellular processes in neuronal development and brain plasticity. Accumulating evidence disclosed rapid and dynamic changes in DNA methylation of plasticity-relevant genes that are important for learning and memory formation. To understand how DNMTs contribute to brain function and how they are regulated by neuronal activity is a prerequisite for a deeper appreciation of activity-dependent gene expression in health and disease. This review discusses the functional role of de novo methyltransferases and in particular DNMT3A1 in the adult brain with special emphasis on synaptic plasticity, memory formation, and brain disorders. PMID:28513272

Individual Differences in Dynamic Functional Brain Connectivity across the Human Lifespan.

PubMed

Davison, Elizabeth N; Turner, Benjamin O; Schlesinger, Kimberly J; Miller, Michael B; Grafton, Scott T; Bassett, Danielle S; Carlson, Jean M

2016-11-01

Individual differences in brain functional networks may be related to complex personal identifiers, including health, age, and ability. Dynamic network theory has been used to identify properties of dynamic brain function from fMRI data, but the majority of analyses and findings remain at the level of the group. Here, we apply hypergraph analysis, a method from dynamic network theory, to quantify individual differences in brain functional dynamics. Using a summary metric derived from the hypergraph formalism-hypergraph cardinality-we investigate individual variations in two separate, complementary data sets. The first data set ("multi-task") consists of 77 individuals engaging in four consecutive cognitive tasks. We observe that hypergraph cardinality exhibits variation across individuals while remaining consistent within individuals between tasks; moreover, the analysis of one of the memory tasks revealed a marginally significant correspondence between hypergraph cardinality and age. This finding motivated a similar analysis of the second data set ("age-memory"), in which 95 individuals, aged 18-75, performed a memory task with a similar structure to the multi-task memory task. With the increased age range in the age-memory data set, the correlation between hypergraph cardinality and age correspondence becomes significant. We discuss these results in the context of the well-known finding linking age with network structure, and suggest that hypergraph analysis should serve as a useful tool in furthering our understanding of the dynamic network structure of the brain.

Tests of the Dynamic Field Theory and The Spatial Precision Hypothesis: Capturing a Qualitative Developmental Transition in Spatial Working Memory

ERIC Educational Resources Information Center

Schutte, Anne R.; Spencer, John P.

2009-01-01

This study tested a dynamic field theory (DFT) of spatial working memory and an associated spatial precision hypothesis (SPH). Between 3 and 6 years of age, there is a qualitative shift in how children use reference axes to remember locations: 3-year-olds' spatial recall responses are biased toward reference axes after short memory delays, whereas…

Synapsin Is Selectively Required for Anesthesia-Sensitive Memory

ERIC Educational Resources Information Center

Knapek, Stephan; Gerber, Bertram; Tanimoto, Hiromu

2010-01-01

Odor-shock memory in "Drosophila melanogaster" consists of heterogeneous components each with different dynamics. We report that a null mutant for the evolutionarily conserved synaptic protein Synapsin entails a memory deficit selectively in early memory, leaving later memory as well as sensory motor function unaffected. Notably, a consolidated…

Effect of water table dynamics on land surface hydrologic memory

NASA Astrophysics Data System (ADS)

Lo, Min-Hui; Famiglietti, James S.

2010-11-01

The representation of groundwater dynamics in land surface models has received considerable attention in recent years. Most studies have found that soil moisture increases after adding a groundwater component because of the additional supply of water to the root zone. However, the effect of groundwater on land surface hydrologic memory (persistence) has not been explored thoroughly. In this study we investigate the effect of water table dynamics on National Center for Atmospheric Research Community Land Model hydrologic simulations in terms of land surface hydrologic memory. Unlike soil water or evapotranspiration, results show that land surface hydrologic memory does not always increase after adding a groundwater component. In regions where the water table level is intermediate, land surface hydrologic memory can even decrease, which occurs when soil moisture and capillary rise from groundwater are not in phase with each other. Further, we explore the hypothesis that in addition to atmospheric forcing, groundwater variations may also play an important role in affecting land surface hydrologic memory. Analyses show that feedbacks of groundwater on land surface hydrologic memory can be positive, negative, or neutral, depending on water table dynamics. In regions where the water table is shallow, the damping process of soil moisture variations by groundwater is not significant, and soil moisture variations are mostly controlled by random noise from atmospheric forcing. In contrast, in regions where the water table is very deep, capillary fluxes from groundwater are small, having limited potential to affect soil moisture variations. Therefore, a positive feedback of groundwater to land surface hydrologic memory is observed in a transition zone between deep and shallow water tables, where capillary fluxes act as a buffer by reducing high-frequency soil moisture variations resulting in longer land surface hydrologic memory.

Dynamics of Conflicts in Wikipedia

PubMed Central

Yasseri, Taha; Sumi, Robert; Rung, András; Kornai, András; Kertész, János

2012-01-01

In this work we study the dynamical features of editorial wars in Wikipedia (WP). Based on our previously established algorithm, we build up samples of controversial and peaceful articles and analyze the temporal characteristics of the activity in these samples. On short time scales, we show that there is a clear correspondence between conflict and burstiness of activity patterns, and that memory effects play an important role in controversies. On long time scales, we identify three distinct developmental patterns for the overall behavior of the articles. We are able to distinguish cases eventually leading to consensus from those cases where a compromise is far from achievable. Finally, we analyze discussion networks and conclude that edit wars are mainly fought by few editors only. PMID:22745683

Neural dynamics associated with semantic and episodic memory for faces: evidence from multiple frequency bands.

PubMed

Zion-Golumbic, Elana; Kutas, Marta; Bentin, Shlomo

2010-02-01

Prior semantic knowledge facilitates episodic recognition memory for faces. To examine the neural manifestation of the interplay between semantic and episodic memory, we investigated neuroelectric dynamics during the creation (study) and the retrieval (test) of episodic memories for famous and nonfamous faces. Episodic memory effects were evident in several EEG frequency bands: theta (4-8 Hz), alpha (9-13 Hz), and gamma (40-100 Hz). Activity in these bands was differentially modulated by preexisting semantic knowledge and by episodic memory, implicating their different functional roles in memory. More specifically, theta activity and alpha suppression were larger for old compared to new faces at test regardless of fame, but were both larger for famous faces during study. This pattern of selective semantic effects suggests that the theta and alpha responses, which are primarily associated with episodic memory, reflect utilization of semantic information only when it is beneficial for task performance. In contrast, gamma activity decreased between the first (study) and second (test) presentation of a face, but overall was larger for famous than nonfamous faces. Hence, the gamma rhythm seems to be primarily related to activation of preexisting neural representations that may contribute to the formation of new episodic traces. Taken together, these data provide new insights into the complex interaction between semantic and episodic memory for faces and the neural dynamics associated with mnemonic processes.

The death of recency: Relationship between end-state comfort and serial position effects in serial recall: Logan and Fischman (2011) revisited.

PubMed

Logan, Samuel W; Fischman, Mark G

2015-12-01

Two experiments examined the dynamic interaction between cognitive resources in short-term memory and bimanual object manipulation by extending recent research by Logan and Fischman (2011). In Experiment 1, 16 participants completed a bimanual end-state comfort task and a memory task requiring serial recall of 12 words or pictures. The end-state comfort task involved moving two glasses between two shelves. Participants viewed the items, performed the end-state comfort task, and then serially recalled the items. Recall was evaluated by the presence or absence of primacy and recency effects. The end-state comfort effect (ESCE) was assessed by the percentage of initial hand positions that allowed the hands to end comfortably. The main findings indicated that the ESCE was disrupted; the primacy effect remained intact; and the recency effect disappeared regardless of the type of memory item recalled. In Experiment 2, 16 participants viewed six items, performed an end-state comfort task, viewed another six items, and then serially recalled all 12 items. Results were essentially the same as in Experiment 1. Findings suggest that executing a bimanual end-state comfort task, regardless of when it is completed during a memory task, diminishes the recency effect irrespective of the type of memory item. Copyright © 2015 Elsevier B.V. All rights reserved.

Memory and Depressive Symptoms Are Dynamically Linked among Married Couples: Longitudinal Evidence from the AHEAD Study

ERIC Educational Resources Information Center

Gerstorf, Denis; Hoppmann, Christiane A.; Kadlec, Kelly M.; McArdle, John J.

2009-01-01

This study examined dyadic interrelations between episodic memory and depressive symptom trajectories of change in old and advanced old age. The authors applied dynamic models to 10-year incomplete longitudinal data of initially 1,599 married couples from the study of Asset and Health Dynamics Among the Oldest Old (M[subscript age] = 75 years at…

A New Role for Attentional Corticopetal Acetylcholine in Cortical Memory Dynamics

NASA Astrophysics Data System (ADS)

Fujii, Hiroshi; Kanamaru, Takashi; Aihara, Kazuyuki; Tsuda, Ichiro

2011-09-01

Although the role of corticopetal acetylcholine (ACh) in higher cognitive functions is increasingly recognized, the questions as (1) how ACh works in attention(s), memory dynamics and cortical state transitions, and also (2) why and how loss of ACh is involved in dysfunctions such as visual hallucinations in dementia with Lewy bodies and deficit of attention(s), are not well understood. From the perspective of a dynamical systems viewpoint, we hypothesize that transient ACh released under top-down attention serves to temporarily invoke attractor-like memories, while a background level of ACh reverses this process returning the dynamical nature of the memory structure back to attractor ruins (quasi-attractors). In fact, transient ACh loosens inhibitions of py ramidal neurons (PYRs) by P V+ fas t spiking (FS) i nterneurons, while a baseline ACh recovers inhibitory actions of P V+ FS. Attentional A Ch thus dynamically modifies brain's connectivity. Th e core of this process is in the depression of GABAergic inhibitory currents in PYRs due to muscarinic (probably M2 subtype) presyn aptic effects on GABAergic synapses of PV+ FS neurons

Scaling laws describe memories of host-pathogen riposte in the HIV population.

PubMed

Barton, John P; Kardar, Mehran; Chakraborty, Arup K

2015-02-17

The enormous genetic diversity and mutability of HIV has prevented effective control of this virus by natural immune responses or vaccination. Evolution of the circulating HIV population has thus occurred in response to diverse, ultimately ineffective, immune selection pressures that randomly change from host to host. We show that the interplay between the diversity of human immune responses and the ways that HIV mutates to evade them results in distinct sets of sequences defined by similar collectively coupled mutations. Scaling laws that relate these sets of sequences resemble those observed in linguistics and other branches of inquiry, and dynamics reminiscent of neural networks are observed. Like neural networks that store memories of past stimulation, the circulating HIV population stores memories of host-pathogen combat won by the virus. We describe an exactly solvable model that captures the main qualitative features of the sets of sequences and a simple mechanistic model for the origin of the observed scaling laws. Our results define collective mutational pathways used by HIV to evade human immune responses, which could guide vaccine design.

The derivation and approximation of coarse-grained dynamics from Langevin dynamics

NASA Astrophysics Data System (ADS)

Ma, Lina; Li, Xiantao; Liu, Chun

2016-11-01

We present a derivation of a coarse-grained description, in the form of a generalized Langevin equation, from the Langevin dynamics model that describes the dynamics of bio-molecules. The focus is placed on the form of the memory kernel function, the colored noise, and the second fluctuation-dissipation theorem that connects them. Also presented is a hierarchy of approximations for the memory and random noise terms, using rational approximations in the Laplace domain. These approximations offer increasing accuracy. More importantly, they eliminate the need to evaluate the integral associated with the memory term at each time step. Direct sampling of the colored noise can also be avoided within this framework. Therefore, the numerical implementation of the generalized Langevin equation is much more efficient.

‘Activity-silent’ working memory in prefrontal cortex: a dynamic coding framework

PubMed Central

Stokes, Mark G.

2015-01-01

Working memory (WM) provides the functional backbone to high-level cognition. Maintenance in WM is often assumed to depend on the stationary persistence of neural activity patterns that represent memory content. However, accumulating evidence suggests that persistent delay activity does not always accompany WM maintenance but instead seems to wax and wane as a function of the current task relevance of memoranda. Furthermore, new methods for measuring and analysing population-level patterns show that activity states are highly dynamic. At first glance, these dynamics seem at odds with the very nature of WM. How can we keep a stable thought in mind while brain activity is constantly changing? This review considers how neural dynamics might be functionally important for WM maintenance. PMID:26051384

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

NASA Astrophysics Data System (ADS)

Comlekoglu, T.; Weinberg, S. H.

2017-09-01

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

The dynamic nature of the reconsolidation process and its boundary conditions: Evidence based on human tests.

PubMed

Fernández, Rodrigo S; Bavassi, Luz; Forcato, Cecilia; Pedreira, María E

2016-04-01

The reconsolidation process is the mechanism by which the strength and/or content of consolidated memories are updated. This process is triggered by the presentation of a reminder (training cues). It is not always possible to trigger the reconsolidation process. For example, memory age and strength are boundary conditions for the reconsolidation process. Here, we investigated the dynamic changes in these conditions. We propose that the boundary conditions of the reconsolidation process are not fixed and vary as a consequence of the interaction between memory features and reminder characteristics. To modify memory properties, participants received a threatening social protocol that improves memory acquisition or a control condition (fake, without social interaction) prior to learning pairs of meaningless syllables. To determine whether a strong young or old declarative memory undergoes the reconsolidation process, we used an interference task (a second list of pairs of meaningless syllables) to disrupt memory re-stabilization. To assess whether the older memory could be strengthened, we repeated the triggering of reconsolidation. Strong young or old memories modulated by a threatening experience could be interfered during reconsolidation and updated (strengthened) by reconsolidation. Rather than being fixed, boundary conditions vary according to the memory features (strong memory), which indicates the dynamic nature of the reconsolidation process. Our findings demonstrate that it is possible to modify these limits by recruiting the reconsolidation process and making it functionally operative again. This novel scenario opens the possibility to new therapeutically approaches that take into account the reconsolidation process. Copyright © 2016 Elsevier Inc. All rights reserved.

Dynamic Organization of Hierarchical Memories

PubMed Central

Kurikawa, Tomoki; Kaneko, Kunihiko

2016-01-01

In the brain, external objects are categorized in a hierarchical way. Although it is widely accepted that objects are represented as static attractors in neural state space, this view does not take account interaction between intrinsic neural dynamics and external input, which is essential to understand how neural system responds to inputs. Indeed, structured spontaneous neural activity without external inputs is known to exist, and its relationship with evoked activities is discussed. Then, how categorical representation is embedded into the spontaneous and evoked activities has to be uncovered. To address this question, we studied bifurcation process with increasing input after hierarchically clustered associative memories are learned. We found a “dynamic categorization”; neural activity without input wanders globally over the state space including all memories. Then with the increase of input strength, diffuse representation of higher category exhibits transitions to focused ones specific to each object. The hierarchy of memories is embedded in the transition probability from one memory to another during the spontaneous dynamics. With increased input strength, neural activity wanders over a narrower state space including a smaller set of memories, showing more specific category or memory corresponding to the applied input. Moreover, such coarse-to-fine transitions are also observed temporally during transient process under constant input, which agrees with experimental findings in the temporal cortex. These results suggest the hierarchy emerging through interaction with an external input underlies hierarchy during transient process, as well as in the spontaneous activity. PMID:27618549

Optimal Recall from Bounded Metaplastic Synapses: Predicting Functional Adaptations in Hippocampal Area CA3

PubMed Central

Savin, Cristina; Dayan, Peter; Lengyel, Máté

2014-01-01

A venerable history of classical work on autoassociative memory has significantly shaped our understanding of several features of the hippocampus, and most prominently of its CA3 area, in relation to memory storage and retrieval. However, existing theories of hippocampal memory processing ignore a key biological constraint affecting memory storage in neural circuits: the bounded dynamical range of synapses. Recent treatments based on the notion of metaplasticity provide a powerful model for individual bounded synapses; however, their implications for the ability of the hippocampus to retrieve memories well and the dynamics of neurons associated with that retrieval are both unknown. Here, we develop a theoretical framework for memory storage and recall with bounded synapses. We formulate the recall of a previously stored pattern from a noisy recall cue and limited-capacity (and therefore lossy) synapses as a probabilistic inference problem, and derive neural dynamics that implement approximate inference algorithms to solve this problem efficiently. In particular, for binary synapses with metaplastic states, we demonstrate for the first time that memories can be efficiently read out with biologically plausible network dynamics that are completely constrained by the synaptic plasticity rule, and the statistics of the stored patterns and of the recall cue. Our theory organises into a coherent framework a wide range of existing data about the regulation of excitability, feedback inhibition, and network oscillations in area CA3, and makes novel and directly testable predictions that can guide future experiments. PMID:24586137

Hierarchical Chunking of Sequential Memory on Neuromorphic Architecture with Reduced Synaptic Plasticity

PubMed Central

Li, Guoqi; Deng, Lei; Wang, Dong; Wang, Wei; Zeng, Fei; Zhang, Ziyang; Li, Huanglong; Song, Sen; Pei, Jing; Shi, Luping

2016-01-01

Chunking refers to a phenomenon whereby individuals group items together when performing a memory task to improve the performance of sequential memory. In this work, we build a bio-plausible hierarchical chunking of sequential memory (HCSM) model to explain why such improvement happens. We address this issue by linking hierarchical chunking with synaptic plasticity and neuromorphic engineering. We uncover that a chunking mechanism reduces the requirements of synaptic plasticity since it allows applying synapses with narrow dynamic range and low precision to perform a memory task. We validate a hardware version of the model through simulation, based on measured memristor behavior with narrow dynamic range in neuromorphic circuits, which reveals how chunking works and what role it plays in encoding sequential memory. Our work deepens the understanding of sequential memory and enables incorporating it for the investigation of the brain-inspired computing on neuromorphic architecture. PMID:28066223

APOLLO II

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

Sanchez, R.; Mondot, J.; Stankovski, Z.

1988-11-01

APOLLO II is a new, multigroup transport code under development at the Commissariat a l'Energie Atomique. The code has a modular structure and uses sophisticated software for data structuralization, dynamic memory management, data storage, and user macrolanguage. This paper gives an overview of the main methods used in the code for (a) multidimensional collision probability calculations, (b) leakage calculations, and (c) homogenization procedures. Numerical examples are given to demonstrate the potential of the modular structure of the code and the novel multilevel flat-flux representation used in the calculation of the collision probabilities.

Multimodal properties and dynamics of gradient echo quantum memory.

PubMed

Hétet, G; Longdell, J J; Sellars, M J; Lam, P K; Buchler, B C

2008-11-14

We investigate the properties of a recently proposed gradient echo memory (GEM) scheme for information mapping between optical and atomic systems. We show that GEM can be described by the dynamic formation of polaritons in k space. This picture highlights the flexibility and robustness with regards to the external control of the storage process. Our results also show that, as GEM is a frequency-encoding memory, it can accurately preserve the shape of signals that have large time-bandwidth products, even at moderate optical depths. At higher optical depths, we show that GEM is a high fidelity multimode quantum memory.

Adaptations in Electronic Structure Calculations in Heterogeneous Environments

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

Talamudupula, Sai

Modern quantum chemistry deals with electronic structure calculations of unprecedented complexity and accuracy. They demand full power of high-performance computing and must be in tune with the given architecture for superior e ciency. To make such applications resourceaware, it is desirable to enable their static and dynamic adaptations using some external software (middleware), which may monitor both system availability and application needs, rather than mix science with system-related calls inside the application. The present work investigates scienti c application interlinking with middleware based on the example of the computational chemistry package GAMESS and middleware NICAN. The existing synchronous model ismore » limited by the possible delays due to the middleware processing time under the sustainable runtime system conditions. Proposed asynchronous and hybrid models aim at overcoming this limitation. When linked with NICAN, the fragment molecular orbital (FMO) method is capable of adapting statically and dynamically its fragment scheduling policy based on the computing platform conditions. Signi cant execution time and throughput gains have been obtained due to such static adaptations when the compute nodes have very di erent core counts. Dynamic adaptations are based on the main memory availability at run time. NICAN prompts FMO to postpone scheduling certain fragments, if there is not enough memory for their immediate execution. Hence, FMO may be able to complete the calculations whereas without such adaptations it aborts.« less

Task modulates functional connectivity networks in free viewing behavior.

PubMed

Seidkhani, Hossein; Nikolaev, Andrey R; Meghanathan, Radha Nila; Pezeshk, Hamid; Masoudi-Nejad, Ali; van Leeuwen, Cees

2017-10-01

In free visual exploration, eye-movement is immediately followed by dynamic reconfiguration of brain functional connectivity. We studied the task-dependency of this process in a combined visual search-change detection experiment. Participants viewed two (nearly) same displays in succession. First time they had to find and remember multiple targets among distractors, so the ongoing task involved memory encoding. Second time they had to determine if a target had changed in orientation, so the ongoing task involved memory retrieval. From multichannel EEG recorded during 200 ms intervals time-locked to fixation onsets, we estimated the functional connectivity using a weighted phase lag index at the frequencies of theta, alpha, and beta bands, and derived global and local measures of the functional connectivity graphs. We found differences between both memory task conditions for several network measures, such as mean path length, radius, diameter, closeness and eccentricity, mainly in the alpha band. Both the local and the global measures indicated that encoding involved a more segregated mode of operation than retrieval. These differences arose immediately after fixation onset and persisted for the entire duration of the lambda complex, an evoked potential commonly associated with early visual perception. We concluded that encoding and retrieval differentially shape network configurations involved in early visual perception, affecting the way the visual input is processed at each fixation. These findings demonstrate that task requirements dynamically control the functional connectivity networks involved in early visual perception. Copyright © 2017 Elsevier Inc. All rights reserved.

Memory versus irreversibility in the thermal densification of amorphous glasses

NASA Astrophysics Data System (ADS)

Ovadyahu, Z.

2017-06-01

We report on dynamic effects associated with thermally annealing amorphous indium-oxide films. In this process, the resistance of a given sample may decrease by several orders of magnitude at room temperatures, while its amorphous structure is preserved. The main effect of the process is densification, i.e., increased system density. The study includes the evolution of the system resistivity during and after the thermal treatment, the changes in the conductance noise, and the accompanying changes in the optical properties. The sample resistance is used to monitor the system dynamics during the annealing period as well as the relaxation that ensues after its termination. These reveal slow processes that fit well with a stretched-exponential law, a behavior that is commonly observed in structural glasses. There is an intriguing similarity between these effects and those obtained in high-pressure densification experiments. Both protocols exhibit the "slow spring-back" effect, a familiar response of memory foams. A heuristic picture based on a modified Lennard-Jones potential for the effective interparticle interaction is argued to qualitatively account for these densification-rarefaction phenomena in amorphous materials, whether affected by thermal treatment or by application of high pressure.

Deterministic ripple-spreading model for complex networks.

PubMed

Hu, Xiao-Bing; Wang, Ming; Leeson, Mark S; Hines, Evor L; Di Paolo, Ezequiel

2011-04-01

This paper proposes a deterministic complex network model, which is inspired by the natural ripple-spreading phenomenon. The motivations and main advantages of the model are the following: (i) The establishment of many real-world networks is a dynamic process, where it is often observed that the influence of a few local events spreads out through nodes, and then largely determines the final network topology. Obviously, this dynamic process involves many spatial and temporal factors. By simulating the natural ripple-spreading process, this paper reports a very natural way to set up a spatial and temporal model for such complex networks. (ii) Existing relevant network models are all stochastic models, i.e., with a given input, they cannot output a unique topology. Differently, the proposed ripple-spreading model can uniquely determine the final network topology, and at the same time, the stochastic feature of complex networks is captured by randomly initializing ripple-spreading related parameters. (iii) The proposed model can use an easily manageable number of ripple-spreading related parameters to precisely describe a network topology, which is more memory efficient when compared with traditional adjacency matrix or similar memory-expensive data structures. (iv) The ripple-spreading model has a very good potential for both extensions and applications.

Working memory dynamics bias the generation of beliefs: the influence of data presentation rate on hypothesis generation.

PubMed

Lange, Nicholas D; Thomas, Rick P; Buttaccio, Daniel R; Illingworth, David A; Davelaar, Eddy J

2013-02-01

Although temporal dynamics are inherent aspects of diagnostic tasks, few studies have investigated how various aspects of time course influence hypothesis generation. An experiment is reported that demonstrates that working memory dynamics operating during serial data acquisition bias hypothesis generation. The presentation rate (and order) of a sequence of serially presented symptoms was manipulated to be either fast (180 ms per symptom) or slow (1,500 ms per symptom) in a simulated medical diagnosis task. When the presentation rate was slow, participants chose the disease hypothesis consistent with the symptoms appearing later in the sequence. When the presentation rate was fast, however, participants chose the disease hypothesis consistent with the symptoms appearing earlier in the sequence, therefore representing a novel primacy effect. We predicted and account for this effect through competitive working memory dynamics governing information acquisition and the contribution of maintained information to the retrieval of hypotheses from long-term memory.

User-Assisted Store Recycling for Dynamic Task Graph Schedulers

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

Kurt, Mehmet Can; Krishnamoorthy, Sriram; Agrawal, Gagan

The emergence of the multi-core era has led to increased interest in designing effective yet practical parallel programming models. Models based on task graphs that operate on single-assignment data are attractive in several ways: they can support dynamic applications and precisely represent the available concurrency. However, they also require nuanced algorithms for scheduling and memory management for efficient execution. In this paper, we consider memory-efficient dynamic scheduling of task graphs. Specifically, we present a novel approach for dynamically recycling the memory locations assigned to data items as they are produced by tasks. We develop algorithms to identify memory-efficient store recyclingmore » functions by systematically evaluating the validity of a set of (user-provided or automatically generated) alternatives. Because recycling function can be input data-dependent, we have also developed support for continued correct execution of a task graph in the presence of a potentially incorrect store recycling function. Experimental evaluation demonstrates that our approach to automatic store recycling incurs little to no overheads, achieves memory usage comparable to the best manually derived solutions, often produces recycling functions valid across problem sizes and input parameters, and efficiently recovers from an incorrect choice of store recycling functions.« less

Oscillatory dynamics and place field maps reflect hippocampal ensemble processing of sequence and place memory under NMDA receptor control.

PubMed

Cabral, Henrique O; Vinck, Martin; Fouquet, Celine; Pennartz, Cyriel M A; Rondi-Reig, Laure; Battaglia, Francesco P

2014-01-22

Place coding in the hippocampus requires flexible combination of sensory inputs (e.g., environmental and self-motion information) with memory of past events. We show that mouse CA1 hippocampal spatial representations may either be anchored to external landmarks (place memory) or reflect memorized sequences of cell assemblies depending on the behavioral strategy spontaneously selected. These computational modalities correspond to different CA1 dynamical states, as expressed by theta and low- and high-frequency gamma oscillations, when switching from place to sequence memory-based processing. These changes are consistent with a shift from entorhinal to CA3 input dominance on CA1. In mice with a deletion of forebrain NMDA receptors, the ability of place cells to maintain a map based on sequence memory is selectively impaired and oscillatory dynamics are correspondingly altered, suggesting that oscillations contribute to selecting behaviorally appropriate computations in the hippocampus and that NMDA receptors are crucial for this function. Copyright © 2014 Elsevier Inc. All rights reserved.

Non-Markovianity-assisted high-fidelity Deutsch-Jozsa algorithm in diamond

NASA Astrophysics Data System (ADS)

Dong, Yang; Zheng, Yu; Li, Shen; Li, Cong-Cong; Chen, Xiang-Dong; Guo, Guang-Can; Sun, Fang-Wen

2018-01-01

The memory effects in non-Markovian quantum dynamics can induce the revival of quantum coherence, which is believed to provide important physical resources for quantum information processing (QIP). However, no real quantum algorithms have been demonstrated with the help of such memory effects. Here, we experimentally implemented a non-Markovianity-assisted high-fidelity refined Deutsch-Jozsa algorithm (RDJA) with a solid spin in diamond. The memory effects can induce pronounced non-monotonic variations in the RDJA results, which were confirmed to follow a non-Markovian quantum process by measuring the non-Markovianity of the spin system. By applying the memory effects as physical resources with the assistance of dynamical decoupling, the probability of success of RDJA was elevated above 97% in the open quantum system. This study not only demonstrates that the non-Markovianity is an important physical resource but also presents a feasible way to employ this physical resource. It will stimulate the application of the memory effects in non-Markovian quantum dynamics to improve the performance of practical QIP.

Staging memory for massively parallel processor

NASA Technical Reports Server (NTRS)

Batcher, Kenneth E. (Inventor)

1988-01-01

The invention herein relates to a computer organization capable of rapidly processing extremely large volumes of data. A staging memory is provided having a main stager portion consisting of a large number of memory banks which are accessed in parallel to receive, store, and transfer data words simultaneous with each other. Substager portions interconnect with the main stager portion to match input and output data formats with the data format of the main stager portion. An address generator is coded for accessing the data banks for receiving or transferring the appropriate words. Input and output permutation networks arrange the lineal order of data into and out of the memory banks.

The Use of Memories in Understanding Interactive Science and Technology Exhibits

NASA Astrophysics Data System (ADS)

Afonso, Ana S.; Gilbert, John K.

2006-10-01

Framed by a “personal constructivist” perspective, this study analyses visitors’ use of spontaneous memories in understanding different types of interactive exhibits, the nature and sources of the retrieved memories, and the way that visitors relate an exhibit analogically to memories of previous exhibits. One hundred and thirteen visitors (either alone or in groups) were observed during their interaction with exhibits and interviewed immediately afterwards. The majority of the retrieved memories were not used in understanding an exhibit; those memories used were mainly semantic and episodic in nature; and exhibits were mainly associated with memories by means of a superficial similarity between them. Suggestions for enhancing the formation of links between visitors’ memories and the understanding of an exhibit intended by the designer of it are made.

The computation of dynamic fractional difference parameter for S&P500 index

NASA Astrophysics Data System (ADS)

Pei, Tan Pei; Cheong, Chin Wen; Galagedera, Don U. A.

2015-10-01

This study evaluates the time-varying long memory behaviors of the S&P500 volatility index using dynamic fractional difference parameters. Time-varying fractional difference parameter shows the dynamic of long memory in volatility series for the pre and post subprime mortgage crisis triggered by U.S. The results find an increasing trend in the S&P500 long memory volatility for the pre-crisis period. However, the onset of Lehman Brothers event reduces the predictability of volatility series following by a slight fluctuation of the factional differencing parameters. After that, the U.S. financial market becomes more informationally efficient and follows a non-stationary random process.

Memory consolidation from seconds to weeks: a three-stage neural network model with autonomous reinstatement dynamics

PubMed Central

Fiebig, Florian; Lansner, Anders

2014-01-01

Declarative long-term memories are not created in an instant. Gradual stabilization and temporally shifting dependence of acquired declarative memories in different brain regions—called systems consolidation—can be tracked in time by lesion experiments. The observation of temporally graded retrograde amnesia (RA) following hippocampal lesions points to a gradual transfer of memory from hippocampus to neocortical long-term memory. Spontaneous reactivations of hippocampal memories, as observed in place cell reactivations during slow-wave-sleep, are supposed to drive neocortical reinstatements and facilitate this process. We propose a functional neural network implementation of these ideas and furthermore suggest an extended three-state framework that includes the prefrontal cortex (PFC). It bridges the temporal chasm between working memory percepts on the scale of seconds and consolidated long-term memory on the scale of weeks or months. We show that our three-stage model can autonomously produce the necessary stochastic reactivation dynamics for successful episodic memory consolidation. The resulting learning system is shown to exhibit classical memory effects seen in experimental studies, such as retrograde and anterograde amnesia (AA) after simulated hippocampal lesioning; furthermore the model reproduces peculiar biological findings on memory modulation, such as retrograde facilitation of memory after suppressed acquisition of new long-term memories—similar to the effects of benzodiazepines on memory. PMID:25071536

Using the memory activation capture (MAC) procedure to investigate the temporal dynamics of hypothesis generation.

PubMed

Lange, Nicholas D; Buttaccio, Daniel R; Davelaar, Eddy J; Thomas, Rick P

2014-02-01

Research investigating top-down capture has demonstrated a coupling of working memory content with attention and eye movements. By capitalizing on this relationship, we have developed a novel methodology, called the memory activation capture (MAC) procedure, for measuring the dynamics of working memory content supporting complex cognitive tasks (e.g., decision making, problem solving). The MAC procedure employs briefly presented visual arrays containing task-relevant information at critical points in a task. By observing which items are preferentially fixated, we gain a measure of working memory content as the task evolves through time. The efficacy of the MAC procedure was demonstrated in a dynamic hypothesis generation task in which some of its advantages over existing methods for measuring changes in the contents of working memory over time are highlighted. In two experiments, the MAC procedure was able to detect the hypothesis that was retrieved and placed into working memory. Moreover, the results from Experiment 2 suggest a two-stage process following hypothesis retrieval, whereby the hypothesis undergoes a brief period of heightened activation before entering a lower activation state in which it is maintained for output. The results of both experiments are of additional general interest, as they represent the first demonstrations of top-down capture driven by participant-established WM content retrieved from long-term memory.

Dynamic Connectivity between Brain Networks Supports Working Memory: Relationships to Dopamine Release and Schizophrenia.

PubMed

Cassidy, Clifford M; Van Snellenberg, Jared X; Benavides, Caridad; Slifstein, Mark; Wang, Zhishun; Moore, Holly; Abi-Dargham, Anissa; Horga, Guillermo

2016-04-13

Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during ann-back working-memory task) and positron emission tomography using the radiotracer [(11)C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. It is unclear how communication between brain networks responds to changing environmental demands during complex cognitive processes. Also, unknown in regard to these network dynamics is the role of neuromodulators, such as dopamine, and whether their dysregulation could underlie cognitive deficits in neuropsychiatric illness. We found that connectivity between brain networks changes with working-memory load and greater increases predict better working memory performance; however, it was not related to capacity for dopamine release in the cortex. Patients with schizophrenia did show dynamic internetwork connectivity; however, this was more weakly associated with successful performance in patients compared with healthy individuals. Our findings indicate that dynamic interactions between brain networks may support the type of flexible adaptations essential to goal-directed behavior. Copyright © 2016 the authors 0270-6474/16/364378-12$15.00/0.

Dynamic Connectivity between Brain Networks Supports Working Memory: Relationships to Dopamine Release and Schizophrenia

PubMed Central

Van Snellenberg, Jared X.; Benavides, Caridad; Slifstein, Mark; Wang, Zhishun; Moore, Holly; Abi-Dargham, Anissa

2016-01-01

Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during an n-back working-memory task) and positron emission tomography using the radiotracer [11C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. SIGNIFICANCE STATEMENT It is unclear how communication between brain networks responds to changing environmental demands during complex cognitive processes. Also, unknown in regard to these network dynamics is the role of neuromodulators, such as dopamine, and whether their dysregulation could underlie cognitive deficits in neuropsychiatric illness. We found that connectivity between brain networks changes with working-memory load and greater increases predict better working memory performance; however, it was not related to capacity for dopamine release in the cortex. Patients with schizophrenia did show dynamic internetwork connectivity; however, this was more weakly associated with successful performance in patients compared with healthy individuals. Our findings indicate that dynamic interactions between brain networks may support the type of flexible adaptations essential to goal-directed behavior. PMID:27076432

Noradrenergic activation of the basolateral amygdala maintains hippocampus-dependent accuracy of remote memory.

PubMed

Atucha, Erika; Vukojevic, Vanja; Fornari, Raquel V; Ronzoni, Giacomo; Demougin, Philippe; Peter, Fabian; Atsak, Piray; Coolen, Marcel W; Papassotiropoulos, Andreas; McGaugh, James L; de Quervain, Dominique J-F; Roozendaal, Benno

2017-08-22

Emotional enhancement of memory by noradrenergic mechanisms is well-described, but the long-term consequences of such enhancement are poorly understood. Over time, memory traces are thought to undergo a neural reorganization, that is, a systems consolidation, during which they are, at least partly, transferred from the hippocampus to neocortical networks. This transfer is accompanied by a decrease in episodic detailedness. Here we investigated whether norepinephrine (NE) administration into the basolateral amygdala after training on an inhibitory avoidance discrimination task, comprising two distinct training contexts, alters systems consolidation dynamics to maintain episodic-like accuracy and hippocampus dependency of remote memory. At a 2-d retention test, both saline- and NE-treated rats accurately discriminated the training context in which they had received footshock. Hippocampal inactivation with muscimol before retention testing disrupted discrimination of the shock context in both treatment groups. At 28 d, saline-treated rats showed hippocampus-independent retrieval and lack of discrimination. In contrast, NE-treated rats continued to display accurate memory of the shock-context association. Hippocampal inactivation at this remote retention test blocked episodic-like accuracy and induced a general memory impairment. These findings suggest that the NE treatment altered systems consolidation dynamics by maintaining hippocampal involvement in the memory. This shift in systems consolidation was paralleled by time-regulated DNA methylation and transcriptional changes of memory-related genes, namely Reln and Pkm ζ, in the hippocampus and neocortex. The findings provide evidence suggesting that consolidation of emotional memories by noradrenergic mechanisms alters systems consolidation dynamics and, as a consequence, influences the maintenance of long-term episodic-like accuracy of memory.

Cortical networks dynamically emerge with the interplay of slow and fast oscillations for memory of a natural scene.

PubMed

Mizuhara, Hiroaki; Sato, Naoyuki; Yamaguchi, Yoko

2015-05-01

Neural oscillations are crucial for revealing dynamic cortical networks and for serving as a possible mechanism of inter-cortical communication, especially in association with mnemonic function. The interplay of the slow and fast oscillations might dynamically coordinate the mnemonic cortical circuits to rehearse stored items during working memory retention. We recorded simultaneous EEG-fMRI during a working memory task involving a natural scene to verify whether the cortical networks emerge with the neural oscillations for memory of the natural scene. The slow EEG power was enhanced in association with the better accuracy of working memory retention, and accompanied cortical activities in the mnemonic circuits for the natural scene. Fast oscillation showed a phase-amplitude coupling to the slow oscillation, and its power was tightly coupled with the cortical activities for representing the visual images of natural scenes. The mnemonic cortical circuit with the slow neural oscillations would rehearse the distributed natural scene representations with the fast oscillation for working memory retention. The coincidence of the natural scene representations could be obtained by the slow oscillation phase to create a coherent whole of the natural scene in the working memory. Copyright © 2015 Elsevier Inc. All rights reserved.

Cocaine Directly Impairs Memory Extinction and Alters Brain DNA Methylation Dynamics in Honey Bees.

PubMed

Søvik, Eirik; Berthier, Pauline; Klare, William P; Helliwell, Paul; Buckle, Edwina L S; Plath, Jenny A; Barron, Andrew B; Maleszka, Ryszard

2018-01-01

Drug addiction is a chronic relapsing behavioral disorder. The high relapse rate has often been attributed to the perseverance of drug-associated memories due to high incentive salience of stimuli learnt under the influence of drugs. Drug addiction has also been interpreted as a memory disorder since drug associated memories are unusually enduring and some drugs, such as cocaine, interfere with neuroepigenetic machinery known to be involved in memory processing. Here we used the honey bee (an established invertebrate model for epigenomics and behavioral studies) to examine whether or not cocaine affects memory processing independently of its effect on incentive salience. Using the proboscis extension reflex training paradigm we found that cocaine strongly impairs consolidation of extinction memory. Based on correlation between the observed effect of cocaine on learning and expression of epigenetic processes, we propose that cocaine interferes with memory processing independently of incentive salience by directly altering DNA methylation dynamics. Our findings emphasize the impact of cocaine on memory systems, with relevance for understanding how cocaine can have such an enduring impact on behavior.

Cocaine Directly Impairs Memory Extinction and Alters Brain DNA Methylation Dynamics in Honey Bees

PubMed Central

Søvik, Eirik; Berthier, Pauline; Klare, William P.; Helliwell, Paul; Buckle, Edwina L. S.; Plath, Jenny A.; Barron, Andrew B.; Maleszka, Ryszard

2018-01-01

Drug addiction is a chronic relapsing behavioral disorder. The high relapse rate has often been attributed to the perseverance of drug-associated memories due to high incentive salience of stimuli learnt under the influence of drugs. Drug addiction has also been interpreted as a memory disorder since drug associated memories are unusually enduring and some drugs, such as cocaine, interfere with neuroepigenetic machinery known to be involved in memory processing. Here we used the honey bee (an established invertebrate model for epigenomics and behavioral studies) to examine whether or not cocaine affects memory processing independently of its effect on incentive salience. Using the proboscis extension reflex training paradigm we found that cocaine strongly impairs consolidation of extinction memory. Based on correlation between the observed effect of cocaine on learning and expression of epigenetic processes, we propose that cocaine interferes with memory processing independently of incentive salience by directly altering DNA methylation dynamics. Our findings emphasize the impact of cocaine on memory systems, with relevance for understanding how cocaine can have such an enduring impact on behavior. PMID:29487536

Slowing dynamics in supercooled liquids and other soft materials

NASA Astrophysics Data System (ADS)

Yardimci, Hasan

The slow structural dynamics displayed by supercooled liquids and the transition to an out-of-equilibrium glass state that they engender are among the most challenging issues in condensed matter physics. This thesis reports experimental studies designed to elucidate central aspects of these slow dynamics and the nature of the glass state. The subjects of these studies include glass forming molecular liquids and other soft materials that have been advanced as model glassy systems such as clay suspensions and block copolymer micelle solutions. The main experimental techniques employed in these investigations have been dielectric susceptibility and neutron scattering. In the first half of this thesis, we report frequency-dependent dielectric susceptibility measurements characterizing the evolution in the dynamical properties, or aging, of two supercooled liquids, sorbitol and xylitol, quenched below their calorimetric glass transition temperatures, Tg. In addition to the alpha relaxation that tracks the structural dynamics, the susceptibilities of both liquids possess a secondary Johari-Goldstein relaxation at higher frequencies. Following a quench below Tg, the susceptibility slowly approaches equilibrium behavior. For both liquids features of the Johari-Goldstein relaxation display a dependence on the time since the quench, or aging time, that is very similar to the age dependence of the alpha peak. Implications of these findings for aging in glasses and the nature of Johari-Goldstein relaxation are discussed. Further investigation of the aging in sorbitol reveals that it displays memory strikingly similar to that of a variety of glassy materials, particularly spin glasses. During a temporary stop in cooling, the susceptibility changes with time due to aging. The memory is revealed upon reheating as the susceptibility retraces these changes. To investigate the out-of-equilibrium state of the liquid as it displays this memory, we have employed a set of intricate thermal histories by interrupting the heating stage of the cycle and characterizing the subsequent aging. At temperatures above that of the original cooling stop, the liquid enters a state on heating with an effective age that is proportional to the duration of the stop, while at lower temperatures no effective age can be assigned and subtler behavior emerges. These results, which reveal differences with memory displayed by spin glasses, are discussed in the context of the liquid's energy landscape. In the second half of the thesis, we report neutron scattering measurements and dielectric studies on a set of disordered soft materials. (Abstract shortened by UMI.)

System for processing an encrypted instruction stream in hardware

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

Griswold, Richard L.; Nickless, William K.; Conrad, Ryan C.

A system and method of processing an encrypted instruction stream in hardware is disclosed. Main memory stores the encrypted instruction stream and unencrypted data. A central processing unit (CPU) is operatively coupled to the main memory. A decryptor is operatively coupled to the main memory and located within the CPU. The decryptor decrypts the encrypted instruction stream upon receipt of an instruction fetch signal from a CPU core. Unencrypted data is passed through to the CPU core without decryption upon receipt of a data fetch signal.

Operation of a quantum dot in the finite-state machine mode: Single-electron dynamic memory

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

Klymenko, M. V.; Klein, M.; Levine, R. D.

2016-07-14

A single electron dynamic memory is designed based on the non-equilibrium dynamics of charge states in electrostatically defined metallic quantum dots. Using the orthodox theory for computing the transfer rates and a master equation, we model the dynamical response of devices consisting of a charge sensor coupled to either a single and or a double quantum dot subjected to a pulsed gate voltage. We show that transition rates between charge states in metallic quantum dots are characterized by an asymmetry that can be controlled by the gate voltage. This effect is more pronounced when the switching between charge states correspondsmore » to a Markovian process involving electron transport through a chain of several quantum dots. By simulating the dynamics of electron transport we demonstrate that the quantum box operates as a finite-state machine that can be addressed by choosing suitable shapes and switching rates of the gate pulses. We further show that writing times in the ns range and retention memory times six orders of magnitude longer, in the ms range, can be achieved on the double quantum dot system using experimentally feasible parameters, thereby demonstrating that the device can operate as a dynamic single electron memory.« less

Prospective Memory and Task Interference in a Continuous Monitoring Dynamic Display Task

ERIC Educational Resources Information Center

Loft, Shayne; Remington, Roger W.

2010-01-01

Theories and methods from the prospective memory literature were used to anticipate how individuals would maintain and retrieve intentions in a continuous monitoring dynamic display task. Participants accepted aircraft into sectors and detected aircraft conflicts during an air traffic control simulation. They were sometimes required to substitute…

Swarming UAS II

DTIC Science & Technology

2010-05-05

employed biomimicry to model a swarm of UAS as a colony of ants, where each UAS dynamically updates a global memory map, allowing pheromone-like...matter of design, DSE-R-0808 employed biomimicry to model a swarm of UAS as a colony of ants, where each UAS dynamically updates a global memory map

Parallel optical image addition and subtraction in a dynamic photorefractive memory by phase-code multiplexing

NASA Astrophysics Data System (ADS)

Denz, Cornelia; Dellwig, Thilo; Lembcke, Jan; Tschudi, Theo

1996-02-01

We propose and demonstrate experimentally a method for utilizing a dynamic phase-encoded photorefractive memory to realize parallel optical addition, subtraction, and inversion operations of stored images. The phase-encoded holographic memory is realized in photorefractive BaTiO3, storing eight images using WalshHadamard binary phase codes and an incremental recording procedure. By subsampling the set of reference beams during the recall operation, the selectivity of the phase address is decreased, allowing one to combine images in such a way that different linear combination of the images can be realized at the output of the memory.

PDA: A coupling of knowledge and memory for case-based reasoning

NASA Technical Reports Server (NTRS)

Bharwani, S.; Walls, J.; Blevins, E.

1988-01-01

Problem solving in most domains requires reference to past knowledge and experience whether such knowledge is represented as rules, decision trees, networks or any variant of attributed graphs. Regardless of the representational form employed, designers of expert systems rarely make a distinction between the static and dynamic aspects of the system's knowledge base. The current paper clearly distinguishes between knowledge-based and memory-based reasoning where the former in its most pure sense is characterized by a static knowledge based resulting in a relatively brittle expert system while the latter is dynamic and analogous to the functions of human memory which learns from experience. The paper discusses the design of an advisory system which combines a knowledge base consisting of domain vocabulary and default dependencies between concepts with a dynamic conceptual memory which stores experimental knowledge in the form of cases. The case memory organizes past experience in the form of MOPs (memory organization packets) and sub-MOPs. Each MOP consists of a context frame and a set of indices. The context frame contains information about the features (norms) common to all the events and sub-MOPs indexed under it.

Memcapacitor model and its application in chaotic oscillator with memristor.

PubMed

Wang, Guangyi; Zang, Shouchi; Wang, Xiaoyuan; Yuan, Fang; Iu, Herbert Ho-Ching

2017-01-01

Memristors and memcapacitors are two new nonlinear elements with memory. In this paper, we present a Hewlett-Packard memristor model and a charge-controlled memcapacitor model and design a new chaotic oscillator based on the two models for exploring the characteristics of memristors and memcapacitors in nonlinear circuits. Furthermore, many basic dynamical behaviors of the oscillator, including equilibrium sets, Lyapunov exponent spectrums, and bifurcations with various circuit parameters, are investigated theoretically and numerically. Our analysis results show that the proposed oscillator possesses complex dynamics such as an infinite number of equilibria, coexistence oscillation, and multi-stability. Finally, a discrete model of the chaotic oscillator is given and the main statistical properties of this oscillator are verified via Digital Signal Processing chip experiments and National Institute of Standards and Technology tests.

High dynamic range adaptive real-time smart camera: an overview of the HDR-ARTiST project

NASA Astrophysics Data System (ADS)

Lapray, Pierre-Jean; Heyrman, Barthélémy; Ginhac, Dominique

2015-04-01

Standard cameras capture only a fraction of the information that is visible to the human visual system. This is specifically true for natural scenes including areas of low and high illumination due to transitions between sunlit and shaded areas. When capturing such a scene, many cameras are unable to store the full Dynamic Range (DR) resulting in low quality video where details are concealed in shadows or washed out by sunlight. The imaging technique that can overcome this problem is called HDR (High Dynamic Range) imaging. This paper describes a complete smart camera built around a standard off-the-shelf LDR (Low Dynamic Range) sensor and a Virtex-6 FPGA board. This smart camera called HDR-ARtiSt (High Dynamic Range Adaptive Real-time Smart camera) is able to produce a real-time HDR live video color stream by recording and combining multiple acquisitions of the same scene while varying the exposure time. This technique appears as one of the most appropriate and cheapest solution to enhance the dynamic range of real-life environments. HDR-ARtiSt embeds real-time multiple captures, HDR processing, data display and transfer of a HDR color video for a full sensor resolution (1280 1024 pixels) at 60 frames per second. The main contributions of this work are: (1) Multiple Exposure Control (MEC) dedicated to the smart image capture with alternating three exposure times that are dynamically evaluated from frame to frame, (2) Multi-streaming Memory Management Unit (MMMU) dedicated to the memory read/write operations of the three parallel video streams, corresponding to the different exposure times, (3) HRD creating by combining the video streams using a specific hardware version of the Devebecs technique, and (4) Global Tone Mapping (GTM) of the HDR scene for display on a standard LCD monitor.

Molecular dynamics of conformational substates for a simplified protein model

NASA Astrophysics Data System (ADS)

Grubmüller, Helmut; Tavan, Paul

1994-09-01

Extended molecular dynamics simulations covering a total of 0.232 μs have been carried out on a simplified protein model. Despite its simplified structure, that model exhibits properties similar to those of more realistic protein models. In particular, the model was found to undergo transitions between conformational substates at a time scale of several hundred picoseconds. The computed trajectories turned out to be sufficiently long as to permit a statistical analysis of that conformational dynamics. To check whether effective descriptions neglecting memory effects can reproduce the observed conformational dynamics, two stochastic models were studied. A one-dimensional Langevin effective potential model derived by elimination of subpicosecond dynamical processes could not describe the observed conformational transition rates. In contrast, a simple Markov model describing the transitions between but neglecting dynamical processes within conformational substates reproduced the observed distribution of first passage times. These findings suggest, that protein dynamics generally does not exhibit memory effects at time scales above a few hundred picoseconds, but confirms the existence of memory effects at a picosecond time scale.

Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation

PubMed Central

Tetzlaff, Christian; Kolodziejski, Christoph; Timme, Marc; Tsodyks, Misha; Wörgötter, Florentin

2013-01-01

Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a long-term storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling – a slow process usually associated with the maintenance of activity homeostasis – combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes. PMID:24204240

Adiabatic quantum optimization for associative memory recall

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

Seddiqi, Hadayat; Humble, Travis S.

Hopfield networks are a variant of associative memory that recall patterns stored in the couplings of an Ising model. Stored memories are conventionally accessed as fixed points in the network dynamics that correspond to energetic minima of the spin state. We show that memories stored in a Hopfield network may also be recalled by energy minimization using adiabatic quantum optimization (AQO). Numerical simulations of the underlying quantum dynamics allow us to quantify AQO recall accuracy with respect to the number of stored memories and noise in the input key. We investigate AQO performance with respect to how memories are storedmore » in the Ising model according to different learning rules. Our results demonstrate that AQO recall accuracy varies strongly with learning rule, a behavior that is attributed to differences in energy landscapes. Consequently, learning rules offer a family of methods for programming adiabatic quantum optimization that we expect to be useful for characterizing AQO performance.« less

Adiabatic Quantum Optimization for Associative Memory Recall

NASA Astrophysics Data System (ADS)

Seddiqi, Hadayat; Humble, Travis

2014-12-01

Hopfield networks are a variant of associative memory that recall patterns stored in the couplings of an Ising model. Stored memories are conventionally accessed as fixed points in the network dynamics that correspond to energetic minima of the spin state. We show that memories stored in a Hopfield network may also be recalled by energy minimization using adiabatic quantum optimization (AQO). Numerical simulations of the underlying quantum dynamics allow us to quantify AQO recall accuracy with respect to the number of stored memories and noise in the input key. We investigate AQO performance with respect to how memories are stored in the Ising model according to different learning rules. Our results demonstrate that AQO recall accuracy varies strongly with learning rule, a behavior that is attributed to differences in energy landscapes. Consequently, learning rules offer a family of methods for programming adiabatic quantum optimization that we expect to be useful for characterizing AQO performance.

Synaptic scaling enables dynamically distinct short- and long-term memory formation.

PubMed

Tetzlaff, Christian; Kolodziejski, Christoph; Timme, Marc; Tsodyks, Misha; Wörgötter, Florentin

2013-10-01

Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a long-term storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling - a slow process usually associated with the maintenance of activity homeostasis - combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes.

Dynamics of memory-guided choice behavior in Drosophila

PubMed Central

ICHINOSE, Toshiharu; TANIMOTO, Hiromu

2016-01-01

Memory retrieval requires both accuracy and speed. Olfactory learning of the fruit fly Drosophila melanogaster serves as a powerful model system to identify molecular and neuronal substrates of memory and memory-guided behavior. The behavioral expression of olfactory memory has traditionally been tested as a conditioned odor response in a simple T-maze, which measures the result, but not the speed, of odor choice. Here, we developed multiplexed T-mazes that allow video recording of the choice behavior. Automatic fly counting in each arm of the maze visualizes choice dynamics. Using this setup, we show that the transient blockade of serotonergic neurons slows down the choice, while leaving the eventual choice intact. In contrast, activation of the same neurons impairs the eventual performance leaving the choice speed unchanged. Our new apparatus contributes to elucidating how the speed and the accuracy of memory retrieval are implemented in the fly brain. PMID:27725473

Large-Scale Fluorescence Calcium-Imaging Methods for Studies of Long-Term Memory in Behaving Mammals

PubMed Central

Jercog, Pablo; Rogerson, Thomas; Schnitzer, Mark J.

2016-01-01

During long-term memory formation, cellular and molecular processes reshape how individual neurons respond to specific patterns of synaptic input. It remains poorly understood how such changes impact information processing across networks of mammalian neurons. To observe how networks encode, store, and retrieve information, neuroscientists must track the dynamics of large ensembles of individual cells in behaving animals, over timescales commensurate with long-term memory. Fluorescence Ca2+-imaging techniques can monitor hundreds of neurons in behaving mice, opening exciting avenues for studies of learning and memory at the network level. Genetically encoded Ca2+ indicators allow neurons to be targeted by genetic type or connectivity. Chronic animal preparations permit repeated imaging of neural Ca2+ dynamics over multiple weeks. Together, these capabilities should enable unprecedented analyses of how ensemble neural codes evolve throughout memory processing and provide new insights into how memories are organized in the brain. PMID:27048190

Adiabatic quantum optimization for associative memory recall

DOE PAGES

Seddiqi, Hadayat; Humble, Travis S.

2014-12-22

Hopfield networks are a variant of associative memory that recall patterns stored in the couplings of an Ising model. Stored memories are conventionally accessed as fixed points in the network dynamics that correspond to energetic minima of the spin state. We show that memories stored in a Hopfield network may also be recalled by energy minimization using adiabatic quantum optimization (AQO). Numerical simulations of the underlying quantum dynamics allow us to quantify AQO recall accuracy with respect to the number of stored memories and noise in the input key. We investigate AQO performance with respect to how memories are storedmore » in the Ising model according to different learning rules. Our results demonstrate that AQO recall accuracy varies strongly with learning rule, a behavior that is attributed to differences in energy landscapes. Consequently, learning rules offer a family of methods for programming adiabatic quantum optimization that we expect to be useful for characterizing AQO performance.« less

Theory of the dynamical thermal conductivity of metals

NASA Astrophysics Data System (ADS)

Bhalla, Pankaj; Kumar, Pradeep; Das, Nabyendu; Singh, Navinder

2016-09-01

The Mori's projection method, known as the memory function method, is an important theoretical formalism to study various transport coefficients. In the present work, we calculate the dynamical thermal conductivity in the case of metals using the memory function formalism. We introduce thermal memory functions for the first time and discuss the behavior of thermal conductivity in both the zero frequency limit and in the case of nonzero frequencies. We compare our results for the zero frequency case with the results obtained by the Bloch-Boltzmann kinetic approach and find that both approaches agree with each other. Motivated by some recent experimental advancements, we obtain several new results for the ac or the dynamical thermal conductivity.

Dynamic frontotemporal systems process space and time in working memory

PubMed Central

Adams, Jenna N.; Solbakk, Anne-Kristin; Endestad, Tor; Larsson, Pål G.; Ivanovic, Jugoslav; Meling, Torstein R.; Lin, Jack J.; Knight, Robert T.

2018-01-01

How do we rapidly process incoming streams of information in working memory, a cognitive mechanism central to human behavior? Dominant views of working memory focus on the prefrontal cortex (PFC), but human hippocampal recordings provide a neurophysiological signature distinct from the PFC. Are these regions independent, or do they interact in the service of working memory? We addressed this core issue in behavior by recording directly from frontotemporal sites in humans performing a visuospatial working memory task that operationalizes the types of identity and spatiotemporal information we encounter every day. Theta band oscillations drove bidirectional interactions between the PFC and medial temporal lobe (MTL; including the hippocampus). MTL theta oscillations directed the PFC preferentially during the processing of spatiotemporal information, while PFC theta oscillations directed the MTL for all types of information being processed in working memory. These findings reveal an MTL theta mechanism for processing space and time and a domain-general PFC theta mechanism, providing evidence that rapid, dynamic MTL–PFC interactions underlie working memory for everyday experiences. PMID:29601574

Quantifying memory in complex physiological time-series.

PubMed

Shirazi, Amir H; Raoufy, Mohammad R; Ebadi, Haleh; De Rui, Michele; Schiff, Sami; Mazloom, Roham; Hajizadeh, Sohrab; Gharibzadeh, Shahriar; Dehpour, Ahmad R; Amodio, Piero; Jafari, G Reza; Montagnese, Sara; Mani, Ali R

2013-01-01

In a time-series, memory is a statistical feature that lasts for a period of time and distinguishes the time-series from a random, or memory-less, process. In the present study, the concept of "memory length" was used to define the time period, or scale over which rare events within a physiological time-series do not appear randomly. The method is based on inverse statistical analysis and provides empiric evidence that rare fluctuations in cardio-respiratory time-series are 'forgotten' quickly in healthy subjects while the memory for such events is significantly prolonged in pathological conditions such as asthma (respiratory time-series) and liver cirrhosis (heart-beat time-series). The memory length was significantly higher in patients with uncontrolled asthma compared to healthy volunteers. Likewise, it was significantly higher in patients with decompensated cirrhosis compared to those with compensated cirrhosis and healthy volunteers. We also observed that the cardio-respiratory system has simple low order dynamics and short memory around its average, and high order dynamics around rare fluctuations.

Quantifying Memory in Complex Physiological Time-Series

PubMed Central

Shirazi, Amir H.; Raoufy, Mohammad R.; Ebadi, Haleh; De Rui, Michele; Schiff, Sami; Mazloom, Roham; Hajizadeh, Sohrab; Gharibzadeh, Shahriar; Dehpour, Ahmad R.; Amodio, Piero; Jafari, G. Reza; Montagnese, Sara; Mani, Ali R.

2013-01-01

In a time-series, memory is a statistical feature that lasts for a period of time and distinguishes the time-series from a random, or memory-less, process. In the present study, the concept of “memory length” was used to define the time period, or scale over which rare events within a physiological time-series do not appear randomly. The method is based on inverse statistical analysis and provides empiric evidence that rare fluctuations in cardio-respiratory time-series are ‘forgotten’ quickly in healthy subjects while the memory for such events is significantly prolonged in pathological conditions such as asthma (respiratory time-series) and liver cirrhosis (heart-beat time-series). The memory length was significantly higher in patients with uncontrolled asthma compared to healthy volunteers. Likewise, it was significantly higher in patients with decompensated cirrhosis compared to those with compensated cirrhosis and healthy volunteers. We also observed that the cardio-respiratory system has simple low order dynamics and short memory around its average, and high order dynamics around rare fluctuations. PMID:24039811

Memory Effects of Benzodiazepines: Memory Stages and Types Versus Binding-Site Subtypes

PubMed Central

Savić, Miroslav M.; Obradović, Dragan I.; Ugrešić, Nenad D.; Bokonjić, Dubravko R.

2005-01-01

Benzodiazepines are well established as inhibitory modulators of memory processing. This effect is especially prominent when applied before the acquisition phase of a memory task. This minireview concentrates on the putative subtype selectivity of the acquisition-impairing action of benzodiazepines. Namely, recent genetic studies and standard behavioral tests employing subtype-selective ligands pointed to the predominant involvement of two subtypes of benzodiazepine binding sites in memory modulation. Explicit memory learning seems to be affected through the GABAA receptors containing the α1 and α1 subunits, whereas the effects on procedural memory can be mainly mediated by the α1 subunit. The pervading involvement of the α1 subunit in memory modulation is not at all unexpected because this subunit is the major subtype, present in 60% of all GABAA receptors. On the other hand, the role of α5 subunits, mainly expressed in the hippocampus, in modulating distinct forms of memory gives promise of selective pharmacological coping with certain memory deficit states. PMID:16444900

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.

Vaccination Expands Antigen-Specific CD4+ Memory T Cells and Mobilizes Bystander Central Memory T Cells

PubMed Central

Li Causi, Eleonora; Parikh, Suraj C.; Chudley, Lindsey; Layfield, David M.; Ottensmeier, Christian H.; Stevenson, Freda K.; Di Genova, Gianfranco

2015-01-01

CD4+ T helper memory (Thmem) cells influence both natural and vaccine-boosted immunity, but mechanisms for their maintenance remain unclear. Pro-survival signals from the common gamma-chain cytokines, in particular IL-7, appear important. Previously we showed in healthy volunteers that a booster vaccination with tetanus toxoid (TT) expanded peripheral blood TT-specific Thmem cells as expected, but was accompanied by parallel increase of Thmem cells specific for two unrelated and non cross-reactive common recall antigens. Here, in a new cohort of healthy human subjects, we compare blood vaccine-specific and bystander Thmem cells in terms of differentiation stage, function, activation and proliferative status. Both responses peaked 1 week post-vaccination. Vaccine-specific cytokine-producing Thmem cells were predominantly effector memory, whereas bystander cells were mainly of central memory phenotype. Importantly, TT-specific Thmem cells were activated (CD38High HLA-DR+), cycling or recently divided (Ki-67+), and apparently vulnerable to death (IL-7RαLow and Bcl-2 Low). In contrast, bystander Thmem cells were resting (CD38Low HLA-DR- Ki-67-) with high expression of IL-7Rα and Bcl-2. These findings allow a clear distinction between vaccine-specific and bystander Thmem cells, suggesting the latter do not derive from recent proliferation but from cells mobilized from as yet undefined reservoirs. Furthermore, they reveal the interdependent dynamics of specific and bystander T-cell responses which will inform assessments of responses to vaccines. PMID:26332995

Understanding human dynamics in microblog posting activities

NASA Astrophysics Data System (ADS)

Jiang, Zhihong; Zhang, Yubao; Wang, Hui; Li, Pei

2013-02-01

Human activity patterns are an important issue in behavior dynamics research. Empirical evidence indicates that human activity patterns can be characterized by a heavy-tailed inter-event time distribution. However, most researchers give an understanding by only modeling the power-law feature of the inter-event time distribution, and those overlooked non-power-law features are likely to be nontrivial. In this work, we propose a behavior dynamics model, called the finite memory model, in which humans adaptively change their activity rates based on a finite memory of recent activities, which is driven by inherent individual interest. Theoretical analysis shows a finite memory model can properly explain various heavy-tailed inter-event time distributions, including a regular power law and some non-power-law deviations. To validate the model, we carry out an empirical study based on microblogging activity from thousands of microbloggers in the Celebrity Hall of the Sina microblog. The results show further that the model is reasonably effective. We conclude that finite memory is an effective dynamics element to describe the heavy-tailed human activity pattern.

Implementing a bubble memory hierarchy system

NASA Technical Reports Server (NTRS)

Segura, R.; Nichols, C. D.

1979-01-01

This paper reports on implementation of a magnetic bubble memory in a two-level hierarchial system. The hierarchy used a major-minor loop device and RAM under microprocessor control. Dynamic memory addressing, dual bus primary memory, and hardware data modification detection are incorporated in the system to minimize access time. It is the objective of the system to incorporate the advantages of bipolar memory with that of bubble domain memory to provide a smart, optimal memory system which is easy to interface and independent of user's system.

Working Memory and Hearing Aid Processing: Literature Findings, Future Directions, and Clinical Applications

PubMed Central

Souza, Pamela; Arehart, Kathryn; Neher, Tobias

2015-01-01

Working memory—the ability to process and store information—has been identified as an important aspect of speech perception in difficult listening environments. Working memory can be envisioned as a limited-capacity system which is engaged when an input signal cannot be readily matched to a stored representation or template. This “mismatch” is expected to occur more frequently when the signal is degraded. Because working memory capacity varies among individuals, those with smaller capacity are expected to demonstrate poorer speech understanding when speech is degraded, such as in background noise. However, it is less clear whether (and how) working memory should influence practical decisions, such as hearing treatment. Here, we consider the relationship between working memory capacity and response to specific hearing aid processing strategies. Three types of signal processing are considered, each of which will alter the acoustic signal: fast-acting wide-dynamic range compression, which smooths the amplitude envelope of the input signal; digital noise reduction, which may inadvertently remove speech signal components as it suppresses noise; and frequency compression, which alters the relationship between spectral peaks. For fast-acting wide-dynamic range compression, a growing body of data suggests that individuals with smaller working memory capacity may be more susceptible to such signal alterations, and may receive greater amplification benefit with “low alteration” processing. While the evidence for a relationship between wide-dynamic range compression and working memory appears robust, the effects of working memory on perceptual response to other forms of hearing aid signal processing are less clear cut. We conclude our review with a discussion of the opportunities (and challenges) in translating information on individual working memory into clinical treatment, including clinically feasible measures of working memory. PMID:26733899

Noradrenergic activation of the basolateral amygdala maintains hippocampus-dependent accuracy of remote memory

PubMed Central

Atucha, Erika; Vukojevic, Vanja; Fornari, Raquel V.; Ronzoni, Giacomo; Demougin, Philippe; Peter, Fabian; Atsak, Piray; Coolen, Marcel W.; Papassotiropoulos, Andreas; McGaugh, James L.; de Quervain, Dominique J.-F.; Roozendaal, Benno

2017-01-01

Emotional enhancement of memory by noradrenergic mechanisms is well-described, but the long-term consequences of such enhancement are poorly understood. Over time, memory traces are thought to undergo a neural reorganization, that is, a systems consolidation, during which they are, at least partly, transferred from the hippocampus to neocortical networks. This transfer is accompanied by a decrease in episodic detailedness. Here we investigated whether norepinephrine (NE) administration into the basolateral amygdala after training on an inhibitory avoidance discrimination task, comprising two distinct training contexts, alters systems consolidation dynamics to maintain episodic-like accuracy and hippocampus dependency of remote memory. At a 2-d retention test, both saline- and NE-treated rats accurately discriminated the training context in which they had received footshock. Hippocampal inactivation with muscimol before retention testing disrupted discrimination of the shock context in both treatment groups. At 28 d, saline-treated rats showed hippocampus-independent retrieval and lack of discrimination. In contrast, NE-treated rats continued to display accurate memory of the shock–context association. Hippocampal inactivation at this remote retention test blocked episodic-like accuracy and induced a general memory impairment. These findings suggest that the NE treatment altered systems consolidation dynamics by maintaining hippocampal involvement in the memory. This shift in systems consolidation was paralleled by time-regulated DNA methylation and transcriptional changes of memory-related genes, namely Reln and Pkmζ, in the hippocampus and neocortex. The findings provide evidence suggesting that consolidation of emotional memories by noradrenergic mechanisms alters systems consolidation dynamics and, as a consequence, influences the maintenance of long-term episodic-like accuracy of memory. PMID:28790188

Increased gamma band power during movement planning coincides with motor memory retrieval.

PubMed

Thürer, Benjamin; Stockinger, Christian; Focke, Anne; Putze, Felix; Schultz, Tanja; Stein, Thorsten

2016-01-15

The retrieval of motor memory requires a previous memory encoding and subsequent consolidation of the specific motor memory. Previous work showed that motor memory seems to rely on different memory components (e.g., implicit, explicit). However, it is still unknown if explicit components contribute to the retrieval of motor memories formed by dynamic adaptation tasks and which neural correlates are linked to memory retrieval. We investigated the lower and higher gamma bands of subjects' electroencephalography during encoding and retrieval of a dynamic adaptation task. A total of 24 subjects were randomly assigned to a treatment and control group. Both groups adapted to a force field A on day 1 and were re-exposed to the same force field A on day 3 of the experiment. On day 2, treatment group learned an interfering force field B whereas control group had a day rest. Kinematic analyses showed that control group improved their initial motor performance from day 1 to day 3 but treatment group did not. This behavioral result coincided with an increased higher gamma band power in the electrodes over prefrontal areas on the initial trials of day 3 for control but not treatment group. Intriguingly, this effect vanished with the subsequent re-adaptation on day 3. We suggest that improved re-test performance in a dynamic motor adaptation task is contributed by explicit memory and that gamma bands in the electrodes over the prefrontal cortex are linked to these explicit components. Furthermore, we suggest that the contribution of explicit memory vanishes with the subsequent re-adaptation while task automaticity increases. Copyright © 2015 Elsevier Inc. All rights reserved.

Chemical Memory Reactions Induced Bursting Dynamics in Gene Expression

PubMed Central

Tian, Tianhai

2013-01-01

Memory is a ubiquitous phenomenon in biological systems in which the present system state is not entirely determined by the current conditions but also depends on the time evolutionary path of the system. Specifically, many memorial phenomena are characterized by chemical memory reactions that may fire under particular system conditions. These conditional chemical reactions contradict to the extant stochastic approaches for modeling chemical kinetics and have increasingly posed significant challenges to mathematical modeling and computer simulation. To tackle the challenge, I proposed a novel theory consisting of the memory chemical master equations and memory stochastic simulation algorithm. A stochastic model for single-gene expression was proposed to illustrate the key function of memory reactions in inducing bursting dynamics of gene expression that has been observed in experiments recently. The importance of memory reactions has been further validated by the stochastic model of the p53-MDM2 core module. Simulations showed that memory reactions is a major mechanism for realizing both sustained oscillations of p53 protein numbers in single cells and damped oscillations over a population of cells. These successful applications of the memory modeling framework suggested that this innovative theory is an effective and powerful tool to study memory process and conditional chemical reactions in a wide range of complex biological systems. PMID:23349679

Chemical memory reactions induced bursting dynamics in gene expression.

PubMed

Tian, Tianhai

2013-01-01

Memory is a ubiquitous phenomenon in biological systems in which the present system state is not entirely determined by the current conditions but also depends on the time evolutionary path of the system. Specifically, many memorial phenomena are characterized by chemical memory reactions that may fire under particular system conditions. These conditional chemical reactions contradict to the extant stochastic approaches for modeling chemical kinetics and have increasingly posed significant challenges to mathematical modeling and computer simulation. To tackle the challenge, I proposed a novel theory consisting of the memory chemical master equations and memory stochastic simulation algorithm. A stochastic model for single-gene expression was proposed to illustrate the key function of memory reactions in inducing bursting dynamics of gene expression that has been observed in experiments recently. The importance of memory reactions has been further validated by the stochastic model of the p53-MDM2 core module. Simulations showed that memory reactions is a major mechanism for realizing both sustained oscillations of p53 protein numbers in single cells and damped oscillations over a population of cells. These successful applications of the memory modeling framework suggested that this innovative theory is an effective and powerful tool to study memory process and conditional chemical reactions in a wide range of complex biological systems.

Dynamic switching between semantic and episodic memory systems.

PubMed

Kompus, Kristiina; Olsson, Carl-Johan; Larsson, Anne; Nyberg, Lars

2009-09-01

It has been suggested that episodic and semantic long-term memory systems interact during retrieval. Here we examined the flexibility of memory retrieval in an associative task taxing memories of different strength, assumed to differentially engage episodic and semantic memory. Healthy volunteers were pre-trained on a set of 36 face-name pairs over a 6-week period. Another set of 36 items was shown only once during the same time period. About 3 months after the training period all items were presented in a randomly intermixed order in an event-related fMRI study of face-name memory. Once presented items differentially activated anterior cingulate cortex and a right prefrontal region that previously have been associated with episodic retrieval mode. High-familiar items were associated with stronger activation of posterior cortices and a left frontal region. These findings fit a model of memory retrieval by which early processes determine, on a trial-by-trial basis, if the task can be solved by the default semantic system. If not, there is a dynamic shift to cognitive control processes that guide retrieval from episodic memory.

Natural variation in learning rate and memory dynamics in parasitoid wasps: opportunities for converging ecology and neuroscience

PubMed Central

Hoedjes, Katja M.; Kruidhof, H. Marjolein; Huigens, Martinus E.; Dicke, Marcel; Vet, Louise E. M.; Smid, Hans M.

2011-01-01

Although the neural and genetic pathways underlying learning and memory formation seem strikingly similar among species of distant animal phyla, several more subtle inter- and intraspecific differences become evident from studies on model organisms. The true significance of such variation can only be understood when integrating this with information on the ecological relevance. Here, we argue that parasitoid wasps provide an excellent opportunity for multi-disciplinary studies that integrate ultimate and proximate approaches. These insects display interspecific variation in learning rate and memory dynamics that reflects natural variation in a daunting foraging task that largely determines their fitness: finding the inconspicuous hosts to which they will assign their offspring to develop. We review bioassays used for oviposition learning, the ecological factors that are considered to underlie the observed differences in learning rate and memory dynamics, and the opportunities for convergence of ecology and neuroscience that are offered by using parasitoid wasps as model species. We advocate that variation in learning and memory traits has evolved to suit an insect's lifestyle within its ecological niche. PMID:21106587

Single-Event Effect Performance of a Conductive-Bridge Memory EEPROM

NASA Technical Reports Server (NTRS)

Chen, Dakai; Wilcox, Edward; Berg, Melanie; Kim, Hak; Phan, Anthony; Figueiredo, Marco; Seidleck, Christina; LaBel, Kenneth

2015-01-01

We investigated the heavy ion single-event effect (SEE) susceptibility of the industry’s first stand-alone memory based on conductive-bridge memory (CBRAM) technology. The device is available as an electrically erasable programmable read-only memory (EEPROM). We found that single-event functional interrupt (SEFI) is the dominant SEE type for each operational mode (standby, dynamic read, and dynamic write/read). SEFIs occurred even while the device is statically biased in standby mode. Worst case SEFIs resulted in errors that filled the entire memory space. Power cycle did not always clear the errors. Thus the corrupted cells had to be reprogrammed in some cases. The device is also vulnerable to bit upsets during dynamic write/read tests, although the frequency of the upsets are relatively low. The linear energy transfer threshold for cell upset is between 10 and 20 megaelectron volts per square centimeter per milligram, with an upper limit cross section of 1.6 times 10(sup -11) square centimeters per bit (95 percent confidence level) at 10 megaelectronvolts per square centimeter per milligram. In standby mode, the CBRAM array appears invulnerable to bit upsets.

Dynamic reconfiguration of frontal brain networks during executive cognition in humans

PubMed Central

Braun, Urs; Schäfer, Axel; Walter, Henrik; Erk, Susanne; Romanczuk-Seiferth, Nina; Haddad, Leila; Schweiger, Janina I.; Grimm, Oliver; Heinz, Andreas; Tost, Heike; Meyer-Lindenberg, Andreas; Bassett, Danielle S.

2015-01-01

The brain is an inherently dynamic system, and executive cognition requires dynamically reconfiguring, highly evolving networks of brain regions that interact in complex and transient communication patterns. However, a precise characterization of these reconfiguration processes during cognitive function in humans remains elusive. Here, we use a series of techniques developed in the field of “dynamic network neuroscience” to investigate the dynamics of functional brain networks in 344 healthy subjects during a working-memory challenge (the “n-back” task). In contrast to a control condition, in which dynamic changes in cortical networks were spread evenly across systems, the effortful working-memory condition was characterized by a reconfiguration of frontoparietal and frontotemporal networks. This reconfiguration, which characterizes “network flexibility,” employs transient and heterogeneous connectivity between frontal systems, which we refer to as “integration.” Frontal integration predicted neuropsychological measures requiring working memory and executive cognition, suggesting that dynamic network reconfiguration between frontal systems supports those functions. Our results characterize dynamic reconfiguration of large-scale distributed neural circuits during executive cognition in humans and have implications for understanding impaired cognitive function in disorders affecting connectivity, such as schizophrenia or dementia. PMID:26324898

Reservoir Computing Beyond Memory-Nonlinearity Trade-off.

PubMed

Inubushi, Masanobu; Yoshimura, Kazuyuki

2017-08-31

Reservoir computing is a brain-inspired machine learning framework that employs a signal-driven dynamical system, in particular harnessing common-signal-induced synchronization which is a widely observed nonlinear phenomenon. Basic understanding of a working principle in reservoir computing can be expected to shed light on how information is stored and processed in nonlinear dynamical systems, potentially leading to progress in a broad range of nonlinear sciences. As a first step toward this goal, from the viewpoint of nonlinear physics and information theory, we study the memory-nonlinearity trade-off uncovered by Dambre et al. (2012). Focusing on a variational equation, we clarify a dynamical mechanism behind the trade-off, which illustrates why nonlinear dynamics degrades memory stored in dynamical system in general. Moreover, based on the trade-off, we propose a mixture reservoir endowed with both linear and nonlinear dynamics and show that it improves the performance of information processing. Interestingly, for some tasks, significant improvements are observed by adding a few linear dynamics to the nonlinear dynamical system. By employing the echo state network model, the effect of the mixture reservoir is numerically verified for a simple function approximation task and for more complex tasks.

Internode data communications in a parallel computer

DOEpatents

Archer, Charles J.; Blocksome, Michael A.; Miller, Douglas R.; Parker, Jeffrey J.; Ratterman, Joseph D.; Smith, Brian E.

2013-09-03

Internode data communications in a parallel computer that includes compute nodes that each include main memory and a messaging unit, the messaging unit including computer memory and coupling compute nodes for data communications, in which, for each compute node at compute node boot time: a messaging unit allocates, in the messaging unit's computer memory, a predefined number of message buffers, each message buffer associated with a process to be initialized on the compute node; receives, prior to initialization of a particular process on the compute node, a data communications message intended for the particular process; and stores the data communications message in the message buffer associated with the particular process. Upon initialization of the particular process, the process establishes a messaging buffer in main memory of the compute node and copies the data communications message from the message buffer of the messaging unit into the message buffer of main memory.

Internode data communications in a parallel computer

DOEpatents

Archer, Charles J; Blocksome, Michael A; Miller, Douglas R; Parker, Jeffrey J; Ratterman, Joseph D; Smith, Brian E

2014-02-11

Internode data communications in a parallel computer that includes compute nodes that each include main memory and a messaging unit, the messaging unit including computer memory and coupling compute nodes for data communications, in which, for each compute node at compute node boot time: a messaging unit allocates, in the messaging unit's computer memory, a predefined number of message buffers, each message buffer associated with a process to be initialized on the compute node; receives, prior to initialization of a particular process on the compute node, a data communications message intended for the particular process; and stores the data communications message in the message buffer associated with the particular process. Upon initialization of the particular process, the process establishes a messaging buffer in main memory of the compute node and copies the data communications message from the message buffer of the messaging unit into the message buffer of main memory.

Chaotic patterns of autonomic activity during hypnotic recall.

PubMed

Bob, Petr; Siroka, Ivana; Susta, Marek

2009-01-01

Chaotic neural dynamics likely emerge in cognitive processes and may present time periods that are extremely sensitive to influences affecting the neural system. Recent findings suggest that this sensitivity may increase during retrieval of stressful emotional experiences reflecting underlying mechanism related to consolidation of traumatic memories. In this context, hypnotic recall of anxiety memories in 10 patients, simultaneously with ECG measurement was performed. The same measurement was performed during control cognitive task in 8 anxiety patients and 22 healthy controls. Nonlinear data analysis of ECG records indicates significant increase in the degree of chaos during retrieval of stressful memory in all the patients. The results suggest a role of chaotic neural dynamics during processing of anxiety-related stressful memories.

Male veterans with PTSD exhibit aberrant neural dynamics during working memory processing: an MEG study

PubMed Central

McDermott, Timothy J.; Badura-Brack, Amy S.; Becker, Katherine M.; Ryan, Tara J.; Khanna, Maya M.; Heinrichs-Graham, Elizabeth; Wilson, Tony W.

2016-01-01

Background Posttraumatic stress disorder (PTSD) is associated with executive functioning deficits, including disruptions in working memory. In this study, we examined the neural dynamics of working memory processing in veterans with PTSD and a matched healthy control sample using magnetoencephalography (MEG). Methods Our sample of recent combat veterans with PTSD and demographically matched participants without PTSD completed a working memory task during a 306-sensor MEG recording. The MEG data were preprocessed and transformed into the time-frequency domain. Significant oscillatory brain responses were imaged using a beamforming approach to identify spatiotemporal dynamics. Results Fifty-one men were included in our analyses: 27 combat veterans with PTSD and 24 controls. Across all participants, a dynamic wave of neural activity spread from posterior visual cortices to left frontotemporal regions during encoding, consistent with a verbal working memory task, and was sustained throughout maintenance. Differences related to PTSD emerged during early encoding, with patients exhibiting stronger α oscillatory responses than controls in the right inferior frontal gyrus (IFG). Differences spread to the right supramarginal and temporal cortices during later encoding where, along with the right IFG, they persisted throughout the maintenance period. Limitations This study focused on men with combat-related PTSD using a verbal working memory task. Future studies should evaluate women and the impact of various traumatic experiences using diverse tasks. Conclusion Posttraumatic stress disorder is associated with neurophysiological abnormalities during working memory encoding and maintenance. Veterans with PTSD engaged a bilateral network, including the inferior prefrontal cortices and supramarginal gyri. Right hemispheric neural activity likely reflects compensatory processing, as veterans with PTSD work to maintain accurate performance despite known cognitive deficits associated with the disorder. PMID:26645740

A Temporal Ratio Model of Memory

ERIC Educational Resources Information Center

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

2007-01-01

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

Efficient bulk-loading of gridfiles

NASA Technical Reports Server (NTRS)

Leutenegger, Scott T.; Nicol, David M.

1994-01-01

This paper considers the problem of bulk-loading large data sets for the gridfile multiattribute indexing technique. We propose a rectilinear partitioning algorithm that heuristically seeks to minimize the size of the gridfile needed to ensure no bucket overflows. Empirical studies on both synthetic data sets and on data sets drawn from computational fluid dynamics applications demonstrate that our algorithm is very efficient, and is able to handle large data sets. In addition, we present an algorithm for bulk-loading data sets too large to fit in main memory. Utilizing a sort of the entire data set it creates a gridfile without incurring any overflows.

Displaying Data As Movies

NASA Technical Reports Server (NTRS)

Moore, Judith G.

1992-01-01

NMSB Movie computer program displays large sets of data (more than million individual values). Presentation dynamic, rapidly displaying sequential image "frames" in main "movie" window. Any sequence of two-dimensional sets of data scaled between 0 and 255 (1-byte resolution) displayed as movie. Time- or slice-wise progression of data illustrated. Originally written to present data from three-dimensional ultrasonic scans of damaged aerospace composite materials, illustrates data acquired by thermal-analysis systems measuring rates of heating and cooling of various materials. Developed on Macintosh IIx computer with 8-bit color display adapter and 8 megabytes of memory using Symantec Corporation's Think C, version 4.0.

On climate prediction: how much can we expect from climate memory?

NASA Astrophysics Data System (ADS)

Yuan, Naiming; Huang, Yan; Duan, Jianping; Zhu, Congwen; Xoplaki, Elena; Luterbacher, Jürg

2018-03-01

Slowing variability in climate system is an important source of climate predictability. However, it is still challenging for current dynamical models to fully capture the variability as well as its impacts on future climate. In this study, instead of simulating the internal multi-scale oscillations in dynamical models, we discussed the effects of internal variability in terms of climate memory. By decomposing climate state x(t) at a certain time point t into memory part M(t) and non-memory part ɛ (t) , climate memory effects from the past 30 years on climate prediction are quantified. For variables with strong climate memory, high variance (over 20% ) in x(t) is explained by the memory part M(t), and the effects of climate memory are non-negligible for most climate variables, but the precipitation. Regarding of multi-steps climate prediction, a power law decay of the explained variance was found, indicating long-lasting climate memory effects. The explained variances by climate memory can remain to be higher than 10% for more than 10 time steps. Accordingly, past climate conditions can affect both short (monthly) and long-term (interannual, decadal, or even multidecadal) climate predictions. With the memory part M(t) precisely calculated from Fractional Integral Statistical Model, one only needs to focus on the non-memory part ɛ (t) , which is an important quantity that determines climate predictive skills.

Context-dependent switching between proactive and reactive working memory control mechanisms in the right inferior frontal gyrus.

PubMed

Marklund, Petter; Persson, Jonas

2012-11-15

A critical feature of higher cognitive functioning is the capacity to flexibly tailor information processing and behaviors to current situational demands. Recent neurocognitive models have been postulated to account for the dynamic nature of human executive processing by invoking two dissociable cognitive control modes, proactive and reactive control. These may involve partially overlapping, but temporally distinct neural implementation in the prefrontal cortex. Prior brain imaging studies exploring proactive control have mainly used tasks requiring only information about single-items to be retained over unfilled delays. Whether proactive control can also be utilized to facilitate performance in more complex working memory tasks, in which concurrent processing of intervening items and updating is mandatory during contextual cue maintenance remains an open question. To examine this issue and to elucidate the extent to which overlapping neural substrates underlie proactive and reactive control we used fMRI and a modified verbal 3-back paradigm with embedded cues predictive of high-interference trials. This task requires context information to be retained over multiple intervening trials. We found that performance improved with item-specific cues predicting forthcoming lures despite increased working memory load. Temporal dynamics of activation in the right inferior frontal gyrus suggest flexible switching between proactive and reactive control in a context-dependent fashion, with greater sustained responses elicited in the 3-back task involving context maintenance of cue information and greater transient responses elicited in the 3-back task absent of cues. Copyright © 2012 Elsevier Inc. All rights reserved.

The structure and dynamics of interactive documents

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

Rocha, J.T.

1999-04-01

Advances in information technology continue to accelerate as the new millennium approaches. With these advances, electronic information management is becoming increasingly important and is now supported by a seemingly bewildering array of hardware and software whose sole purpose is the design and implementation of interactive documents employing multimedia applications. Multimedia memory and storage applications such as Compact Disk-Read Only Memory (CD-ROMs) are already a familiar interactive tool in both the entertainment and business sectors. Even home enthusiasts now have the means at their disposal to design and produce CD-ROMs. More recently, Digital Video Disk (DVD) technology is carving its ownmore » niche in these markets and may (once application bugs are corrected and prices are lowered) eventually supplant CD-ROM technology. CD-ROM and DVD are not the only memory and storage applications capable of supporting interactive media. External, high-capacity drives and disks such as the Iomega{copyright} zip{reg_sign} and jaz{reg_sign} are also useful platforms for launching interactive documents without the need for additional hardware such as CD-ROM burners and copiers. The main drawback here, however, is the relatively high unit price per disk when compared to the unit cost of CD-ROMs. Regardless of the application chosen, there are fundamental structural characteristics that must be considered before effective interactive documents can be created. Additionally, the dynamics of interactive documents employing hypertext links are unique and bear only slight resemblance to those of their traditional hard-copy counterparts. These two considerations form the essential content of this paper.« less

Hopf bifurcation of an (n + 1) -neuron bidirectional associative memory neural network model with delays.

PubMed

Xiao, Min; Zheng, Wei Xing; Cao, Jinde

2013-01-01

Recent studies on Hopf bifurcations of neural networks with delays are confined to simplified neural network models consisting of only two, three, four, five, or six neurons. It is well known that neural networks are complex and large-scale nonlinear dynamical systems, so the dynamics of the delayed neural networks are very rich and complicated. Although discussing the dynamics of networks with a few neurons may help us to understand large-scale networks, there are inevitably some complicated problems that may be overlooked if simplified networks are carried over to large-scale networks. In this paper, a general delayed bidirectional associative memory neural network model with n + 1 neurons is considered. By analyzing the associated characteristic equation, the local stability of the trivial steady state is examined, and then the existence of the Hopf bifurcation at the trivial steady state is established. By applying the normal form theory and the center manifold reduction, explicit formulae are derived to determine the direction and stability of the bifurcating periodic solution. Furthermore, the paper highlights situations where the Hopf bifurcations are particularly critical, in the sense that the amplitude and the period of oscillations are very sensitive to errors due to tolerances in the implementation of neuron interconnections. It is shown that the sensitivity is crucially dependent on the delay and also significantly influenced by the feature of the number of neurons. Numerical simulations are carried out to illustrate the main results.

Motion control in free-standing shape-memory actuators

NASA Astrophysics Data System (ADS)

Belmonte, Alberto; Lama, Giuseppe C.; Cerruti, Pierfrancesco; Ambrogi, Veronica; Fernández-Francos, Xavier; De la Flor, Silvia

2018-07-01

In this work, free-standing shape-memory thermally triggered actuators are developed by laminating ‘thiol-epoxy’-based glassy thermoset (GT) and stretched liquid-crystalline network (LCN) films. A sequential curing process was used to obtain GTs with tailored thermomechanical properties and network relaxation dynamics, and also to assemble the final actuator. The actuation extent, rate and time were studied by varying the GT and the heating rate in thermo-actuation with an experimental approach. The results demonstrate that it is possible to tailor the actuation rate and time by designing GT materials with a glass transition temperature close to that of the liquid-crystalline-to-isotropic phase transition of the LCN, thus making it possible to couple the two processes. Such coupling is also possible in rapid heating processes even when the glass transition temperature of the GT is clearly lower than the isotropization temperature of the LCN, depending on the network relaxation dynamics of the GT and the presence of thermal gradients within the actuators. Interestingly, varying the GT network relaxation dynamics does not affect the actuation extent. As predicted by the analytical model developed in our previous work, the modulus of the GT layer is mainly responsible for the actuation extent. Finally, to demonstrate the enhanced control of the actuation, specifically designed actuators were assembled in a three-dimensional actuating device able to make complex motions (including ‘S-type’ bending). This approach makes it possible to engineer advanced functional materials for application in self-adaptable structures and soft robotics.

Response-cue interval effects in extended-runs task switching: memory, or monitoring?

PubMed

Altmann, Erik M

2017-09-26

This study investigated effects of manipulating the response-cue interval (RCI) in the extended-runs task-switching procedure. In this procedure, a task cue is presented at the start of a run of trials and then withdrawn, such that the task has to be stored in memory to guide performance until the next task cue is presented. The effects of the RCI manipulation were not as predicted by an existing model of memory processes in task switching (Altmann and Gray, Psychol Rev 115:602-639, 2008), suggesting that either the model is incorrect or the RCI manipulation did not have the intended effect. The manipulation did produce a theoretically meaningful pattern, in the form of a main effect on response time that was not accompanied by a similar effect on the error rate. This pattern, which replicated across two experiments, is interpreted here in terms of a process that monitors for the next task cue, with a longer RCI acting as a stronger signal that a cue is about to appear. The results have implications for the human factors of dynamic task environments in which critical events occur unpredictably.

Changing organizational structure and organizational memory in primary care practices: a qualitative interview study.

PubMed

Alyahya, Mohammad

2012-02-01

Organizational structure is built through dynamic processes which blend historical force and management decisions, as a part of a broader process of constructing organizational memory (OM). OM is considered to be one of the main competences leading to the organization's success. This study focuses on the impact of the Quality and Outcome Framework (QOF), which is a Pay-for-Performance scheme, on general practitioner (GP) practices in the UK. The study is based on semistructured interviews with four GP practices in the north of England involving 39 informants. The findings show that the way practices assigned different functions into specialized units, divisions or departments shows the degree of specialization in their organizational structures. More specialized unit arrangements, such as an IT division, particular chronic disease clinics or competence-based job distributions enhanced procedural memory development through enabling regular use of knowledge in specific context, which led to competence building. In turn, such competence at particular functions or jobs made it possible for the practices to achieve their goals more efficiently. This study concludes that organizational structure contributed strongly to the enhancement of OM, which in turn led to better organizational competence.

Intelligibility and Clarity of Reverberant Speech: Effects of Wide Dynamic Range Compression Release Time and Working Memory

ERIC Educational Resources Information Center

Reinhart, Paul N.; Souza, Pamela E.

2016-01-01

Purpose: The purpose of this study was to examine the effects of varying wide dynamic range compression (WDRC) release time on intelligibility and clarity of reverberant speech. The study also considered the role of individual working memory. Method: Thirty older listeners with mild to moderately-severe sloping sensorineural hearing loss…

Dynamic overset grid communication on distributed memory parallel processors

NASA Technical Reports Server (NTRS)

Barszcz, Eric; Weeratunga, Sisira K.; Meakin, Robert L.

1993-01-01

A parallel distributed memory implementation of intergrid communication for dynamic overset grids is presented. Included are discussions of various options considered during development. Results are presented comparing an Intel iPSC/860 to a single processor Cray Y-MP. Results for grids in relative motion show the iPSC/860 implementation to be faster than the Cray implementation.

Dynamic Testing, Working Memory, and Reading Comprehension Growth in Children with Reading Disabilities

ERIC Educational Resources Information Center

Swanson, H. Lee

2011-01-01

This longitudinal study assessed (a) whether performance changes in working memory (WM) as a function of dynamic testing were related to growth in reading comprehension and (b) whether WM performance among subgroups of children with reading disabilities (RD; children with RD only, children with both reading and arithmetic deficits, and low verbal…

Impact of Aging on the Dynamics of Memory Retrieval: A Time-Course Analysis

ERIC Educational Resources Information Center

Oztekin, Ilke; Gungor, Nur Zeynep; Badre, David

2012-01-01

The response-signal speed-accuracy trade-off (SAT) procedure was used to provide an in-depth investigation of the impact of aging on the dynamics of short-term memory retrieval. Young and older adults studied sequentially presented 3-item lists, immediately followed by a recognition probe. Analyses of composite list and serial position SAT…

Transitions to Chaos in a Seven-Equation Model of the Business Cycle with Income Redistribution and Private Debt

NASA Astrophysics Data System (ADS)

Colacchio, Giorgio

In the present paper, we investigate the chaotic implications of a seven-equation model of the business cycle. The main distinguishing features of the model are related to: (a) the role played by the bargaining power in the process of income redistribution; (b) the consideration of hysteresis effects on workers’ consumption demand; (c) the effect of public expenditure on labor productivity. In addition, the role played by the agents’ memory on the actual dynamics of the economic system, with particular regard to their learning-by-doing process, is particularly emphasized. Under all these assumptions, the system exhibits a rich and complex phenomenology, characterized by a number of transitions to chaos (in particular via sequences of period doubling bifurcations), aperiodic behavior, bistability, tristability, etc. We maintain that our analysis takes us another step forward in the building of a more general model of the business cycle. In particular, the model we propose may be of help in the explanation of some peculiar features of advanced capitalist economies, with particular regard to the role played by the State in the determination of agents’ disposable income, to the debt dynamics of the various macroagents, and to the main dilemmas of economic policy. More in general, the main lesson one learns from our investigation is that “disequilibrium paths”, characterized by “complicated” dynamics which, more often than not, takes the form of aperiodic motion, should be considered as the “normal” state of the system.

Analysis of a digital RF memory in a signal-delay application

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

Jelinek, D.A.

1992-03-01

Laboratory simulation of the approach of a radar fuze towards a target is an important factor in our ability to accurately measure the radar's performance. This simulation is achieved, in part, by dynamically delaying and attenuating the radar's transmitted pulse and sending the result back to the radar's receiver. Historically, the device used to perform the dynamic delay has been a limiting factor in the evaluation of a radar's performance and characteristics. A new device has been proposed that appears to have more capability than previous dynamic delay devices. This device is the digital RF memory. This report presents themore » results of an analysis of a digital RF memory used in a signal-delay application. 2 refs.« less

From Contextual Fear to a Dynamic View of Memory Systems

PubMed Central

Fanselow, Michael S

2009-01-01

The brain does not learn and remember in a unitary fashion. Rather, different circuits specialize in certain classes of problems and encode different types of information. Damage to one of these systems typically results in amnesia only for the form of memory that is the affected region's specialty. How does the brain allocate a specific category of memory to a particular circuit? This question has received little attention. The currently dominant view, Multiple Memory Systems Theory, assumes that such abilities are hard-wired. Using fear conditioning as a paradigmatic case, I propose an alternative model in which mnemonic processing is allocated to specific circuits through a dynamic process. Potential circuits compete to form memories with the most efficient circuits emerging as winners. However, alternate circuits compensate when these “primary” circuits are compromised. PMID:19939724

An UV photochromic memory effect in proton-based WO3 electrochromic devices

NASA Astrophysics Data System (ADS)

Zhang, Yong; Lee, S.-H.; Mascarenhas, A.; Deb, S. K.

2008-11-01

We report an UV photochromic memory effect on a standard proton-based WO3 electrochromic device. It exhibits two memory states, associated with the colored and bleached states of the device, respectively. Such an effect can be used to enhance device performance (increasing the dynamic range), re-energize commercial electrochromic devices, and develop memory devices.

Understanding original antigenic sin in influenza with a dynamical system.

PubMed

Pan, Keyao

2011-01-01

Original antigenic sin is the phenomenon in which prior exposure to an antigen leads to a subsequent suboptimal immune response to a related antigen. Immune memory normally allows for an improved and rapid response to antigens previously seen and is the mechanism by which vaccination works. I here develop a dynamical system model of the mechanism of original antigenic sin in influenza, clarifying and explaining the detailed spin-glass treatment of original antigenic sin. The dynamical system describes the viral load, the quantities of healthy and infected epithelial cells, the concentrations of naïve and memory antibodies, and the affinities of naïve and memory antibodies. I give explicit correspondences between the microscopic variables of the spin-glass model and those of the present dynamical system model. The dynamical system model reproduces the phenomenon of original antigenic sin and describes how a competition between different types of B cells compromises the overall effect of immune response. I illustrate the competition between the naïve and the memory antibodies as a function of the antigenic distance between the initial and subsequent antigens. The suboptimal immune response caused by original antigenic sin is observed when the host is exposed to an antigen which has intermediate antigenic distance to a second antigen previously recognized by the host's immune system.

Cyclic Nucleotide-Gated Channels, Calmodulin, Adenylyl Cyclase, and Calcium/Calmodulin-Dependent Protein Kinase II Are Required for Late, but Not Early, Long-Term Memory Formation in the Honeybee

ERIC Educational Resources Information Center

Matsumoto, Yukihisa; Sandoz, Jean-Christophe; Devaud, Jean-Marc; Lormant, Flore; Mizunami, Makoto; Giurfa, Martin

2014-01-01

Memory is a dynamic process that allows encoding, storage, and retrieval of information acquired through individual experience. In the honeybee "Apis mellifera," olfactory conditioning of the proboscis extension response (PER) has shown that besides short-term memory (STM) and mid-term memory (MTM), two phases of long-term memory (LTM)…

Memory Transformation Enhances Reinforcement Learning in Dynamic Environments.

PubMed

Santoro, Adam; Frankland, Paul W; Richards, Blake A

2016-11-30

Over the course of systems consolidation, there is a switch from a reliance on detailed episodic memories to generalized schematic memories. This switch is sometimes referred to as "memory transformation." Here we demonstrate a previously unappreciated benefit of memory transformation, namely, its ability to enhance reinforcement learning in a dynamic environment. We developed a neural network that is trained to find rewards in a foraging task where reward locations are continuously changing. The network can use memories for specific locations (episodic memories) and statistical patterns of locations (schematic memories) to guide its search. We find that switching from an episodic to a schematic strategy over time leads to enhanced performance due to the tendency for the reward location to be highly correlated with itself in the short-term, but regress to a stable distribution in the long-term. We also show that the statistics of the environment determine the optimal utilization of both types of memory. Our work recasts the theoretical question of why memory transformation occurs, shifting the focus from the avoidance of memory interference toward the enhancement of reinforcement learning across multiple timescales. As time passes, memories transform from a highly detailed state to a more gist-like state, in a process called "memory transformation." Theories of memory transformation speak to its advantages in terms of reducing memory interference, increasing memory robustness, and building models of the environment. However, the role of memory transformation from the perspective of an agent that continuously acts and receives reward in its environment is not well explored. In this work, we demonstrate a view of memory transformation that defines it as a way of optimizing behavior across multiple timescales. Copyright © 2016 the authors 0270-6474/16/3612228-15$15.00/0.

Two-level main memory co-design: Multi-threaded algorithmic primitives, analysis, and simulation

DOE PAGES

Bender, Michael A.; Berry, Jonathan W.; Hammond, Simon D.; ...

2017-01-03

A challenge in computer architecture is that processors often cannot be fed data from DRAM as fast as CPUs can consume it. Therefore, many applications are memory-bandwidth bound. With this motivation and the realization that traditional architectures (with all DRAM reachable only via bus) are insufficient to feed groups of modern processing units, vendors have introduced a variety of non-DDR 3D memory technologies (Hybrid Memory Cube (HMC),Wide I/O 2, High Bandwidth Memory (HBM)). These offer higher bandwidth and lower power by stacking DRAM chips on the processor or nearby on a silicon interposer. We will call these solutions “near-memory,” andmore » if user-addressable, “scratchpad.” High-performance systems on the market now offer two levels of main memory: near-memory on package and traditional DRAM further away. In the near term we expect the latencies near-memory and DRAM to be similar. Here, it is natural to think of near-memory as another module on the DRAM level of the memory hierarchy. Vendors are expected to offer modes in which the near memory is used as cache, but we believe that this will be inefficient.« less

A weak electric field-assisted ultrafast electrical switching dynamics in In3SbTe2 phase-change memory devices

NASA Astrophysics Data System (ADS)

Pandey, Shivendra Kumar; Manivannan, Anbarasu

2017-07-01

Prefixing a weak electric field (incubation) might enhance the crystallization speed via pre-structural ordering and thereby achieving faster programming of phase change memory (PCM) devices. We employed a weak electric field, equivalent to a constant small voltage (that is incubation voltage, Vi of 0.3 V) to the applied voltage pulse, VA (main pulse) for a systematic understanding of voltage-dependent rapid threshold switching characteristics and crystallization (set) process of In3SbTe2 (IST) PCM devices. Our experimental results on incubation-assisted switching elucidate strikingly one order faster threshold switching, with an extremely small delay time, td of 300 ps, as compared with no incubation voltage (Vi = 0 V) for the same VA. Also, the voltage dependent characteristics of incubation-assisted switching dynamics confirm that the initiation of threshold switching occurs at a lower voltage of 0.82 times of VA. Furthermore, we demonstrate an incubation assisted ultrafast set process of IST device for a low VA of 1.7 V (˜18 % lesser compared to without incubation) within a short pulse-width of 1.5 ns (full width half maximum, FWHM). These findings of ultrafast switching, yet low power set process would immensely be helpful towards designing high speed PCM devices with low power operation.

The Importance of Encoding-Related Neural Dynamics in the Prediction of Inter-Individual Differences in Verbal Working Memory Performance

PubMed Central

Majerus, Steve; Salmon, Eric; Attout, Lucie

2013-01-01

Studies of brain-behaviour interactions in the field of working memory (WM) have associated WM success with activation of a fronto-parietal network during the maintenance stage, and this mainly for visuo-spatial WM. Using an inter-individual differences approach, we demonstrate here the equal importance of neural dynamics during the encoding stage, and this in the context of verbal WM tasks which are characterized by encoding phases of long duration and sustained attentional demands. Participants encoded and maintained 5-word lists, half of them containing an unexpected word intended to disturb WM encoding and associated task-related attention processes. We observed that inter-individual differences in WM performance for lists containing disturbing stimuli were related to activation levels in a region previously associated with task-related attentional processing, the left intraparietal sulcus (IPS), and this during stimulus encoding but not maintenance; functional connectivity strength between the left IPS and lateral prefrontal cortex (PFC) further predicted WM performance. This study highlights the critical role, during WM encoding, of neural substrates involved in task-related attentional processes for predicting inter-individual differences in verbal WM performance, and, more generally, provides support for attention-based models of WM. PMID:23874935

Memory in Microbes: Quantifying History-Dependent Behavior in a Bacterium

PubMed Central

Bischofs, Ilka; Price, Gavin; Keasling, Jay; Arkin, Adam P.

2008-01-01

Memory is usually associated with higher organisms rather than bacteria. However, evidence is mounting that many regulatory networks within bacteria are capable of complex dynamics and multi-stable behaviors that have been linked to memory in other systems. Moreover, it is recognized that bacteria that have experienced different environmental histories may respond differently to current conditions. These “memory” effects may be more than incidental to the regulatory mechanisms controlling acclimation or to the status of the metabolic stores. Rather, they may be regulated by the cell and confer fitness to the organism in the evolutionary game it participates in. Here, we propose that history-dependent behavior is a potentially important manifestation of memory, worth classifying and quantifying. To this end, we develop an information-theory based conceptual framework for measuring both the persistence of memory in microbes and the amount of information about the past encoded in history-dependent dynamics. This method produces a phenomenological measure of cellular memory without regard to the specific cellular mechanisms encoding it. We then apply this framework to a strain of Bacillus subtilis engineered to report on commitment to sporulation and degradative enzyme (AprE) synthesis and estimate the capacity of these systems and growth dynamics to ‘remember’ 10 distinct cell histories prior to application of a common stressor. The analysis suggests that B. subtilis remembers, both in short and long term, aspects of its cell history, and that this memory is distributed differently among the observables. While this study does not examine the mechanistic bases for memory, it presents a framework for quantifying memory in cellular behaviors and is thus a starting point for studying new questions about cellular regulation and evolutionary strategy. PMID:18324309

Precision Quantum Control and Error-Suppressing Quantum Firmware for Robust Quantum Computing

DTIC Science & Technology

2014-09-24

Biercuk, Lorenza Viola. Long-time Low - latency Quantum Memory by Dynamical Decoupling, arXiv:1206.6087v1 (06 2012) L. Viola, G. A. Paz-Silva . A...International Patent Application (PCT/AU2013/000649) D. Hayes, K. Khodjasteh L. Viola, M.J. Biercuk, “Long-time low - latency quantum memory by dynamical...Khodjasteh L. Viola, M.J. Biercuk, University of Sydney A28 Physics Road Sydney NS 2006 Long-time low - latency quantum membory by dynamical decoupling

Neuromorphic Implementation of Attractor Dynamics in a Two-Variable Winner-Take-All Circuit with NMDARs: A Simulation Study

PubMed Central

You, Hongzhi; Wang, Da-Hui

2017-01-01

Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems. PMID:28223913

Neuromorphic Implementation of Attractor Dynamics in a Two-Variable Winner-Take-All Circuit with NMDARs: A Simulation Study.

PubMed

You, Hongzhi; Wang, Da-Hui

2017-01-01

Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems.

An abstraction layer for efficient memory management of tabulated chemistry and flamelet solutions

NASA Astrophysics Data System (ADS)

Weise, Steffen; Messig, Danny; Meyer, Bernd; Hasse, Christian

2013-06-01

A large number of methods for simulating reactive flows exist, some of them, for example, directly use detailed chemical kinetics or use precomputed and tabulated flame solutions. Both approaches couple the research fields computational fluid dynamics and chemistry tightly together using either an online or offline approach to solve the chemistry domain. The offline approach usually involves a method of generating databases or so-called Lookup-Tables (LUTs). As these LUTs are extended to not only contain material properties but interactions between chemistry and turbulent flow, the number of parameters and thus dimensions increases. Given a reasonable discretisation, file sizes can increase drastically. The main goal of this work is to provide methods that handle large database files efficiently. A Memory Abstraction Layer (MAL) has been developed that handles requested LUT entries efficiently by splitting the database file into several smaller blocks. It keeps the total memory usage at a minimum using thin allocation methods and compression to minimise filesystem operations. The MAL has been evaluated using three different test cases. The first rather generic one is a sequential reading operation on an LUT to evaluate the runtime behaviour as well as the memory consumption of the MAL. The second test case is a simulation of a non-premixed turbulent flame, the so-called HM1 flame, which is a well-known test case in the turbulent combustion community. The third test case is a simulation of a non-premixed laminar flame as described by McEnally in 1996 and Bennett in 2000. Using the previously developed solver 'flameletFoam' in conjunction with the MAL, memory consumption and the performance penalty introduced were studied. The total memory used while running a parallel simulation was reduced significantly while the CPU time overhead associated with the MAL remained low.

k(+)-buffer: An Efficient, Memory-Friendly and Dynamic k-buffer Framework.

PubMed

Vasilakis, Andreas-Alexandros; Papaioannou, Georgios; Fudos, Ioannis

2015-06-01

Depth-sorted fragment determination is fundamental for a host of image-based techniques which simulates complex rendering effects. It is also a challenging task in terms of time and space required when rasterizing scenes with high depth complexity. When low graphics memory requirements are of utmost importance, k-buffer can objectively be considered as the most preferred framework which advantageously ensures the correct depth order on a subset of all generated fragments. Although various alternatives have been introduced to partially or completely alleviate the noticeable quality artifacts produced by the initial k-buffer algorithm in the expense of memory increase or performance downgrade, appropriate tools to automatically and dynamically compute the most suitable value of k are still missing. To this end, we introduce k(+)-buffer, a fast framework that accurately simulates the behavior of k-buffer in a single rendering pass. Two memory-bounded data structures: (i) the max-array and (ii) the max-heap are developed on the GPU to concurrently maintain the k-foremost fragments per pixel by exploring pixel synchronization and fragment culling. Memory-friendly strategies are further introduced to dynamically (a) lessen the wasteful memory allocation of individual pixels with low depth complexity frequencies, (b) minimize the allocated size of k-buffer according to different application goals and hardware limitations via a straightforward depth histogram analysis and (c) manage local GPU cache with a fixed-memory depth-sorting mechanism. Finally, an extensive experimental evaluation is provided demonstrating the advantages of our work over all prior k-buffer variants in terms of memory usage, performance cost and image quality.

IOPS advisor: Research in progress on knowledge-intensive methods for irregular operations airline scheduling

NASA Technical Reports Server (NTRS)

Borse, John E.; Owens, Christopher C.

1992-01-01

Our research focuses on the problem of recovering from perturbations in large-scale schedules, specifically on the ability of a human-machine partnership to dynamically modify an airline schedule in response to unanticipated disruptions. This task is characterized by massive interdependencies and a large space of possible actions. Our approach is to apply the following: qualitative, knowledge-intensive techniques relying on a memory of stereotypical failures and appropriate recoveries; and quantitative techniques drawn from the Operations Research community's work on scheduling. Our main scientific challenge is to represent schedules, failures, and repairs so as to make both sets of techniques applicable to the same data. This paper outlines ongoing research in which we are cooperating with United Airlines to develop our understanding of the scientific issues underlying the practicalities of dynamic, real-time schedule repair.

Multilevel Resistance Programming in Conductive Bridge Resistive Memory

NASA Astrophysics Data System (ADS)

Mahalanabis, Debayan

This work focuses on the existence of multiple resistance states in a type of emerging non-volatile resistive memory device known commonly as Programmable Metallization Cell (PMC) or Conductive Bridge Random Access Memory (CBRAM), which can be important for applications such as multi-bit memory as well as non-volatile logic and neuromorphic computing. First, experimental data from small signal, quasi-static and pulsed mode electrical characterization of such devices are presented which clearly demonstrate the inherent multi-level resistance programmability property in CBRAM devices. A physics based analytical CBRAM compact model is then presented which simulates the ion-transport dynamics and filamentary growth mechanism that causes resistance change in such devices. Simulation results from the model are fitted to experimental dynamic resistance switching characteristics. The model designed using Verilog-a language is computation-efficient and can be integrated with industry standard circuit simulation tools for design and analysis of hybrid circuits involving both CMOS and CBRAM devices. Three main circuit applications for CBRAM devices are explored in this work. Firstly, the susceptibility of CBRAM memory arrays to single event induced upsets is analyzed via compact model simulation and experimental heavy ion testing data that show possibility of both high resistance to low resistance and low resistance to high resistance transitions due to ion strikes. Next, a non-volatile sense amplifier based flip-flop architecture is proposed which can help make leakage power consumption negligible by allowing complete shutdown of power supply while retaining its output data in CBRAM devices. Reliability and energy consumption of the flip-flop circuit for different CBRAM low resistance levels and supply voltage values are analyzed and compared to CMOS designs. Possible extension of this architecture for threshold logic function computation using the CBRAM devices as re-configurable resistive weights is also discussed. Lastly, Spike timing dependent plasticity (STDP) based gradual resistance change behavior in CBRAM device fabricated in back-end-of-line on a CMOS die containing integrate and fire CMOS neuron circuits is demonstrated for the first time which indicates the feasibility of using CBRAM devices as electronic synapses in spiking neural network hardware implementations for non-Boolean neuromorphic computing.

Fast dynamics in glass-forming polymers revisited

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

Colmenero, J.; Arbe, A.; Mijangos, C.

1997-12-31

The so called fast-dynamics of glass-forming systems as observed by time of flight (TOF) neutron scattering techniques is revisited. TOF-results corresponding to several glass-forming polymers with different chemical microstructure and glass-transition temperature are presented together with the theoretical framework proposed by the authors to interpret these results. The main conclusion is that the TOF-data can be explained in terms of quasiharmonic vibrations and the particular short time behavior of the segmental dynamics. The segmental dynamics display in the very short time range (t {approx} 2 ps) a crossover from a simple exponential behavior towards a non-exponential regime. The first exponentialmore » decay, which is controlled by C-C rotational barriers, can be understood as a trace of the behavior of the system in absence of the effects (correlations, cooperativity, memory effects {hor_ellipsis}) which characterize the dense supercooled liquid like state against the normal liquid state. The non-exponential regime at t > 2 ps corresponds to what is usually understood as {alpha} and {beta} relaxations. Some implications of these results are also discussed.« less

Significantly enhanced memory effect in metallic glass by multistep training

NASA Astrophysics Data System (ADS)

Li, M. X.; Luo, P.; Sun, Y. T.; Wen, P.; Bai, H. Y.; Liu, Y. H.; Wang, W. H.

2017-11-01

The state of metastable equilibrium glass can carry an imprint of the past and exhibit memory effect. As a hallmark of glassy dynamics, memory effect can affect glassy behavior as it evolves further upon time. Even though the physical picture of the memory effect has been well studied, it is unclear whether a glass can recall as many pieces of information as possible, and if so, how the glass will accordingly behave. We report that by fractionizing temperature interval, inserting multistep aging protocols, and optimizing the time of each temperature step, i.e., by imposing a multistep "training" on a prototypical P d40N i10C u30P20 metallic glass, the memory of the trained glass can be significantly strengthened, marked by a pronounced augment in potential energy. These findings provide a new guide for regulating the energy state of glass by enhancing the nonequilibrium behaviors of the memory effect and offer an opportunity to develop a clearer physical picture of glassy dynamics.

Task set induces dynamic reallocation of resources in visual short-term memory.

PubMed

Sheremata, Summer L; Shomstein, Sarah

2017-08-01

Successful interaction with the environment requires the ability to flexibly allocate resources to different locations in the visual field. Recent evidence suggests that visual short-term memory (VSTM) resources are distributed asymmetrically across the visual field based upon task demands. Here, we propose that context, rather than the stimulus itself, determines asymmetrical distribution of VSTM resources. To test whether context modulates the reallocation of resources to the right visual field, task set, defined by memory-load, was manipulated to influence visual short-term memory performance. Performance was measured for single-feature objects embedded within predominantly single- or two-feature memory blocks. Therefore, context was varied to determine whether task set directly predicts changes in visual field biases. In accord with the dynamic reallocation of resources hypothesis, task set, rather than aspects of the physical stimulus, drove improvements in performance in the right- visual field. Our results show, for the first time, that preparation for upcoming memory demands directly determines how resources are allocated across the visual field.

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.

Dendritic spine dynamics in synaptogenesis after repeated LTP inductions: Dependence on pre-existing spine density

PubMed Central

Oe, Yuki; Tominaga-Yoshino, Keiko; Hasegawa, Sho; Ogura, Akihiko

2013-01-01

Not only from our daily experience but from learning experiments in animals, we know that the establishment of long-lasting memory requires repeated practice. However, cellular backgrounds underlying this repetition-dependent consolidation of memory remain largely unclear. We reported previously using organotypic slice cultures of rodent hippocampus that the repeated inductions of LTP (long-term potentiation) lead to a slowly developing long-lasting synaptic enhancement accompanied by synaptogenesis distinct from LTP itself, and proposed this phenomenon as a model system suitable for the analysis of the repetition-dependent consolidation of memory. Here we examined the dynamics of individual dendritic spines after repeated LTP-inductions and found the existence of two phases in the spines' stochastic behavior that eventually lead to the increase in spine density. This spine dynamics occurred preferentially in the dendritic segments having low pre-existing spine density. Our results may provide clues for understanding the cellular bases underlying the repetition-dependent consolidation of memory. PMID:23739837

Extended Plefka expansion for stochastic dynamics

NASA Astrophysics Data System (ADS)

Bravi, B.; Sollich, P.; Opper, M.

2016-05-01

We propose an extension of the Plefka expansion, which is well known for the dynamics of discrete spins, to stochastic differential equations with continuous degrees of freedom and exhibiting generic nonlinearities. The scenario is sufficiently general to allow application to e.g. biochemical networks involved in metabolism and regulation. The main feature of our approach is to constrain in the Plefka expansion not just first moments akin to magnetizations, but also second moments, specifically two-time correlations and responses for each degree of freedom. The end result is an effective equation of motion for each single degree of freedom, where couplings to other variables appear as a self-coupling to the past (i.e. memory term) and a coloured noise. This constitutes a new mean field approximation that should become exact in the thermodynamic limit of a large network, for suitably long-ranged couplings. For the analytically tractable case of linear dynamics we establish this exactness explicitly by appeal to spectral methods of random matrix theory, for Gaussian couplings with arbitrary degree of symmetry.

An ultrafast programmable electrical tester for enabling time-resolved, sub-nanosecond switching dynamics and programming of nanoscale memory devices.

PubMed

Shukla, Krishna Dayal; Saxena, Nishant; Manivannan, Anbarasu

2017-12-01

Recent advancements in commercialization of high-speed non-volatile electronic memories including phase change memory (PCM) have shown potential not only for advanced data storage but also for novel computing concepts. However, an in-depth understanding on ultrafast electrical switching dynamics is a key challenge for defining the ultimate speed of nanoscale memory devices that demands for an unconventional electrical setup, specifically capable of handling extremely fast electrical pulses. In the present work, an ultrafast programmable electrical tester (PET) setup has been developed exceptionally for unravelling time-resolved electrical switching dynamics and programming characteristics of nanoscale memory devices at the picosecond (ps) time scale. This setup consists of novel high-frequency contact-boards carefully designed to capture extremely fast switching transient characteristics within 200 ± 25 ps using time-resolved current-voltage measurements. All the instruments in the system are synchronized using LabVIEW, which helps to achieve various programming characteristics such as voltage-dependent transient parameters, read/write operations, and endurance test of memory devices systematically using short voltage pulses having pulse parameters varied from 1 ns rise/fall time and 1.5 ns pulse width (full width half maximum). Furthermore, the setup has successfully demonstrated strikingly one order faster switching characteristics of Ag 5 In 5 Sb 60 Te 30 (AIST) PCM devices within 250 ps. Hence, this novel electrical setup would be immensely helpful for realizing the ultimate speed limits of various high-speed memory technologies for future computing.

An ultrafast programmable electrical tester for enabling time-resolved, sub-nanosecond switching dynamics and programming of nanoscale memory devices

NASA Astrophysics Data System (ADS)

Shukla, Krishna Dayal; Saxena, Nishant; Manivannan, Anbarasu

2017-12-01

Recent advancements in commercialization of high-speed non-volatile electronic memories including phase change memory (PCM) have shown potential not only for advanced data storage but also for novel computing concepts. However, an in-depth understanding on ultrafast electrical switching dynamics is a key challenge for defining the ultimate speed of nanoscale memory devices that demands for an unconventional electrical setup, specifically capable of handling extremely fast electrical pulses. In the present work, an ultrafast programmable electrical tester (PET) setup has been developed exceptionally for unravelling time-resolved electrical switching dynamics and programming characteristics of nanoscale memory devices at the picosecond (ps) time scale. This setup consists of novel high-frequency contact-boards carefully designed to capture extremely fast switching transient characteristics within 200 ± 25 ps using time-resolved current-voltage measurements. All the instruments in the system are synchronized using LabVIEW, which helps to achieve various programming characteristics such as voltage-dependent transient parameters, read/write operations, and endurance test of memory devices systematically using short voltage pulses having pulse parameters varied from 1 ns rise/fall time and 1.5 ns pulse width (full width half maximum). Furthermore, the setup has successfully demonstrated strikingly one order faster switching characteristics of Ag5In5Sb60Te30 (AIST) PCM devices within 250 ps. Hence, this novel electrical setup would be immensely helpful for realizing the ultimate speed limits of various high-speed memory technologies for future computing.

Dynamics of social contagions with memory of nonredundant information

NASA Astrophysics Data System (ADS)

Wang, Wei; Tang, Ming; Zhang, Hai-Feng; Lai, Ying-Cheng

2015-07-01

A key ingredient in social contagion dynamics is reinforcement, as adopting a certain social behavior requires verification of its credibility and legitimacy. Memory of nonredundant information plays an important role in reinforcement, which so far has eluded theoretical analysis. We first propose a general social contagion model with reinforcement derived from nonredundant information memory. Then, we develop a unified edge-based compartmental theory to analyze this model, and a remarkable agreement with numerics is obtained on some specific models. We use a spreading threshold model as a specific example to understand the memory effect, in which each individual adopts a social behavior only when the cumulative pieces of information that the individual received from his or her neighbors exceeds an adoption threshold. Through analysis and numerical simulations, we find that the memory characteristic markedly affects the dynamics as quantified by the final adoption size. Strikingly, we uncover a transition phenomenon in which the dependence of the final adoption size on some key parameters, such as the transmission probability, can change from being discontinuous to being continuous. The transition can be triggered by proper parameters and structural perturbations to the system, such as decreasing individuals' adoption threshold, increasing initial seed size, or enhancing the network heterogeneity.

Spatial and temporal dynamics of cortical networks engaged in memory encoding and retrieval

PubMed Central

Miller, Brian T.; D'Esposito, Mark

2012-01-01

Memory operations such as encoding and retrieval require the coordinated interplay of cortical regions with distinct functional contributions. The mechanistic nature of these interactions, however, remains unspecified. During the performance of a face memory task during fMRI scanning, we measured the magnitude (a measure of the strength of coupling between areas) and phase (a measure of the relative timing across areas) of coherence between regions of interest and the rest of the brain. The fusiform face area (FFA) showed robust coherence with a distributed network of subregions in the prefrontal cortex (PFC), posterior parietal cortex (PPC), precuneus, and hippocampus across both memory operations. While these findings reveal significant overlap in the cortical networks underlying mnemonic encoding and retrieval, coherence phase analyses revealed context-dependent differences in cortical dynamics. During both encoding and retrieval, PFC and PPC exhibited earlier activity than in the FFA and hippocampus. Also, during retrieval, PFC activity preceded PPC activity. These findings are consistent with prior physiology studies suggesting an early contribution of PFC and PPC in mnemonic control. Together, these findings contribute to the growing literature exploring the spatio-temporal dynamics of basic memory operations. PMID:22557959

An approach to predict the shape-memory behavior of amorphous polymers from Dynamic Mechanical Analysis (DMA) data

NASA Astrophysics Data System (ADS)

Kuki, Ákos; Czifrák, Katalin; Karger-Kocsis, József; Zsuga, Miklós; Kéki, Sándor

2015-02-01

The prediction of shape-memory behavior is essential regarding the design of a smart material for different applications. This paper proposes a simple and quick method for the prediction of shape-memory behavior of amorphous shape memory polymers (SMPs) on the basis of a single dynamic mechanical analysis (DMA) temperature sweep at constant frequency. All the parameters of the constitutive equations for linear viscoelasticity are obtained by fitting the DMA curves. The change with the temperature of the time-temperature superposition shift factor ( a T ) is expressed by the Williams-Landel-Ferry (WLF) model near and above the glass transition temperature ( T g ), and by the Arrhenius law below T g . The constants of the WLF and Arrhenius equations can also be determined. The results of our calculations agree satisfactorily with the experimental free recovery curves from shape-memory tests.

Time Constraints and Resource Sharing in Adults' Working Memory Spans

ERIC Educational Resources Information Center

Barrouillet, Pierre; Bernardin, Sophie; Camos, Valerie

2004-01-01

This article presents a new model that accounts for working memory spans in adults, the time-based resource-sharing model. The model assumes that both components (i.e., processing and maintenance) of the main working memory tasks require attention and that memory traces decay as soon as attention is switched away. Because memory retrievals are…

Reconsolidation of a Well-Learned Instrumental Memory

ERIC Educational Resources Information Center

Exton-McGuinness, Marc T. J.; Patton, Rosemary C.; Sacco, Lawrence B.; Lee, Jonathan L. C.

2014-01-01

Once consolidated, memories are dynamic entities that go through phases of instability in order to be updated with new information, via a process of reconsolidation. The phenomenon of reconsolidation has been demonstrated in a wide variety of experimental paradigms. However, the memories underpinning instrumental behaviors are currently not…

Aging, memory, and nonhierarchical energy landscape of spin jam

NASA Astrophysics Data System (ADS)

Samarakoon, Anjana; Sato, Taku J.; Chen, Tianran; Chern, Gai-Wei; Yang, Junjie; Klich, Israel; Sinclair, Ryan; Zhou, Haidong; Lee, Seung-Hun

2016-10-01

The notion of complex energy landscape underpins the intriguing dynamical behaviors in many complex systems ranging from polymers, to brain activity, to social networks and glass transitions. The spin glass state found in dilute magnetic alloys has been an exceptionally convenient laboratory frame for studying complex dynamics resulting from a hierarchical energy landscape with rugged funnels. Here, we show, by a bulk susceptibility and Monte Carlo simulation study, that densely populated frustrated magnets in a spin jam state exhibit much weaker memory effects than spin glasses, and the characteristic properties can be reproduced by a nonhierarchical landscape with a wide and nearly flat but rough bottom. Our results illustrate that the memory effects can be used to probe different slow dynamics of glassy materials, hence opening a window to explore their distinct energy landscapes.

Analysis of a digital RF memory in a signal-delay application

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

Jelinek, D.A.

1992-03-01

Laboratory simulation of the approach of a radar fuze towards a target is an important factor in our ability to accurately measure the radar`s performance. This simulation is achieved, in part, by dynamically delaying and attenuating the radar`s transmitted pulse and sending the result back to the radar`s receiver. Historically, the device used to perform the dynamic delay has been a limiting factor in the evaluation of a radar`s performance and characteristics. A new device has been proposed that appears to have more capability than previous dynamic delay devices. This device is the digital RF memory. This report presents themore » results of an analysis of a digital RF memory used in a signal-delay application. 2 refs.« less

Structural network heterogeneities and network dynamics: a possible dynamical mechanism for hippocampal memory reactivation.

NASA Astrophysics Data System (ADS)

Jablonski, Piotr; Poe, Gina; Zochowski, Michal

2007-03-01

The hippocampus has the capacity for reactivating recently acquired memories and it is hypothesized that one of the functions of sleep reactivation is the facilitation of consolidation of novel memory traces. The dynamic and network processes underlying such a reactivation remain, however, unknown. We show that such a reactivation characterized by local, self-sustained activity of a network region may be an inherent property of the recurrent excitatory-inhibitory network with a heterogeneous structure. The entry into the reactivation phase is mediated through a physiologically feasible regulation of global excitability and external input sources, while the reactivated component of the network is formed through induced network heterogeneities during learning. We show that structural changes needed for robust reactivation of a given network region are well within known physiological parameters.

Structural network heterogeneities and network dynamics: A possible dynamical mechanism for hippocampal memory reactivation

NASA Astrophysics Data System (ADS)

Jablonski, Piotr; Poe, Gina R.; Zochowski, Michal

2007-01-01

The hippocampus has the capacity for reactivating recently acquired memories and it is hypothesized that one of the functions of sleep reactivation is the facilitation of consolidation of novel memory traces. The dynamic and network processes underlying such a reactivation remain, however, unknown. We show that such a reactivation characterized by local, self-sustained activity of a network region may be an inherent property of the recurrent excitatory-inhibitory network with a heterogeneous structure. The entry into the reactivation phase is mediated through a physiologically feasible regulation of global excitability and external input sources, while the reactivated component of the network is formed through induced network heterogeneities during learning. We show that structural changes needed for robust reactivation of a given network region are well within known physiological parameters.

Individual Differences in Dynamic Functional Brain Connectivity across the Human Lifespan

PubMed Central

Davison, Elizabeth N.; Turner, Benjamin O.; Miller, Michael B.; Carlson, Jean M.

2016-01-01

Individual differences in brain functional networks may be related to complex personal identifiers, including health, age, and ability. Dynamic network theory has been used to identify properties of dynamic brain function from fMRI data, but the majority of analyses and findings remain at the level of the group. Here, we apply hypergraph analysis, a method from dynamic network theory, to quantify individual differences in brain functional dynamics. Using a summary metric derived from the hypergraph formalism—hypergraph cardinality—we investigate individual variations in two separate, complementary data sets. The first data set (“multi-task”) consists of 77 individuals engaging in four consecutive cognitive tasks. We observe that hypergraph cardinality exhibits variation across individuals while remaining consistent within individuals between tasks; moreover, the analysis of one of the memory tasks revealed a marginally significant correspondence between hypergraph cardinality and age. This finding motivated a similar analysis of the second data set (“age-memory”), in which 95 individuals, aged 18–75, performed a memory task with a similar structure to the multi-task memory task. With the increased age range in the age-memory data set, the correlation between hypergraph cardinality and age correspondence becomes significant. We discuss these results in the context of the well-known finding linking age with network structure, and suggest that hypergraph analysis should serve as a useful tool in furthering our understanding of the dynamic network structure of the brain. PMID:27880785

Spin-transfer torque magnetoresistive random-access memory technologies for normally off computing (invited)

NASA Astrophysics Data System (ADS)

Ando, K.; Fujita, S.; Ito, J.; Yuasa, S.; Suzuki, Y.; Nakatani, Y.; Miyazaki, T.; Yoda, H.

2014-05-01

Most parts of present computer systems are made of volatile devices, and the power to supply them to avoid information loss causes huge energy losses. We can eliminate this meaningless energy loss by utilizing the non-volatile function of advanced spin-transfer torque magnetoresistive random-access memory (STT-MRAM) technology and create a new type of computer, i.e., normally off computers. Critical tasks to achieve normally off computers are implementations of STT-MRAM technologies in the main memory and low-level cache memories. STT-MRAM technology for applications to the main memory has been successfully developed by using perpendicular STT-MRAMs, and faster STT-MRAM technologies for applications to the cache memory are now being developed. The present status of STT-MRAMs and challenges that remain for normally off computers are discussed.

[Anterograde declarative memory and its models].

PubMed

Barbeau, E-J; Puel, M; Pariente, J

2010-01-01

Patient H.M.'s recent death provides the opportunity to highlight the importance of his contribution to a better understanding of the anterograde amnesic syndrome. The thorough study of this patient over five decades largely contributed to shape the unitary model of declarative memory. This model holds that declarative memory is a single system that cannot be fractionated into subcomponents. As a system, it depends mainly on medial temporal lobes structures. The objective of this review is to present the main characteristics of different modular models that have been proposed as alternatives to the unitary model. It is also an opportunity to present different patients, who, although less famous than H.M., helped make signification contribution to the field of memory. The characteristics of the five main modular models are presented, including the most recent one (the perceptual-mnemonic model). The differences as well as how these models converge are highlighted. Different possibilities that could help reconcile unitary and modular approaches are considered. Although modular models differ significantly in many aspects, all converge to the notion that memory for single items and semantic memory could be dissociated from memory for complex material and context-rich episodes. In addition, these models converge concerning the involvement of critical brain structures for these stages: Item and semantic memory, as well as familiarity, are thought to largely depend on anterior subhippocampal areas, while relational, context-rich memory and recollective experiences are thought to largely depend on the hippocampal formation. Copyright © 2010 Elsevier Masson SAS. All rights reserved.

Functional and evolutionary trade-offs co-occur between two consolidated memory phases in Drosophila melanogaster

PubMed Central

Lagasse, Fabrice; Moreno, Celine; Preat, Thomas; Mery, Frederic

2012-01-01

Memory is a complex and dynamic process that is composed of different phases. Its evolution under natural selection probably depends on a balance between fitness benefits and costs. In Drosophila, two separate forms of consolidated memory phases can be generated experimentally: anaesthesia-resistant memory (ARM) and long-term memory (LTM). In recent years, several studies have focused on the differences between these long-lasting memory types and have found that, at the functional level, ARM and LTM are antagonistic. How this functional relationship will affect their evolutionary dynamics remains unknown. We selected for flies with either improved ARM or improved LTM over several generations, and found that flies selected specifically for improvement of one consolidated memory phase show reduced performance in the other memory phase. We also found that improved LTM was linked to decreased longevity in male flies but not in females. Conversely, males with improved ARM had increased longevity. We found no correlation between either improved ARM or LTM and other phenotypic traits. This is, to our knowledge, the first evidence of a symmetrical evolutionary trade-off between two memory phases for the same learning task. Such trade-offs may have an important impact on the evolution of cognitive capacities. On a neural level, these results support the hypothesis that mechanisms underlying these forms of consolidated memory are, to some degree, antagonistic. PMID:22859595

Neural Correlates of Odor Learning in the Presynaptic Microglomerular Circuitry in the Honeybee Mushroom Body Calyx.

PubMed

Haenicke, Joachim; Yamagata, Nobuhiro; Zwaka, Hanna; Nawrot, Martin; Menzel, Randolf

2018-01-01

The mushroom body (MB) in insects is known as a major center for associative learning and memory, although exact locations for the correlating memory traces remain to be elucidated. Here, we asked whether presynaptic boutons of olfactory projection neurons (PNs) in the main input site of the MB undergo neuronal plasticity during classical odor-reward conditioning and correlate with the conditioned behavior. We simultaneously measured Ca 2+ responses in the boutons and conditioned behavioral responses to learned odors in honeybees. We found that the absolute amount of the neural change for the rewarded but not for the unrewarded odor was correlated with the behavioral learning rate across individuals. The temporal profile of the induced changes matched with odor response dynamics of the MB-associated inhibitory neurons, suggestive of activity modulation of boutons by this neural class. We hypothesize the circuit-specific neural plasticity relates to the learned value of the stimulus and underlies the conditioned behavior of the bees.

Automatic humidification system to support the assessment of food drying processes

NASA Astrophysics Data System (ADS)

Ortiz Hernández, B. D.; Carreño Olejua, A. R.; Castellanos Olarte, J. M.

2016-07-01

This work shows the main features of an automatic humidification system to provide drying air that match environmental conditions of different climate zones. This conditioned air is then used to assess the drying process of different agro-industrial products at the Automation and Control for Agro-industrial Processes Laboratory of the Pontifical Bolivarian University of Bucaramanga, Colombia. The automatic system allows creating and improving control strategies to supply drying air under specified conditions of temperature and humidity. The development of automatic routines to control and acquire real time data was made possible by the use of robust control systems and suitable instrumentation. The signals are read and directed to a controller memory where they are scaled and transferred to a memory unit. Using the IP address is possible to access data to perform supervision tasks. One important characteristic of this automatic system is the Dynamic Data Exchange Server (DDE) to allow direct communication between the control unit and the computer used to build experimental curves.

Temporal Dynamics of Recovery from Extinction Shortly after Extinction Acquisition

ERIC Educational Resources Information Center

Archbold, Georgina E.; Dobbek, Nick; Nader, Karim

2013-01-01

Evidence suggests that extinction is new learning. Memory acquisition involves both short-term memory (STM) and long-term memory (LTM) components; however, few studies have examined early phases of extinction retention. Retention of auditory fear extinction was examined at various time points. Shortly (1-4 h) after extinction acquisition…

A Principal Components Analysis of Dynamic Spatial Memory Biases

ERIC Educational Resources Information Center

Motes, Michael A.; Hubbard, Timothy L.; Courtney, Jon R.; Rypma, Bart

2008-01-01

Research has shown that spatial memory for moving targets is often biased in the direction of implied momentum and implied gravity, suggesting that representations of the subjective experiences of these physical principles contribute to such biases. The present study examined the association between these spatial memory biases. Observers viewed…

Ferroelectric memory evaluation and development system

NASA Astrophysics Data System (ADS)

Bondurant, David W.

Attention is given to the Ramtron FEDS-1, an IBM PC/AT compatible single-board 16-b microcomputer with 8-kbyte program/data memory implemented with nonvolatile ferroelectric dynamic RAM. This is the first demonstration of a new type of solid state nonvolatile read/write memory, the ferroelectric RAM (FRAM). It is suggested that this memory technology will have a significant impact on avionics system performance and reliability.

Messier: A Detailed NVM-Based DIMM Model for the SST Simulation Framework.

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

Awad, Amro; Voskuilen, Gwendolyn Renae; Rodrigues, Arun F.

2017-02-01

DRAM technology is the main building block of main memory, however, DRAM scaling is becoming very challenging. The main issues for DRAM scaling are the increasing error rates with each new generation, the geometric and physical constraints of scaling the capacitor part of the DRAM cells, and the high power consumption caused by the continuous need for refreshing cell values. At the same time, emerging Non- Volatile Memory (NVM) technologies, such as Phase-Change Memory (PCM), are emerging as promising replacements for DRAM. NVMs, when compared to current technologies e.g., NAND-based ash, have latencies comparable to DRAM. Additionally, NVMs are non-volatile,more » which eliminates the need for refresh power and enables persistent memory applications. Finally, NVMs have promising densities and the potential for multi-level cell (MLC) storage.« less

The Sleep Elaboration-Awake Pruning (SEAP) theory of memory: long term memories grow in complexity during sleep and undergo selection while awake. Clinical, psychopharmacological and creative implications.

PubMed

Charlton, Bruce G; Andras, Peter

2009-07-01

Long term memory (LTM) systems need to be adaptive such that they enhance an organism's reproductive fitness and self-reproducing in order to maintain their complexity of communications over time in the face of entropic loss of information. Traditional 'representation-consolidation' accounts conceptualize memory adaptiveness as due to memories being 'representations' of the environment, and the longevity of memories as due to 'consolidation' processes. The assumption is that memory representations are formed while an animal is awake and interacting with the environment, and these memories are consolidated mainly while the animal is asleep. So the traditional view of memory is 'instructionist' and assumes that information is transferred from the environment into the brain. By contrast, we see memories as arising endogenously within the brain's LTM system mainly during sleep, to create complex but probably maladaptive memories which are then simplified ('pruned') and selected during the awake period. When awake the LTM system is brought into a more intense interaction with past and present experience. Ours is therefore a 'selectionist' account of memory, and could be termed the Sleep Elaboration-Awake Pruning (or SEAP) theory. The SEAP theory explains the longevity of memories in the face of entropy by the tendency for memories to grow in complexity during sleep; and explains the adaptiveness of memory by selection for consistency with perceptions and previous memories during the awake state. Sleep is therefore that behavioural state during which most of the internal processing of the system of LTM occurs; and the reason sleep remains poorly understood is that its primary activity is the expansion of long term memories. By re-conceptualizing the relationship between memory, sleep and the environment; SEAP provides a radically new framework for memory research, with implications for the measurement of memory and the design of empirical investigations in clinical, psychopharmacological and creative domains. For example, it would be predicted that states of insufficient alertness such as delirium would produce errors of commission (memory distortion and false memories, as with psychotic delusions), while sleep deprivation would produce errors of memory omission (memory loss). Ultimately, the main argument in favour of SEAP is that long term memory must be a complex adaptive system, and complex systems arise, are selected and sustained according to the principles of systems theory; and therefore LTM cannot be functioning in the way assumed by 'representation-consolidation' theories.

Attention and Memory for Faces and Actions in Infancy: The Salience of Actions over Faces in Dynamic Events.

ERIC Educational Resources Information Center

Bahrick, Lorraine E.; Gogate, Lakshmi J.; Ruiz, Ivonne

2002-01-01

Three experiments investigated discrimination and memory of 5.5-month-olds for videotapes of women performing different activities (blowing bubbles, brushing hair, brushing teeth) or static displays after a 1-minute and a 7-week delay. Findings demonstrate the attentional salience of actions over faces in dynamic events to 5.5-month-olds. Findings…

Sleep after Learning Aids Memory Recall

ERIC Educational Resources Information Center

Born, Jan; Gais, Steffen; Lucas, Brian

2006-01-01

In recent years, the effect of sleep on memory consolidation has received considerable attention. In humans, these studies concentrated mainly on procedural types of memory, which are considered to be hippocampus-independent. Here, we show that sleep also has a persisting effect on hippocampus-dependent declarative memory. In two experiments, we…

Controlling quantum memory-assisted entropic uncertainty in non-Markovian environments

NASA Astrophysics Data System (ADS)

Zhang, Yanliang; Fang, Maofa; Kang, Guodong; Zhou, Qingping

2018-03-01

Quantum memory-assisted entropic uncertainty relation (QMA EUR) addresses that the lower bound of Maassen and Uffink's entropic uncertainty relation (without quantum memory) can be broken. In this paper, we investigated the dynamical features of QMA EUR in the Markovian and non-Markovian dissipative environments. It is found that dynamical process of QMA EUR is oscillation in non-Markovian environment, and the strong interaction is favorable for suppressing the amount of entropic uncertainty. Furthermore, we presented two schemes by means of prior weak measurement and posterior weak measurement reversal to control the amount of entropic uncertainty of Pauli observables in dissipative environments. The numerical results show that the prior weak measurement can effectively reduce the wave peak values of the QMA-EUA dynamic process in non-Markovian environment for long periods of time, but it is ineffectual on the wave minima of dynamic process. However, the posterior weak measurement reversal has an opposite effects on the dynamic process. Moreover, the success probability entirely depends on the quantum measurement strength. We hope that our proposal could be verified experimentally and might possibly have future applications in quantum information processing.

INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization

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

Groer, Christopher S; Sullivan, Blair D; Weerapurage, Dinesh P

2012-10-01

It is well-known that dynamic programming algorithms can utilize tree decompositions to provide a way to solve some \\emph{NP}-hard problems on graphs where the complexity is polynomial in the number of nodes and edges in the graph, but exponential in the width of the underlying tree decomposition. However, there has been relatively little computational work done to determine the practical utility of such dynamic programming algorithms. We have developed software to construct tree decompositions using various heuristics and have created a fast, memory-efficient dynamic programming implementation for solving maximum weighted independent set. We describe our software and the algorithms wemore » have implemented, focusing on memory saving techniques for the dynamic programming. We compare the running time and memory usage of our implementation with other techniques for solving maximum weighted independent set, including a commercial integer programming solver and a semi-definite programming solver. Our results indicate that it is possible to solve some instances where the underlying decomposition has width much larger than suggested by the literature. For certain types of problems, our dynamic programming code runs several times faster than these other methods.« less

Stochastic dynamics of time correlation in complex systems with discrete time

NASA Astrophysics Data System (ADS)

Yulmetyev, Renat; Hänggi, Peter; Gafarov, Fail

2000-11-01

In this paper we present the concept of description of random processes in complex systems with discrete time. It involves the description of kinetics of discrete processes by means of the chain of finite-difference non-Markov equations for time correlation functions (TCFs). We have introduced the dynamic (time dependent) information Shannon entropy Si(t) where i=0,1,2,3,..., as an information measure of stochastic dynamics of time correlation (i=0) and time memory (i=1,2,3,...). The set of functions Si(t) constitute the quantitative measure of time correlation disorder (i=0) and time memory disorder (i=1,2,3,...) in complex system. The theory developed started from the careful analysis of time correlation involving dynamics of vectors set of various chaotic states. We examine two stochastic processes involving the creation and annihilation of time correlation (or time memory) in details. We carry out the analysis of vectors' dynamics employing finite-difference equations for random variables and the evolution operator describing their natural motion. The existence of TCF results in the construction of the set of projection operators by the usage of scalar product operation. Harnessing the infinite set of orthogonal dynamic random variables on a basis of Gram-Shmidt orthogonalization procedure tends to creation of infinite chain of finite-difference non-Markov kinetic equations for discrete TCFs and memory functions (MFs). The solution of the equations above thereof brings to the recurrence relations between the TCF and MF of senior and junior orders. This offers new opportunities for detecting the frequency spectra of power of entropy function Si(t) for time correlation (i=0) and time memory (i=1,2,3,...). The results obtained offer considerable scope for attack on stochastic dynamics of discrete random processes in a complex systems. Application of this technique on the analysis of stochastic dynamics of RR intervals from human ECG's shows convincing evidence for a non-Markovian phenomemena associated with a peculiarities in short- and long-range scaling. This method may be of use in distinguishing healthy from pathologic data sets based in differences in these non-Markovian properties.

The Memory of What We Do Not Recall: Dissociations and Theoretical Debates in the Study of Implicit Memory

ERIC Educational Resources Information Center

Ramos, Tania; Marques, João; Garcia-Marques, Leonel

2017-01-01

Implicit memory reflects itself on situations in which previously acquired information is expressed, without awareness or intention. The study of implicit memory has had a profound impact on how researchers have investigated the human memory. In this paper, we review the main studies which have revealed dissociations between direct and indirect…

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

Neurotoxic impact of mercury on the central nervous system evaluated by neuropsychological tests and on the autonomic nervous system evaluated by dynamic pupillometry.

PubMed

Milioni, Ana Luiza V; Nagy, Balázs V; Moura, Ana Laura A; Zachi, Elaine C; Barboni, Mirella T S; Ventura, Dora F

2017-03-01

Mercury vapor is highly toxic to the human body. The present study aimed to investigate the occurrence of neuropsychological dysfunction in former workers of fluorescent lamps factories that were exposed to mercury vapor (years after cessation of exposure), diagnosed with chronic mercurialism, and to investigate the effects of such exposure on the Autonomic Nervous System (ANS) using the non-invasive method of dynamic pupillometry. The exposed group and a control group matched by age and educational level were evaluated by the Beck Depression Inventory and with the computerized neuropsychological battery CANTABeclipse - subtests of working memory (Spatial Span), spatial memory (Spatial Recognition Memory), visual memory (Pattern Recognition Memory) and action planning (Stockings of Cambridge). The ANS was assessed by dynamic pupillometry, which provides information on the operation on both the sympathetic and parasympathetic functions. Depression scores were significantly higher among the former workers when compared with the control group. The exposed group also showed significantly worse performance in most of the cognitive functions assessed. In the dynamic pupillometry test, former workers showed significantly lower response than the control group in the sympathetic response parameter (time of 75% of pupillary recovery at 10cd/m 2 luminance). Our study found indications that are suggestive of cognitive deficits and losses in sympathetic autonomic activity among patients occupationally exposed to mercury vapor. Copyright © 2016 Elsevier B.V. All rights reserved.

From antenna to antenna: lateral shift of olfactory memory recall by honeybees.

PubMed

Rogers, Lesley J; Vallortigara, Giorgio

2008-06-04

Honeybees, Apis mellifera, readily learn to associate odours with sugar rewards and we show here that recall of the olfactory memory, as demonstrated by the bee extending its proboscis when presented with the trained odour, involves first the right and then the left antenna. At 1-2 hour after training using both antennae, recall is possible mainly when the bee uses its right antenna but by 6 hours after training a lateral shift has occurred and the memory can now be recalled mainly when the left antenna is in use. Long-term memory one day after training is also accessed mainly via the left antenna. This time-dependent shift from right to left antenna is also seen as side biases in responding to odour presented to the bee's left or right side. Hence, not only are the cellular events of memory formation similar in bees and vertebrate species but also the lateralized networks involved may be similar. These findings therefore seem to call for remarkable parallel evolution and suggest that the proper functioning of memory formation in a bilateral animal, either vertebrate or invertebrate, requires lateralization of processing.

Effective visual working memory capacity: an emergent effect from the neural dynamics in an attractor network.

PubMed

Dempere-Marco, Laura; Melcher, David P; Deco, Gustavo

2012-01-01

The study of working memory capacity is of outmost importance in cognitive psychology as working memory is at the basis of general cognitive function. Although the working memory capacity limit has been thoroughly studied, its origin still remains a matter of strong debate. Only recently has the role of visual saliency in modulating working memory storage capacity been assessed experimentally and proved to provide valuable insights into working memory function. In the computational arena, attractor networks have successfully accounted for psychophysical and neurophysiological data in numerous working memory tasks given their ability to produce a sustained elevated firing rate during a delay period. Here we investigate the mechanisms underlying working memory capacity by means of a biophysically-realistic attractor network with spiking neurons while accounting for two recent experimental observations: 1) the presence of a visually salient item reduces the number of items that can be held in working memory, and 2) visually salient items are commonly kept in memory at the cost of not keeping as many non-salient items. Our model suggests that working memory capacity is determined by two fundamental processes: encoding of visual items into working memory and maintenance of the encoded items upon their removal from the visual display. While maintenance critically depends on the constraints that lateral inhibition imposes to the mnemonic activity, encoding is limited by the ability of the stimulated neural assemblies to reach a sufficiently high level of excitation, a process governed by the dynamics of competition and cooperation among neuronal pools. Encoding is therefore contingent upon the visual working memory task and has led us to introduce the concept of effective working memory capacity (eWMC) in contrast to the maximal upper capacity limit only reached under ideal conditions.

Effective Visual Working Memory Capacity: An Emergent Effect from the Neural Dynamics in an Attractor Network

PubMed Central

Dempere-Marco, Laura; Melcher, David P.; Deco, Gustavo

2012-01-01

The study of working memory capacity is of outmost importance in cognitive psychology as working memory is at the basis of general cognitive function. Although the working memory capacity limit has been thoroughly studied, its origin still remains a matter of strong debate. Only recently has the role of visual saliency in modulating working memory storage capacity been assessed experimentally and proved to provide valuable insights into working memory function. In the computational arena, attractor networks have successfully accounted for psychophysical and neurophysiological data in numerous working memory tasks given their ability to produce a sustained elevated firing rate during a delay period. Here we investigate the mechanisms underlying working memory capacity by means of a biophysically-realistic attractor network with spiking neurons while accounting for two recent experimental observations: 1) the presence of a visually salient item reduces the number of items that can be held in working memory, and 2) visually salient items are commonly kept in memory at the cost of not keeping as many non-salient items. Our model suggests that working memory capacity is determined by two fundamental processes: encoding of visual items into working memory and maintenance of the encoded items upon their removal from the visual display. While maintenance critically depends on the constraints that lateral inhibition imposes to the mnemonic activity, encoding is limited by the ability of the stimulated neural assemblies to reach a sufficiently high level of excitation, a process governed by the dynamics of competition and cooperation among neuronal pools. Encoding is therefore contingent upon the visual working memory task and has led us to introduce the concept of effective working memory capacity (eWMC) in contrast to the maximal upper capacity limit only reached under ideal conditions. PMID:22952608

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

PubMed

Eustache, Francis; Viard, Armelle; Desgranges, Béatrice

2016-07-01

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

Two Unipolar Terminal-Attractor-Based Associative Memories

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang; Wu, Chwan-Hwa

1995-01-01

Two unipolar mathematical models of electronic neural network functioning as terminal-attractor-based associative memory (TABAM) developed. Models comprise sets of equations describing interactions between time-varying inputs and outputs of neural-network memory, regarded as dynamical system. Simplifies design and operation of optoelectronic processor to implement TABAM performing associative recall of images. TABAM concept described in "Optoelectronic Terminal-Attractor-Based Associative Memory" (NPO-18790). Experimental optoelectronic apparatus that performed associative recall of binary images described in "Optoelectronic Inner-Product Neural Associative Memory" (NPO-18491).

Forgetfulness can help you win games.

PubMed

Burridge, James; Gao, Yu; Mao, Yong

2015-09-01

We present a simple game model where agents with different memory lengths compete for finite resources. We show by simulation and analytically that an instability exists at a critical memory length, and as a result, different memory lengths can compete and coexist in a dynamical equilibrium. Our analytical formulation makes a connection to statistical urn models, and we show that temperature is mirrored by the agent's memory. Our simple model of memory may be incorporated into other game models with implications that we briefly discuss.

Circuit engineering principles for construction of bipolar large-scale integrated circuit storage devices and very large-scale main memory

NASA Astrophysics Data System (ADS)

Neklyudov, A. A.; Savenkov, V. N.; Sergeyez, A. G.

1984-06-01

Memories are improved by increasing speed or the memory volume on a single chip. The most effective means for increasing speeds in bipolar memories are current control circuits with the lowest extraction times for a specific power consumption (1/4 pJ/bit). The control current circuitry involves multistage current switches and circuits accelerating transient processes in storage elements and links. Circuit principles for the design of bipolar memories with maximum speeds for an assigned minimum of circuit topology are analyzed. Two main classes of storage with current control are considered: the ECL type and super-integrated injection type storage with data capacities of N = 1/4 and N 4/16, respectively. The circuits reduce logic voltage differentials and the volumes of lexical and discharge buses and control circuit buses. The limiting speed is determined by the antiinterference requirements of the memory in storage and extraction modes.

Aging, memory, and nonhierarchical energy landscape of spin jam

PubMed Central

Samarakoon, Anjana; Sato, Taku J.; Chen, Tianran; Chern, Gai-Wei; Yang, Junjie; Klich, Israel; Sinclair, Ryan; Zhou, Haidong; Lee, Seung-Hun

2016-01-01

The notion of complex energy landscape underpins the intriguing dynamical behaviors in many complex systems ranging from polymers, to brain activity, to social networks and glass transitions. The spin glass state found in dilute magnetic alloys has been an exceptionally convenient laboratory frame for studying complex dynamics resulting from a hierarchical energy landscape with rugged funnels. Here, we show, by a bulk susceptibility and Monte Carlo simulation study, that densely populated frustrated magnets in a spin jam state exhibit much weaker memory effects than spin glasses, and the characteristic properties can be reproduced by a nonhierarchical landscape with a wide and nearly flat but rough bottom. Our results illustrate that the memory effects can be used to probe different slow dynamics of glassy materials, hence opening a window to explore their distinct energy landscapes. PMID:27698141

Opportunities for nonvolatile memory systems in extreme-scale high-performance computing

DOE PAGES

Vetter, Jeffrey S.; Mittal, Sparsh

2015-01-12

For extreme-scale high-performance computing systems, system-wide power consumption has been identified as one of the key constraints moving forward, where DRAM main memory systems account for about 30 to 50 percent of a node's overall power consumption. As the benefits of device scaling for DRAM memory slow, it will become increasingly difficult to keep memory capacities balanced with increasing computational rates offered by next-generation processors. However, several emerging memory technologies related to nonvolatile memory (NVM) devices are being investigated as an alternative for DRAM. Moving forward, NVM devices could offer solutions for HPC architectures. Researchers are investigating how to integratemore » these emerging technologies into future extreme-scale HPC systems and how to expose these capabilities in the software stack and applications. In addition, current results show several of these strategies could offer high-bandwidth I/O, larger main memory capacities, persistent data structures, and new approaches for application resilience and output postprocessing, such as transaction-based incremental checkpointing and in situ visualization, respectively.« less

Convergence of high order memory kernels in the Nakajima-Zwanzig generalized master equation and rate constants: Case study of the spin-boson model.

PubMed

Xu, Meng; Yan, Yaming; Liu, Yanying; Shi, Qiang

2018-04-28

The Nakajima-Zwanzig generalized master equation provides a formally exact framework to simulate quantum dynamics in condensed phases. Yet, the exact memory kernel is hard to obtain and calculations based on perturbative expansions are often employed. By using the spin-boson model as an example, we assess the convergence of high order memory kernels in the Nakajima-Zwanzig generalized master equation. The exact memory kernels are calculated by combining the hierarchical equation of motion approach and the Dyson expansion of the exact memory kernel. High order expansions of the memory kernels are obtained by extending our previous work to calculate perturbative expansions of open system quantum dynamics [M. Xu et al., J. Chem. Phys. 146, 064102 (2017)]. It is found that the high order expansions do not necessarily converge in certain parameter regimes where the exact kernel show a long memory time, especially in cases of slow bath, weak system-bath coupling, and low temperature. Effectiveness of the Padé and Landau-Zener resummation approaches is tested, and the convergence of higher order rate constants beyond Fermi's golden rule is investigated.

Convergence of high order memory kernels in the Nakajima-Zwanzig generalized master equation and rate constants: Case study of the spin-boson model

NASA Astrophysics Data System (ADS)

Xu, Meng; Yan, Yaming; Liu, Yanying; Shi, Qiang

2018-04-01

The Nakajima-Zwanzig generalized master equation provides a formally exact framework to simulate quantum dynamics in condensed phases. Yet, the exact memory kernel is hard to obtain and calculations based on perturbative expansions are often employed. By using the spin-boson model as an example, we assess the convergence of high order memory kernels in the Nakajima-Zwanzig generalized master equation. The exact memory kernels are calculated by combining the hierarchical equation of motion approach and the Dyson expansion of the exact memory kernel. High order expansions of the memory kernels are obtained by extending our previous work to calculate perturbative expansions of open system quantum dynamics [M. Xu et al., J. Chem. Phys. 146, 064102 (2017)]. It is found that the high order expansions do not necessarily converge in certain parameter regimes where the exact kernel show a long memory time, especially in cases of slow bath, weak system-bath coupling, and low temperature. Effectiveness of the Padé and Landau-Zener resummation approaches is tested, and the convergence of higher order rate constants beyond Fermi's golden rule is investigated.

Stress time-dependently influences the acquisition and retrieval of unrelated information by producing a memory of its own.

PubMed

Cadle, Chelsea E; Zoladz, Phillip R

2015-01-01

Stress induces several temporally guided "waves" of psychobiological responses that differentially influence learning and memory. One way to understand how the temporal dynamics of stress influence these cognitive processes is to consider stress, itself, as a learning experience that influences additional learning and memory. Indeed, research has shown that stress results in electrophysiological and biochemical activity that is remarkably similar to the activity observed as a result of learning. In this review, we will present the idea that when a stressful episode immediately precedes or follows learning, such learning is enhanced because the learned information becomes a part of the stress context and is tagged by the emotional memory being formed. In contrast, when a stressful episode is temporally separated from learning or is experienced prior to retrieval, such learning or memory is impaired because the learning or memory is experienced outside the context of the stress episode or subsequent to a saturation of synaptic plasticity, which renders the retrieval of information improbable. The temporal dynamics of emotional memory formation, along with the neurobiological correlates of the stress response, are discussed to support these hypotheses.

AKAPS Act in a Two-Step Mechanism of Memory Acquisition

PubMed Central

Scheunemann, Lisa; Skroblin, Philipp; Hundsrucker, Christian; Klussmann, Enno; Efetova, Marina

2013-01-01

Defining the molecular and neuronal basis of associative memories is based upon behavioral preparations that yield high performance due to selection of salient stimuli, strong reinforcement, and repeated conditioning trials. One of those preparations is the Drosophila aversive olfactory conditioning procedure where animals initiate multiple memory components after experience of a single cycle training procedure. Here, we explored the analysis of acquisition dynamics as a means to define memory components and revealed strong correlations between particular chronologies of shock impact and number experienced during the associative training situation and subsequent performance of conditioned avoidance. Analyzing acquisition dynamics in Drosophila memory mutants revealed that rutabaga (rut)-dependent cAMP signals couple in a divergent fashion for support of different memory components. In case of anesthesia-sensitive memory (ASM) we identified a characteristic two-step mechanism that links rut-AC1 to A-kinase anchoring proteins (AKAP)-sequestered protein kinase A at the level of Kenyon cells, a recognized center of olfactory learning within the fly brain. We propose that integration of rut-derived cAMP signals at level of AKAPs might serve as counting register that accounts for the two-step mechanism of ASM acquisition. PMID:24174675

Transmitting Memory between and beyond Generations: The Rotterdam Bombardment in Local Memory Culture and Education from 1980 to 2015

ERIC Educational Resources Information Center

Hogervorst, Susan

2015-01-01

This article analyses three local educational projects about the Nazi bombing of Rotterdam in May 1940, all of which took place from 1980 to the present day in the context of the dynamic memory culture of the bombardment. These three contexts testify to a process by which memory, increasingly derived from authentic locations and objects instead of…

Symbolic Model of Perception in Dynamic 3D Environments

DTIC Science & Technology

2006-11-01

can retrieve memories , work on goals, recognize visual or aural percepts, and perform actions. ACT-R has been selected for the current...types of memory . Procedural memory is the store of condition- action productions that are selected and executed by the core production system...a declarative memory chunk that is made available to the core production system through the vision module . 4 The vision module has been

The effects of velocity difference changes with memory on the dynamics characteristics and fuel economy of traffic flow

NASA Astrophysics Data System (ADS)

Yu, Shaowei; Zhao, Xiangmo; Xu, Zhigang; Zhang, Licheng

2016-11-01

To evaluate the effects of velocity difference changes with memory in the intelligent transportation environment on the dynamics and fuel consumptions of traffic flow, we first investigate the linkage between velocity difference changes with memory and car-following behaviors with the measured data in cities, and then propose an improved cooperative car-following model considering multiple velocity difference changes with memory in the cooperative adaptive cruise control strategy, finally carry out several numerical simulations under the periodic boundary condition and at signalized intersections to explore how velocity difference changes with memory affect car's velocity, velocity fluctuation, acceleration and fuel consumptions in the intelligent transportation environment. The results show that velocity difference changes with memory have obvious effects on car-following behaviors, that the improved cooperative car-following model can describe the phase transition of traffic flow and estimate the evolution of traffic congestion, that the stability and fuel economy of traffic flow simulated by the improved car-following model with velocity difference changes with memory is obviously superior to those without velocity difference changes, and that taking velocity difference changes with memory into account in designing the advanced adaptive cruise control strategy can significantly improve the stability and fuel economy of traffic flow.

Working Memory and Reasoning Benefit from Different Modes of Large-scale Brain Dynamics in Healthy Older Adults.

PubMed

Lebedev, Alexander V; Nilsson, Jonna; Lövdén, Martin

2018-07-01

Researchers have proposed that solving complex reasoning problems, a key indicator of fluid intelligence, involves the same cognitive processes as solving working memory tasks. This proposal is supported by an overlap of the functional brain activations associated with the two types of tasks and by high correlations between interindividual differences in performance. We replicated these findings in 53 older participants but also showed that solving reasoning and working memory problems benefits from different configurations of the functional connectome and that this dissimilarity increases with a higher difficulty load. Specifically, superior performance in a typical working memory paradigm ( n-back) was associated with upregulation of modularity (increased between-network segregation), whereas performance in the reasoning task was associated with effective downregulation of modularity. We also showed that working memory training promotes task-invariant increases in modularity. Because superior reasoning performance is associated with downregulation of modular dynamics, training may thus have fostered an inefficient way of solving the reasoning tasks. This could help explain why working memory training does little to promote complex reasoning performance. The study concludes that complex reasoning abilities cannot be reduced to working memory and suggests the need to reconsider the feasibility of using working memory training interventions to attempt to achieve effects that transfer to broader cognition.

The Durability of Collective Memory: Reconciling the "Greensboro Massacre"

ERIC Educational Resources Information Center

Cunningham, David; Nugent, Colleen; Slodden, Caitlin

2010-01-01

While the general dynamics governing collective memory processes are well developed theoretically, our tool kit for systematically assessing how collective memory changes over time remains limited. Here, we focus on a particular tragic event--the killing of five participants in an anti-KKK march in Greensboro, North Carolina, on Nov. 3, 1979--to…

Short-Term Memory in Orthogonal Neural Networks

NASA Astrophysics Data System (ADS)

White, Olivia L.; Lee, Daniel D.; Sompolinsky, Haim

2004-04-01

We study the ability of linear recurrent networks obeying discrete time dynamics to store long temporal sequences that are retrievable from the instantaneous state of the network. We calculate this temporal memory capacity for both distributed shift register and random orthogonal connectivity matrices. We show that the memory capacity of these networks scales with system size.

Region-Specific Involvement of Actin Rearrangement-Related Synaptic Structure Alterations in Conditioned Taste Aversion Memory

ERIC Educational Resources Information Center

Bi, Ai-Ling; Wang, Yue; Li, Bo-Qin; Wang, Qian-Qian; Ma, Ling; Yu, Hui; Zhao, Ling; Chen, Zhe-Yu

2010-01-01

Actin rearrangement plays an essential role in learning and memory; however, the spatial and temporal regulation of actin dynamics in different phases of associative memory has not been fully understood. Here, using the conditioned taste aversion (CTA) paradigm, we investigated the region-specific involvement of actin rearrangement-related…

General purpose programmable accelerator board

DOEpatents

Robertson, Perry J.; Witzke, Edward L.

2001-01-01

A general purpose accelerator board and acceleration method comprising use of: one or more programmable logic devices; a plurality of memory blocks; bus interface for communicating data between the memory blocks and devices external to the board; and dynamic programming capabilities for providing logic to the programmable logic device to be executed on data in the memory blocks.

On the Law Relating Processing to Storage in Working Memory

ERIC Educational Resources Information Center

Barrouillet, Pierre; Portrat, Sophie; Camos, Valerie

2011-01-01

"Working memory" is usually defined in cognitive psychology as a system devoted to the simultaneous processing and maintenance of information. However, although many models of working memory have been put forward during the last decades, they often leave underspecified the dynamic interplay between processing and storage. Moreover, the account of…

Persistence and memory timescales in root-zone soil moisture dynamics

Treesearch

Khaled Ghannam; Taro Nakai; Athanasios Paschalis; Andrew C. Oishi; Ayumi Kotani; Yasunori Igarashi; Tomo' omi Kumagai; Gabriel G. Katul

2016-01-01

The memory timescale that characterizes root-zone soil moisture remains the dominant measure in seasonal forecasts of land-climate interactions. This memory is a quasi-deterministic timescale associated with the losses (e.g., evapotranspiration) from the soil column and is often interpreted as persistence in soil moisture states. Persistence, however,...

Application of source biasing technique for energy efficient DECODER circuit design: memory array application

NASA Astrophysics Data System (ADS)

Gupta, Neha; Parihar, Priyanka; Neema, Vaibhav

2018-04-01

Researchers have proposed many circuit techniques to reduce leakage power dissipation in memory cells. If we want to reduce the overall power in the memory system, we have to work on the input circuitry of memory architecture i.e. row and column decoder. In this research work, low leakage power with a high speed row and column decoder for memory array application is designed and four new techniques are proposed. In this work, the comparison of cluster DECODER, body bias DECODER, source bias DECODER, and source coupling DECODER are designed and analyzed for memory array application. Simulation is performed for the comparative analysis of different DECODER design parameters at 180 nm GPDK technology file using the CADENCE tool. Simulation results show that the proposed source bias DECODER circuit technique decreases the leakage current by 99.92% and static energy by 99.92% at a supply voltage of 1.2 V. The proposed circuit also improves dynamic power dissipation by 5.69%, dynamic PDP/EDP 65.03% and delay 57.25% at 1.2 V supply voltage.

Memory recall and spike-frequency adaptation

NASA Astrophysics Data System (ADS)

Roach, James P.; Sander, Leonard M.; Zochowski, Michal R.

2016-05-01

The brain can reproduce memories from partial data; this ability is critical for memory recall. The process of memory recall has been studied using autoassociative networks such as the Hopfield model. This kind of model reliably converges to stored patterns that contain the memory. However, it is unclear how the behavior is controlled by the brain so that after convergence to one configuration, it can proceed with recognition of another one. In the Hopfield model, this happens only through unrealistic changes of an effective global temperature that destabilizes all stored configurations. Here we show that spike-frequency adaptation (SFA), a common mechanism affecting neuron activation in the brain, can provide state-dependent control of pattern retrieval. We demonstrate this in a Hopfield network modified to include SFA, and also in a model network of biophysical neurons. In both cases, SFA allows for selective stabilization of attractors with different basins of attraction, and also for temporal dynamics of attractor switching that is not possible in standard autoassociative schemes. The dynamics of our models give a plausible account of different sorts of memory retrieval.

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

Controlling uncertainty: a review of human behavior in complex dynamic environments.

PubMed

Osman, Magda

2010-01-01

Complex dynamic control (CDC) tasks are a type of problem-solving environment used for examining many cognitive activities (e.g., attention, control, decision making, hypothesis testing, implicit learning, memory, monitoring, planning, and problem solving). Because of their popularity, there have been many findings from diverse domains of research (economics, engineering, ergonomics, human-computer interaction, management, psychology), but they remain largely disconnected from each other. The objective of this article is to review theoretical developments and empirical work on CDC tasks, and to introduce a novel framework (monitoring and control framework) as a tool for integrating theory and findings. The main thesis of the monitoring and control framework is that CDC tasks are characteristically uncertain environments, and subjective judgments of uncertainty guide the way in which monitoring and control behaviors attempt to reduce it. The article concludes by discussing new insights into continuing debates and future directions for research on CDC tasks.

An attachment model of depression: integrating findings from the mood disorder laboratory.

PubMed

Holmes, Jeremy

2013-01-01

This paper is written from a psychodynamic clinician's perspective, juxtaposing a psychoanalytic-attachment model of depression with recent developments in neuroscience. Three main components of the attachment approach are described: the role of loss, of childhood trauma predisposing to depression in later life, and failure of co-regulation of role of primitive emotions, such as fear, despair, and helplessness. Blatt's distinction between anaclitic and introjective depression is delineated and related to hyper- and de-activation of the attachment dynamic. Recent advances in evolutionary, sociological, epigenetic, biochemical, and neuro-imaging studies of depression are reviewed. A dynamic model of depression is proposed, linking interpersonal and intra-psychic perspectives with neuro-anatomical models. The final section of the paper considers the specific role of psychodynamic approaches to the treatment of refractory depression. These include length of treatment, capacity to rework implicit memories, and focus on transference and counter-transference.

Application of real-time database to LAMOST control system

NASA Astrophysics Data System (ADS)

Xu, Lingzhe; Xu, Xinqi

2004-09-01

The QNX based real time database is one of main features for Large sky Area Multi-Object fiber Spectroscopic Telescope's (LAMOST) control system, which serves as a storage and platform for data flow, recording and updating timely various status of moving components in the telescope structure as well as environmental parameters around it. The database joins harmonically in the administration of the Telescope Control System (TCS). The paper presents methodology and technique tips in designing the EMPRESS database GUI software package, such as the dynamic creation of control widgets, dynamic query and share memory. The seamless connection between EMPRESS and the graphical development tool of QNX"s Photon Application Builder (PhAB) has been realized, and so have the Windows look and feel yet under Unix-like operating system. In particular, the real time feature of the database is analyzed that satisfies the needs of the control system.

Functional expansion representations of artificial neural networks

NASA Technical Reports Server (NTRS)

Gray, W. Steven

1992-01-01

In the past few years, significant interest has developed in using artificial neural networks to model and control nonlinear dynamical systems. While there exists many proposed schemes for accomplishing this and a wealth of supporting empirical results, most approaches to date tend to be ad hoc in nature and rely mainly on heuristic justifications. The purpose of this project was to further develop some analytical tools for representing nonlinear discrete-time input-output systems, which when applied to neural networks would give insight on architecture selection, pruning strategies, and learning algorithms. A long term goal is to determine in what sense, if any, a neural network can be used as a universal approximator for nonliner input-output maps with memory (i.e., realized by a dynamical system). This property is well known for the case of static or memoryless input-output maps. The general architecture under consideration in this project was a single-input, single-output recurrent feedforward network.

Unstructured Adaptive Meshes: Bad for Your Memory?

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Feng, Hui-Yu; VanderWijngaart, Rob

2003-01-01

This viewgraph presentation explores the need for a NASA Advanced Supercomputing (NAS) parallel benchmark for problems with irregular dynamical memory access. This benchmark is important and necessary because: 1) Problems with localized error source benefit from adaptive nonuniform meshes; 2) Certain machines perform poorly on such problems; 3) Parallel implementation may provide further performance improvement but is difficult. Some examples of problems which use irregular dynamical memory access include: 1) Heat transfer problem; 2) Heat source term; 3) Spectral element method; 4) Base functions; 5) Elemental discrete equations; 6) Global discrete equations. Nonconforming Mesh and Mortar Element Method are covered in greater detail in this presentation.

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.

Efficient calculation of open quantum system dynamics and time-resolved spectroscopy with distributed memory HEOM (DM-HEOM).

PubMed

Kramer, Tobias; Noack, Matthias; Reinefeld, Alexander; Rodríguez, Mirta; Zelinskyy, Yaroslav

2018-06-11

Time- and frequency-resolved optical signals provide insights into the properties of light-harvesting molecular complexes, including excitation energies, dipole strengths and orientations, as well as in the exciton energy flow through the complex. The hierarchical equations of motion (HEOM) provide a unifying theory, which allows one to study the combined effects of system-environment dissipation and non-Markovian memory without making restrictive assumptions about weak or strong couplings or separability of vibrational and electronic degrees of freedom. With increasing system size the exact solution of the open quantum system dynamics requires memory and compute resources beyond a single compute node. To overcome this barrier, we developed a scalable variant of HEOM. Our distributed memory HEOM, DM-HEOM, is a universal tool for open quantum system dynamics. It is used to accurately compute all experimentally accessible time- and frequency-resolved processes in light-harvesting molecular complexes with arbitrary system-environment couplings for a wide range of temperatures and complex sizes. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Post-learning hippocampal dynamics promote preferential retention of rewarding events

PubMed Central

Gruber, Matthias J.; Ritchey, Maureen; Wang, Shao-Fang; Doss, Manoj K.; Ranganath, Charan

2016-01-01

Reward motivation is known to modulate memory encoding, and this effect depends on interactions between the substantia nigra/ ventral tegmental area complex (SN/VTA) and the hippocampus. It is unknown, however, whether these interactions influence offline neural activity in the human brain that is thought to promote memory consolidation. Here, we used functional magnetic resonance imaging (fMRI) to test the effect of reward motivation on post-learning neural dynamics and subsequent memory for objects that were learned in high- or low-reward motivation contexts. We found that post-learning increases in resting-state functional connectivity between the SN/VTA and hippocampus predicted preferential retention of objects that were learned in high-reward contexts. In addition, multivariate pattern classification revealed that hippocampal representations of high-reward contexts were preferentially reactivated during post-learning rest, and the number of hippocampal reactivations was predictive of preferential retention of items learned in high-reward contexts. These findings indicate that reward motivation alters offline post-learning dynamics between the SN/VTA and hippocampus, providing novel evidence for a potential mechanism by which reward could influence memory consolidation. PMID:26875624

Managing internode data communications for an uninitialized process in a parallel computer

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

Archer, Charles J; Blocksome, Michael A; Miller, Douglas R

2014-05-20

A parallel computer includes nodes, each having main memory and a messaging unit (MU). Each MU includes computer memory, which in turn includes, MU message buffers. Each MU message buffer is associated with an uninitialized process on the compute node. In the parallel computer, managing internode data communications for an uninitialized process includes: receiving, by an MU of a compute node, one or more data communications messages in an MU message buffer associated with an uninitialized process on the compute node; determining, by an application agent, that the MU message buffer associated with the uninitialized process is full prior tomore » initialization of the uninitialized process; establishing, by the application agent, a temporary message buffer for the uninitialized process in main computer memory; and moving, by the application agent, data communications messages from the MU message buffer associated with the uninitialized process to the temporary message buffer in main computer memory.« less

Managing internode data communications for an uninitialized process in a parallel computer

DOEpatents

Archer, Charles J; Blocksome, Michael A; Miller, Douglas R; Parker, Jeffrey J; Ratterman, Joseph D; Smith, Brian E

2014-05-20

A parallel computer includes nodes, each having main memory and a messaging unit (MU). Each MU includes computer memory, which in turn includes, MU message buffers. Each MU message buffer is associated with an uninitialized process on the compute node. In the parallel computer, managing internode data communications for an uninitialized process includes: receiving, by an MU of a compute node, one or more data communications messages in an MU message buffer associated with an uninitialized process on the compute node; determining, by an application agent, that the MU message buffer associated with the uninitialized process is full prior to initialization of the uninitialized process; establishing, by the application agent, a temporary message buffer for the uninitialized process in main computer memory; and moving, by the application agent, data communications messages from the MU message buffer associated with the uninitialized process to the temporary message buffer in main computer memory.

Human memory retrieval as Lévy foraging

NASA Astrophysics Data System (ADS)

Rhodes, Theo; Turvey, Michael T.

2007-11-01

When people attempt to recall as many words as possible from a specific category (e.g., animal names) their retrievals occur sporadically over an extended temporal period. Retrievals decline as recall progresses, but short retrieval bursts can occur even after tens of minutes of performing the task. To date, efforts to gain insight into the nature of retrieval from this fundamental phenomenon of semantic memory have focused primarily upon the exponential growth rate of cumulative recall. Here we focus upon the time intervals between retrievals. We expected and found that, for each participant in our experiment, these intervals conformed to a Lévy distribution suggesting that the Lévy flight dynamics that characterize foraging behavior may also characterize retrieval from semantic memory. The closer the exponent on the inverse square power-law distribution of retrieval intervals approximated the optimal foraging value of 2, the more efficient was the retrieval. At an abstract dynamical level, foraging for particular foods in one's niche and searching for particular words in one's memory must be similar processes if particular foods and particular words are randomly and sparsely located in their respective spaces at sites that are not known a priori. We discuss whether Lévy dynamics imply that memory processes, like foraging, are optimized in an ecological way.

Electronic implementation of associative memory based on neural network models

NASA Technical Reports Server (NTRS)

Moopenn, A.; Lambe, John; Thakoor, A. P.

1987-01-01

An electronic embodiment of a neural network based associative memory in the form of a binary connection matrix is described. The nature of false memory errors, their effect on the information storage capacity of binary connection matrix memories, and a novel technique to eliminate such errors with the help of asymmetrical extra connections are discussed. The stability of the matrix memory system incorporating a unique local inhibition scheme is analyzed in terms of local minimization of an energy function. The memory's stability, dynamic behavior, and recall capability are investigated using a 32-'neuron' electronic neural network memory with a 1024-programmable binary connection matrix.

Memory as the "whole brain work": a large-scale model based on "oscillations in super-synergy".

PubMed

Başar, Erol

2005-01-01

According to recent trends, memory depends on several brain structures working in concert across many levels of neural organization; "memory is a constant work-in progress." The proposition of a brain theory based on super-synergy in neural populations is most pertinent for the understanding of this constant work in progress. This report introduces a new model on memory basing on the processes of EEG oscillations and Brain Dynamics. This model is shaped by the following conceptual and experimental steps: 1. The machineries of super-synergy in the whole brain are responsible for formation of sensory-cognitive percepts. 2. The expression "dynamic memory" is used for memory processes that evoke relevant changes in alpha, gamma, theta and delta activities. The concerted action of distributed multiple oscillatory processes provides a major key for understanding of distributed memory. It comprehends also the phyletic memory and reflexes. 3. The evolving memory, which incorporates reciprocal actions or reverberations in the APLR alliance and during working memory processes, is especially emphasized. 4. A new model related to "hierarchy of memories as a continuum" is introduced. 5. The notions of "longer activated memory" and "persistent memory" are proposed instead of long-term memory. 6. The new analysis to recognize faces emphasizes the importance of EEG oscillations in neurophysiology and Gestalt analysis. 7. The proposed basic framework called "Memory in the Whole Brain Work" emphasizes that memory and all brain functions are inseparable and are acting as a "whole" in the whole brain. 8. The role of genetic factors is fundamental in living system settings and oscillations and accordingly in memory, according to recent publications. 9. A link from the "whole brain" to "whole body," and incorporation of vegetative and neurological system, is proposed, EEG oscillations and ultraslow oscillations being a control parameter.

Pre- and long-term postoperative courses of hippocampus-associated memory impairment in epilepsy patients with antibody-associated limbic encephalitis and selective amygdalohippocampectomy.

PubMed

Hansen, Niels; Ernst, Leon; Rüber, Theodor; Widman, Guido; Becker, Albert J; Elger, Christian E; Helmstaedter, Christoph

2018-02-01

Limbic encephalitis (LE) is defined by mesiotemporal lobe structure abnormalities, seizures, memory, and psychiatric disturbances. This study aimed to identify the long-term clinical and neuropsychological outcome of selective amygdalohippocampectomy (sAH) in drug-resistant patients with temporal lobe epilepsy due to known or later diagnosed subacute LE not responding to immunotherapy associated with neuronal autoantibodies. In seven patients with temporal lobe epilepsy due to antibody positive LE (glutamic acid decarboxylase (GAD65): n=5; voltage-gated potassium channel complex (VGKC), N-methyl d-aspartate receptor (NMDAR): n=1; Ma-2/Ta: n=1) sAH (6 left, 1 right) was performed. Those patients underwent repeated electroencephalography (EEG) recordings, magnetic resonance imaging (MRI) volumetry of the amygdala and hippocampus, and neuropsychological examinations and were followed up for 6-7years on average. Verbal memory and figural memory were affected in 57% of patients at baseline and 71% at the last follow-up. At the last follow-up, 14% of the patients had declined in verbal memory and figural memory. We observed improved memory in 43% of patients regarding figural memory, but not in a single patient regarding verbal memory. Repeated evaluations across the individual courses reveal cognitive and MRI dynamics that appear to be unrelated to surgery and drug treatment. Three of the seven patients with LE with different antibodies (NMDAR: n=1, Ma-2/Ta: n=1 and GAD65: n=1) achieved persistent seizure freedom along with no accelerated memory decline after surgery. Two of the five GAD65-antibody patients positive with LE showed progressive memory decline and a long-term tendency to contralateral hippocampus atrophy. While memory demonstrated some decline in the long run, what is most important is that a progressive decline in memory is seldom found after sAH in patients with LE. Moreover, the dynamics in performance and MRI before and after surgery reveal disease dynamics independent of surgery. Selective amygdalohippocampectomy can lead to seizure freedom, but should be considered as a last resort treatment option for drug-resistant patients with temporal lobe epilepsy due to LE. Particular caution is recommended in patients with GAD65-LE. Copyright © 2017 Elsevier Inc. All rights reserved.

Semantic congruence enhances memory of episodic associations: role of theta oscillations.

PubMed

Atienza, Mercedes; Crespo-Garcia, Maite; Cantero, Jose L

2011-01-01

Growing evidence suggests that theta oscillations play a crucial role in episodic encoding. The present study evaluates whether changes in electroencephalographic theta source dynamics mediate the positive influence of semantic congruence on incidental associative learning. Here we show that memory for episodic associations (face-location) is more accurate when studied under semantically congruent contexts. However, only participants showing RT priming effect in a conceptual priming test (priming group) also gave faster responses when recollecting source information of semantically congruent faces as compared with semantically incongruent faces. This improved episodic retrieval was positively correlated with increases in theta power during the study phase mainly in the bilateral parahippocampal gyrus, left superior temporal gyrus, and left lateral posterior parietal lobe. Reconstructed signals from the estimated sources showed higher theta power for congruent than incongruent faces and also for the priming than the nonpriming group. These results are in agreement with the attention to memory model. Besides directing top-down attention to goal-relevant semantic information during encoding, the dorsal parietal lobe may also be involved in redirecting attention to bottom-up-driven memories thanks to connections between the medial-temporal and the left ventral parietal lobe. The latter function can either facilitate or interfere with encoding of face-location associations depending on whether they are preceded by semantically congruent or incongruent contexts, respectively, because only in the former condition retrieved representations related to the cue and the face are both coherent with the person identity and are both associated with the same location.

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

PubMed

Simmering, Vanessa R

2016-09-01

Working memory is a vital cognitive skill that underlies a broad range of behaviors. Higher cognitive functions are reliably predicted by working memory measures from two domains: children's performance on complex span tasks, and infants' performance in looking paradigms. Despite the similar predictive power across these research areas, theories of working memory development have not connected these different task types and developmental periods. The current project takes a first step toward bridging this gap by presenting a process-oriented theory, focusing on two tasks designed to assess visual working memory capacity in infants (the change-preference task) versus children and adults (the change detection task). Previous studies have shown inconsistent results, with capacity estimates increasing from one to four items during infancy, but only two to three items during early childhood. A probable source of this discrepancy is the different task structures used with each age group, but prior theories were not sufficiently specific to explain how performance relates across tasks. The current theory focuses on cognitive dynamics, that is, how memory representations are formed, maintained, and used within specific task contexts over development. This theory was formalized in a computational model to generate three predictions: 1) capacity estimates in the change-preference task should continue to increase beyond infancy; 2) capacity estimates should be higher in the change-preference versus change detection task when tested within individuals; and 3) performance should correlate across tasks because both rely on the same underlying memory system. I also tested a fourth prediction, that development across tasks could be explained through increasing real-time stability, realized computationally as strengthening connectivity within the model. Results confirmed these predictions, supporting the cognitive dynamics account of performance and developmental changes in real-time stability. The monograph concludes with implications for understanding memory, behavior, and development in a broader range of cognitive development. © 2016 The Society for Research in Child Development, Inc.

PREFACE: Special section on Computational Fluid Dynamics—in memory of Professor Kunio Kuwahara Special section on Computational Fluid Dynamics—in memory of Professor Kunio Kuwahara

NASA Astrophysics Data System (ADS)

Ishii, Katsuya

2011-08-01

This issue includes a special section on computational fluid dynamics (CFD) in memory of the late Professor Kunio Kuwahara, who passed away on 15 September 2008, at the age of 66. In this special section, five articles are included that are based on the lectures and discussions at `The 7th International Nobeyama Workshop on CFD: To the Memory of Professor Kuwahara' held in Tokyo on 23 and 24 September 2009. Professor Kuwahara started his research in fluid dynamics under Professor Imai at the University of Tokyo. His first paper was published in 1969 with the title 'Steady Viscous Flow within Circular Boundary', with Professor Imai. In this paper, he combined theoretical and numerical methods in fluid dynamics. Since that time, he made significant and seminal contributions to computational fluid dynamics. He undertook pioneering numerical studies on the vortex method in 1970s. From then to the early nineties, he developed numerical analyses on a variety of three-dimensional unsteady phenomena of incompressible and compressible fluid flows and/or complex fluid flows using his own supercomputers with academic and industrial co-workers and members of his private research institute, ICFD in Tokyo. In addition, a number of senior and young researchers of fluid mechanics around the world were invited to ICFD and the Nobeyama workshops, which were held near his villa, and they intensively discussed new frontier problems of fluid physics and fluid engineering at Professor Kuwahara's kind hospitality. At the memorial Nobeyama workshop held in 2009, 24 overseas speakers presented their papers, including the talks of Dr J P Boris (Naval Research Laboratory), Dr E S Oran (Naval Research Laboratory), Professor Z J Wang (Iowa State University), Dr M Meinke (RWTH Aachen), Professor K Ghia (University of Cincinnati), Professor U Ghia (University of Cincinnati), Professor F Hussain (University of Houston), Professor M Farge (École Normale Superieure), Professor J Y Yong (National Taiwan University), and Professor H S Kwak (Kumoh National Institute of Technology). For his contributions to CFD, Professor Kuwahara received Awards from the Japan Society of Automobile Engineers and the Japan Society of Mechanical Engineers in 1992, the Computational Mechanics Achievement Award from the Japan Society of Mechanical Engineers in 1993, and the Max Planck Research Award in 1993. He received the Computational Mechanics Award from the Japan Society of Mechanical Engineers again in 2008. Professor Kuwahara also supported the development of the Japan Society of Fluid Mechanics, whose office is located in the same building as ICFD. In the proceedings of the 6th International Nobeyama Workshop on CFD to commemorate the 60th birthday of Professor Kuwahara, Professor Jae Min Hyun of KAIST wrote 'The major professional achievement of Professor Kuwahara may be compressed into two main categories. First and foremost, Professor Kuwahara will long be recorded as the front-line pioneer in using numerical computations to tackle complex problems in fluid mechanics. ...Another important contribution of Professor Kuwahara was in the training and fostering of talented manpower of computational mechanics research.'[1] Among the various topics of the five papers in this special section are examples of Professor Kuwahara's works mentioned by Professor Hyun. The main authors of all papers have grown up in the research circle of Professor Kuwahara. All the papers demostrate the challenge of new aspects of computational fluid dynamics; a new numerical method for compressible flows, thermo-acoustic flows of helium gas in a small tube, electro-osmic flows in a micro/nano channel, MHD flows over a wavy disk, and a new extraction method of multi-object aircraft design rules. Last but not least, this special section is cordially dedicated to the late Professor Kuwahara and his family. Reference [1] Hyun J M 2005 Preface of New Developments in Computational Fluid Dynamics vol 90 Notes on Numerical Fluid Mechanics and Multidisciplinary Design ed K Fujii et al (Berlin: Springer)

Progress In Optical Memory Technology

NASA Astrophysics Data System (ADS)

Tsunoda, Yoshito

1987-01-01

More than 20 years have passed since the concept of optical memory was first proposed in 1966. Since then considerable progress has been made in this area together with the creation of completely new markets of optical memory in consumer and computer application areas. The first generation of optical memory was mainly developed with holographic recording technology in late 1960s and early 1970s. Considerable number of developments have been done in both analog and digital memory applications. Unfortunately, these technologies did not meet a chance to be a commercial product. The second generation of optical memory started at the beginning of 1970s with bit by bit recording technology. Read-only type optical memories such as video disks and compact audio disks have extensively investigated. Since laser diodes were first applied to optical video disk read out in 1976, there have been extensive developments of laser diode pick-ups for optical disk memory systems. The third generation of optical memory started in 1978 with bit by bit read/write technology using laser diodes. Developments of recording materials including both write-once and erasable have been actively pursued at several research institutes. These technologies are mainly focused on the optical memory systems for computer application. Such practical applications of optical memory technology has resulted in the creation of such new products as compact audio disks and computer file memories.

Emotion, gender, and gender typical identity in autobiographical memory.

PubMed

Grysman, Azriel; Merrill, Natalie; Fivush, Robyn

2017-03-01

Gender differences in the emotional intensity and content of autobiographical memory (AM) are inconsistent across studies, and may be influenced as much by gender identity as by categorical gender. To explore this question, data were collected from 196 participants (age 18-40), split evenly between men and women. Participants narrated four memories, a neutral event, high point event, low point event, and self-defining memory, completed ratings of emotional intensity for each event, and completed four measures of gender typical identity. For self-reported emotional intensity, gender differences in AM were mediated by identification with stereotypical feminine gender norms. For narrative use of affect terms, both gender and gender typical identity predicted affective expression. The results confirm contextual models of gender identity (e.g., Diamond, 2012 . The desire disorder in research on sexual orientation in women: Contributions of dynamical systems theory. Archives of Sexual Behavior, 41, 73-83) and underscore the dynamic interplay between gender and gender identity in the emotional expression of autobiographical memories.

Real-time tracking of cell cycle progression during CD8+ effector and memory T-cell differentiation

PubMed Central

Kinjyo, Ichiko; Qin, Jim; Tan, Sioh-Yang; Wellard, Cameron J.; Mrass, Paulus; Ritchie, William; Doi, Atsushi; Cavanagh, Lois L.; Tomura, Michio; Sakaue-Sawano, Asako; Kanagawa, Osami; Miyawaki, Atsushi; Hodgkin, Philip D.; Weninger, Wolfgang

2015-01-01

The precise pathways of memory T-cell differentiation are incompletely understood. Here we exploit transgenic mice expressing fluorescent cell cycle indicators to longitudinally track the division dynamics of individual CD8+ T cells. During influenza virus infection in vivo, naive T cells enter a CD62Lintermediate state of fast proliferation, which continues for at least nine generations. At the peak of the anti-viral immune response, a subpopulation of these cells markedly reduces their cycling speed and acquires a CD62Lhi central memory cell phenotype. Construction of T-cell family division trees in vitro reveals two patterns of proliferation dynamics. While cells initially divide rapidly with moderate stochastic variations of cycling times after each generation, a slow-cycling subpopulation displaying a CD62Lhi memory phenotype appears after eight divisions. Phenotype and cell cycle duration are inherited by the progeny of slow cyclers. We propose that memory precursors cell-intrinsically modulate their proliferative activity to diversify differentiation pathways. PMID:25709008

Real-time tracking of cell cycle progression during CD8+ effector and memory T-cell differentiation.

PubMed

Kinjyo, Ichiko; Qin, Jim; Tan, Sioh-Yang; Wellard, Cameron J; Mrass, Paulus; Ritchie, William; Doi, Atsushi; Cavanagh, Lois L; Tomura, Michio; Sakaue-Sawano, Asako; Kanagawa, Osami; Miyawaki, Atsushi; Hodgkin, Philip D; Weninger, Wolfgang

2015-02-24

The precise pathways of memory T-cell differentiation are incompletely understood. Here we exploit transgenic mice expressing fluorescent cell cycle indicators to longitudinally track the division dynamics of individual CD8(+) T cells. During influenza virus infection in vivo, naive T cells enter a CD62L(intermediate) state of fast proliferation, which continues for at least nine generations. At the peak of the anti-viral immune response, a subpopulation of these cells markedly reduces their cycling speed and acquires a CD62L(hi) central memory cell phenotype. Construction of T-cell family division trees in vitro reveals two patterns of proliferation dynamics. While cells initially divide rapidly with moderate stochastic variations of cycling times after each generation, a slow-cycling subpopulation displaying a CD62L(hi) memory phenotype appears after eight divisions. Phenotype and cell cycle duration are inherited by the progeny of slow cyclers. We propose that memory precursors cell-intrinsically modulate their proliferative activity to diversify differentiation pathways.

Reduced effects of pictorial distinctiveness on false memory following dynamic visual noise.

PubMed

Parker, Andrew; Kember, Timothy; Dagnall, Neil

2017-07-01

High levels of false recognition for non-presented items typically occur following exposure to lists of associated words. These false recognition effects can be reduced by making the studied items more distinctive by the presentation of pictures during encoding. One explanation of this is that during recognition, participants expect or attempt to retrieve distinctive pictorial information in order to evaluate the study status of the test item. If this involves the retrieval and use of visual imagery, then interfering with imagery processing should reduce the effectiveness of pictorial information in false memory reduction. In the current experiment, visual-imagery processing was disrupted at retrieval by the use of dynamic visual noise (DVN). It was found that effects of DVN dissociated true from false memory. Memory for studied words was not influenced by the presence of an interfering noise field. However, false memory was increased and the effects of picture-induced distinctiveness was eliminated. DVN also increased false recollection and remember responses to unstudied items.

Environmental invariants in the representation of motion: Implied dynamics and representational momentum, gravity, friction, and centripetal force.

PubMed

Hubbard, T L

1995-09-01

Memory for the final position of a moving target is often shifted or displaced from the true final position of that target. Early studies of this memory shift focused on parallels between the momentum of the target and the momentum of the representation of the target and called this displacementrepresentational momentum, but many factors other than momentum contribute to the memory shift. A consideration of the empirical literature on representational momentum and related types of displacement suggests there are at least four different types of factors influencing the direction and magnitude of such memory shifts: stimulus characteristics (e.g., target direction, target velocity), implied dynamics and environmental invariants (e.g., implied momentum, gravity, friction, centripetal force), memory averaging of target and nontarget context (e.g., biases toward previous target locations or nontarget context), and observers' expectations (both tacit and conscious) regarding future target motion and target/context interactions. Several theories purporting to account for representational momentum and related types of displacement are also considered.

Expert system shell to reason on large amounts of data

NASA Technical Reports Server (NTRS)

Giuffrida, Gionanni

1994-01-01

The current data base management systems (DBMS's) do not provide a sophisticated environment to develop rule based expert systems applications. Some of the new DBMS's come with some sort of rule mechanism; these are active and deductive database systems. However, both of these are not featured enough to support full implementation based on rules. On the other hand, current expert system shells do not provide any link with external databases. That is, all the data are kept in the system working memory. Such working memory is maintained in main memory. For some applications the reduced size of the available working memory could represent a constraint for the development. Typically these are applications which require reasoning on huge amounts of data. All these data do not fit into the computer main memory. Moreover, in some cases these data can be already available in some database systems and continuously updated while the expert system is running. This paper proposes an architecture which employs knowledge discovering techniques to reduce the amount of data to be stored in the main memory; in this architecture a standard DBMS is coupled with a rule-based language. The data are stored into the DBMS. An interface between the two systems is responsible for inducing knowledge from the set of relations. Such induced knowledge is then transferred to the rule-based language working memory.

An Interactive Simulation Program for Exploring Computational Models of Auto-Associative Memory.

PubMed

Fink, Christian G

2017-01-01

While neuroscience students typically learn about activity-dependent plasticity early in their education, they often struggle to conceptually connect modification at the synaptic scale with network-level neuronal dynamics, not to mention with their own everyday experience of recalling a memory. We have developed an interactive simulation program (based on the Hopfield model of auto-associative memory) that enables the user to visualize the connections generated by any pattern of neural activity, as well as to simulate the network dynamics resulting from such connectivity. An accompanying set of student exercises introduces the concepts of pattern completion, pattern separation, and sparse versus distributed neural representations. Results from a conceptual assessment administered before and after students worked through these exercises indicate that the simulation program is a useful pedagogical tool for illustrating fundamental concepts of computational models of memory.

Adjusting process count on demand for petascale global optimization

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

Sosonkina, Masha; Watson, Layne T.; Radcliffe, Nicholas R.

2012-11-23

There are many challenges that need to be met before efficient and reliable computation at the petascale is possible. Many scientific and engineering codes running at the petascale are likely to be memory intensive, which makes thrashing a serious problem for many petascale applications. One way to overcome this challenge is to use a dynamic number of processes, so that the total amount of memory available for the computation can be increased on demand. This paper describes modifications made to the massively parallel global optimization code pVTdirect in order to allow for a dynamic number of processes. In particular, themore » modified version of the code monitors memory use and spawns new processes if the amount of available memory is determined to be insufficient. The primary design challenges are discussed, and performance results are presented and analyzed.« less

Digital MOS integrated circuits

NASA Astrophysics Data System (ADS)

Elmasry, M. I.

MOS in digital circuit design is considered along with aspects of digital VLSI, taking into account a comparison of MOSFET logic circuits, 1-micrometer MOSFET VLSI technology, a generalized guide for MOSFET miniaturization, processing technologies, novel circuit structures for VLSI, and questions of circuit and system design for VLSI. MOS memory cells and circuits are discussed, giving attention to a survey of high-density dynamic RAM cell concepts, one-device cells for dynamic random-access memories, variable resistance polysilicon for high density CMOS Ram, high performance MOS EPROMs using a stacked-gate cell, and the optimization of the latching pulse for dynamic flip-flop sensors. Programmable logic arrays are considered along with digital signal processors, microprocessors, static RAMs, and dynamic RAMs.

Exterior view, westsouthwest, of Jeudevine Memorial Library. Built 18961897 and ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Exterior view, west-southwest, of Jeudevine Memorial Library. Built 1896-1897 and designed by local architect Lambert Packard, the library is an excellent example of Richardsonian Romanesque architecture. - Jeudevine Memorial Library, 93 North Main Street, Hardwick, Caledonia County, VT

On the dynamic nature of the engram: evidence for circuit-level reorganization of object memory traces following reactivation.

PubMed

Winters, Boyer D; Tucci, Mark C; Jacklin, Derek L; Reid, James M; Newsome, James

2011-11-30

Research has implicated the perirhinal cortex (PRh) in several aspects of object recognition memory. The specific role of the hippocampus (HPC) remains controversial, but its involvement in object recognition may pertain to processing contextual information in relation to objects rather than object representation per se. Here we investigated the roles of the PRh and HPC in object memory reconsolidation using the spontaneous object recognition task for rats. Intra-PRh infusions of the protein synthesis inhibitor anisomycin immediately following memory reactivation prevented object memory reconsolidation. Similar deficits were observed when a novel object or a salient contextual change was introduced during the reactivation phase. Intra-HPC infusions of anisomycin, however, blocked object memory reconsolidation only when a contextual change was introduced during reactivation. Moreover, disrupting functional interaction between the HPC and PRh by infusing anisomycin unilaterally into each structure in opposite hemispheres also impaired reconsolidation when reactivation was done in an altered context. These results show for the first time that the PRh is critical for reconsolidation of object memory traces and provide insight into the dynamic process of object memory storage; the selective requirement for hippocampal involvement following reactivation in an altered context suggests a substantial circuit level object trace reorganization whereby an initially PRh-dependent object memory becomes reliant on both the HPC and PRh and their interaction. Such trace reorganization may play a central role in reconsolidation-mediated memory updating and could represent an important aspect of lingering consolidation processes proposed to underlie long-term memory modulation and stabilization.

The Role and Dynamic of Strengthening in the Reconsolidation Process in a Human Declarative Memory: What Decides the Fate of Recent and Older Memories?

PubMed Central

Pedreira, María E.

2013-01-01

Several reports have shown that after specific reminders are presented, consolidated memories pass from a stable state to one in which the memory is reactivated. This reactivation implies that memories are labile and susceptible to amnesic agents. This susceptibility decreases over time and leads to a re-stabilization phase usually known as reconsolidation. With respect to the biological role of reconsolidation, two functions have been proposed. First, the reconsolidation process allows new information to be integrated into the background of the original memory; second, it strengthens the original memory. We have previously demonstrated that both of these functions occur in the reconsolidation of human declarative memories. Our paradigm consisted of learning verbal material (lists of five pairs of nonsense syllables) acquired by a training process (L1-training) on Day 1 of our experiment. After this declarative memory is consolidated, it can be made labile by presenting a specific reminder. After this, the memory passes through a subsequent stabilization process. Strengthening creates a new scenario for the reconsolidation process; this function represents a new factor that may transform the dynamic of memories. First, we analyzed whether the repeated labilization-reconsolidation processes maintained the memory for longer periods of time. We showed that at least one labilization-reconsolidation process strengthens a memory via evaluation 5 days after its re-stabilization. We also demonstrated that this effect is not triggered by retrieval only. We then analyzed the way strengthening modified the effect of an amnesic agent that was presented immediately after repeated labilizations. The repeated labilization-reconsolidation processes made the memory more resistant to interference during re-stabilization. Finally, we evaluated whether the effect of strengthening may depend on the age of the memory. We found that the effect of strengthening did depend on the age of the memory. Forgetting may represent a process that weakens the effect of strengthening. PMID:23658614

The role and dynamic of strengthening in the reconsolidation process in a human declarative memory: what decides the fate of recent and older memories?

PubMed

Forcato, Cecilia; Fernandez, Rodrigo S; Pedreira, María E

2013-01-01

Several reports have shown that after specific reminders are presented, consolidated memories pass from a stable state to one in which the memory is reactivated. This reactivation implies that memories are labile and susceptible to amnesic agents. This susceptibility decreases over time and leads to a re-stabilization phase usually known as reconsolidation. With respect to the biological role of reconsolidation, two functions have been proposed. First, the reconsolidation process allows new information to be integrated into the background of the original memory; second, it strengthens the original memory. We have previously demonstrated that both of these functions occur in the reconsolidation of human declarative memories. Our paradigm consisted of learning verbal material (lists of five pairs of nonsense syllables) acquired by a training process (L1-training) on Day 1 of our experiment. After this declarative memory is consolidated, it can be made labile by presenting a specific reminder. After this, the memory passes through a subsequent stabilization process. Strengthening creates a new scenario for the reconsolidation process; this function represents a new factor that may transform the dynamic of memories. First, we analyzed whether the repeated labilization-reconsolidation processes maintained the memory for longer periods of time. We showed that at least one labilization-reconsolidation process strengthens a memory via evaluation 5 days after its re-stabilization. We also demonstrated that this effect is not triggered by retrieval only. We then analyzed the way strengthening modified the effect of an amnesic agent that was presented immediately after repeated labilizations. The repeated labilization-reconsolidation processes made the memory more resistant to interference during re-stabilization. Finally, we evaluated whether the effect of strengthening may depend on the age of the memory. We found that the effect of strengthening did depend on the age of the memory. Forgetting may represent a process that weakens the effect of strengthening.

Compression in Working Memory and Its Relationship with Fluid Intelligence

ERIC Educational Resources Information Center

Chekaf, Mustapha; Gauvrit, Nicolas; Guida, Alessandro; Mathy, Fabien

2018-01-01

Working memory has been shown to be strongly related to fluid intelligence; however, our goal is to shed further light on the process of information compression in working memory as a determining factor of fluid intelligence. Our main hypothesis was that compression in working memory is an excellent indicator for studying the relationship between…

Mobile, Virtual Enhancements for Rehabilitation (MOVER)

DTIC Science & Technology

2013-11-28

Modeling Autobiographical Memory for Believable Agents, AIIDE, Boston, MA. 2013. From the abstract: “We present a multi-layer hierarchical...connectionist network model for simulating human autobiographical memory in believable agents. Grounded in psychological theory, this model improves on...previous attempts to model agents’ event knowledge by providing a more dynamic and nondeterministic representation of autobiographical memories .” This

Crew exploration vehicle (CEV) attitude control using a neural-immunology/memory network

NASA Astrophysics Data System (ADS)

Weng, Liguo; Xia, Min; Wang, Wei; Liu, Qingshan

2015-01-01

This paper addresses the problem of the crew exploration vehicle (CEV) attitude control. CEVs are NASA's next-generation human spaceflight vehicles, and they use reaction control system (RCS) jet engines for attitude adjustment, which calls for control algorithms for firing the small propulsion engines mounted on vehicles. In this work, the resultant CEV dynamics combines both actuation and attitude dynamics. Therefore, it is highly nonlinear and even coupled with significant uncertainties. To cope with this situation, a neural-immunology/memory network is proposed. It is inspired by the human memory and immune systems. The control network does not rely on precise system dynamics information. Furthermore, the overall control scheme has a simple structure and demands much less computation as compared with most existing methods, making it attractive for real-time implementation. The effectiveness of this approach is also verified via simulation.

Memory for incidentally perceived social cues: Effects on person judgment.

PubMed

Pawling, Ralph; Kirkham, Alexander J; Tipper, Steven P; Over, Harriet

2017-02-01

Dynamic face cues can be very salient, as when observing sudden shifts of gaze to a new location, or a change of expression from happy to angry. These highly salient social cues influence judgments of another person during the course of an interaction. However, other dynamic cues, such as pupil dilation, are much more subtle, affecting judgments of another person even without awareness. We asked whether such subtle, incidentally perceived, dynamic cues could be encoded in to memory and retrieved at a later time. The current study demonstrates that in some circumstances changes in pupil size in another person are indeed encoded into memory and influence judgments of that individual at a later time. Furthermore, these judgments interact with the perceived trustworthiness of the individual and the nature of the social context. The effect is somewhat variable, however, possibly reflecting individual differences and the inherent ambiguity of pupil dilation/constriction. © 2016 The British Psychological Society.

Dendritic spine dynamics leading to spine elimination after repeated inductions of LTD

PubMed Central

Hasegawa, Sho; Sakuragi, Shigeo; Tominaga-Yoshino, Keiko; Ogura, Akihiko

2015-01-01

Memory is fixed solidly by repetition. However, the cellular mechanism underlying this repetition-dependent memory consolidation/reconsolidation remains unclear. In our previous study using stable slice cultures of the rodent hippocampus, we found long-lasting synaptic enhancement/suppression coupled with synapse formation/elimination after repeated inductions of chemical LTP/LTD, respectively. We proposed these phenomena as useful model systems for analyzing repetition-dependent memory consolidation. Recently, we analyzed the dynamics of dendritic spines during development of the enhancement, and found that the spines increased in number following characteristic stochastic processes. The current study investigates spine dynamics during the development of the suppression. We found that the rate of spine retraction increased immediately leaving that of spine generation unaltered. Spine elimination occurred independent of the pre-existing spine density on the dendritic segment. In terms of elimination, mushroom-type spines were not necessarily more stable than stubby-type and thin-type spines. PMID:25573377

When anticipation beats accuracy: Threat alters memory for dynamic scenes.

PubMed

Greenstein, Michael; Franklin, Nancy; Martins, Mariana; Sewack, Christine; Meier, Markus A

2016-05-01

Threat frequently leads to the prioritization of survival-relevant processes. Much of the work examining threat-related processing advantages has focused on the detection of static threats or long-term memory for details. In the present study, we examined immediate memory for dynamic threatening situations. We presented participants with visually neutral, dynamic stimuli using a representational momentum (RM) paradigm, and manipulated threat conceptually. Although the participants in both the threatening and nonthreatening conditions produced classic RM effects, RM was stronger for scenarios involving threat (Exps. 1 and 2). Experiments 2 and 3 showed that this effect does not generalize to the nonthreatening objects within a threatening scene, and that it does not extend to arousing happy situations. Although the increased RM effect for threatening objects by definition reflects reduced accuracy, we argue that this reduced accuracy may be offset by a superior ability to predict, and thereby evade, a moving threat.

Design of membrane actuators based on ferromagnetic shape memory alloy composite for the synthetic jet actuator

NASA Astrophysics Data System (ADS)

Liang, Yuanchang; Taya, Minoru; Kuga, Yasuo

2004-07-01

A new membrane actuator based on our previous diaphragm actuator was designed and constructed to improve the dynamic performance. The finite element analysis was used to estimate the frequency response of the composite membrane which will be driven close to its resonance to obtain a large stroke. The membrane is made of ferromagnetic shape memory alloy (FSMA) composite including a ferromagnetic soft iron pad and a superelastic grade of NiTi shape memory alloy (SMA). The actuation mechanism for the FSMA composite membrane of the actuator is the hybrid mechanism that we proposed previously. This membrane actuator is designed for a new synthetic jet actuator package that will be used for active flow control technology on airplane wings. Based on the FEM results, the new membrane actuator system was assembled and its static and dynamic performance was experimentally evaluated including the dynamic magnetic response of the hybrid magnet.

Inflated speedups in parallel simulations via malloc()

NASA Technical Reports Server (NTRS)

Nicol, David M.

1990-01-01

Discrete-event simulation programs make heavy use of dynamic memory allocation in order to support simulation's very dynamic space requirements. When programming in C one is likely to use the malloc() routine. However, a parallel simulation which uses the standard Unix System V malloc() implementation may achieve an overly optimistic speedup, possibly superlinear. An alternate implementation provided on some (but not all systems) can avoid the speedup anomaly, but at the price of significantly reduced available free space. This is especially severe on most parallel architectures, which tend not to support virtual memory. It is shown how a simply implemented user-constructed interface to malloc() can both avoid artificially inflated speedups, and make efficient use of the dynamic memory space. The interface simply catches blocks on the basis of their size. The problem is demonstrated empirically, and the effectiveness of the solution is shown both empirically and analytically.

Fast and efficient STT switching in MTJ using additional transient pulse current

NASA Astrophysics Data System (ADS)

Pathak, Sachin; Cha, Jongin; Jo, Kangwook; Yoon, Hongil; Hong, Jongill

2017-06-01

We propose a profile of write pulse current-density to switch magnetization in a perpendicular magnetic tunnel junction to reduce switching time and write energy as well. Our simulated results show that an overshoot transient pulse current-density (current spike) imposed to conventional rectangular-shaped pulse current-density (main pulse) significantly improves switching speed that yields the reduction in write energy accordingly. For example, we could dramatically reduce the switching time by 80% and thereby reduce the write energy over 9% in comparison to the switching without current spike. The current spike affects the spin dynamics of the free layer and reduces the switching time mainly due to spin torque induced. On the other hand, the large Oersted field induced causes changes in spin texture. We believe our proposed write scheme can make a breakthrough in magnetic random access memory technology seeking both high speed operation and low energy consumption.

Fast analysis of molecular dynamics trajectories with graphics processing units-Radial distribution function histogramming

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

Levine, Benjamin G., E-mail: ben.levine@temple.ed; Stone, John E., E-mail: johns@ks.uiuc.ed; Kohlmeyer, Axel, E-mail: akohlmey@temple.ed

2011-05-01

The calculation of radial distribution functions (RDFs) from molecular dynamics trajectory data is a common and computationally expensive analysis task. The rate limiting step in the calculation of the RDF is building a histogram of the distance between atom pairs in each trajectory frame. Here we present an implementation of this histogramming scheme for multiple graphics processing units (GPUs). The algorithm features a tiling scheme to maximize the reuse of data at the fastest levels of the GPU's memory hierarchy and dynamic load balancing to allow high performance on heterogeneous configurations of GPUs. Several versions of the RDF algorithm aremore » presented, utilizing the specific hardware features found on different generations of GPUs. We take advantage of larger shared memory and atomic memory operations available on state-of-the-art GPUs to accelerate the code significantly. The use of atomic memory operations allows the fast, limited-capacity on-chip memory to be used much more efficiently, resulting in a fivefold increase in performance compared to the version of the algorithm without atomic operations. The ultimate version of the algorithm running in parallel on four NVIDIA GeForce GTX 480 (Fermi) GPUs was found to be 92 times faster than a multithreaded implementation running on an Intel Xeon 5550 CPU. On this multi-GPU hardware, the RDF between two selections of 1,000,000 atoms each can be calculated in 26.9 s per frame. The multi-GPU RDF algorithms described here are implemented in VMD, a widely used and freely available software package for molecular dynamics visualization and analysis.« less

Fast Analysis of Molecular Dynamics Trajectories with Graphics Processing Units—Radial Distribution Function Histogramming

PubMed Central

Stone, John E.; Kohlmeyer, Axel

2011-01-01

The calculation of radial distribution functions (RDFs) from molecular dynamics trajectory data is a common and computationally expensive analysis task. The rate limiting step in the calculation of the RDF is building a histogram of the distance between atom pairs in each trajectory frame. Here we present an implementation of this histogramming scheme for multiple graphics processing units (GPUs). The algorithm features a tiling scheme to maximize the reuse of data at the fastest levels of the GPU’s memory hierarchy and dynamic load balancing to allow high performance on heterogeneous configurations of GPUs. Several versions of the RDF algorithm are presented, utilizing the specific hardware features found on different generations of GPUs. We take advantage of larger shared memory and atomic memory operations available on state-of-the-art GPUs to accelerate the code significantly. The use of atomic memory operations allows the fast, limited-capacity on-chip memory to be used much more efficiently, resulting in a fivefold increase in performance compared to the version of the algorithm without atomic operations. The ultimate version of the algorithm running in parallel on four NVIDIA GeForce GTX 480 (Fermi) GPUs was found to be 92 times faster than a multithreaded implementation running on an Intel Xeon 5550 CPU. On this multi-GPU hardware, the RDF between two selections of 1,000,000 atoms each can be calculated in 26.9 seconds per frame. The multi-GPU RDF algorithms described here are implemented in VMD, a widely used and freely available software package for molecular dynamics visualization and analysis. PMID:21547007

Emotional contexts modulate intentional memory suppression of neutral faces: Insights from ERPs.

PubMed

Pierguidi, Lapo; Righi, Stefania; Gronchi, Giorgio; Marzi, Tessa; Caharel, Stephanie; Giovannelli, Fabio; Viggiano, Maria Pia

2016-08-01

The main goal of present work is to gain new insight into the temporal dynamics underlying the voluntary memory control for neutral faces associated with neutral, positive and negative contexts. A directed forgetting (DF) procedure was used during the recording of EEG to answer the question whether is it possible to forget a face that has been encoded within a particular emotional context. A face-scene phase in which a neutral face was showed in a neutral or emotional scene (positive, negative) was followed by the voluntary memory cue (cue phase) indicating whether the face had to-be remember or to-be-forgotten (TBR and TBF). Memory for faces was then assessed with an old/new recognition task. Behaviorally, we found that it is harder to suppress faces-in-positive-scenes compared to faces-in-negative and neutral-scenes. The temporal information obtained by the ERPs showed: 1) during the face-scene phase, the Late Positive Potential (LPP), which indexes motivated emotional attention, was larger for faces-in-negative-scenes compared to faces-in-neutral-scenes. 2) Remarkably, during the cue phase, ERPs were significantly modulated by the emotional contexts. Faces-in-neutral scenes showed an ERP pattern that has been typically associated to DF effect whereas faces-in-positive-scenes elicited the reverse ERP pattern. Faces-in-negative scenes did not show differences in the DF-related neural activities but larger N1 amplitude for TBF vs. TBR faces may index early attentional deployment. These results support the hypothesis that the pleasantness or unpleasantness of the contexts (through attentional broadening and narrowing mechanisms, respectively) may modulate the effectiveness of intentional memory suppression for neutral information. Copyright © 2016 Elsevier B.V. All rights reserved.

Weather prediction using a genetic memory

NASA Technical Reports Server (NTRS)

Rogers, David

1990-01-01

Kanaerva's sparse distributed memory (SDM) is an associative memory model based on the mathematical properties of high dimensional binary address spaces. Holland's genetic algorithms are a search technique for high dimensional spaces inspired by evolutional processes of DNA. Genetic Memory is a hybrid of the above two systems, in which the memory uses a genetic algorithm to dynamically reconfigure its physical storage locations to reflect correlations between the stored addresses and data. This architecture is designed to maximize the ability of the system to scale-up to handle real world problems.

Thermomechanical Response of Shape Memory Alloy Hybrid Composites. Degree awarded by Virginia Polytechnic Inst. and State Univ., Blackburg, Virginia, Nov. 2000.

NASA Technical Reports Server (NTRS)

Turner, Travis L.

2001-01-01

This study examines the use of embedded shape memory alloy (SMA) actuators for adaptive control of the thermomechanical response of composite structures. A nonlinear thermomechanical model is presented for analyzing shape memory alloy hybrid composite (SMAHC) structures exposed to steady-state thermal and dynamic mechanical loads. Also presented are (1) fabrication procedures for SMAHC specimens, (2) characterization of the constituent materials for model quantification, (3) development of the test apparatus for conducting static and dynamic experiments on specimens with and without SMA, (4) discussion of the experimental results, and (5) validation of the analytical and numerical tools developed in the study. Excellent agreement is achieved between the predicted and measured SAMHC responses including thermal buckling, thermal post-buckling and dynamic response due to inertial loading. The validated model and thermomechanical analysis tools are used to demonstrate a variety of static and dynamic response behaviors including control of static (thermal buckling and post-buckling) and dynamic responses (vibration, sonic fatigue, and acoustic transmission). and SMAHC design considerations for these applications. SMAHCs are shown to have significant advantages over conventional response abatement approaches for vibration, sonic fatigue, and noise control.

Is bigger always better? A critical appraisal of the use of volumetric analysis in the study of the hippocampus.

PubMed

Roth, Timothy C; Brodin, Anders; Smulders, Tom V; LaDage, Lara D; Pravosudov, Vladimir V

2010-03-27

A well-developed spatial memory is important for many animals, but appears especially important for scatter-hoarding species. Consequently, the scatter-hoarding system provides an excellent paradigm in which to study the integrative aspects of memory use within an ecological and evolutionary framework. One of the main tenets of this paradigm is that selection for enhanced spatial memory for cache locations should specialize the brain areas involved in memory. One such brain area is the hippocampus (Hp). Many studies have examined this adaptive specialization hypothesis, typically relating spatial memory to Hp volume. However, it is unclear how the volume of the Hp is related to its function for spatial memory. Thus, the goal of this article is to evaluate volume as a main measurement of the degree of morphological and physiological adaptation of the Hp as it relates to memory. We will briefly review the evidence for the specialization of memory in food-hoarding animals and discuss the philosophy behind volume as the main currency. We will then examine the problems associated with this approach, attempting to understand the advantages and limitations of using volume and discuss alternatives that might yield more specific hypotheses. Overall, there is strong evidence that the Hp is involved in the specialization of spatial memory in scatter-hoarding animals. However, volume may be only a coarse proxy for more relevant and subtle changes in the structure of the brain underlying changes in behaviour. To better understand the nature of this brain/memory relationship, we suggest focusing on more specific and relevant features of the Hp, such as the number or size of neurons, variation in connectivity depending on dendritic and axonal arborization and the number of synapses. These should generate more specific hypotheses derived from a solid theoretical background and should provide a better understanding of both neural mechanisms of memory and their evolution.

A Case Study on Neural Inspired Dynamic Memory Management Strategies for High Performance Computing.

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

Vineyard, Craig Michael; Verzi, Stephen Joseph

As high performance computing architectures pursue more computational power there is a need for increased memory capacity and bandwidth as well. A multi-level memory (MLM) architecture addresses this need by combining multiple memory types with different characteristics as varying levels of the same architecture. How to efficiently utilize this memory infrastructure is an unknown challenge, and in this research we sought to investigate whether neural inspired approaches can meaningfully help with memory management. In particular we explored neurogenesis inspired re- source allocation, and were able to show a neural inspired mixed controller policy can beneficially impact how MLM architectures utilizemore » memory.« less

Performance of real time associative memory using a photorefractive crystal and liquid crystal electrooptic switches

NASA Astrophysics Data System (ADS)

Xu, Haiying; Yuan, Yang; Yu, Youlong; Xu, Kebin; Xu, Yuhuan

1990-08-01

This paper presents a real time holographic associative memory implemented with photorefractive KNSBN:Co crystal as the memory element and a liquid crystal electrooptic switch array as the reflective thresholding device. The experiment stores and recalls two images and shows that the system has real-time multiple-image storage and recall functions. An associative memory with a dynamic threshold level to decide the closest match of an incomplete input is proposed.

Rutger's CAM2000 chip architecture

NASA Technical Reports Server (NTRS)

Smith, Donald E.; Hall, J. Storrs; Miyake, Keith

1993-01-01

This report describes the architecture and instruction set of the Rutgers CAM2000 memory chip. The CAM2000 combines features of Associative Processing (AP), Content Addressable Memory (CAM), and Dynamic Random Access Memory (DRAM) in a single chip package that is not only DRAM compatible but capable of applying simple massively parallel operations to memory. This document reflects the current status of the CAM2000 architecture and is continually updated to reflect the current state of the architecture and instruction set.

Final Project Report: Data Locality Enhancement of Dynamic Simulations for Exascale Computing

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

Shen, Xipeng

The goal of this project is to develop a set of techniques and software tools to enhance the matching between memory accesses in dynamic simulations and the prominent features of modern and future manycore systems, alleviating the memory performance issues for exascale computing. In the first three years, the PI and his group have achieves some significant progress towards the goal, producing a set of novel techniques for improving the memory performance and data locality in manycore systems, yielding 18 conference and workshop papers and 4 journal papers and graduating 6 Ph.Ds. This report summarizes the research results of thismore » project through that period.« less

Working memory load modulation of parieto-frontal connections: evidence from dynamic causal modeling

PubMed Central

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

2011-01-01

Previous neuroimaging studies have shown that working memory load has marked effects on regional neural activation. However, the mechanism through which working memory load modulates brain connectivity is still unclear. In this study, this issue was addressed using dynamic causal modeling (DCM) based on functional magnetic resonance imaging (fMRI) data. Eighteen normal healthy subjects were scanned while they performed a working memory task with variable memory load, as parameterized by two levels of memory delay and three levels of digit load (number of digits presented in each visual stimulus). Eight regions of interest, i.e., bilateral middle frontal gyrus (MFG), anterior cingulate cortex (ACC), inferior frontal cortex (IFC), and posterior parietal cortex (PPC), were chosen for DCM analyses. Analysis of the behavioral data during the fMRI scan revealed that accuracy decreased as digit load increased. Bayesian inference on model structure indicated that a bilinear DCM in which memory delay was the driving input to bilateral PPC and in which digit load modulated several parieto-frontal connections was the optimal model. Analysis of model parameters showed that higher digit load enhanced connection from L PPC to L IFC, and lower digit load inhibited connection from R PPC to L ACC. These findings suggest that working memory load modulates brain connectivity in a parieto-frontal network, and may reflect altered neuronal processes, e.g., information processing or error monitoring, with the change in working memory load. PMID:21692148

Mori-Zwanzig theory for dissipative forces in coarse-grained dynamics in the Markov limit

NASA Astrophysics Data System (ADS)

Izvekov, Sergei

2017-01-01

We derive alternative Markov approximations for the projected (stochastic) force and memory function in the coarse-grained (CG) generalized Langevin equation, which describes the time evolution of the center-of-mass coordinates of clusters of particles in the microscopic ensemble. This is done with the aid of the Mori-Zwanzig projection operator method based on the recently introduced projection operator [S. Izvekov, J. Chem. Phys. 138, 134106 (2013), 10.1063/1.4795091]. The derivation exploits the "generalized additive fluctuating force" representation to which the projected force reduces in the adopted projection operator formalism. For the projected force, we present a first-order time expansion which correctly extends the static fluctuating force ansatz with the terms necessary to maintain the required orthogonality of the projected dynamics in the Markov limit to the space of CG phase variables. The approximant of the memory function correctly accounts for the momentum dependence in the lowest (second) order and indicates that such a dependence may be important in the CG dynamics approaching the Markov limit. In the case of CG dynamics with a weak dependence of the memory effects on the particle momenta, the expression for the memory function presented in this work is applicable to non-Markov systems. The approximations are formulated in a propagator-free form allowing their efficient evaluation from the microscopic data sampled by standard molecular dynamics simulations. A numerical application is presented for a molecular liquid (nitromethane). With our formalism we do not observe the "plateau-value problem" if the friction tensors for dissipative particle dynamics (DPD) are computed using the Green-Kubo relation. Our formalism provides a consistent bottom-up route for hierarchical parametrization of DPD models from atomistic simulations.

Virtual memory

NASA Technical Reports Server (NTRS)

Denning, P. J.

1986-01-01

Virtual memory was conceived as a way to automate overlaying of program segments. Modern computers have very large main memories, but need automatic solutions to the relocation and protection problems. Virtual memory serves this need as well and is thus useful in computers of all sizes. The history of the idea is traced, showing how it has become a widespread, little noticed feature of computers today.

Enhancement of fear memory by retrieval through reconsolidation

PubMed Central

Fukushima, Hotaka; Zhang, Yue; Archbold, Georgia; Ishikawa, Rie; Nader, Karim; Kida, Satoshi

2014-01-01

Memory retrieval is considered to have roles in memory enhancement. Recently, memory reconsolidation was suggested to reinforce or integrate new information into reactivated memory. Here, we show that reactivated inhibitory avoidance (IA) memory is enhanced through reconsolidation under conditions in which memory extinction is not induced. This memory enhancement is mediated by neurons in the amygdala, hippocampus, and medial prefrontal cortex (mPFC) through the simultaneous activation of calcineurin-induced proteasome-dependent protein degradation and cAMP responsive element binding protein-mediated gene expression. Interestingly, the amygdala is required for memory reconsolidation and enhancement, whereas the hippocampus and mPFC are required for only memory enhancement. Furthermore, memory enhancement triggered by retrieval utilizes distinct mechanisms to strengthen IA memory by additional learning that depends only on the amygdala. Our findings indicate that reconsolidation functions to strengthen the original memory and show the dynamic nature of reactivated memory through protein degradation and gene expression in multiple brain regions. DOI: http://dx.doi.org/10.7554/eLife.02736.001 PMID:24963141

Relations between episodic memory, suggestibility, theory of mind, and cognitive inhibition in the preschool child.

PubMed

Melinder, Annika; Endestad, Tor; Magnussen, Svein

2006-12-01

The development of episodic memory, its relation to theory of mind (ToM), executive functions (e.g., cognitive inhibition), and to suggestibility was studied. Children (n= 115) between 3 and 6 years of age saw two versions of a video film and were tested for their memory of critical elements of the videos. Results indicated similar developmental trends for all memory measures, ToM, and inhibition, but ToM and inhibition were not associated with any memory measures. Correlations involving source memory was found in relation to specific questions, whereas inhibition and ToM were significantly correlated to resistance to suggestions. A regression analysis showed that age was the main contributor to resistance to suggestions, to correct source monitoring, and to correct responses to specific questions. Inhibition was also a significant main predictor of resistance to suggestive questions, whereas the relative contribution of ToM was wiped out when an extended model was tested.

Comparison and Analysis of 3,4 dihydrocylmandelic acid (DHMA) and noremetanephrine (NMN) on Amyloid-Beta 40 Monomer for treatment of Alzheimer's Disease using Molecular Dynamics Simulation

NASA Astrophysics Data System (ADS)

Choi, Woosung; Jee, Sang Eun; Jang, Seung Soon

Alzheimer's disease (AD) is type of degenerative dementia caused memory loss and behavior problem. Main reason of AD is Amyloid-Beta 40(A β) mostly composed of α -helix form misfolds to insoluble fibrils and soluble oilgomer. This insoluble fibrils aggregate with beta sheet structure and form the plaque which is caused nurotoxicity in brain. Both 3,4 dihydrocylmandelic acid (DHMA) and noremetanephrine (NMN) are the metabolite of norepinephrine in brain . Also these are inhibit the changing formation of fibrils and maintain the α -helix structure. In this computational modeling study, both NMN and DHMA molecules were modified and analyzed for specific effect on the A β-monomer using molecular dynamics simulation. Using molecular dynamic simulation, NMN and DHMA act as modulator on three A β-monomer batches and could observe the conformational changing of these A β-monomer under the physiologocal condition. This computational experiment is designed to compare and analyze both of chemicals for determining which chamecal would be more effective on the conformation of A β 40 monomer.

A Component-Based FPGA Design Framework for Neuronal Ion Channel Dynamics Simulations

PubMed Central

Mak, Terrence S. T.; Rachmuth, Guy; Lam, Kai-Pui; Poon, Chi-Sang

2008-01-01

Neuron-machine interfaces such as dynamic clamp and brain-implantable neuroprosthetic devices require real-time simulations of neuronal ion channel dynamics. Field Programmable Gate Array (FPGA) has emerged as a high-speed digital platform ideal for such application-specific computations. We propose an efficient and flexible component-based FPGA design framework for neuronal ion channel dynamics simulations, which overcomes certain limitations of the recently proposed memory-based approach. A parallel processing strategy is used to minimize computational delay, and a hardware-efficient factoring approach for calculating exponential and division functions in neuronal ion channel models is used to conserve resource consumption. Performances of the various FPGA design approaches are compared theoretically and experimentally in corresponding implementations of the AMPA and NMDA synaptic ion channel models. Our results suggest that the component-based design framework provides a more memory economic solution as well as more efficient logic utilization for large word lengths, whereas the memory-based approach may be suitable for time-critical applications where a higher throughput rate is desired. PMID:17190033

Feedback coupling in dynamical systems

NASA Astrophysics Data System (ADS)

Trimper, Steffen; Zabrocki, Knud

2003-05-01

Different evolution models are considered with feedback-couplings. In particular, we study the Lotka-Volterra system under the influence of a cumulative term, the Ginzburg-Landau model with a convolution memory term and chemical rate equations with time delay. The memory leads to a modified dynamical behavior. In case of a positive coupling the generalized Lotka-Volterra system exhibits a maximum gain achieved after a finite time, but the population will die out in the long time limit. In the opposite case, the time evolution is terminated in a crash. Due to the nonlinear feedback coupling the two branches of a bistable model are controlled by the the strength and the sign of the memory. For a negative coupling the system is able to switch over between both branches of the stationary solution. The dynamics of the system is further controlled by the initial condition. The diffusion-limited reaction is likewise studied in case the reacting entities are not available simultaneously. Whereas for an external feedback the dynamics is altered, but the stationary solution remain unchanged, a self-organized internal feedback leads to a time persistent solution.

Dynamic visual noise reduces confidence in short-term memory for visual information.

PubMed

Kemps, Eva; Andrade, Jackie

2012-05-01

Previous research has shown effects of the visual interference technique, dynamic visual noise (DVN), on visual imagery, but not on visual short-term memory, unless retention of precise visual detail is required. This study tested the prediction that DVN does also affect retention of gross visual information, specifically by reducing confidence. Participants performed a matrix pattern memory task with three retention interval interference conditions (DVN, static visual noise and no interference control) that varied from trial to trial. At recall, participants indicated whether or not they were sure of their responses. As in previous research, DVN did not impair recall accuracy or latency on the task, but it did reduce recall confidence relative to static visual noise and no interference. We conclude that DVN does distort visual representations in short-term memory, but standard coarse-grained recall measures are insensitive to these distortions.

Formation of visual memories controlled by gamma power phase-locked to alpha oscillations.

PubMed

Park, Hyojin; Lee, Dong Soo; Kang, Eunjoo; Kang, Hyejin; Hahm, Jarang; Kim, June Sic; Chung, Chun Kee; Jiang, Haiteng; Gross, Joachim; Jensen, Ole

2016-06-16

Neuronal oscillations provide a window for understanding the brain dynamics that organize the flow of information from sensory to memory areas. While it has been suggested that gamma power reflects feedforward processing and alpha oscillations feedback control, it remains unknown how these oscillations dynamically interact. Magnetoencephalography (MEG) data was acquired from healthy subjects who were cued to either remember or not remember presented pictures. Our analysis revealed that in anticipation of a picture to be remembered, alpha power decreased while the cross-frequency coupling between gamma power and alpha phase increased. A measure of directionality between alpha phase and gamma power predicted individual ability to encode memory: stronger control of alpha phase over gamma power was associated with better memory. These findings demonstrate that encoding of visual information is reflected by a state determined by the interaction between alpha and gamma activity.

Set selection dynamical system neural networks with partial memories, with applications to Sudoku and KenKen puzzles.

PubMed

Boreland, B; Clement, G; Kunze, H

2015-08-01

After reviewing set selection and memory model dynamical system neural networks, we introduce a neural network model that combines set selection with partial memories (stored memories on subsets of states in the network). We establish that feasible equilibria with all states equal to ± 1 correspond to answers to a particular set theoretic problem. We show that KenKen puzzles can be formulated as a particular case of this set theoretic problem and use the neural network model to solve them; in addition, we use a similar approach to solve Sudoku. We illustrate the approach in examples. As a heuristic experiment, we use online or print resources to identify the difficulty of the puzzles and compare these difficulties to the number of iterations used by the appropriate neural network solver, finding a strong relationship. Copyright © 2015 Elsevier Ltd. All rights reserved.

Formation of visual memories controlled by gamma power phase-locked to alpha oscillations

PubMed Central

Park, Hyojin; Lee, Dong Soo; Kang, Eunjoo; Kang, Hyejin; Hahm, Jarang; Kim, June Sic; Chung, Chun Kee; Jiang, Haiteng; Gross, Joachim; Jensen, Ole

2016-01-01

Neuronal oscillations provide a window for understanding the brain dynamics that organize the flow of information from sensory to memory areas. While it has been suggested that gamma power reflects feedforward processing and alpha oscillations feedback control, it remains unknown how these oscillations dynamically interact. Magnetoencephalography (MEG) data was acquired from healthy subjects who were cued to either remember or not remember presented pictures. Our analysis revealed that in anticipation of a picture to be remembered, alpha power decreased while the cross-frequency coupling between gamma power and alpha phase increased. A measure of directionality between alpha phase and gamma power predicted individual ability to encode memory: stronger control of alpha phase over gamma power was associated with better memory. These findings demonstrate that encoding of visual information is reflected by a state determined by the interaction between alpha and gamma activity. PMID:27306959

Formation of visual memories controlled by gamma power phase-locked to alpha oscillations

NASA Astrophysics Data System (ADS)

Park, Hyojin; Lee, Dong Soo; Kang, Eunjoo; Kang, Hyejin; Hahm, Jarang; Kim, June Sic; Chung, Chun Kee; Jiang, Haiteng; Gross, Joachim; Jensen, Ole

2016-06-01

Neuronal oscillations provide a window for understanding the brain dynamics that organize the flow of information from sensory to memory areas. While it has been suggested that gamma power reflects feedforward processing and alpha oscillations feedback control, it remains unknown how these oscillations dynamically interact. Magnetoencephalography (MEG) data was acquired from healthy subjects who were cued to either remember or not remember presented pictures. Our analysis revealed that in anticipation of a picture to be remembered, alpha power decreased while the cross-frequency coupling between gamma power and alpha phase increased. A measure of directionality between alpha phase and gamma power predicted individual ability to encode memory: stronger control of alpha phase over gamma power was associated with better memory. These findings demonstrate that encoding of visual information is reflected by a state determined by the interaction between alpha and gamma activity.

Does predictability matter? Effects of cue predictability on neurocognitive mechanisms underlying prospective memory.

PubMed

Cona, Giorgia; Arcara, Giorgio; Tarantino, Vincenza; Bisiacchi, Patrizia S

2015-01-01

Prospective memory (PM) represents the ability to successfully realize intentions when the appropriate moment or cue occurs. In this study, we used event-related potentials (ERPs) to explore the impact of cue predictability on the cognitive and neural mechanisms supporting PM. Participants performed an ongoing task and, simultaneously, had to remember to execute a pre-specified action when they encountered the PM cues. The occurrence of the PM cues was predictable (being signaled by a warning cue) for some participants and was completely unpredictable for others. In the predictable cue condition, the behavioral and ERP correlates of strategic monitoring were observed mainly in the ongoing trials wherein the PM cue was expected. In the unpredictable cue condition they were instead shown throughout the whole PM block. This pattern of results suggests that, in the predictable cue condition, participants engaged monitoring only when subjected to a context wherein the PM cue was expected, and disengaged monitoring when the PM cue was not expected. Conversely, participants in the unpredictable cue condition distributed their resources for strategic monitoring in more continuous manner. The findings of this study support the most recent views-the "Dynamic Multiprocess Framework" and the "Attention to Delayed Intention" (AtoDI) model-confirming that strategic monitoring is a flexible mechanism that is recruited mainly when a PM cue is expected and that may interact with bottom-up spontaneous processes.

Dynamic Load Balancing for Adaptive Computations on Distributed-Memory Machines

NASA Technical Reports Server (NTRS)

1999-01-01

Dynamic load balancing is central to adaptive mesh-based computations on large-scale parallel computers. The principal investigator has investigated various issues on the dynamic load balancing problem under NASA JOVE and JAG rants. The major accomplishments of the project are two graph partitioning algorithms and a load balancing framework. The S-HARP dynamic graph partitioner is known to be the fastest among the known dynamic graph partitioners to date. It can partition a graph of over 100,000 vertices in 0.25 seconds on a 64- processor Cray T3E distributed-memory multiprocessor while maintaining the scalability of over 16-fold speedup. Other known and widely used dynamic graph partitioners take over a second or two while giving low scalability of a few fold speedup on 64 processors. These results have been published in journals and peer-reviewed flagship conferences.

Josephson-CMOS Hybrid Memories

DTIC Science & Technology

2007-04-25

threshold voltage. The subthreshold behavior is critical for dynamic circuits since it determines the static power and retention time of a dynamic memory...results of subthreshold behaviors for different temperatures are shown in Fig. 2.9, the simulated results con- firm the analysis above. Also, experimental...0.5-26.5 GHz 25 dB gain), but they are not on-chip because they comsume so much power (9 W) that you cannot afford to build them on chip. [52] Another

A Time-Aware Routing Map for Indoor Evacuation †

PubMed Central

Zhao, Haifeng; Winter, Stephan

2016-01-01

Knowledge of dynamic environments expires over time. Thus, using static maps of the environment for decision making is problematic, especially in emergency situations, such as evacuations. This paper suggests a fading memory model for mapping dynamic environments: a mechanism to put less trust on older knowledge in decision making. The model has been assessed by simulating indoor evacuations, adopting and comparing various strategies in decision making. Results suggest that fading memory generally improves this decision making. PMID:26797610

Representational momentum in dynamic facial expressions is modulated by the level of expressed pain: Amplitude and direction effects.

PubMed

Prigent, Elise; Amorim, Michel-Ange; de Oliveira, Armando Mónica

2018-01-01

Humans have developed a specific capacity to rapidly perceive and anticipate other people's facial expressions so as to get an immediate impression of their emotional state of mind. We carried out two experiments to examine the perceptual and memory dynamics of facial expressions of pain. In the first experiment, we investigated how people estimate other people's levels of pain based on the perception of various dynamic facial expressions; these differ both in terms of the amount and intensity of activated action units. A second experiment used a representational momentum (RM) paradigm to study the emotional anticipation (memory bias) elicited by the same facial expressions of pain studied in Experiment 1. Our results highlighted the relationship between the level of perceived pain (in Experiment 1) and the direction and magnitude of memory bias (in Experiment 2): When perceived pain increases, the memory bias tends to be reduced (if positive) and ultimately becomes negative. Dynamic facial expressions of pain may reenact an "immediate perceptual history" in the perceiver before leading to an emotional anticipation of the agent's upcoming state. Thus, a subtle facial expression of pain (i.e., a low contraction around the eyes) that leads to a significant positive anticipation can be considered an adaptive process-one through which we can swiftly and involuntarily detect other people's pain.

Overcoming the drawback of lower sense margin in tunnel FET based dynamic memory along with enhanced charge retention and scalability

NASA Astrophysics Data System (ADS)

Navlakha, Nupur; Kranti, Abhinav

2017-11-01

The work reports on the use of a planar tri-gate tunnel field effect transistor (TFET) to operate as dynamic memory at 85 °C with an enhanced sense margin (SM). Two symmetric gates (G1) aligned to the source at a partial region of intrinsic film result into better electrostatic control that regulates the read mechanism based on band-to-band tunneling, while the other gate (G2), positioned adjacent to the first front gate is responsible for charge storage and sustenance. The proposed architecture results in an enhanced SM of ˜1.2 μA μm-1 along with a longer retention time (RT) of ˜1.8 s at 85 °C, for a total length of 600 nm. The double gate architecture towards the source increases the tunneling current and also reduces short channel effects, enhancing SM and scalability, thereby overcoming the critical bottleneck faced by TFET based dynamic memories. The work also discusses the impact of overlap/underlap and interface charges on the performance of TFET based dynamic memory. Insights into device operation demonstrate that the choice of appropriate architecture and biases not only limit the trade-off between SM and RT, but also result in improved scalability with drain voltage and total length being scaled down to 0.8 V and 115 nm, respectively.

Two Spatial Memories Are Not Better than One: Evidence of Exclusivity in Memory for Object Location

ERIC Educational Resources Information Center

Baguley, Thom; Lansdale, Mark W.; Lines, Lorna K.; Parkin, Jennifer K.

2006-01-01

This paper studies the dynamics of attempting to access two spatial memories simultaneously and its implications for the accuracy of recall. Experiment 1 demonstrates in a range of conditions that two cues pointing to different experiences of the same object location produce little or no higher recall than that observed with a single cue.…

The Dynamics of Scaling: A Memory-Based Anchor Model of Category Rating and Absolute Identification

ERIC Educational Resources Information Center

Petrov, Alexander A.; Anderson, John R.

2005-01-01

A memory-based scaling model--ANCHOR--is proposed and tested. The perceived magnitude of the target stimulus is compared with a set of anchors in memory. Anchor selection is probabilistic and sensitive to similarity, base-level strength, and recency. The winning anchor provides a reference point near the target and thereby converts the global…

Synaptic consolidation as a temporally variable process: Uncovering the parameters modulating its time-course.

PubMed

Casagrande, Mirelle A; Haubrich, Josué; Pedraza, Lizeth K; Popik, Bruno; Quillfeldt, Jorge A; de Oliveira Alvares, Lucas

2018-04-01

Memories are not instantly created in the brain, requiring a gradual stabilization process called consolidation to be stored and persist in a long-lasting manner. However, little is known whether this time-dependent process is dynamic or static, and the factors that might modulate it. Here, we hypothesized that the time-course of consolidation could be affected by specific learning parameters, changing the time window where memory is susceptible to retroactive interference. In the rodent contextual fear conditioning paradigm, we compared weak and strong training protocols and found that in the latter memory is susceptible to post-training hippocampal inactivation for a shorter period of time. The accelerated consolidation process triggered by the strong training was mediated by glucocorticoids, since this effect was blocked by pre-training administration of metyrapone. In addition, we found that pre-exposure to the training context also accelerates fear memory consolidation. Hence, our results demonstrate that the time window in which memory is susceptible to post-training interferences varies depending on fear conditioning intensity and contextual familiarity. We propose that the time-course of memory consolidation is dynamic, being directly affected by attributes of the learning experiences. Copyright © 2018 Elsevier Inc. All rights reserved.

An Implementation Method of the Fractional-Order PID Control System Considering the Memory Constraint and its Application to the Temperature Control of Heat Plate

NASA Astrophysics Data System (ADS)

Sasano, Koji; Okajima, Hiroshi; Matsunaga, Nobutomo

Recently, the fractional order PID (FO-PID) control, which is the extension of the PID control, has been focused on. Even though the FO-PID requires the high-order filter, it is difficult to realize the high-order filter due to the memory limitation of digital computer. For implementation of FO-PID, approximation of the fractional integrator and differentiator are required. Short memory principle (SMP) is one of the effective approximation methods. However, there is a disadvantage that the approximated filter with SMP cannot eliminate the steady-state error. For this problem, we introduce the distributed implementation of the integrator and the dynamic quantizer to make the efficient use of permissible memory. The objective of this study is to clarify how to implement the accurate FO-PID with limited memories. In this paper, we propose the implementation method of FO-PID with memory constraint using dynamic quantizer. And the trade off between approximation of fractional elements and quantized data size are examined so as to close to the ideal FO-PID responses. The effectiveness of proposed method is evaluated by numerical example and experiment in the temperature control of heat plate.

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

PubMed Central

D’Esposito, Mark

2017-01-01

Recent work has established that visual working memory is subject to serial dependence: current information in memory blends with that from the recent past as a function of their similarity. This tuned temporal smoothing likely promotes the stability of memory in the face of noise and occlusion. Serial dependence accumulates over several seconds in memory and deteriorates with increased separation between trials. While this phenomenon has been extensively characterized in behavior, its neural mechanism is unknown. In the present study, we investigate the circuit-level origins of serial dependence in a biophysical model of cortex. We explore two distinct kinds of mechanisms: stable persistent activity during the memory delay period and dynamic “activity-silent” synaptic plasticity. We find that networks endowed with both strong reverberation to support persistent activity and dynamic synapses can closely reproduce behavioral serial dependence. Specifically, elevated activity drives synaptic augmentation, which biases activity on the subsequent trial, giving rise to a spatiotemporally tuned shift in the population response. Our hybrid neural model is a theoretical advance beyond abstract mathematical characterizations, offers testable hypotheses for physiological research, and demonstrates the power of biological insights to provide a quantitative explanation of human behavior. PMID:29244810

Rapid learning dynamics in individual honeybees during classical conditioning.

PubMed

Pamir, Evren; Szyszka, Paul; Scheiner, Ricarda; Nawrot, Martin P

2014-01-01

Associative learning in insects has been studied extensively by a multitude of classical conditioning protocols. However, so far little emphasis has been put on the dynamics of learning in individuals. The honeybee is a well-established animal model for learning and memory. We here studied associative learning as expressed in individual behavior based on a large collection of data on olfactory classical conditioning (25 datasets, 3298 animals). We show that the group-averaged learning curve and memory retention score confound three attributes of individual learning: the ability or inability to learn a given task, the generally fast acquisition of a conditioned response (CR) in learners, and the high stability of the CR during consecutive training and memory retention trials. We reassessed the prevailing view that more training results in better memory performance and found that 24 h memory retention can be indistinguishable after single-trial and multiple-trial conditioning in individuals. We explain how inter-individual differences in learning can be accommodated within the Rescorla-Wagner theory of associative learning. In both data-analysis and modeling we demonstrate how the conflict between population-level and single-animal perspectives on learning and memory can be disentangled.

Rapid learning dynamics in individual honeybees during classical conditioning

PubMed Central

Pamir, Evren; Szyszka, Paul; Scheiner, Ricarda; Nawrot, Martin P.

2014-01-01

Associative learning in insects has been studied extensively by a multitude of classical conditioning protocols. However, so far little emphasis has been put on the dynamics of learning in individuals. The honeybee is a well-established animal model for learning and memory. We here studied associative learning as expressed in individual behavior based on a large collection of data on olfactory classical conditioning (25 datasets, 3298 animals). We show that the group-averaged learning curve and memory retention score confound three attributes of individual learning: the ability or inability to learn a given task, the generally fast acquisition of a conditioned response (CR) in learners, and the high stability of the CR during consecutive training and memory retention trials. We reassessed the prevailing view that more training results in better memory performance and found that 24 h memory retention can be indistinguishable after single-trial and multiple-trial conditioning in individuals. We explain how inter-individual differences in learning can be accommodated within the Rescorla–Wagner theory of associative learning. In both data-analysis and modeling we demonstrate how the conflict between population-level and single-animal perspectives on learning and memory can be disentangled. PMID:25309366

Spectral decomposition of nonlinear systems with memory

NASA Astrophysics Data System (ADS)

Svenkeson, Adam; Glaz, Bryan; Stanton, Samuel; West, Bruce J.

2016-02-01

We present an alternative approach to the analysis of nonlinear systems with long-term memory that is based on the Koopman operator and a Lévy transformation in time. Memory effects are considered to be the result of interactions between a system and its surrounding environment. The analysis leads to the decomposition of a nonlinear system with memory into modes whose temporal behavior is anomalous and lacks a characteristic scale. On average, the time evolution of a mode follows a Mittag-Leffler function, and the system can be described using the fractional calculus. The general theory is demonstrated on the fractional linear harmonic oscillator and the fractional nonlinear logistic equation. When analyzing data from an ill-defined (black-box) system, the spectral decomposition in terms of Mittag-Leffler functions that we propose may uncover inherent memory effects through identification of a small set of dynamically relevant structures that would otherwise be obscured by conventional spectral methods. Consequently, the theoretical concepts we present may be useful for developing more general methods for numerical modeling that are able to determine whether observables of a dynamical system are better represented by memoryless operators, or operators with long-term memory in time, when model details are unknown.

Dynamics of Hippocampal Protein Expression During Long-term Spatial Memory Formation*

PubMed Central

Borovok, Natalia; Nesher, Elimelech; Levin, Yishai; Reichenstein, Michal; Pinhasov, Albert

2016-01-01

Spatial memory depends on the hippocampus, which is particularly vulnerable to aging. This vulnerability has implications for the impairment of navigation capacities in older people, who may show a marked drop in performance of spatial tasks with advancing age. Contemporary understanding of long-term memory formation relies on molecular mechanisms underlying long-term synaptic plasticity. With memory acquisition, activity-dependent changes occurring in synapses initiate multiple signal transduction pathways enhancing protein turnover. This enhancement facilitates de novo synthesis of plasticity related proteins, crucial factors for establishing persistent long-term synaptic plasticity and forming memory engrams. Extensive studies have been performed to elucidate molecular mechanisms of memory traces formation; however, the identity of plasticity related proteins is still evasive. In this study, we investigated protein turnover in mouse hippocampus during long-term spatial memory formation using the reference memory version of radial arm maze (RAM) paradigm. We identified 1592 proteins, which exhibited a complex picture of expression changes during spatial memory formation. Variable linear decomposition reduced significantly data dimensionality and enriched three principal factors responsible for variance of memory-related protein levels at (1) the initial phase of memory acquisition (165 proteins), (2) during the steep learning improvement (148 proteins), and (3) the final phase of the learning curve (123 proteins). Gene ontology and signaling pathways analysis revealed a clear correlation between memory improvement and learning phase-curbed expression profiles of proteins belonging to specific functional categories. We found differential enrichment of (1) neurotrophic factors signaling pathways, proteins regulating synaptic transmission, and actin microfilament during the first day of the learning curve; (2) transcription and translation machinery, protein trafficking, enhancement of metabolic activity, and Wnt signaling pathway during the steep phase of memory formation; and (3) cytoskeleton organization proteins. Taken together, this study clearly demonstrates dynamic assembly and disassembly of protein-protein interaction networks depending on the stage of memory formation engrams. PMID:26598641

A cross-cultural perspective on aging and memory: Comparisons between Bangladesh and Sweden.

PubMed

Sternäng, Ola; Kabir, Zarina N; Hamadani, Jena D; Wahlin, Åke

2012-12-01

Most studies on cognitive aging have been conducted in high-income countries (mainly on Western populations). The main aim of this study was to compare the relative importance of predictors of episodic and semantic memory performance in older people (≥60 years) from Bangladesh (n = 400) and Sweden (n = 1,098). Hierarchical regression models were used in order to study the importance of some commonly used predictors in the two countries. A main finding was that variations in age did not have much impact on episodic and semantic memory performance in Bangladesh. Instead, sex was a strong predictor for semantic memory performance. In Sweden this pattern was reversed. In the Western world, chronological age is believed to be strongly associated with memory performance in cross-sectional studies, particularly in people greater than 60 years of age. This study indicates that the difference between the two countries (in relative importance of the predictors included in this study) is mainly due to the fact that years of education is connected to age in the Western world but to sex in Bangladesh. It remains to be examined whether earlier selective survival is also responsible for the relative absence of cognitive age differences in Bangladesh. © 2012 The Institute of Psychology, Chinese Academy of Sciences and Blackwell Publishing Asia Pty Ltd.

Past makes future: role of pFC in prediction.

PubMed

Fuster, Joaquín M; Bressler, Steven L

2015-04-01

The pFC enables the essential human capacities for predicting future events and preadapting to them. These capacities rest on both the structure and dynamics of the human pFC. Structurally, pFC, together with posterior association cortex, is at the highest hierarchical level of cortical organization, harboring neural networks that represent complex goal-directed actions. Dynamically, pFC is at the highest level of the perception-action cycle, the circular processing loop through the cortex that interfaces the organism with the environment in the pursuit of goals. In its predictive and preadaptive roles, pFC supports cognitive functions that are critical for the temporal organization of future behavior, including planning, attentional set, working memory, decision-making, and error monitoring. These functions have a common future perspective and are dynamically intertwined in goal-directed action. They all utilize the same neural infrastructure: a vast array of widely distributed, overlapping, and interactive cortical networks of personal memory and semantic knowledge, named cognits, which are formed by synaptic reinforcement in learning and memory acquisition. From this cortex-wide reservoir of memory and knowledge, pFC generates purposeful, goal-directed actions that are preadapted to predicted future events.

A Scalable Multicore Architecture With Heterogeneous Memory Structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs).

PubMed

Moradi, Saber; Qiao, Ning; Stefanini, Fabio; Indiveri, Giacomo

2018-02-01

Neuromorphic computing systems comprise networks of neurons that use asynchronous events for both computation and communication. This type of representation offers several advantages in terms of bandwidth and power consumption in neuromorphic electronic systems. However, managing the traffic of asynchronous events in large scale systems is a daunting task, both in terms of circuit complexity and memory requirements. Here, we present a novel routing methodology that employs both hierarchical and mesh routing strategies and combines heterogeneous memory structures for minimizing both memory requirements and latency, while maximizing programming flexibility to support a wide range of event-based neural network architectures, through parameter configuration. We validated the proposed scheme in a prototype multicore neuromorphic processor chip that employs hybrid analog/digital circuits for emulating synapse and neuron dynamics together with asynchronous digital circuits for managing the address-event traffic. We present a theoretical analysis of the proposed connectivity scheme, describe the methods and circuits used to implement such scheme, and characterize the prototype chip. Finally, we demonstrate the use of the neuromorphic processor with a convolutional neural network for the real-time classification of visual symbols being flashed to a dynamic vision sensor (DVS) at high speed.

Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision.

PubMed

Shi, Junxing; Wen, Haiguang; Zhang, Yizhen; Han, Kuan; Liu, Zhongming

2018-05-01

The human visual cortex extracts both spatial and temporal visual features to support perception and guide behavior. Deep convolutional neural networks (CNNs) provide a computational framework to model cortical representation and organization for spatial visual processing, but unable to explain how the brain processes temporal information. To overcome this limitation, we extended a CNN by adding recurrent connections to different layers of the CNN to allow spatial representations to be remembered and accumulated over time. The extended model, or the recurrent neural network (RNN), embodied a hierarchical and distributed model of process memory as an integral part of visual processing. Unlike the CNN, the RNN learned spatiotemporal features from videos to enable action recognition. The RNN better predicted cortical responses to natural movie stimuli than the CNN, at all visual areas, especially those along the dorsal stream. As a fully observable model of visual processing, the RNN also revealed a cortical hierarchy of temporal receptive window, dynamics of process memory, and spatiotemporal representations. These results support the hypothesis of process memory, and demonstrate the potential of using the RNN for in-depth computational understanding of dynamic natural vision. © 2018 Wiley Periodicals, Inc.

The Role of Semantic Representations in Verbal Working Memory

ERIC Educational Resources Information Center

Loaiza, Vanessa M.; Camos, Valérie

2018-01-01

Two main mechanisms, articulatory rehearsal and attentional refreshing, are argued to be involved in the maintenance of verbal information in working memory (WM). Whereas converging research has suggested that rehearsal promotes the phonological representations of memoranda in working memory, little is known about the representations that…

Multifractal analysis of information processing in hippocampal neural ensembles during working memory under Δ9-tetrahydrocannabinol administration

PubMed Central

Fetterhoff, Dustin; Opris, Ioan; Simpson, Sean L.; Deadwyler, Sam A.; Hampson, Robert E.; Kraft, Robert A.

2014-01-01

Background Multifractal analysis quantifies the time-scale-invariant properties in data by describing the structure of variability over time. By applying this analysis to hippocampal interspike interval sequences recorded during performance of a working memory task, a measure of long-range temporal correlations and multifractal dynamics can reveal single neuron correlates of information processing. New method Wavelet leaders-based multifractal analysis (WLMA) was applied to hippocampal interspike intervals recorded during a working memory task. WLMA can be used to identify neurons likely to exhibit information processing relevant to operation of brain–computer interfaces and nonlinear neuronal models. Results Neurons involved in memory processing (“Functional Cell Types” or FCTs) showed a greater degree of multifractal firing properties than neurons without task-relevant firing characteristics. In addition, previously unidentified FCTs were revealed because multifractal analysis suggested further functional classification. The cannabinoid-type 1 receptor partial agonist, tetrahydrocannabinol (THC), selectively reduced multifractal dynamics in FCT neurons compared to non-FCT neurons. Comparison with existing methods WLMA is an objective tool for quantifying the memory-correlated complexity represented by FCTs that reveals additional information compared to classification of FCTs using traditional z-scores to identify neuronal correlates of behavioral events. Conclusion z-Score-based FCT classification provides limited information about the dynamical range of neuronal activity characterized by WLMA. Increased complexity, as measured with multifractal analysis, may be a marker of functional involvement in memory processing. The level of multifractal attributes can be used to differentially emphasize neural signals to improve computational models and algorithms underlying brain–computer interfaces. PMID:25086297

Cue-independent memory impairment by reactivation-coupled interference in human declarative memory.

PubMed

Zhu, Zijian; Wang, Yingying; Cao, Zhijun; Chen, Biqing; Cai, Huaqian; Wu, Yanhong; Rao, Yi

2016-10-01

Memory is a dynamic process. While memory becomes increasingly resistant to interference after consolidation, a brief reactivation renders it unstable again. Previous studies have shown that interference, when applied upon reactivation, impairs the consolidated memory, presumably by disrupting the reconsolidation of the memory. However, attempts have failed in disrupting human declarative memory, raising a question about whether declarative memory becomes unstable upon reactivation. Here, we used a double-cue/one-target paradigm, which associated the same target with two different cues in initial memory formation. Only one cue/target association was later reactivated and treated with behavioral interference. Our results showed, for the first time, that reactivation-coupled interference caused cue-independent memory impairment that generalized to other cues associated with the memory. Critically, such memory impairment appeared immediately after interference, before the reconsolidation process was completed, suggesting that common manipulations of reactivation-coupled interference procedures might disrupt other processes in addition to the reconsolidation process in human declarative memory. Copyright © 2016. Published by Elsevier B.V.

Optical quantum memory based on electromagnetically induced transparency

PubMed Central

Ma, Lijun; Slattery, Oliver

2017-01-01

Electromagnetically induced transparency (EIT) is a promising approach to implement quantum memory in quantum communication and quantum computing applications. In this paper, following a brief overview of the main approaches to quantum memory, we provide details of the physical principle and theory of quantum memory based specifically on EIT. We discuss the key technologies for implementing quantum memory based on EIT and review important milestones, from the first experimental demonstration to current applications in quantum information systems. PMID:28828172

Optical quantum memory based on electromagnetically induced transparency.

PubMed

Ma, Lijun; Slattery, Oliver; Tang, Xiao

2017-04-01

Electromagnetically induced transparency (EIT) is a promising approach to implement quantum memory in quantum communication and quantum computing applications. In this paper, following a brief overview of the main approaches to quantum memory, we provide details of the physical principle and theory of quantum memory based specifically on EIT. We discuss the key technologies for implementing quantum memory based on EIT and review important milestones, from the first experimental demonstration to current applications in quantum information systems.

Episodic memory and self-reference via semantic autobiographical memory: insights from an fMRI study in younger and older adults.

PubMed

Kalenzaga, Sandrine; Sperduti, Marco; Anssens, Adèle; Martinelli, Penelope; Devauchelle, Anne-Dominique; Gallarda, Thierry; Delhommeau, Marion; Lion, Stéphanie; Amado, Isabelle; Krebs, Marie-Odile; Oppenheim, Catherine; Piolino, Pascale

2014-01-01

Self-referential processing relies mainly on the medial prefrontal cortex (MPFC) and enhances memory encoding (i.e., Self-Reference Effect, SRE) as it improves the accuracy and richness of remembering in both young and older adults. However, studies on age-related changes in the neural correlates of the SRE on the subjective (i.e., autonoetic consciousness) and the objective (i.e., source memory) qualitative features of episodic memory are lacking. In the present fMRI study, we compared the effects of a self-related (semantic autobiographical memory task) and a non self-related (general semantic memory task) encoding condition on subsequent episodic memory retrieval. We investigated encoding-related activity during each condition in two groups of 19 younger and 16 older adults. Behaviorally, the SRE improved subjective memory performance in both groups but objective memory only in young adults. At the neural level, a direct comparison between self-related and non self-related conditions revealed that SRE mainly activated the cortical midline system, especially the MPFC, in both groups. Additionally, in older adults and regardless of the condition, greater activity was found in a fronto-parietal network. Overall, correlations were noted between source memory performance and activity in the MPFC (irrespective of age) and visual areas (mediated by age). Thus, the present findings expand evidence of the role of the MPFC in self-referential processing in the context of source memory benefit in both young and older adults using incidental encoding via semantic autobiographical memory. However, our finding suggests that its role is less effective in aging.

Episodic memory and self-reference via semantic autobiographical memory: insights from an fMRI study in younger and older adults

PubMed Central

Kalenzaga, Sandrine; Sperduti, Marco; Anssens, Adèle; Martinelli, Penelope; Devauchelle, Anne-Dominique; Gallarda, Thierry; Delhommeau, Marion; Lion, Stéphanie; Amado, Isabelle; Krebs, Marie-Odile; Oppenheim, Catherine; Piolino, Pascale

2015-01-01

Self-referential processing relies mainly on the medial prefrontal cortex (MPFC) and enhances memory encoding (i.e., Self-Reference Effect, SRE) as it improves the accuracy and richness of remembering in both young and older adults. However, studies on age-related changes in the neural correlates of the SRE on the subjective (i.e., autonoetic consciousness) and the objective (i.e., source memory) qualitative features of episodic memory are lacking. In the present fMRI study, we compared the effects of a self-related (semantic autobiographical memory task) and a non self-related (general semantic memory task) encoding condition on subsequent episodic memory retrieval. We investigated encoding-related activity during each condition in two groups of 19 younger and 16 older adults. Behaviorally, the SRE improved subjective memory performance in both groups but objective memory only in young adults. At the neural level, a direct comparison between self-related and non self-related conditions revealed that SRE mainly activated the cortical midline system, especially the MPFC, in both groups. Additionally, in older adults and regardless of the condition, greater activity was found in a fronto-parietal network. Overall, correlations were noted between source memory performance and activity in the MPFC (irrespective of age) and visual areas (mediated by age). Thus, the present findings expand evidence of the role of the MPFC in self-referential processing in the context of source memory benefit in both young and older adults using incidental encoding via semantic autobiographical memory. However, our finding suggests that its role is less effective in aging. PMID:25628546

Subjective Memory Impairment and Well-Being in Community-Dwelling Older Adults

PubMed Central

Zuniga, Krystle E.; Mackenzie, Michael; Kramer, Arthur; McAuley, Edward

2015-01-01

Background The relationship between subjective memory impairment (SMI), future cognitive decline and negative health status provides an opportunity for interventions to reduce memory complaints in high risk groups. This study aimed to examine the relationship between subjective memory impairment (SMI) and indicators of well-being in older adults enrolled in an exercise trial. Additionally, the study examined whether two different modes of exercise training, aerobic walking or non-aerobic flexibility, toning, and balance, differentially influenced subjective memory across the trial. Methods Community-dwelling older adults (n=179, Mage=66.4) were randomly assigned to a walking or flexibility, toning, and balance group for 12 months. Subjective memory, happiness, perceived stress, and symptom reporting were measured at baseline, 6 months and 12 months. Results A main effect of subjective memory indicated that individuals with the fewest memory complaints had lower perceived stress (P<0.001) and physical symptom reporting (P<0.001), and higher happiness (P<0.001) across all measurement occasions. Both main and interaction effects of time and group on SMI were not significant, suggesting SMI remained stable across the intervention and was not significantly impacted by participation in exercise training. Conclusions SMI was not responsive to exercise interventions, and the relationship between subjective memory impairment (SMI) and negative well- being demonstrates a need for interventions to reduce memory complaints in high risk groups. PMID:25737426

Method and device for maximizing memory system bandwidth by accessing data in a dynamically determined order

NASA Technical Reports Server (NTRS)

Schwab, Andrew J. (Inventor); Aylor, James (Inventor); Hitchcock, Charles Young (Inventor); Wulf, William A. (Inventor); McKee, Sally A. (Inventor); Moyer, Stephen A. (Inventor); Klenke, Robert (Inventor)

2000-01-01

A data processing system is disclosed which comprises a data processor and memory control device for controlling the access of information from the memory. The memory control device includes temporary storage and decision ability for determining what order to execute the memory accesses. The compiler detects the requirements of the data processor and selects the data to stream to the memory control device which determines a memory access order. The order in which to access said information is selected based on the location of information stored in the memory. The information is repeatedly accessed from memory and stored in the temporary storage until all streamed information is accessed. The information is stored until required by the data processor. The selection of the order in which to access information maximizes bandwidth and decreases the retrieval time.

Remembrance of Things Past

ERIC Educational Resources Information Center

Heckel, Robert V.; Heckel, Nancy W.

1976-01-01

An attempt was undertaken to demonstrate a relationship between earliest memories and a perception of significant future events. Relevance here was in the role that early memories play in the theoretical bases and treatment processes of all dynamically oriented therapies. (Author/RK)

Synchronization of heteroclinic circuits through learning in coupled neural networks

NASA Astrophysics Data System (ADS)

Selskii, Anton; Makarov, Valeri A.

2016-01-01

The synchronization of oscillatory activity in neural networks is usually implemented by coupling the state variables describing neuronal dynamics. Here we study another, but complementary mechanism based on a learning process with memory. A driver network, acting as a teacher, exhibits winner-less competition (WLC) dynamics, while a driven network, a learner, tunes its internal couplings according to the oscillations observed in the teacher. We show that under appropriate training the learner can "copy" the coupling structure and thus synchronize oscillations with the teacher. The replication of the WLC dynamics occurs for intermediate memory lengths only, consequently, the learner network exhibits a phenomenon of learning resonance.

Research on memory management in embedded systems

NASA Astrophysics Data System (ADS)

Huang, Xian-ying; Yang, Wu

2005-12-01

Memory is a scarce resource in embedded system due to cost and size. Thus, applications in embedded systems cannot use memory randomly, such as in desktop applications. However, data and code must be stored into memory for running. The purpose of this paper is to save memory in developing embedded applications and guarantee running under limited memory conditions. Embedded systems often have small memory and are required to run a long time. Thus, a purpose of this study is to construct an allocator that can allocate memory effectively and bear a long-time running situation, reduce memory fragmentation and memory exhaustion. Memory fragmentation and exhaustion are related to the algorithm memory allocated. Static memory allocation cannot produce fragmentation. In this paper it is attempted to find an effective allocation algorithm dynamically, which can reduce memory fragmentation. Data is the critical part that ensures an application can run regularly, which takes up a large amount of memory. The amount of data that can be stored in the same size of memory is relevant with the selected data structure. Skills for designing application data in mobile phone are explained and discussed also.

Does reactivation trigger episodic memory change? A meta-analysis.

PubMed

Scully, Iiona D; Napper, Lucy E; Hupbach, Almut

2017-07-01

According to the reconsolidation hypothesis, long-term memories return to a plastic state upon their reactivation, leaving them vulnerable to interference effects and requiring re-storage processes or else these memories might be permanently lost. The present study used a meta-analytic approach to critically evaluate the evidence for reactivation-induced changes in human episodic memory. Results indicated that reactivation makes episodic memories susceptible to physiological and behavioral interference. When applied shortly after reactivation, interference manipulations altered the amount of information that could be retrieved from the original learning event. This effect was more pronounced for remote memories and memories of narrative structure. Additionally, new learning following reactivation reliably increased the number of intrusions from new information into the original memory. These findings support a dynamic view of long-term memory by showing that memories can be changed long after they were acquired. Copyright © 2016 Elsevier Inc. All rights reserved.

Virtual Reality as an Ecologically Valid Tool for Assessing Multifaceted Episodic Memory in Children and Adolescents

ERIC Educational Resources Information Center

Picard, Laurence; Abram, Maria; Orriols, Eric; Piolino, Pascale

2017-01-01

The majority of episodic memory (EM) tests are far removed from what we experience in daily life and from the definition of this type of memory. This study examines the developmental trajectory of the main aspects of episodic memory--what, where, and when--and of feature binding in a naturalistic virtual environment. A population of 125…

Identification of a novel protein for memory regulation in the hippocampus.

PubMed

Zhang, Xue-Han; Zhang, Hui; Tu, Yanyang; Gao, Xiang; Zhou, Changfu; Jin, Meilei; Zhao, Guoping; Jing, Naihe; Li, Bao-Ming; Yu, Lei

2005-08-26

Memory formation, maintenance, and retrieval are a dynamic process, reflecting a combined outcome of new memory formation on one hand, and older memory suppression/clearance on the other. Although much knowledge has been gained regarding new memory formation, less is known about the molecular components and processes that serve the function of memory suppression/clearance. Here, we report the identification of a novel protein, termed hippyragranin (HGN), that is expressed in the rat hippocampus and its expression is reduced by hippocampal denervation. Inhibition of HGN by antisense oligonucleotide in area CA1 results in enhanced performance in Morris water maze, as well as elevated long-term potentiation. These results suggest that HGN is involved in negative memory regulation.

Human TSCM cell dynamics in vivo are compatible with long-lived immunological memory and stemness.

PubMed

Del Amo, Pedro Costa; Beneytez, Julio Lahoz; Boelen, Lies; Ahmed, Raya; Miners, Kelly L; Zhang, Yan; Roger, Laureline; Jones, Rhiannon E; Marraco, Silvia A Fuertes; Speiser, Daniel E; Baird, Duncan M; Price, David A; Ladell, Kristin; Macallan, Derek; Asquith, Becca

2018-06-22

Adaptive immunity relies on the generation and maintenance of memory T cells to provide protection against repeated antigen exposure. It has been hypothesised that a self-renewing population of T cells, named stem cell-like memory T (TSCM) cells, are responsible for maintaining memory. However, it is not clear if the dynamics of TSCM cells in vivo are compatible with this hypothesis. To address this issue, we investigated the dynamics of TSCM cells under physiological conditions in humans in vivo using a multidisciplinary approach that combines mathematical modelling, stable isotope labelling, telomere length analysis, and cross-sectional data from vaccine recipients. We show that, unexpectedly, the average longevity of a TSCM clone is very short (half-life < 1 year, degree of self-renewal = 430 days): far too short to constitute a stem cell population. However, we also find that the TSCM population is comprised of at least 2 kinetically distinct subpopulations that turn over at different rates. Whilst one subpopulation is rapidly replaced (half-life = 5 months) and explains the rapid average turnover of the bulk TSCM population, the half-life of the other TSCM subpopulation is approximately 9 years, consistent with the longevity of the recall response. We also show that this latter population exhibited a high degree of self-renewal, with a cell residing without dying or differentiating for 15% of our lifetime. Finally, although small, the population was not subject to excessive stochasticity. We conclude that the majority of TSCM cells are not stem cell-like but that there is a subpopulation of TSCM cells whose dynamics are compatible with their putative role in the maintenance of T cell memory.

Effective connectivity within the frontoparietal control network differentiates cognitive control and working memory.

PubMed

Harding, Ian H; Yücel, Murat; Harrison, Ben J; Pantelis, Christos; Breakspear, Michael

2015-02-01

Cognitive control and working memory rely upon a common fronto-parietal network that includes the inferior frontal junction (IFJ), dorsolateral prefrontal cortex (dlPFC), pre-supplementary motor area/dorsal anterior cingulate cortex (pSMA/dACC), and intraparietal sulcus (IPS). This network is able to flexibly adapt its function in response to changing behavioral goals, mediating a wide range of cognitive demands. Here we apply dynamic causal modeling to functional magnetic resonance imaging data to characterize task-related alterations in the strength of network interactions across distinct cognitive processes. Evidence in favor of task-related connectivity dynamics was accrued across a very large space of possible network structures. Cognitive control and working memory demands were manipulated using a factorial combination of the multi-source interference task and a verbal 2-back working memory task, respectively. Both were found to alter the sensitivity of the IFJ to perceptual information, and to increase IFJ-to-pSMA/dACC connectivity. In contrast, increased connectivity from the pSMA/dACC to the IPS, as well as from the dlPFC to the IFJ, was uniquely driven by cognitive control demands; a task-induced negative influence of the dlPFC on the pSMA/dACC was specific to working memory demands. These results reflect a system of both shared and unique context-dependent dynamics within the fronto-parietal network. Mechanisms supporting cognitive engagement, response selection, and action evaluation may be shared across cognitive domains, while dynamic updating of task and context representations within this network are potentially specific to changing demands on cognitive control. Copyright © 2014 Elsevier Inc. All rights reserved.

76 FR 18778 - Flight 93 National Memorial Advisory Commission

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-05

... DEPARTMENT OF THE INTERIOR National Park Service Flight 93 National Memorial Advisory Commission... forth the date of the May 7, 2011, meeting of the Flight 93 Advisory Commission. DATES: The public...). Location: The meeting will be held at the Flight 93 National Memorial Office, 109 West Main Street Suite...

77 FR 24220 - Flight 93 National Memorial Advisory Commission

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-23

... DEPARTMENT OF THE INTERIOR National Park Service Flight 93 National Memorial Advisory Commission... sets forth the date of the May 5, 2012, for meeting of the Flight 93 Advisory Commission. DATES: The.... (Eastern). Location: The meeting will be held at the Flight 93 National Memorial Office, 109 West Main...

Autobiographical Memory and Suicide Attempts in Schizophrenia

ERIC Educational Resources Information Center

Pettersen, Kenneth; Rydningen, Nora Nord; Christensen, Tore Buer; Walby, Fredrik A.

2010-01-01

According to the cry of pain model of suicidal behavior, an over-general autobiographical memory function is often found in suicide attempters. The model has received empirical support in several studies, mainly of depressed patients. The present study investigated whether deficits in autobiographical memory may be associated with an increased…

Human Stem Cell-like Memory T Cells Are Maintained in a State of Dynamic Flux.

PubMed

Ahmed, Raya; Roger, Laureline; Costa Del Amo, Pedro; Miners, Kelly L; Jones, Rhiannon E; Boelen, Lies; Fali, Tinhinane; Elemans, Marjet; Zhang, Yan; Appay, Victor; Baird, Duncan M; Asquith, Becca; Price, David A; Macallan, Derek C; Ladell, Kristin

2016-12-13

Adaptive immunity requires the generation of memory T cells from naive precursors selected in the thymus. The key intermediaries in this process are stem cell-like memory T (T SCM ) cells, multipotent progenitors that can both self-renew and replenish more differentiated subsets of memory T cells. In theory, antigen specificity within the T SCM pool may be imprinted statically as a function of largely dormant cells and/or retained dynamically by more transitory subpopulations. To explore the origins of immunological memory, we measured the turnover of T SCM cells in vivo using stable isotope labeling with heavy water. The data indicate that T SCM cells in both young and elderly subjects are maintained by ongoing proliferation. In line with this finding, T SCM cells displayed limited telomere length erosion coupled with high expression levels of active telomerase and Ki67. Collectively, these observations show that T SCM cells exist in a state of perpetual flux throughout the human lifespan. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Zero-dynamics principle for perfect quantum memory in linear networks

NASA Astrophysics Data System (ADS)

Yamamoto, Naoki; James, Matthew R.

2014-07-01

In this paper, we study a general linear networked system that contains a tunable memory subsystem; that is, it is decoupled from an optical field for state transportation during the storage process, while it couples to the field during the writing or reading process. The input is given by a single photon state or a coherent state in a pulsed light field. We then completely and explicitly characterize the condition required on the pulse shape achieving the perfect state transfer from the light field to the memory subsystem. The key idea to obtain this result is the use of zero-dynamics principle, which in our case means that, for perfect state transfer, the output field during the writing process must be a vacuum. A useful interpretation of the result in terms of the transfer function is also given. Moreover, a four-node network composed of atomic ensembles is studied as an example, demonstrating how the input field state is transferred to the memory subsystem and what the input pulse shape to be engineered for perfect memory looks like.

Light sensitivity of a one transistor-one capacitor memory cell when used as a micromirror actuator in projector applications

NASA Astrophysics Data System (ADS)

Huffman, James Douglas

2001-11-01

The most important issue facing the future business success of the Digital Micromirror Device or DMD™ produced by Texas Instruments is the cost of the actual device. As the business and consumer markets call for higher resolution displays, the array size will have to be increased to incorporate more pixels. The manufacturing costs associated with building these higher resolution displays follow an exponential relation with the number of pixels due to yield loss and reduced number of chips per silicon wafer. Each pixel is actuated by electrostatics that are provided by a memory cell that is built in the underlying silicon substrate. One way to decrease cost of the wafer is to change the memory cell architecture from a static random access configuration or SRAM to a dynamic random access configuration or DRAM. This change has the benefits of having fewer components per area and a lower metal density. This reduction in the component count and metal density has a dramatic effect on the yield of the memory array by reducing the particle sensitivity of the underlying cell. The main drawback to using a DRAM configuration in a display application is the light sensitivity of a charge storage device built in the silicon substrate. As the photons pass through the mechanical micromirrors and illuminate the DRAM cell, the effective electrostatic potential of the memory element used for the mirror actuation is reduced. This dissertation outlines the issues associated with the light sensitivity of a DRAM memory cell as the actuation element for a micromirror. The concept of charge depletion on a silicon capacitor due to recombination of photogenerated carriers is explored and experimentally verified. The effects of the reduced potential on the capacitor on the micromirror are also explored. Optical modeling is used to determine the incoming photon flux to determine the benefits of adding a charge recombination region as part of the DRAM memory cell. Several options are explored to reduce the effect of the incoming photons on the potential of the memory cell. The results will show that a 1T1C memory cell with N-type recombination regions and maximum light shielding is sufficient for a projector application.

Design of Unstructured Adaptive (UA) NAS Parallel Benchmark Featuring Irregular, Dynamic Memory Accesses

NASA Technical Reports Server (NTRS)

Feng, Hui-Yu; VanderWijngaart, Rob; Biswas, Rupak; Biegel, Bryan (Technical Monitor)

2001-01-01

We describe the design of a new method for the measurement of the performance of modern computer systems when solving scientific problems featuring irregular, dynamic memory accesses. The method involves the solution of a stylized heat transfer problem on an unstructured, adaptive grid. A Spectral Element Method (SEM) with an adaptive, nonconforming mesh is selected to discretize the transport equation. The relatively high order of the SEM lowers the fraction of wall clock time spent on inter-processor communication, which eases the load balancing task and allows us to concentrate on the memory accesses. The benchmark is designed to be three-dimensional. Parallelization and load balance issues of a reference implementation will be described in detail in future reports.

A portable approach for PIC on emerging architectures

NASA Astrophysics Data System (ADS)

Decyk, Viktor

2016-03-01

A portable approach for designing Particle-in-Cell (PIC) algorithms on emerging exascale computers, is based on the recognition that 3 distinct programming paradigms are needed. They are: low level vector (SIMD) processing, middle level shared memory parallel programing, and high level distributed memory programming. In addition, there is a memory hierarchy associated with each level. Such algorithms can be initially developed using vectorizing compilers, OpenMP, and MPI. This is the approach recommended by Intel for the Phi processor. These algorithms can then be translated and possibly specialized to other programming models and languages, as needed. For example, the vector processing and shared memory programming might be done with CUDA instead of vectorizing compilers and OpenMP, but generally the algorithm itself is not greatly changed. The UCLA PICKSC web site at http://www.idre.ucla.edu/ contains example open source skeleton codes (mini-apps) illustrating each of these three programming models, individually and in combination. Fortran2003 now supports abstract data types, and design patterns can be used to support a variety of implementations within the same code base. Fortran2003 also supports interoperability with C so that implementations in C languages are also easy to use. Finally, main codes can be translated into dynamic environments such as Python, while still taking advantage of high performing compiled languages. Parallel languages are still evolving with interesting developments in co-Array Fortran, UPC, and OpenACC, among others, and these can also be supported within the same software architecture. Work supported by NSF and DOE Grants.

The influence of seizure frequency on anterograde and remote memory in mesial temporal lobe epilepsy.

PubMed

Voltzenlogel, Virginie; Vignal, Jean-Pierre; Hirsch, Edouard; Manning, Liliann

2014-10-01

Seizure frequency, although considered as an important factor in memory impairment in mesial temporal epilepsy (mTLE), is mostly confounded with other clinical variables, making it unclear to what extent recurrent seizures actually interfere with memory. The present study focuses on the influence of seizure frequency, studied as a main variable, on anterograde and remote memory. Seventy-one patients with unilateral mTLE were divided into two subgroups, as a function of their seizure frequency (monthly versus weekly seizures). Other seizure-related variables were controlled, namely, lateralisation and type of lesion, age at onset, years of ongoing seizures, etiologic factors, and number of AED. A comprehensive neuropsychological examination, including anterograde memory (verbal and non verbal recognition memory and free recall) tasks together with a large range of tests exploring different domains of remote memory, was carried out. Despite similar results on IQ, executive functions and attention, the low seizure-frequency group performed significantly better than the high seizure-frequency group on anterograde memory tests. Loss of autobiographical episodes and public-events memory, concomitant with spared personal semantic knowledge, was observed in both patient groups compared with healthy subjects. A worsening effect of high seizure frequency was recorded for autobiographical incidents and news-events memory, but unexpectedly, not for memory for famous people. The study of seizure frequency as the main variable leads us to suggest that high seizure frequency, itself, potentiates the effects of mesial temporal lobe damage on episodic memory deficits. Copyright © 2014 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Dynamic interactions between visual working memory and saccade target selection

PubMed Central

Schneegans, Sebastian; Spencer, John P.; Schöner, Gregor; Hwang, Seongmin; Hollingworth, Andrew

2014-01-01

Recent psychophysical experiments have shown that working memory for visual surface features interacts with saccadic motor planning, even in tasks where the saccade target is unambiguously specified by spatial cues. Specifically, a match between a memorized color and the color of either the designated target or a distractor stimulus influences saccade target selection, saccade amplitudes, and latencies in a systematic fashion. To elucidate these effects, we present a dynamic neural field model in combination with new experimental data. The model captures the neural processes underlying visual perception, working memory, and saccade planning relevant to the psychophysical experiment. It consists of a low-level visual sensory representation that interacts with two separate pathways: a spatial pathway implementing spatial attention and saccade generation, and a surface feature pathway implementing color working memory and feature attention. Due to bidirectional coupling between visual working memory and feature attention in the model, the working memory content can indirectly exert an effect on perceptual processing in the low-level sensory representation. This in turn biases saccadic movement planning in the spatial pathway, allowing the model to quantitatively reproduce the observed interaction effects. The continuous coupling between representations in the model also implies that modulation should be bidirectional, and model simulations provide specific predictions for complementary effects of saccade target selection on visual working memory. These predictions were empirically confirmed in a new experiment: Memory for a sample color was biased toward the color of a task-irrelevant saccade target object, demonstrating the bidirectional coupling between visual working memory and perceptual processing. PMID:25228628

The mysteries of remote memory.

PubMed

Albo, Zimbul; Gräff, Johannes

2018-03-19

Long-lasting memories form the basis of our identity as individuals and lie central in shaping future behaviours that guide survival. Surprisingly, however, our current knowledge of how such memories are stored in the brain and retrieved, as well as the dynamics of the circuits involved, remains scarce despite seminal technical and experimental breakthroughs in recent years. Traditionally, it has been proposed that, over time, information initially learnt in the hippocampus is stored in distributed cortical networks. This process-the standard theory of memory consolidation-would stabilize the newly encoded information into a lasting memory, become independent of the hippocampus, and remain essentially unmodifiable throughout the lifetime of the individual. In recent years, several pieces of evidence have started to challenge this view and indicate that long-lasting memories might already ab ovo be encoded, and subsequently stored in distributed cortical networks, akin to the multiple trace theory of memory consolidation. In this review, we summarize these recent findings and attempt to identify the biologically plausible mechanisms based on which a contextual memory becomes remote by integrating different levels of analysis: from neural circuits to cell ensembles across synaptic remodelling and epigenetic modifications. From these studies, remote memory formation and maintenance appear to occur through a multi-trace, dynamic and integrative cellular process ranging from the synapse to the nucleus, and represent an exciting field of research primed to change quickly as new experimental evidence emerges.This article is part of a discussion meeting issue 'Of mice and mental health: facilitating dialogue between basic and clinical neuroscientists'. © 2018 The Authors.

Memory and Energy Optimization Strategies for Multithreaded Operating System on the Resource-Constrained Wireless Sensor Node

PubMed Central

Liu, Xing; Hou, Kun Mean; de Vaulx, Christophe; Xu, Jun; Yang, Jianfeng; Zhou, Haiying; Shi, Hongling; Zhou, Peng

2015-01-01

Memory and energy optimization strategies are essential for the resource-constrained wireless sensor network (WSN) nodes. In this article, a new memory-optimized and energy-optimized multithreaded WSN operating system (OS) LiveOS is designed and implemented. Memory cost of LiveOS is optimized by using the stack-shifting hybrid scheduling approach. Different from the traditional multithreaded OS in which thread stacks are allocated statically by the pre-reservation, thread stacks in LiveOS are allocated dynamically by using the stack-shifting technique. As a result, memory waste problems caused by the static pre-reservation can be avoided. In addition to the stack-shifting dynamic allocation approach, the hybrid scheduling mechanism which can decrease both the thread scheduling overhead and the thread stack number is also implemented in LiveOS. With these mechanisms, the stack memory cost of LiveOS can be reduced more than 50% if compared to that of a traditional multithreaded OS. Not is memory cost optimized, but also the energy cost is optimized in LiveOS, and this is achieved by using the multi-core “context aware” and multi-core “power-off/wakeup” energy conservation approaches. By using these approaches, energy cost of LiveOS can be reduced more than 30% when compared to the single-core WSN system. Memory and energy optimization strategies in LiveOS not only prolong the lifetime of WSN nodes, but also make the multithreaded OS feasible to run on the memory-constrained WSN nodes. PMID:25545264

The mysteries of remote memory

PubMed Central

2018-01-01

Long-lasting memories form the basis of our identity as individuals and lie central in shaping future behaviours that guide survival. Surprisingly, however, our current knowledge of how such memories are stored in the brain and retrieved, as well as the dynamics of the circuits involved, remains scarce despite seminal technical and experimental breakthroughs in recent years. Traditionally, it has been proposed that, over time, information initially learnt in the hippocampus is stored in distributed cortical networks. This process—the standard theory of memory consolidation—would stabilize the newly encoded information into a lasting memory, become independent of the hippocampus, and remain essentially unmodifiable throughout the lifetime of the individual. In recent years, several pieces of evidence have started to challenge this view and indicate that long-lasting memories might already ab ovo be encoded, and subsequently stored in distributed cortical networks, akin to the multiple trace theory of memory consolidation. In this review, we summarize these recent findings and attempt to identify the biologically plausible mechanisms based on which a contextual memory becomes remote by integrating different levels of analysis: from neural circuits to cell ensembles across synaptic remodelling and epigenetic modifications. From these studies, remote memory formation and maintenance appear to occur through a multi-trace, dynamic and integrative cellular process ranging from the synapse to the nucleus, and represent an exciting field of research primed to change quickly as new experimental evidence emerges. This article is part of a discussion meeting issue ‘Of mice and mental health: facilitating dialogue between basic and clinical neuroscientists’. PMID:29352028

Fast but fleeting: adaptive motor learning processes associated with aging and cognitive decline.

PubMed

Trewartha, Kevin M; Garcia, Angeles; Wolpert, Daniel M; Flanagan, J Randall

2014-10-01

Motor learning has been shown to depend on multiple interacting learning processes. For example, learning to adapt when moving grasped objects with novel dynamics involves a fast process that adapts and decays quickly-and that has been linked to explicit memory-and a slower process that adapts and decays more gradually. Each process is characterized by a learning rate that controls how strongly motor memory is updated based on experienced errors and a retention factor determining the movement-to-movement decay in motor memory. Here we examined whether fast and slow motor learning processes involved in learning novel dynamics differ between younger and older adults. In addition, we investigated how age-related decline in explicit memory performance influences learning and retention parameters. Although the groups adapted equally well, they did so with markedly different underlying processes. Whereas the groups had similar fast processes, they had different slow processes. Specifically, the older adults exhibited decreased retention in their slow process compared with younger adults. Within the older group, who exhibited considerable variation in explicit memory performance, we found that poor explicit memory was associated with reduced retention in the fast process, as well as the slow process. These findings suggest that explicit memory resources are a determining factor in impairments in the both the fast and slow processes for motor learning but that aging effects on the slow process are independent of explicit memory declines. Copyright © 2014 the authors 0270-6474/14/3413411-11$15.00/0.

Influence of Response Prepotency Strength, General Working Memory Resources, and Specific Working Memory Load on the Ability to Inhibit Predominant Responses: A Comparison of Young and Elderly Participants

ERIC Educational Resources Information Center

Grandjean, Julien; Collette, Fabienne

2011-01-01

One conception of inhibitory functioning suggests that the ability to successfully inhibit a predominant response depends mainly on the strength of that response, the general functioning of working memory processes, and the working memory demand of the task (Roberts, Hager, & Heron, 1994). The proposal that inhibition and functional working memory…

Efficient Parallelization of a Dynamic Unstructured Application on the Tera MTA

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Biswas, Rupak

1999-01-01

The success of parallel computing in solving real-life computationally-intensive problems relies on their efficient mapping and execution on large-scale multiprocessor architectures. Many important applications are both unstructured and dynamic in nature, making their efficient parallel implementation a daunting task. This paper presents the parallelization of a dynamic unstructured mesh adaptation algorithm using three popular programming paradigms on three leading supercomputers. We examine an MPI message-passing implementation on the Cray T3E and the SGI Origin2OOO, a shared-memory implementation using cache coherent nonuniform memory access (CC-NUMA) of the Origin2OOO, and a multi-threaded version on the newly-released Tera Multi-threaded Architecture (MTA). We compare several critical factors of this parallel code development, including runtime, scalability, programmability, and memory overhead. Our overall results demonstrate that multi-threaded systems offer tremendous potential for quickly and efficiently solving some of the most challenging real-life problems on parallel computers.

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.

Recollecting, recognizing, and other acts of remembering: an overview of human memory.

PubMed

LaVoie, Donna J; Cobia, Derin J

2007-09-01

The question of whether memory is important to human existence is simple to answer: life without memory would be devoid of any meaning. The question of what memory is, however, is much more difficult to answer. The main purpose of this article is to provide an overview of memory function, by drawing distinctions between different memory systems, specifically declarative (ie, conscious) versus nondeclarative (ie, nonconscious) memory systems. To distinguish between these larger systems and their various components, we include discussion of deficits in memory that occur as a consequence of brain injury and normative aging processes. Included in these descriptions is discussion of the neuroanatomical correlates of each memory component described to illustrate the importance of particular brain regions to different aspects of memory function.

Experimental Effects of Acute Exercise on Iconic Memory, Short-Term Episodic, and Long-Term Episodic Memory.

PubMed

Yanes, Danielle; Loprinzi, Paul D

2018-06-11

The present experiment evaluated the effects of acute exercise on iconic memory and short- and long-term episodic memory. A two-arm, parallel-group randomized experiment was employed ( n = 20 per group; M age = 21 year). The experimental group engaged in an acute bout of moderate-intensity treadmill exercise for 15 min, while the control group engaged in a seated, time-matched computer task. Afterwards, the participants engaged in a paragraph-level episodic memory task (20 min delay and 24 h delay recall) as well as an iconic memory task, which involved 10 trials (at various speeds from 100 ms to 800 ms) of recalling letters from a 3 × 3 array matrix. For iconic memory, there was a significant main effect for time (F = 42.9, p < 0.001, η² p = 0.53) and a trend towards a group × time interaction (F = 2.90, p = 0.09, η² p = 0.07), but no main effect for group (F = 0.82, p = 0.37, η² p = 0.02). The experimental group had higher episodic memory scores at both the baseline (19.22 vs. 17.20) and follow-up (18.15 vs. 15.77), but these results were not statistically significant. These findings provide some suggestive evidence hinting towards an iconic memory and episodic benefit from acute exercise engagement.

Granger causality analysis reveals distinct spatio-temporal connectivity patterns in motor and perceptual visuo-spatial working memory.

PubMed

Protopapa, Foteini; Siettos, Constantinos I; Evdokimidis, Ioannis; Smyrnis, Nikolaos

2014-01-01

We employed spectral Granger causality analysis on a full set of 56 electroencephalographic recordings acquired during the execution of either a 2D movement pointing or a perceptual (yes/no) change detection task with memory and non-memory conditions. On the basis of network characteristics across frequency bands, we provide evidence for the full dissociation of the corresponding cognitive processes. Movement-memory trial types exhibited higher degree nodes during the first 2 s of the delay period, mainly at central, left frontal and right-parietal areas. Change detection-memory trial types resulted in a three-peak temporal pattern of the total degree with higher degree nodes emerging mainly at central, right frontal, and occipital areas. Functional connectivity networks resulting from non-memory trial types were characterized by more sparse structures for both tasks. The movement-memory trial types encompassed an apparent coarse flow from frontal to parietal areas while the opposite flow from occipital, parietal to central and frontal areas was evident for the change detection-memory trial types. The differences among tasks and conditions were more profound in α (8-12 Hz) and β (12-30 Hz) and less in γ (30-45 Hz) band. Our results favor the hypothesis which considers spatial working memory as a by-product of specific mental processes that engages common brain areas under different network organizations.

Fast Pixel Buffer For Processing With Lookup Tables

NASA Technical Reports Server (NTRS)

Fisher, Timothy E.

1992-01-01

Proposed scheme for buffering data on intensities of picture elements (pixels) of image increases rate or processing beyond that attainable when data read, one pixel at time, from main image memory. Scheme applied in design of specialized image-processing circuitry. Intended to optimize performance of processor in which electronic equivalent of address-lookup table used to address those pixels in main image memory required for processing.

T-Tau is Associated with Objective Memory Decline Over Two Years in Persons Seeking Help for Subjective Cognitive Decline: A Report from the Gothenburg-Oslo MCI Study.

PubMed

Hessen, Erik; Nordlund, Arto; Stålhammar, Jacob; Eckerström, Marie; Bjerke, Maria; Eckerström, Carl; Göthlin, Mattias; Fladby, Tormod; Reinvang, Ivar; Wallin, Anders

2015-01-01

There is a need to find very early markers for pre-clinical Alzheimer's disease as interventions early in the disease process are thought to be most effective. The present study aimed to address the potential relation between cerebrospinal fluid (CSF) biomarkers and reduced cognitive function in a relatively young cohort of memory clinic patients with subjective cognitive decline. 122 patients (mean age 63 years) with subjective cognitive decline were recruited from two university memory clinics and followed for two years. The main finding was that the subgroup with objective memory decline during the study period had significantly higher T-tau at baseline than the group with improved memory. Baseline CSF variables showed a trend toward more pathological values in the patients with memory decline compared to those who improved or remained stable. The baseline memory score of those who declined was significantly better than the baseline score of those who improved over two years. The general trend for the whole group was improved memory and executive test scores. There were no differences in cognitive scores based on CSF quartiles at baseline, nor were there differences in cognitive outcome for patients with early amnestic mild cognitive impairment versus average cognitive function at baseline. The main finding that T-tau rather than amyloid-β was associated with memory decline do not support the prevailing opinion about the chain of events assumed to take place in Alzheimer's disease. In addition, memory decline was not associated with poor baseline memory score. Thus, a memory cut-off indicating low baseline memory would not would have identified the declining group.

Modifying Memory: Selectively Enhancing and Updating Personal Memories for a Museum Tour by Reactivating Them

PubMed Central

St. Jacques, Peggy L.; Schacter, Daniel L.

2013-01-01

Memory can be modified when reactivated, but little is known about how the properties and extent of reactivation can selectively affect subsequent memory. We developed a novel museum paradigm to directly investigate reactivation-induced plasticity for personal memories. Participants reactivated memories triggered by photos taken from a camera they wore during a museum tour and made relatedness judgments on novel photos taken from a different tour of the same museum. Subsequent recognition memory for events at the museum was better for memories that were highly reactivated (i.e., the retrieval cues during reactivation matched the encoding experience) than for memories that were reactivated at a lower level (i.e., the retrieval cues during reactivation mismatched the encoding experience), but reactivation also increased false recognition of photographs depicting stops that were not experienced during the museum tour. Reactivation thus enables memories to be selectively enhanced and distorted via updating, thereby supporting the dynamic and flexible nature of memory. PMID:23406611

Task-dependent activity and connectivity predict episodic memory network-based responses to brain stimulation in healthy aging

PubMed Central

Vidal-Piñeiro, Dídac; Martin-Trias, Pablo; Arenaza-Urquijo, Eider M.; Sala-Llonch, Roser; Mena-Sánchez, Isaias; Bargalló, Núria; Falcón, Carles; Pascual-Leone, Álvaro; Bartrés-Faz, David

2015-01-01

Background Transcranial Magnetic Stimulation (TMS) can affect episodic memory, one of the main cognitive hallmarks of aging, but the mechanisms of action remain unclear. Objectives To evaluate the behavioral and functional impact of excitatory TMS in a group of healthy elders. Methods We applied a paradigm of repetitive TMS -intermittent theta-burst stimulation- over left inferior frontal gyrus in healthy elders (n=24) and evaluated its impact on the performance of an episodic memory task with two levels of processing and the associated brain activity as captured by a pre and post fMRI scans. Results In the post-TMS fMRI we found TMS-related activity increases in left prefrontal and cerebellum-occipital areas specifically during deep encoding but not during shallow encoding or at rest. Furthermore, we found a task-dependent change in connectivity during the encoding task between cerebellum-occipital areas and the TMS-targeted left inferior frontal region. This connectivity change correlated with the TMS effects over brain networks. Conclusions The results suggest that the aged brain responds to brain stimulation in a state-dependent manner as engaged by different tasks components and that TMS effect is related to inter-individual connectivity changes measures. These findings reveal fundamental insights into brain network dynamics in aging and the capacity to probe them with combined behavioral and stimulation approaches. PMID:24485466

Task-dependent activity and connectivity predict episodic memory network-based responses to brain stimulation in healthy aging.

PubMed

Vidal-Piñeiro, Dídac; Martin-Trias, Pablo; Arenaza-Urquijo, Eider M; Sala-Llonch, Roser; Clemente, Imma C; Mena-Sánchez, Isaias; Bargalló, Núria; Falcón, Carles; Pascual-Leone, Álvaro; Bartrés-Faz, David

2014-01-01

Transcranial magnetic stimulation (TMS) can affect episodic memory, one of the main cognitive hallmarks of aging, but the mechanisms of action remain unclear. To evaluate the behavioral and functional impact of excitatory TMS in a group of healthy elders. We applied a paradigm of repetitive TMS - intermittent theta-burst stimulation - over left inferior frontal gyrus in healthy elders (n = 24) and evaluated its impact on the performance of an episodic memory task with two levels of processing and the associated brain activity as captured by a pre and post fMRI scans. In the post-TMS fMRI we found TMS-related activity increases in left prefrontal and cerebellum-occipital areas specifically during deep encoding but not during shallow encoding or at rest. Furthermore, we found a task-dependent change in connectivity during the encoding task between cerebellum-occipital areas and the TMS-targeted left inferior frontal region. This connectivity change correlated with the TMS effects over brain networks. The results suggest that the aged brain responds to brain stimulation in a state-dependent manner as engaged by different tasks components and that TMS effect is related to inter-individual connectivity changes measures. These findings reveal fundamental insights into brain network dynamics in aging and the capacity to probe them with combined behavioral and stimulation approaches. Copyright © 2014 Elsevier Inc. All rights reserved.

77 FR 37709 - Notice of July 28, 2012, Meeting for Flight 93 National Memorial Advisory Commission

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-22

..., 2012, Meeting for Flight 93 National Memorial Advisory Commission AGENCY: National Park Service... the Flight 93 Advisory Commission. DATES: The public meeting of the Advisory Commission will be held... held at the Flight 93 National Memorial Office, 109 West Main Street Suite 104, Somerset, PA 15501...

Archives, Libraries and Museums as Communicators of Memory in the European Union Projects

ERIC Educational Resources Information Center

Manzuch, Zinaida

2009-01-01

Introduction: Explores the approach to communication of memory in archives, libraries and museums in European Union research projects in 2000-2005. The main objectives were: to identify predominant aspects of heritage communication; to determine whether and how heritage communication was related to memory; to establish patterns of participation in…

Cache write generate for parallel image processing on shared memory architectures.

PubMed

Wittenbrink, C M; Somani, A K; Chen, C H

1996-01-01

We investigate cache write generate, our cache mode invention. We demonstrate that for parallel image processing applications, the new mode improves main memory bandwidth, CPU efficiency, cache hits, and cache latency. We use register level simulations validated by the UW-Proteus system. Many memory, cache, and processor configurations are evaluated.

An Agent-Based Model for the Role of Short-Term Memory Enhancement in the Emergence of Grammatical Agreement.

PubMed

Vera, Javier

2018-01-01

What is the influence of short-term memory enhancement on the emergence of grammatical agreement systems in multi-agent language games? Agreement systems suppose that at least two words share some features with each other, such as gender, number, or case. Previous work, within the multi-agent language-game framework, has recently proposed models stressing the hypothesis that the emergence of a grammatical agreement system arises from the minimization of semantic ambiguity. On the other hand, neurobiological evidence argues for the hypothesis that language evolution has mainly related to an increasing of short-term memory capacity, which has allowed the online manipulation of words and meanings participating particularly in grammatical agreement systems. Here, the main aim is to propose a multi-agent language game for the emergence of a grammatical agreement system, under measurable long-range relations depending on the short-term memory capacity. Computer simulations, based on a parameter that measures the amount of short-term memory capacity, suggest that agreement marker systems arise in a population of agents equipped at least with a critical short-term memory capacity.

Membrane Capacitive Memory Alters Spiking in Neurons Described by the Fractional-Order Hodgkin-Huxley Model

PubMed Central

Weinberg, Seth H.

2015-01-01

Excitable cells and cell membranes are often modeled by the simple yet elegant parallel resistor-capacitor circuit. However, studies have shown that the passive properties of membranes may be more appropriately modeled with a non-ideal capacitor, in which the current-voltage relationship is given by a fractional-order derivative. Fractional-order membrane potential dynamics introduce capacitive memory effects, i.e., dynamics are influenced by a weighted sum of the membrane potential prior history. However, it is not clear to what extent fractional-order dynamics may alter the properties of active excitable cells. In this study, we investigate the spiking properties of the neuronal membrane patch, nerve axon, and neural networks described by the fractional-order Hodgkin-Huxley neuron model. We find that in the membrane patch model, as fractional-order decreases, i.e., a greater influence of membrane potential memory, peak sodium and potassium currents are altered, and spike frequency and amplitude are generally reduced. In the nerve axon, the velocity of spike propagation increases as fractional-order decreases, while in a neural network, electrical activity is more likely to cease for smaller fractional-order. Importantly, we demonstrate that the modulation of the peak ionic currents that occurs for reduced fractional-order alone fails to reproduce many of the key alterations in spiking properties, suggesting that membrane capacitive memory and fractional-order membrane potential dynamics are important and necessary to reproduce neuronal electrical activity. PMID:25970534

PERK Regulates Working Memory and Protein Synthesis-Dependent Memory Flexibility

PubMed Central

Zhu, Siying; Henninger, Keely; McGrath, Barbara C.; Cavener, Douglas R.

2016-01-01

PERK (EIF2AK3) is an ER-resident eIF2α kinase required for memory flexibility and metabotropic glutamate receptor-dependent long-term depression, processes known to be dependent on new protein synthesis. Here we investigated PERK’s role in working memory, a cognitive ability that is independent of new protein synthesis, but instead is dependent on cellular Ca2+ dynamics. We found that working memory is impaired in forebrain-specific Perk knockout and pharmacologically PERK-inhibited mice. Moreover, inhibition of PERK in wild-type mice mimics the fear extinction impairment observed in forebrain-specific Perk knockout mice. Our findings reveal a novel role of PERK in cognitive functions and suggest that PERK regulates both Ca2+ -dependent working memory and protein synthesis-dependent memory flexibility. PMID:27627766

Brain-Based Devices for Neuromorphic Computer Systems

DTIC Science & Technology

2013-07-01

and Deco, G. (2012). Effective Visual Working Memory Capacity: An Emergent Effect from the Neural Dynamics in an Attractor Network. PLoS ONE 7, e42719...models, apply them to a recognition task, and to demonstrate a working memory . In the course of this work a new analytical method for spiking data was...4 3.4 Spiking Neural Model Simulation of Working Memory ..................................... 5 3.5 A Novel Method for Analysis

Dynamic burstiness of word-occurrence and network modularity in textbook systems

NASA Astrophysics Data System (ADS)

Cui, Xue-Mei; Yoon, Chang No; Youn, Hyejin; Lee, Sang Hoon; Jung, Jean S.; Han, Seung Kee

2017-12-01

We show that the dynamic burstiness of word occurrence in textbook systems is attributed to the modularity of the word association networks. At first, a measure of dynamic burstiness is introduced to quantify burstiness of word occurrence in a textbook. The advantage of this measure is that the dynamic burstiness is decomposable into two contributions: one coming from the inter-event variance and the other from the memory effects. Comparing network structures of physics textbook systems with those of surrogate random textbooks without the memory or variance effects are absent, we show that the network modularity increases systematically with the dynamic burstiness. The intra-connectivity of individual word representing the strength of a tie with which a node is bound to a module accordingly increases with the dynamic burstiness, suggesting individual words with high burstiness are strongly bound to one module. Based on the frequency and dynamic burstiness, physics terminology is classified into four categories: fundamental words, topical words, special words, and common words. In addition, we test the correlation between the dynamic burstiness of word occurrence and network modularity using a two-state model of burst generation.

Fame emerges as a result of small memory

NASA Astrophysics Data System (ADS)

Bingol, Haluk

2008-03-01

A dynamic memory model is proposed in which an agent “learns” a new agent by means of recommendation. The agents can also “remember” and “forget.” The memory size is decreased while the population size is kept constant. “Fame” emerged as a few agents become very well known in expense of the majority being completely forgotten. The minimum and the maximum of fame change linearly with the relative memory size. The network properties of the who-knows-who graph, which represents the state of the system, are investigated.

Fabry-Perot confocal resonator optical associative memory

NASA Astrophysics Data System (ADS)

Burns, Thomas J.; Rogers, Steven K.; Vogel, George A.

1993-03-01

A unique optical associative memory architecture is presented that combines the optical processing environment of a Fabry-Perot confocal resonator with the dynamic storage and recall properties of volume holograms. The confocal resonator reduces the size and complexity of previous associative memory architectures by folding a large number of discrete optical components into an integrated, compact optical processing environment. Experimental results demonstrate the system is capable of recalling a complete object from memory when presented with partial information about the object. A Fourier optics model of the system's operation shows it implements a spatially continuous version of a discrete, binary Hopfield neural network associative memory.

A Feedback Control Model of Comprehensive Therapy for Treating Immunogenic Tumours

NASA Astrophysics Data System (ADS)

Tang, Biao; Xiao, Yanni; Tang, Sanyi; Cheke, Robert A.

Surgery is the traditional method for treating cancers, but it often fails to cure patients for complex reasons so new therapeutic approaches that include both surgery and immunotherapy have recently been proposed. These have been shown to be effective, clinically, in inhibiting cancer cells while allowing retention of immunologic memory. This comprehensive strategy is guided by whether a population of tumour cells has or has not exceeded a threshold density. Conditions for successful control of tumours in an immune tumour system were modeled and the related dynamics were addressed. A mathematical model with state-dependent impulsive interventions is formulated to describe combinations of surgery with immunotherapy. By analyzing the properties of the Poincaré map, we examine the global dynamics of the immune tumour system with state-dependent feedback control, including the existence and stability of the semi-trivial order-1 periodic solution and the positive order-k periodic solution. The main results showed that surgery alone can only control the tumour size below a certain level while there is no immunologic memory. If comprehensive therapy involving combining surgery with immunotherapy is considered, then not only can the cancers be controlled below a certain level, but the immune system can also retain its activity. The existence of positive order-k periodic solutions implies that periodical therapy is needed to control the cancers. However, choosing the treatment frequency and the strength of the therapy remains challenging, and hence a strategy of individual-based therapy is suggested.

I/O Parallelization for the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

NASA Technical Reports Server (NTRS)

Lucchesi, Rob; Sawyer, W.; Takacs, L. L.; Lyster, P.; Zero, J.

1998-01-01

The National Aeronautics and Space Administration (NASA) Data Assimilation Office (DAO) at the Goddard Space Flight Center (GSFC) has developed the GEOS DAS, a data assimilation system that provides production support for NASA missions and will support NASA's Earth Observing System (EOS) in the coming years. The GEOS DAS will be used to provide background fields of meteorological quantities to EOS satellite instrument teams for use in their data algorithms as well as providing assimilated data sets for climate studies on decadal time scales. The DAO has been involved in prototyping parallel implementations of the GEOS DAS for a number of years and is now embarking on an effort to convert the production version from shared-memory parallelism to distributed-memory parallelism using the portable Message-Passing Interface (MPI). The GEOS DAS consists of two main components, an atmospheric General Circulation Model (GCM) and a Physical-space Statistical Analysis System (PSAS). The GCM operates on data that are stored on a regular grid while PSAS works with observational data that are scattered irregularly throughout the atmosphere. As a result, the two components have different data decompositions. The GCM is decomposed horizontally as a checkerboard with all vertical levels of each box existing on the same processing element(PE). The dynamical core of the GCM can also operate on a rotated grid, which requires communication-intensive grid transformations during GCM integration. PSAS groups observations on PEs in a more irregular and dynamic fashion.

Emulating short-term synaptic dynamics with memristive devices

NASA Astrophysics Data System (ADS)

Berdan, Radu; Vasilaki, Eleni; Khiat, Ali; Indiveri, Giacomo; Serb, Alexandru; Prodromakis, Themistoklis

2016-01-01

Neuromorphic architectures offer great promise for achieving computation capacities beyond conventional Von Neumann machines. The essential elements for achieving this vision are highly scalable synaptic mimics that do not undermine biological fidelity. Here we demonstrate that single solid-state TiO2 memristors can exhibit non-associative plasticity phenomena observed in biological synapses, supported by their metastable memory state transition properties. We show that, contrary to conventional uses of solid-state memory, the existence of rate-limiting volatility is a key feature for capturing short-term synaptic dynamics. We also show how the temporal dynamics of our prototypes can be exploited to implement spatio-temporal computation, demonstrating the memristors full potential for building biophysically realistic neural processing systems.

Dynamic Neuroplasticity after Human Prefrontal Cortex Damage

PubMed Central

Voytek, Bradley; Davis, Matar; Yago, Elena; Barceló, Francisco; Vogel, Edward K.; Knight, Robert T.

2010-01-01

Summary Memory and attention deficits are common after prefrontal cortex (PFC) damage, yet people generally recover some function over time. Recovery is thought to be dependent upon undamaged brain regions but the temporal dynamics underlying cognitive recovery are poorly understood. Here we provide evidence that the intact PFC compensates for damage in the lesioned PFC on a trial-by-trial basis dependent on cognitive load. The extent of this rapid functional compensation is indexed by transient increases in electrophysiological measures of attention and memory in the intact PFC, detectable within a second after stimulus presentation and only when the lesioned hemisphere is challenged. These observations provide evidence supporting a dynamic and flexible model of compensatory neural plasticity. PMID:21040843

Learning to recognize objects on the fly: a neurally based dynamic field approach.

PubMed

Faubel, Christian; Schöner, Gregor

2008-05-01

Autonomous robots interacting with human users need to build and continuously update scene representations. This entails the problem of rapidly learning to recognize new objects under user guidance. Based on analogies with human visual working memory, we propose a dynamical field architecture, in which localized peaks of activation represent objects over a small number of simple feature dimensions. Learning consists of laying down memory traces of such peaks. We implement the dynamical field model on a service robot and demonstrate how it learns 30 objects from a very small number of views (about 5 per object are sufficient). We also illustrate how properties of feature binding emerge from this framework.

Computer Vision for Artificially Intelligent Robotic Systems

NASA Astrophysics Data System (ADS)

Ma, Chialo; Ma, Yung-Lung

1987-04-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts -- position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed bye the main control unit. In Pulse-Echo Signal Process Unit, we ultilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by u law coding method, and this data together with delay time T, angle information OH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Model, we use a narrow beam transducer and it's input voltage is 50V p-p. A RobOt equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Improved Performance Characteristics For Indium Antimonide Photovoltaic Detector Arrays Using A FET-Switched Multiplexing Technique

NASA Astrophysics Data System (ADS)

Ma, Yung-Lung; Ma, Chialo

1987-03-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts _ position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed by the main control unit. In Pulse-Echo Signal Process Unit, we utilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by p law coding method, and this data together with delay time T, angle information eH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Models, we use a narrow beam transducer and it's input voltage is 50V p-p. A Robot equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Dynamism in Electronic Performance Support Systems.

ERIC Educational Resources Information Center

Laffey, James

1995-01-01

Describes a model for dynamic electronic performance support systems based on NNAble, a system developed by the training group at Apple Computer. Principles for designing dynamic performance support are discussed, including a systems approach, performer-centered design, awareness of situated cognition, organizational memory, and technology use.…

Retrieval Demands Adaptively Change Striatal Old/New Signals and Boost Subsequent Long-Term Memory.

PubMed

Herweg, Nora A; Sommer, Tobias; Bunzeck, Nico

2018-01-17

The striatum is a central part of the dopaminergic mesolimbic system and contributes both to the encoding and retrieval of long-term memories. In this regard, the co-occurrence of striatal novelty and retrieval success effects in independent studies underlines the structure's double duty and suggests dynamic contextual adaptation. To test this hypothesis and further investigate the underlying mechanisms of encoding and retrieval dynamics, human subjects viewed pre-familiarized scene images intermixed with new scenes and classified them as indoor versus outdoor (encoding task) or old versus new (retrieval task), while fMRI and eye tracking data were recorded. Subsequently, subjects performed a final recognition task. As hypothesized, striatal activity and pupil size reflected task-conditional salience of old and new stimuli, but, unexpectedly, this effect was not reflected in the substantia nigra and ventral tegmental area (SN/VTA), medial temporal lobe, or subsequent memory performance. Instead, subsequent memory generally benefitted from retrieval, an effect possibly driven by task difficulty and activity in a network including different parts of the striatum and SN/VTA. Our findings extend memory models of encoding and retrieval dynamics by pinpointing a specific contextual factor that differentially modulates the functional properties of the mesolimbic system. SIGNIFICANCE STATEMENT The mesolimbic system is involved in the encoding and retrieval of information but it is unclear how these two processes are achieved within the same network of brain regions. In particular, memory retrieval and novelty encoding were considered in independent studies, implying that novelty (new > old) and retrieval success (old > new) effects may co-occur in the striatum. Here, we used a common framework implicating the striatum, but not other parts of the mesolimbic system, in tracking context-dependent salience of old and new information. The current study, therefore, paves the way for a more comprehensive understanding of the functional properties of the mesolimbic system during memory encoding and retrieval. Copyright © 2018 the authors 0270-6474/18/380745-10$15.00/0.

Field enhanced charge carrier reconfiguration in electronic and ionic coupled dynamic polymer resistive memory.

PubMed

Zhao, Jun Hui; Thomson, Douglas J; Pilapil, Matt; Pillai, Rajesh G; Rahman, G M Aminur; Freund, Michael S

2010-04-02

Dynamic resistive memory devices based on a conjugated polymer composite (PPy(0)DBS(-)Li(+) (PPy: polypyrrole; DBS(-): dodecylbenzenesulfonate)), with field-driven ion migration, have been demonstrated. In this work the dynamics of these systems has been investigated and it has been concluded that increasing the applied field can dramatically increase the rate at which information can be 'written' into these devices. A conductance model using space charge limited current coupled with an electric field induced ion reconfiguration has been successfully utilized to interpret the experimentally observed transient conducting behaviors. The memory devices use the rising and falling transient current states for the storage of digital states. The magnitude of these transient currents is controlled by the magnitude and width of the write/read pulse. For the 500 nm length devices used in this work an increase in 'write' potential from 2.5 to 5.5 V decreased the time required to create a transient conductance state that can be converted into the digital signal by 50 times. This work suggests that the scaling of these devices will be favorable and that 'write' times for the conjugated polymer composite memory devices will decrease rapidly as ion driving fields increase with decreasing device size.

Experiments and Analyses of Data Transfers Over Wide-Area Dedicated Connections

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

Rao, Nageswara S.; Liu, Qiang; Sen, Satyabrata

Dedicated wide-area network connections are increasingly employed in high-performance computing and big data scenarios. One might expect the performance and dynamics of data transfers over such connections to be easy to analyze due to the lack of competing traffic. However, non-linear transport dynamics and end-system complexities (e.g., multi-core hosts and distributed filesystems) can in fact make analysis surprisingly challenging. We present extensive measurements of memory-to-memory and disk-to-disk file transfers over 10 Gbps physical and emulated connections with 0–366 ms round trip times (RTTs). For memory-to-memory transfers, profiles of both TCP and UDT throughput as a function of RTT show concavemore » and convex regions; large buffer sizes and more parallel flows lead to wider concave regions, which are highly desirable. TCP and UDT both also display complex throughput dynamics, as indicated by their Poincare maps and Lyapunov exponents. For disk-to-disk transfers, we determine that high throughput can be achieved via a combination of parallel I/O threads, parallel network threads, and direct I/O mode. Our measurements also show that Lustre filesystems can be mounted over long-haul connections using LNet routers, although challenges remain in jointly optimizing file I/O and transport method parameters to achieve peak throughput.« less

Cannabinoids disrupt memory encoding by functionally isolating hippocampal CA1 from CA3.

PubMed

Sandler, Roman A; Fetterhoff, Dustin; Hampson, Robert E; Deadwyler, Sam A; Marmarelis, Vasilis Z

2017-07-01

Much of the research on cannabinoids (CBs) has focused on their effects at the molecular and synaptic level. However, the effects of CBs on the dynamics of neural circuits remains poorly understood. This study aims to disentangle the effects of CBs on the functional dynamics of the hippocampal Schaffer collateral synapse by using data-driven nonparametric modeling. Multi-unit activity was recorded from rats doing an working memory task in control sessions and under the influence of exogenously administered tetrahydrocannabinol (THC), the primary CB found in marijuana. It was found that THC left firing rate unaltered and only slightly reduced theta oscillations. Multivariate autoregressive models, estimated from spontaneous spiking activity, were then used to describe the dynamical transformation from CA3 to CA1. They revealed that THC served to functionally isolate CA1 from CA3 by reducing feedforward excitation and theta information flow. The functional isolation was compensated by increased feedback excitation within CA1, thus leading to unaltered firing rates. Finally, both of these effects were shown to be correlated with memory impairments in the working memory task. By elucidating the circuit mechanisms of CBs, these results help close the gap in knowledge between the cellular and behavioral effects of CBs.

The dynamics of access to groups in working memory.

PubMed

Farrell, Simon; Lelièvre, Anna

2012-11-01

The finding that participants leave a pause between groups when attempting serial recall of temporally grouped lists has been taken to indicate access to a hierarchical representation of the list in working memory. An alternative explanation is that the dynamics of serial recall solely reflect output (rather than memorial) processes, with the temporal pattern at input merely suggesting a basis for the pattern of output buffering. Three experiments are presented here that disentangle input structure from output buffering in serial recall. In Experiment 1, participants were asked to recall a subset of visually presented digits from a temporally grouped list in their original order, where either within-group position or group position was kept constant. In Experiment 2, participants performed more standard serial recall of spoken digits, and input and output position were dissociated by asking participants to initiate recall from a post-cued position in the list. In Experiment 3, participants were asked to serially recall temporally grouped lists of visually presented digits where the grouping structure was unpredictable, under either articulatory suppression or silent conditions. The 3 experiments point to a tight linkage between implied memorial structures (i.e., the pattern of grouping at encoding) and the output structure implied by retrieval times and call into question a purely motoric account of the dynamics of recall.

Cannabinoids disrupt memory encoding by functionally isolating hippocampal CA1 from CA3

PubMed Central

Fetterhoff, Dustin; Hampson, Robert E.; Deadwyler, Sam A.; Marmarelis, Vasilis Z.

2017-01-01

Much of the research on cannabinoids (CBs) has focused on their effects at the molecular and synaptic level. However, the effects of CBs on the dynamics of neural circuits remains poorly understood. This study aims to disentangle the effects of CBs on the functional dynamics of the hippocampal Schaffer collateral synapse by using data-driven nonparametric modeling. Multi-unit activity was recorded from rats doing an working memory task in control sessions and under the influence of exogenously administered tetrahydrocannabinol (THC), the primary CB found in marijuana. It was found that THC left firing rate unaltered and only slightly reduced theta oscillations. Multivariate autoregressive models, estimated from spontaneous spiking activity, were then used to describe the dynamical transformation from CA3 to CA1. They revealed that THC served to functionally isolate CA1 from CA3 by reducing feedforward excitation and theta information flow. The functional isolation was compensated by increased feedback excitation within CA1, thus leading to unaltered firing rates. Finally, both of these effects were shown to be correlated with memory impairments in the working memory task. By elucidating the circuit mechanisms of CBs, these results help close the gap in knowledge between the cellular and behavioral effects of CBs. PMID:28686594

A Dynamical Systems Explanation of the Hurst Effect and Atmospheric Low-Frequency Variability

PubMed Central

Franzke, Christian L. E.; Osprey, Scott M.; Davini, Paolo; Watkins, Nicholas W.

2015-01-01

The Hurst effect plays an important role in many areas such as physics, climate and finance. It describes the anomalous growth of range and constrains the behavior and predictability of these systems. The Hurst effect is frequently taken to be synonymous with Long-Range Dependence (LRD) and is typically assumed to be produced by a stationary stochastic process which has infinite memory. However, infinite memory appears to be at odds with the Markovian nature of most physical laws while the stationarity assumption lacks robustness. Here we use Lorenz's paradigmatic chaotic model to show that regime behavior can also cause the Hurst effect. By giving an alternative, parsimonious, explanation using nonstationary Markovian dynamics, our results question the common belief that the Hurst effect necessarily implies a stationary infinite memory process. We also demonstrate that our results can explain atmospheric variability without the infinite memory previously thought necessary and are consistent with climate model simulations. PMID:25765880

Multiple-object permanence tracking: limitation in maintenance and transformation of perceptual objects.

PubMed

Saiki, Jun

2002-01-01

Research on change blindness and transsaccadic memory revealed that a limited amount of information is retained across visual disruptions in visual working memory. It has been proposed that visual working memory can hold four to five coherent object representations. To investigate their maintenance and transformation in dynamic situations, I devised an experimental paradigm called multiple-object permanence tracking (MOPT) that measures memory for multiple feature-location bindings in dynamic situations. Observers were asked to detect any color switch in the middle of a regular rotation of a pattern with multiple colored disks behind an occluder. The color-switch detection performance dramatically declined as the pattern rotation velocity increased, and this effect of object motion was independent of the number of targets. The MOPT task with various shapes and colors showed that color-shape conjunctions are not available in the MOPT task. These results suggest that even completely predictable motion severely reduces our capacity of object representations, from four to only one or two.

Scaling properties and universality of first-passage-time probabilities in financial markets

NASA Astrophysics Data System (ADS)

Perelló, Josep; Gutiérrez-Roig, Mario; Masoliver, Jaume

2011-12-01

Financial markets provide an ideal frame for the study of crossing or first-passage time events of non-Gaussian correlated dynamics, mainly because large data sets are available. Tick-by-tick data of six futures markets are herein considered, resulting in fat-tailed first-passage time probabilities. The scaling of the return with its standard deviation collapses the probabilities of all markets examined—and also for different time horizons—into single curves, suggesting that first-passage statistics is market independent (at least for high-frequency data). On the other hand, a very closely related quantity, the survival probability, shows, away from the center and tails of the distribution, a hyperbolic t-1/2 decay typical of a Markovian dynamics, albeit the existence of memory in markets. Modifications of the Weibull and Student distributions are good candidates for the phenomenological description of first-passage time properties under certain regimes. The scaling strategies shown may be useful for risk control and algorithmic trading.

Computing by physical interaction in neurons.

PubMed

Aur, Dorian; Jog, Mandar; Poznanski, Roman R

2011-12-01

The electrodynamics of action potentials represents the fundamental level where information is integrated and processed in neurons. The Hodgkin-Huxley model cannot explain the non-stereotyped spatial charge density dynamics that occur during action potential propagation. Revealed in experiments as spike directivity, the non-uniform charge density dynamics within neurons carry meaningful information and suggest that fragments of information regarding our memories are endogenously stored in structural patterns at a molecular level and are revealed only during spiking activity. The main conceptual idea is that under the influence of electric fields, efficient computation by interaction occurs between charge densities embedded within molecular structures and the transient developed flow of electrical charges. This process of computation underlying electrical interactions and molecular mechanisms at the subcellular level is dissimilar from spiking neuron models that are completely devoid of physical interactions. Computation by interaction describes a more powerful continuous model of computation than the one that consists of discrete steps as represented in Turing machines.

Astrocyte glycogen and lactate: New insights into learning and memory mechanisms.

PubMed

Alberini, Cristina M; Cruz, Emmanuel; Descalzi, Giannina; Bessières, Benjamin; Gao, Virginia

2018-06-01

Memory, the ability to retain learned information, is necessary for survival. Thus far, molecular and cellular investigations of memory formation and storage have mainly focused on neuronal mechanisms. In addition to neurons, however, the brain comprises other types of cells and systems, including glia and vasculature. Accordingly, recent experimental work has begun to ask questions about the roles of non-neuronal cells in memory formation. These studies provide evidence that all types of glial cells (astrocytes, oligodendrocytes, and microglia) make important contributions to the processing of encoded information and storing memories. In this review, we summarize and discuss recent findings on the critical role of astrocytes as providers of energy for the long-lasting neuronal changes that are necessary for long-term memory formation. We focus on three main findings: first, the role of glucose metabolism and the learning- and activity-dependent metabolic coupling between astrocytes and neurons in the service of long-term memory formation; second, the role of astrocytic glucose metabolism in arousal, a state that contributes to the formation of very long-lasting and detailed memories; and finally, in light of the high energy demands of the brain during early development, we will discuss the possible role of astrocytic and neuronal glucose metabolisms in the formation of early-life memories. We conclude by proposing future directions and discussing the implications of these findings for brain health and disease. Astrocyte glycogenolysis and lactate play a critical role in memory formation. Emotionally salient experiences form strong memories by recruiting astrocytic β2 adrenergic receptors and astrocyte-generated lactate. Glycogenolysis and astrocyte-neuron metabolic coupling may also play critical roles in memory formation during development, when the energy requirements of brain metabolism are at their peak. © 2017 Wiley Periodicals, Inc.

Working memory capacity and retrieval limitations from long-term memory: an examination of differences in accessibility.

PubMed

Unsworth, Nash; Spillers, Gregory J; Brewer, Gene A

2012-01-01

In two experiments, the locus of individual differences in working memory capacity and long-term memory recall was examined. Participants performed categorical cued and free recall tasks, and individual differences in the dynamics of recall were interpreted in terms of a hierarchical-search framework. The results from this study are in accordance with recent theorizing suggesting a strong relation between working memory capacity and retrieval from long-term memory. Furthermore, the results also indicate that individual differences in categorical recall are partially due to differences in accessibility. In terms of accessibility of target information, two important factors drive the difference between high- and low-working-memory-capacity participants. Low-working-memory-capacity participants fail to utilize appropriate retrieval strategies to access cues, and they also have difficulty resolving cue overload. Thus, when low-working-memory-capacity participants were given specific cues that activated a smaller set of potential targets, their recall performance was the same as that of high-working-memory-capacity participants.

A Putative Biochemical Engram of Long-term Memory

PubMed Central

Li, Liying; Sanchez, Consuelo Perez; Slaughter, Brian D.; Zhao, Yubai; Khan, Mohammed Repon; Unruh, Jay R.; Rubinstein, Boris; Si, Kausik

2016-01-01

Summary How a transient experience creates an enduring yet dynamic memory remains an unresolved issue in studies of memory. Experience-dependent aggregation of the RNA-binding protein CPEB/Orb2 is one of the candidate mechanisms of memory maintenance. Here, using tools that allow rapid and reversible inactivation of Orb2 protein in neurons we find that Orb2 activity is required for encoding and recall of memory. From a screen we have identified a DNA-J family chaperone, JJJ2, which facilitates Orb2 aggregation, and ectopic expression of JJJ2 enhances the animal’s capacity to form long-term memory. Finally, we have developed tools to visualize training-dependent aggregation of Orb2. We find that aggregated Orb2 in a subset of mushroom body neurons can serve as a “molecular signature” of memory and predict memory strength. Our data indicates that self-sustaining aggregates of Orb2 may serve as a physical substrate of memory and provide a molecular basis for the perduring yet malleable nature of memory. PMID:27818176

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

Medial temporal and neocortical contributions to remote memory for semantic narratives: evidence from amnesia.

PubMed

Verfaellie, Mieke; Bousquet, Kathryn; Keane, Margaret M

2014-08-01

Studies of remote memory for semantic facts and concepts suggest that hippocampal lesions lead to a temporally graded impairment that extends no more than ten years prior to the onset of amnesia. Such findings have led to the notion that once consolidated, semantic memories are represented neocortically and are no longer dependent on the hippocampus. Here, we examined the fate of well-established semantic narratives following medial temporal lobe (MTL) lesions. Seven amnesic patients, five with lesions restricted to the MTL and two with lesions extending into lateral temporal cortex (MTL+), were asked to recount fairy tales and bible stories that they rated as familiar. Narratives were scored for number and type of details, number of main thematic elements, and order in which the main thematic elements were recounted. In comparison to controls, patients with MTL lesions produced fewer details, but the number and order of main thematic elements generated was intact. By contrast, patients with MTL+ lesions showed a pervasive impairment, affecting not only the generation of details, but also the generation and ordering of main steps. These findings challenge the notion that, once consolidated, semantic memories are no longer dependent on the hippocampus for retrieval. Possible hippocampal contributions to the retrieval of detailed semantic narratives are discussed. Published by Elsevier Ltd.

Feedback control stabilization of critical dynamics via resource transport on multilayer networks: How glia enable learning dynamics in the brain

NASA Astrophysics Data System (ADS)

Virkar, Yogesh S.; Shew, Woodrow L.; Restrepo, Juan G.; Ott, Edward

2016-10-01

Learning and memory are acquired through long-lasting changes in synapses. In the simplest models, such synaptic potentiation typically leads to runaway excitation, but in reality there must exist processes that robustly preserve overall stability of the neural system dynamics. How is this accomplished? Various approaches to this basic question have been considered. Here we propose a particularly compelling and natural mechanism for preserving stability of learning neural systems. This mechanism is based on the global processes by which metabolic resources are distributed to the neurons by glial cells. Specifically, we introduce and study a model composed of two interacting networks: a model neural network interconnected by synapses that undergo spike-timing-dependent plasticity; and a model glial network interconnected by gap junctions that diffusively transport metabolic resources among the glia and, ultimately, to neural synapses where they are consumed. Our main result is that the biophysical constraints imposed by diffusive transport of metabolic resources through the glial network can prevent runaway growth of synaptic strength, both during ongoing activity and during learning. Our findings suggest a previously unappreciated role for glial transport of metabolites in the feedback control stabilization of neural network dynamics during learning.

Robust dynamical decoupling for quantum computing and quantum memory.

PubMed

Souza, Alexandre M; Alvarez, Gonzalo A; Suter, Dieter

2011-06-17

Dynamical decoupling (DD) is a popular technique for protecting qubits from the environment. However, unless special care is taken, experimental errors in the control pulses used in this technique can destroy the quantum information instead of preserving it. Here, we investigate techniques for making DD sequences robust against different types of experimental errors while retaining good decoupling efficiency in a fluctuating environment. We present experimental data from solid-state nuclear spin qubits and introduce a new DD sequence that is suitable for quantum computing and quantum memory.

Mitigating Upsets in SRAM-Based FPGAs from the Xilinx Virtex 2 Family

NASA Technical Reports Server (NTRS)

Swift, G. M.; Yui, C. C.; Carmichael, C.; Koga, R.; George, J. S.

2003-01-01

Static random access memory (SRAM) upset rates in field programmable gate arrays (FPGAs) from the Xilinx Virtex 2 family have been tested for radiation effects on configuration memory, block RAM and the power-on-reset (POR) and SelectMAP single event functional interrupts (SEFIs). Dynamic testing has shown the effectiveness and value of Triple Module Redundancy (TMR) and partial reconfiguration when used in conjunction. Continuing dynamic testing for more complex designs and other Virtex 2 capabilities (i.e., I/O standards, digital clock managers (DCM), etc.) is scheduled.

Cholinergic manipulations bidirectionally regulate object memory destabilization

PubMed Central

Stiver, Mikaela L.; Jacklin, Derek L.; Mitchnick, Krista A.; Vicic, Nevena; Carlin, Justine; O'Hara, Matthew

2015-01-01

Consolidated memories can become destabilized and open to modification upon retrieval. Destabilization is most reliably prompted when novel information is present during memory reactivation. We hypothesized that the neurotransmitter acetylcholine (ACh) plays an important role in novelty-induced memory destabilization because of its established involvement in new learning. Accordingly, we investigated the effects of cholinergic manipulations in rats using an object recognition paradigm that requires reactivation novelty to destabilize object memories. The muscarinic receptor antagonist scopolamine, systemically or infused directly into the perirhinal cortex, blocked this novelty-induced memory destabilization. Conversely, systemic oxotremorine or carbachol, muscarinic receptor agonists, administered systemically or intraperirhinally, respectively, mimicked the destabilizing effect of novel information during reactivation. These bidirectional effects suggest a crucial influence of ACh on memory destabilization and the updating functions of reconsolidation. This is a hitherto unappreciated mnemonic role for ACh with implications for its potential involvement in cognitive flexibility and the dynamic process of long-term memory storage. PMID:25776038

A semi-floating gate memory based on van der Waals heterostructures for quasi-non-volatile applications

NASA Astrophysics Data System (ADS)

Liu, Chunsen; Yan, Xiao; Song, Xiongfei; Ding, Shijin; Zhang, David Wei; Zhou, Peng

2018-05-01

As conventional circuits based on field-effect transistors are approaching their physical limits due to quantum phenomena, semi-floating gate transistors have emerged as an alternative ultrafast and silicon-compatible technology. Here, we show a quasi-non-volatile memory featuring a semi-floating gate architecture with band-engineered van der Waals heterostructures. This two-dimensional semi-floating gate memory demonstrates 156 times longer refresh time with respect to that of dynamic random access memory and ultrahigh-speed writing operations on nanosecond timescales. The semi-floating gate architecture greatly enhances the writing operation performance and is approximately 106 times faster than other memories based on two-dimensional materials. The demonstrated characteristics suggest that the quasi-non-volatile memory has the potential to bridge the gap between volatile and non-volatile memory technologies and decrease the power consumption required for frequent refresh operations, enabling a high-speed and low-power random access memory.

Checkpoint-Restart in User Space

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

CRUISE implements a user-space file system that stores data in main memory and transparently spills over to other storage, like local flash memory or the parallel file system, as needed. CRUISE also exposes file contents fo remote direct memory access, allowing external tools to copy files to the parallel file system in the background with reduced CPU interruption.

Seven-Year-Olds Allocate Attention Like Adults Unless Working Memory Is Overloaded

ERIC Educational Resources Information Center

Cowan, Nelson; Morey, Candice C.; AuBuchon, Angela M.; Zwilling, Christopher E.; Gilchrist, Amanda L.

2010-01-01

Previous studies have indicated that visual working memory performance increases with age in childhood, but it is not clear why. One main hypothesis has been that younger children are less efficient in their attention; specifically, they are less able to exclude irrelevant items from working memory to make room for relevant items. We examined this…

Effects of Self-Paced Encoding and Practice on Age-Related Deficits in Binding Three Features

ERIC Educational Resources Information Center

Kinjo, Hikari

2010-01-01

Although much literature suggests that the age-related decline in episodic memory could be due to difficulties in binding features of information, previous studies focused mainly on memory of paired associations rather than memory of multiple bound features. In reality, however, there are many situations that require binding multiple features…

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

Edwards, Harold C.; Ibanez, Daniel Alejandro

This report documents the ASC/ATDM Kokkos deliverable "Production Portable Dy- namic Task DAG Capability." This capability enables applications to create and execute a dynamic task DAG ; a collection of heterogeneous computational tasks with a directed acyclic graph (DAG) of "execute after" dependencies where tasks and their dependencies are dynamically created and destroyed as tasks execute. The Kokkos task scheduler executes the dynamic task DAG on the target execution resource; e.g. a multicore CPU, a manycore CPU such as Intel's Knights Landing (KNL), or an NVIDIA GPU. Several major technical challenges had to be addressed during development of Kokkos' Taskmore » DAG capability: (1) portability to a GPU with it's simplified hardware and micro- runtime, (2) thread-scalable memory allocation and deallocation from a bounded pool of memory, (3) thread-scalable scheduler for dynamic task DAG, (4) usability by applications.« less

Enhanced oscillatory activity in the hippocampal-prefrontal network is related to short-term memory function after early-life seizures

PubMed Central

Kleen, Jonathan K.; Wu, Edie X.; Holmes, Gregory L.; Scott, Rod C.; Lenck-Santini, Pierre-Pascal

2011-01-01

Neurological insults during development are associated with later impairments in learning and memory. Although remedial training can help restore cognitive function, the neural mechanisms of this recovery in memory systems are largely unknown. To examine this issue we measured electrophysiological oscillatory activity in the hippocampus (both CA3 and CA1) and prefrontal cortex of adult rats that had experienced repeated seizures in the first weeks of life, while they were remedially trained on a delayed-nonmatch-to-sample memory task. Seizure-exposed rats showed initial difficulties learning the task but performed similar to control rats after extra training. Whole-session analyses illustrated enhanced theta power in all three structures while seizure rats learned response tasks prior to the memory task. Whilst performing the memory task, dynamic oscillation patterns revealed that prefrontal cortex theta power was increased among seizure-exposed rats. This enhancement appeared after the first memory training steps using short delays and plateaued at the most difficult steps which included both short and long delays. Further, seizure rats showed enhanced CA1-prefrontal theta coherence in correct trials compared to incorrect trials when long delays were imposed, suggesting increased hippocampal-prefrontal synchrony for the task in this group when memory demand was high. Seizure-exposed rats also showed heightened gamma power and coherence among all three structures during the trials. Our results demonstrate the first evidence of hippocampal-prefrontal enhancements following seizures in early development. Dynamic compensatory changes in this network and interconnected circuits may underpin cognitive rehabilitation following other neurological insults to higher cognitive systems. PMID:22031886

Dynamic phenotypic restructuring of the CD4 and CD8 T-cell subsets with age in healthy humans: a compartmental model analysis.

PubMed

Jackola, D R; Hallgren, H M

1998-11-16

In healthy humans, phenotypic restructuring occurs with age within the CD3+ T-lymphocyte complement. This is characterized by a non-linear decrease of the percentage of 'naive' (CD45RA+) cells and a corresponding non-linear increase of the percentage of 'memory' (CD45R0+) cells among both the CD4+ and CD8+ T-cell subsets. We devised a simple compartmental model to study the age-dependent kinetics of phenotypic restructuring. We also derived differential equations whose parameters determined yearly gains minus losses of the percentage and absolute numbers of circulating naive cells, yearly gains minus losses of the percentage and absolute numbers of circulating memory cells, and the yearly rate of conversion of naive to memory cells. Solutions of these evaluative differential equations demonstrate the following: (1) the memory cell complement 'resides' within its compartment for a longer time than the naive cell complement within its compartment for both CD4 and CD8 cells; (2) the average, annual 'turnover rate' is the same for CD4 and CD8 naive cells. In contrast, the average, annual 'turnover rate' for memory CD8 cells is 1.5 times that of memory CD4 cells; (3) the average, annual conversion rate of CD4 naive cells to memory cells is twice that of the CD8 conversion rate; (4) a transition in dynamic restructuring occurs during the third decade of life that is due to these differences in turnover and conversion rates, between and from naive to memory cells.

Improving Memory for Optimization and Learning in Dynamic Environments

DTIC Science & Technology

2011-07-01

algorithm uses simple, in- cremental clustering to separate solutions into memory entries. The cluster centers are used as the models in the memory. This is...entire days of traffic with realistic traffic de - mands and turning ratios on a 32 intersection network modeled on downtown Pittsburgh, Pennsyl- vania...early/tardy problem. Management Science, 35(2):177–191, 1989. [78] Daniel Parrott and Xiaodong Li. A particle swarm model for tracking multiple peaks in

Associative memory in phasing neuron networks

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

Nair, Niketh S; Bochove, Erik J.; Braiman, Yehuda

2014-01-01

We studied pattern formation in a network of coupled Hindmarsh-Rose model neurons and introduced a new model for associative memory retrieval using networks of Kuramoto oscillators. Hindmarsh-Rose Neural Networks can exhibit a rich set of collective dynamics that can be controlled by their connectivity. Specifically, we showed an instance of Hebb's rule where spiking was correlated with network topology. Based on this, we presented a simple model of associative memory in coupled phase oscillators.

A Hardware Platform for Characterizing and Validating 1-Dimensional Optical Systems

DTIC Science & Technology

2014-09-01

principle laboratory experiments, a bread -board sensor and data collection system was created to gather fuze data to postprocess after the event...merely differentiates this bistable memory category from dynamic random access memory [RAM], which must be periodically refreshed to retain data.) A

Kinetic memory based on the enzyme-limited competition.

PubMed

Hatakeyama, Tetsuhiro S; Kaneko, Kunihiko

2014-08-01

Cellular memory, which allows cells to retain information from their environment, is important for a variety of cellular functions, such as adaptation to external stimuli, cell differentiation, and synaptic plasticity. Although posttranslational modifications have received much attention as a source of cellular memory, the mechanisms directing such alterations have not been fully uncovered. It may be possible to embed memory in multiple stable states in dynamical systems governing modifications. However, several experiments on modifications of proteins suggest long-term relaxation depending on experienced external conditions, without explicit switches over multi-stable states. As an alternative to a multistability memory scheme, we propose "kinetic memory" for epigenetic cellular memory, in which memory is stored as a slow-relaxation process far from a stable fixed state. Information from previous environmental exposure is retained as the long-term maintenance of a cellular state, rather than switches over fixed states. To demonstrate this kinetic memory, we study several models in which multimeric proteins undergo catalytic modifications (e.g., phosphorylation and methylation), and find that a slow relaxation process of the modification state, logarithmic in time, appears when the concentration of a catalyst (enzyme) involved in the modification reactions is lower than that of the substrates. Sharp transitions from a normal fast-relaxation phase into this slow-relaxation phase are revealed, and explained by enzyme-limited competition among modification reactions. The slow-relaxation process is confirmed by simulations of several models of catalytic reactions of protein modifications, and it enables the memorization of external stimuli, as its time course depends crucially on the history of the stimuli. This kinetic memory provides novel insight into a broad class of cellular memory and functions. In particular, applications for long-term potentiation are discussed, including dynamic modifications of calcium-calmodulin kinase II and cAMP-response element-binding protein essential for synaptic plasticity.

Examining Event-Related Potential (ERP) Correlates of Decision Bias in Recognition Memory Judgments

PubMed Central

Hill, Holger; Windmann, Sabine

2014-01-01

Memory judgments can be based on accurate memory information or on decision bias (the tendency to report that an event is part of episodic memory when one is in fact unsure). Event related potentials (ERP) correlates are important research tools for elucidating the dynamics underlying memory judgments but so far have been established only for investigations of accurate old/new discrimination. To identify the ERP correlates of bias, and observe how these interact with ERP correlates of memory, we conducted three experiments that manipulated decision bias within participants via instructions during recognition memory tests while their ERPs were recorded. In Experiment 1, the bias manipulation was performed between blocks of trials (automatized bias) and compared to trial-by-trial shifts of bias in accord with an external cue (flexibly controlled bias). In Experiment 2, the bias manipulation was performed at two different levels of accurate old/new discrimination as the memory strength of old (studied) items was varied. In Experiment 3, the bias manipulation was added to another, bottom-up driven manipulation of bias induced via familiarity. In the first two Experiments, and in the low familiarity condition of Experiment 3, we found evidence of an early frontocentral ERP component at 320 ms poststimulus (the FN320) that was sensitive to the manipulation of bias via instruction, with more negative amplitudes indexing more liberal bias. By contrast, later during the trial (500–700 ms poststimulus), bias effects interacted with old/new effects across all three experiments. Results suggest that the decision criterion is typically activated early during recognition memory trials, and is integrated with retrieved memory signals and task-specific processing demands later during the trial. More generally, the findings demonstrate how ERPs can help to specify the dynamics of recognition memory processes under top-down and bottom-up controlled retrieval conditions. PMID:25264982

Examining Event-Related Potential (ERP) correlates of decision bias in recognition memory judgments.

PubMed

Hill, Holger; Windmann, Sabine

2014-01-01

Memory judgments can be based on accurate memory information or on decision bias (the tendency to report that an event is part of episodic memory when one is in fact unsure). Event related potentials (ERP) correlates are important research tools for elucidating the dynamics underlying memory judgments but so far have been established only for investigations of accurate old/new discrimination. To identify the ERP correlates of bias, and observe how these interact with ERP correlates of memory, we conducted three experiments that manipulated decision bias within participants via instructions during recognition memory tests while their ERPs were recorded. In Experiment 1, the bias manipulation was performed between blocks of trials (automatized bias) and compared to trial-by-trial shifts of bias in accord with an external cue (flexibly controlled bias). In Experiment 2, the bias manipulation was performed at two different levels of accurate old/new discrimination as the memory strength of old (studied) items was varied. In Experiment 3, the bias manipulation was added to another, bottom-up driven manipulation of bias induced via familiarity. In the first two Experiments, and in the low familiarity condition of Experiment 3, we found evidence of an early frontocentral ERP component at 320 ms poststimulus (the FN320) that was sensitive to the manipulation of bias via instruction, with more negative amplitudes indexing more liberal bias. By contrast, later during the trial (500-700 ms poststimulus), bias effects interacted with old/new effects across all three experiments. Results suggest that the decision criterion is typically activated early during recognition memory trials, and is integrated with retrieved memory signals and task-specific processing demands later during the trial. More generally, the findings demonstrate how ERPs can help to specify the dynamics of recognition memory processes under top-down and bottom-up controlled retrieval conditions.

A review of visual memory capacity: Beyond individual items and towards structured representations

PubMed Central

Brady, Timothy F.; Konkle, Talia; Alvarez, George A.

2012-01-01

Traditional memory research has focused on identifying separate memory systems and exploring different stages of memory processing. This approach has been valuable for establishing a taxonomy of memory systems and characterizing their function, but has been less informative about the nature of stored memory representations. Recent research on visual memory has shifted towards a representation-based emphasis, focusing on the contents of memory, and attempting to determine the format and structure of remembered information. The main thesis of this review will be that one cannot fully understand memory systems or memory processes without also determining the nature of memory representations. Nowhere is this connection more obvious than in research that attempts to measure the capacity of visual memory. We will review research on the capacity of visual working memory and visual long-term memory, highlighting recent work that emphasizes the contents of memory. This focus impacts not only how we estimate the capacity of the system - going beyond quantifying how many items can be remembered, and moving towards structured representations - but how we model memory systems and memory processes. PMID:21617025

Offline memory reprocessing: involvement of the brain's default network in spontaneous thought processes.

PubMed

Wang, Kun; Yu, Chunshui; Xu, Lijuan; Qin, Wen; Li, Kuncheng; Xu, Lin; Jiang, Tianzi

2009-01-01

Spontaneous thought processes (STPs), also called daydreaming or mind-wandering, occur ubiquitously in daily life. However, the functional significance of STPs remains largely unknown. Using functional magnetic resonance imaging (fMRI), we first identified an STPs-network whose activity was positively correlated with the subjects' tendency of having STPs during a task-free state. The STPs-network was then found to be strongly associated with the default network, which has previously been established as being active during the task-free state. Interestingly, we found that offline reprocessing of previously memorized information further increased the activity of the STPs-network regions, although during a state with less STPs. In addition, we found that the STPs-network kept a dynamic balance between functional integration and functional separation among its component regions to execute offline memory reprocessing in STPs. These findings strengthen a view that offline memory reprocessing and STPs share the brain's default network, and thus implicate that offline memory reprocessing may be a predetermined function of STPs. This supports the perspective that memory can be consolidated and modified during STPs, and thus gives rise to a dynamic behavior dependent on both previous external and internal experiences.

Dynamic working memory performance in individuals with single-domain amnestic mild cognitive impairment.

PubMed

Guild, Emma B; Vasquez, Brandon P; Maione, Andrea M; Mah, Linda; Ween, Jon; Anderson, Nicole D

2014-01-01

Previous studies have observed poorer working memory performance in individuals with amnestic mild cognitive impairment than in healthy older adults. It is unclear, however, whether these difficulties are true only of the multiple-domain clinical subtype in whom poorer executive functioning is common. The current study examined working memory, as measured by the self-ordered pointing task (SOPT) and an n-back task, in healthy older adults and adults with single-domain amnestic mild cognitive impairment (aMCI). Individuals with single-domain aMCI committed more errors and required longer to develop an organizational strategy on the SOPT. The single-domain aMCI group did not differ from healthy older adults on the 1-back or 2-back, but had poorer discrimination on the 3-back task. This is, to our knowledge, the first characterization of dynamic working memory performance in a single-domain aMCI group. These results lend support for the idea that clinical amnestic MCI subtypes may reflect different stages on a continuum of progression to dementia and question whether standardized measures of working memory (span tasks) are sensitive enough to capture subtle changes in performance.

Colloquium: Non-Markovian dynamics in open quantum systems

NASA Astrophysics Data System (ADS)

Breuer, Heinz-Peter; Laine, Elsi-Mari; Piilo, Jyrki; Vacchini, Bassano

2016-04-01

The dynamical behavior of open quantum systems plays a key role in many applications of quantum mechanics, examples ranging from fundamental problems, such as the environment-induced decay of quantum coherence and relaxation in many-body systems, to applications in condensed matter theory, quantum transport, quantum chemistry, and quantum information. In close analogy to a classical Markovian stochastic process, the interaction of an open quantum system with a noisy environment is often modeled phenomenologically by means of a dynamical semigroup with a corresponding time-independent generator in Lindblad form, which describes a memoryless dynamics of the open system typically leading to an irreversible loss of characteristic quantum features. However, in many applications open systems exhibit pronounced memory effects and a revival of genuine quantum properties such as quantum coherence, correlations, and entanglement. Here recent theoretical results on the rich non-Markovian quantum dynamics of open systems are discussed, paying particular attention to the rigorous mathematical definition, to the physical interpretation and classification, as well as to the quantification of quantum memory effects. The general theory is illustrated by a series of physical examples. The analysis reveals that memory effects of the open system dynamics reflect characteristic features of the environment which opens a new perspective for applications, namely, to exploit a small open system as a quantum probe signifying nontrivial features of the environment it is interacting with. This Colloquium further explores the various physical sources of non-Markovian quantum dynamics, such as structured environmental spectral densities, nonlocal correlations between environmental degrees of freedom, and correlations in the initial system-environment state, in addition to developing schemes for their local detection. Recent experiments addressing the detection, quantification, and control of non-Markovian quantum dynamics are also briefly discussed.

Leptin attenuates the detrimental effects of β-amyloid on spatial memory and hippocampal later-phase long term potentiation in rats.

PubMed

Tong, Jia-Qing; Zhang, Jun; Hao, Ming; Yang, Ju; Han, Yu-Fei; Liu, Xiao-Jie; Shi, Hui; Wu, Mei-Na; Liu, Qing-Song; Qi, Jin-Shun

2015-07-01

β-Amyloid (Aβ) is the main component of amyloid plaques developed in the brain of patients with Alzheimer's disease (AD). The increasing burden of Aβ in the cortex and hippocampus is closely correlated with memory loss and cognition deficits in AD. Recently, leptin, a 16kD peptide derived mainly from white adipocyte tissue, has been appreciated for its neuroprotective function, although less is known about the effects of leptin on spatial memory and synaptic plasticity. The present study investigated the neuroprotective effects of leptin against Aβ-induced deficits in spatial memory and in vivo hippocampal late-phase long-term potentiation (L-LTP) in rats. Y maze spontaneous alternation was used to assess short term working memory, and the Morris water maze task was used to assess long term reference memory. Hippocampal field potential recordings were performed to observe changes in L-LTP. We found that chronically intracerebroventricular injection of leptin (1μg) effectively alleviated Aβ1-42 (20μg)-induced spatial memory impairments of Y maze spontaneous alternation and Morris water maze. In addition, chronic administration of leptin also reversed Aβ1-42-induced suppression of in vivo hippocampal L-LTP in rats. Together, these results suggest that chronic leptin treatments reversed Aβ-induced deficits in learning and memory and the maintenance of L-LTP. Copyright © 2015 Elsevier Inc. All rights reserved.

Normal versus anomalous self-diffusion in two-dimensional fluids: memory function approach and generalized asymptotic Einstein relation.

PubMed

Shin, Hyun Kyung; Choi, Bongsik; Talkner, Peter; Lee, Eok Kyun

2014-12-07

Based on the generalized Langevin equation for the momentum of a Brownian particle a generalized asymptotic Einstein relation is derived. It agrees with the well-known Einstein relation in the case of normal diffusion but continues to hold for sub- and super-diffusive spreading of the Brownian particle's mean square displacement. The generalized asymptotic Einstein relation is used to analyze data obtained from molecular dynamics simulations of a two-dimensional soft disk fluid. We mainly concentrated on medium densities for which we found super-diffusive behavior of a tagged fluid particle. At higher densities a range of normal diffusion can be identified. The motion presumably changes to sub-diffusion for even higher densities.

Normal versus anomalous self-diffusion in two-dimensional fluids: Memory function approach and generalized asymptotic Einstein relation

NASA Astrophysics Data System (ADS)

Shin, Hyun Kyung; Choi, Bongsik; Talkner, Peter; Lee, Eok Kyun

2014-12-01

Based on the generalized Langevin equation for the momentum of a Brownian particle a generalized asymptotic Einstein relation is derived. It agrees with the well-known Einstein relation in the case of normal diffusion but continues to hold for sub- and super-diffusive spreading of the Brownian particle's mean square displacement. The generalized asymptotic Einstein relation is used to analyze data obtained from molecular dynamics simulations of a two-dimensional soft disk fluid. We mainly concentrated on medium densities for which we found super-diffusive behavior of a tagged fluid particle. At higher densities a range of normal diffusion can be identified. The motion presumably changes to sub-diffusion for even higher densities.

Dynamic testing in schizophrenia: does training change the construct validity of a test?

PubMed

Wiedl, Karl H; Schöttke, Henning; Green, Michael F; Nuechterlein, Keith H

2004-01-01

Dynamic testing typically involves specific interventions for a test to assess the extent to which test performance can be modified, beyond level of baseline (static) performance. This study used a dynamic version of the Wisconsin Card Sorting Test (WCST) that is based on cognitive remediation techniques within a test-training-test procedure. From results of previous studies with schizophrenia patients, we concluded that the dynamic and static versions of the WCST should have different construct validity. This hypothesis was tested by examining the patterns of correlations with measures of executive functioning, secondary verbal memory, and verbal intelligence. Results demonstrated a specific construct validity of WCST dynamic (i.e., posttest) scores as an index of problem solving (Tower of Hanoi) and secondary verbal memory and learning (Auditory Verbal Learning Test), whereas the impact of general verbal capacity and selective attention (Verbal IQ, Stroop Test) was reduced. It is concluded that the construct validity of the test changes with dynamic administration and that this difference helps to explain why the dynamic version of the WCST predicts functional outcome better than the static version.