Support for Programming Models in Network-on-Chip-based Many-core Systems

DEFF Research Database (Denmark)

Rasmussen, Morten Sleth

This thesis addresses aspects of support for programming models in Network-on- Chip-based many-core architectures. The main focus is to consider architectural support for a plethora of programming models in a single system. The thesis has three main parts. The first part considers parallelization...... models to be supported by a single architecture. The architecture features a specialized network interface processor which allows extensive configurability of the memory system. Based on this architecture, a detailed implementation of the cache coherent shared memory programming model is presented...

Assessing Programming Costs of Explicit Memory Localization on a Large Scale Shared Memory Multiprocessor

Directory of Open Access Journals (Sweden)

Silvio Picano

1992-01-01

Full Text Available We present detailed experimental work involving a commercially available large scale shared memory multiple instruction stream-multiple data stream (MIMD parallel computer having a software controlled cache coherence mechanism. To make effective use of such an architecture, the programmer is responsible for designing the program's structure to match the underlying multiprocessors capabilities. We describe the techniques used to exploit our multiprocessor (the BBN TC2000 on a network simulation program, showing the resulting performance gains and the associated programming costs. We show that an efficient implementation relies heavily on the user's ability to explicitly manage the memory system.

PDDP, A Data Parallel Programming Model

Directory of Open Access Journals (Sweden)

Karen H. Warren

1996-01-01

Full Text Available PDDP, the parallel data distribution preprocessor, is a data parallel programming model for distributed memory parallel computers. PDDP implements high-performance Fortran-compatible data distribution directives and parallelism expressed by the use of Fortran 90 array syntax, the FORALL statement, and the WHERE construct. Distributed data objects belong to a global name space; other data objects are treated as local and replicated on each processor. PDDP allows the user to program in a shared memory style and generates codes that are portable to a variety of parallel machines. For interprocessor communication, PDDP uses the fastest communication primitives on each platform.

Programming model for distributed intelligent systems

Science.gov (United States)

Sztipanovits, J.; Biegl, C.; Karsai, G.; Bogunovic, N.; Purves, B.; Williams, R.; Christiansen, T.

1988-01-01

A programming model and architecture which was developed for the design and implementation of complex, heterogeneous measurement and control systems is described. The Multigraph Architecture integrates artificial intelligence techniques with conventional software technologies, offers a unified framework for distributed and shared memory based parallel computational models and supports multiple programming paradigms. The system can be implemented on different hardware architectures and can be adapted to strongly different applications.

Modeling reconsolidation in kernel associative memory.

Directory of Open Access Journals (Sweden)

Dimitri Nowicki

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

NVL-C: Static Analysis Techniques for Efficient, Correct Programming of Non-Volatile Main Memory Systems

Energy Technology Data Exchange (ETDEWEB)

Lee, Seyong [ORNL; Vetter, Jeffrey S [ORNL

2016-01-01

Computer architecture experts expect that non-volatile memory (NVM) hierarchies will play a more significant role in future systems including mobile, enterprise, and HPC architectures. With this expectation in mind, we present NVL-C: a novel programming system that facilitates the efficient and correct programming of NVM main memory systems. The NVL-C programming abstraction extends C with a small set of intuitive language features that target NVM main memory, and can be combined directly with traditional C memory model features for DRAM. We have designed these new features to enable compiler analyses and run-time checks that can improve performance and guard against a number of subtle programming errors, which, when left uncorrected, can corrupt NVM-stored data. Moreover, to enable recovery of data across application or system failures, these NVL-C features include a flexible directive for specifying NVM transactions. So that our implementation might be extended to other compiler front ends and languages, the majority of our compiler analyses are implemented in an extended version of LLVM's intermediate representation (LLVM IR). We evaluate NVL-C on a number of applications to show its flexibility, performance, and correctness.

Flash Memory Reliability: Read, Program, and Erase Latency Versus Endurance Cycling

Science.gov (United States)

Heidecker, Jason

2010-01-01

This report documents the efforts and results of the fiscal year (FY) 2010 NASA Electronic Parts and Packaging Program (NEPP) task for nonvolatile memory (NVM) reliability. This year's focus was to measure latency (read, program, and erase) of NAND Flash memories and determine how these parameters drift with erase/program/read endurance cycling.

Memory for radio advertisements: the effect of program and typicality.

Science.gov (United States)

Martín-Luengo, Beatriz; Luna, Karlos; Migueles, Malen

2013-01-01

We examined the influence of the type of radio program on the memory for radio advertisements. We also investigated the role in memory of the typicality (high or low) of the elements of the products advertised. Participants listened to three types of programs (interesting, boring, enjoyable) with two advertisements embedded in each. After completing a filler task, the participants performed a true/false recognition test. Hits and false alarm rates were higher for the interesting and enjoyable programs than for the boring one. There were also more hits and false alarms for the high-typicality elements. The response criterion for the advertisements embedded in the boring program was stricter than for the advertisements in other types of programs. We conclude that the type of program in which an advertisement is inserted and the nature of the elements of the advertisement affect both the number of hits and false alarms and the response criterion, but not the accuracy of the memory.

Enabling Highly-Scalable Remote Memory Access Programming with MPI-3 One Sided

Directory of Open Access Journals (Sweden)

Robert Gerstenberger

2014-01-01

Full Text Available Modern interconnects offer remote direct memory access (RDMA features. Yet, most applications rely on explicit message passing for communications albeit their unwanted overheads. The MPI-3.0 standard defines a programming interface for exploiting RDMA networks directly, however, it's scalability and practicability has to be demonstrated in practice. In this work, we develop scalable bufferless protocols that implement the MPI-3.0 specification. Our protocols support scaling to millions of cores with negligible memory consumption while providing highest performance and minimal overheads. To arm programmers, we provide a spectrum of performance models for all critical functions and demonstrate the usability of our library and models with several application studies with up to half a million processes. We show that our design is comparable to, or better than UPC and Fortran Coarrays in terms of latency, bandwidth and message rate. We also demonstrate application performance improvements with comparable programming complexity.

Translation techniques for distributed-shared memory programming models

Energy Technology Data Exchange (ETDEWEB)

Fuller, Douglas James [Iowa State Univ., Ames, IA (United States)

2005-01-01

The high performance computing community has experienced an explosive improvement in distributed-shared memory hardware. Driven by increasing real-world problem complexity, this explosion has ushered in vast numbers of new systems. Each new system presents new challenges to programmers and application developers. Part of the challenge is adapting to new architectures with new performance characteristics. Different vendors release systems with widely varying architectures that perform differently in different situations. Furthermore, since vendors need only provide a single performance number (total MFLOPS, typically for a single benchmark), they only have strong incentive initially to optimize the API of their choice. Consequently, only a fraction of the available APIs are well optimized on most systems. This causes issues porting and writing maintainable software, let alone issues for programmers burdened with mastering each new API as it is released. Also, programmers wishing to use a certain machine must choose their API based on the underlying hardware instead of the application. This thesis argues that a flexible, extensible translator for distributed-shared memory APIs can help address some of these issues. For example, a translator might take as input code in one API and output an equivalent program in another. Such a translator could provide instant porting for applications to new systems that do not support the application's library or language natively. While open-source APIs are abundant, they do not perform optimally everywhere. A translator would also allow performance testing using a single base code translated to a number of different APIs. Most significantly, this type of translator frees programmers to select the most appropriate API for a given application based on the application (and developer) itself instead of the underlying hardware.

Thermodynamic Model of Spatial Memory

Science.gov (United States)

Kaufman, Miron; Allen, P.

1998-03-01

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

Summary Report for ASC L2 Milestone #4782: Assess Newly Emerging Programming and Memory Models for Advanced Architectures on Integrated Codes

Energy Technology Data Exchange (ETDEWEB)

Neely, J. R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hornung, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Black, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Robinson, P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2014-09-29

This document serves as a detailed companion to the powerpoint slides presented as part of the ASC L2 milestone review for Integrated Codes milestone #4782 titled “Assess Newly Emerging Programming and Memory Models for Advanced Architectures on Integrated Codes”, due on 9/30/2014, and presented for formal program review on 9/12/2014. The program review committee is represented by Mike Zika (A Program Project Lead for Kull), Brian Pudliner (B Program Project Lead for Ares), Scott Futral (DEG Group Lead in LC), and Mike Glass (Sierra Project Lead at Sandia). This document, along with the presentation materials, and a letter of completion signed by the review committee will act as proof of completion for this milestone.

Comparison of systems for memory allocation in the C programming language

OpenAIRE

Zavrtanik, Matej

2016-01-01

The bachelor thesis describes memory allocation. Work begins with description of mechanism, system calls and data structures used in memory allocators. Goals of memory allocation ares listed along with problems which must be avoided. Afterwards construction and allocating of popular memory allocators is described. Work ends with comparison of memory allocators based on time of execution of programs and memory usage, on which conclusion is based.

A Programming Model for Massive Data Parallelism with Data Dependencies

International Nuclear Information System (INIS)

Cui, Xiaohui; Mueller, Frank; Potok, Thomas E.; Zhang, Yongpeng

2009-01-01

Accelerating processors can often be more cost and energy effective for a wide range of data-parallel computing problems than general-purpose processors. For graphics processor units (GPUs), this is particularly the case when program development is aided by environments such as NVIDIA s Compute Unified Device Architecture (CUDA), which dramatically reduces the gap between domain-specific architectures and general purpose programming. Nonetheless, general-purpose GPU (GPGPU) programming remains subject to several restrictions. Most significantly, the separation of host (CPU) and accelerator (GPU) address spaces requires explicit management of GPU memory resources, especially for massive data parallelism that well exceeds the memory capacity of GPUs. One solution to this problem is to transfer data between the GPU and host memories frequently. In this work, we investigate another approach. We run massively data-parallel applications on GPU clusters. We further propose a programming model for massive data parallelism with data dependencies for this scenario. Experience from micro benchmarks and real-world applications shows that our model provides not only ease of programming but also significant performance gains

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

Science.gov (United States)

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

2018-06-01

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

A Temporal Ratio Model of Memory

Science.gov (United States)

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

2007-01-01

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

Waking Up Buried Memories of Old TV Programs.

Science.gov (United States)

Larzabal, Christelle; Bacon-Macé, Nadège; Muratot, Sophie; Thorpe, Simon J

2017-01-01

Although it has been demonstrated that visual and auditory stimuli can be recalled decades after the initial exposure, previous studies have generally not ruled out the possibility that the material may have been seen or heard during the intervening period. Evidence shows that reactivations of a long-term memory trace play a role in its update and maintenance. In the case of remote or very long-term memories, it is most likely that these reactivations are triggered by the actual re-exposure to the stimulus. In this study we decided to explore whether it is possible to recall stimuli that could not have been re-experienced in the intervening period. We tested the ability of French participants ( N = 34, 31 female) to recall 50 TV programs broadcast on average for the last time 44 years ago (from the 60's and early 70's). Potential recall was elicited by the presentation of short audiovisual excerpts of these TV programs. The absence of potential re-exposure to the material was strictly controlled by selecting TV programs that have never been rebroadcast and were not available in the public domain. Our results show that six TV programs were particularly well identified on average across the 34 participants with a median percentage of 71.7% ( SD = 13.6, range: 48.5-87.9%). We also obtained 50 single case reports with associated information about the viewing of 23 TV programs including the 6 previous ones. More strikingly, for two cases, retrieval of the title was made spontaneously without the need of a four-proposition choice. These results suggest that re-exposures to the stimuli are not necessary to maintain a memory for a lifetime. These new findings raise fundamental questions about the underlying mechanisms used by the brain to store these very old sensory memories.

Attempting to model dissociations of memory.

Science.gov (United States)

Reber, Paul J.

2002-05-01

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

Modeling Active Aging and Explicit Memory: An Empirical Study.

Science.gov (United States)

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

2015-08-01

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

Honoring our donors: a survey of memorial ceremonies in United States anatomy programs.

Science.gov (United States)

Jones, Trahern W; Lachman, Nirusha; Pawlina, Wojciech

2014-01-01

Many anatomy programs that incorporate dissection of donated human bodies hold memorial ceremonies of gratitude towards body donors. The content of these ceremonies may include learners' reflections on mortality, respect, altruism, and personal growth told through various humanities modalities. The task of planning is usually student- and faculty-led with participation from other health care students. Objective information on current memorial ceremonies for body donors in anatomy programs in the United States appears to be lacking. The number of programs in the United States that currently plan these memorial ceremonies and information on trends in programs undertaking such ceremonies remain unknown. Gross anatomy program directors throughout the United States were contacted and asked to respond to a voluntary questionnaire on memorial ceremonies held at their institution. The results (response rate 68.2%) indicated that a majority of human anatomy programs (95.5%) hold memorial ceremonies. These ceremonies are, for the most part, student-driven and nondenominational or secular in nature. Participants heavily rely upon speech, music, poetry, and written essays, with a small inclusion of other humanities modalities, such as dance or visual art, to explore a variety of themes during these ceremonies. © 2013 American Association of Anatomists.

Modeling Implicit and Explicit Memory.

NARCIS (Netherlands)

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

2005-01-01

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

The Generalized Quantum Episodic Memory Model.

Science.gov (United States)

Trueblood, Jennifer S; Hemmer, Pernille

2017-11-01

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

ANDRA's Long-Term Memory-Preservation Program

International Nuclear Information System (INIS)

Charton, Patrick; Dumont, Jean-Noel

2012-01-01

Maintaining the memory of repositories over the long term is required not only to ensure safety and reversibility (legal requirements), but also in response to social expectations. Since 2010, ANDRA has been implementing a long-term memory preservation program to reinforce and diversify its current arrangements in that field, as well as explore opportunities to extend memory keeping over thousands of years. As a reference solution, ANDRA uses the arrangement and practices in place at its surface disposal facilities. Although at ANDRA they are well aware of the fact that the operational time of a LILW disposal corresponds more or less with the implementation time of a geological disposal, useful insights can nevertheless be gained from the experience with short-lived LILW. The reference solution implemented at the Centre de la Manche and de l'Aube includes five memorization devises, differentiating between passive and active memory keeping. There are three passive memories, consisting of copies with various degrees of information on permanent paper, and two active memories, consisting of oral transmissions under the form of events and meetings with various (local) stakeholders. For HLW, ANDRA calculates a timescale of 200 years for the total implementation of a geological disposal, and a minimum of memory of 500 years afterwards, which necessitates conservation of RK and M for 700 years in total. Permanent paper lasts 600-1000 years. ANDRA also developed a sapphire disk which can contain large amounts of records and endure 1 million years. In fact this device created more questions; the purpose is exactly to question 'solutions' that are solely based on engineering. It for instance evokes questions such as 'Which languages should we use, which graphical material should we add, how can we avoid vandalism, what meaning will future generations give to the traces we leave?' All these issues and more are being investigated under ANDRA's long term memory preservation

Modeling the Cray memory scheduler

Energy Technology Data Exchange (ETDEWEB)

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

1992-04-01

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

A dual-trace model for visual sensory memory.

Science.gov (United States)

Cappiello, Marcus; Zhang, Weiwei

2016-11-01

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

Chemically programmed ink-jet printed resistive WORM memory array and readout circuit

International Nuclear Information System (INIS)

Andersson, H; Manuilskiy, A; Sidén, J; Gao, J; Kunninmel, G V; Nilsson, H-E; Hummelgård, M

2014-01-01

In this paper an ink-jet printed write once read many (WORM) resistive memory fabricated on paper substrate is presented. The memory elements are programmed for different resistance states by printing triethylene glycol monoethyl ether on the substrate before the actual memory element is printed using silver nano particle ink. The resistance is thus able to be set to a broad range of values without changing the geometry of the elements. A memory card consisting of 16 elements is manufactured for which the elements are each programmed to one of four defined logic levels, providing a total of 4294 967 296 unique possible combinations. Using a readout circuit, originally developed for resistive sensors to avoid crosstalk between elements, a memory card reader is manufactured that is able to read the values of the memory card and transfer the data to a PC. Such printed memory cards can be used in various applications. (paper)

Cache memory modelling method and system

OpenAIRE

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

2011-01-01

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

Virtual reality-based prospective memory training program for people with acquired brain injury.

Science.gov (United States)

Yip, Ben C B; Man, David W K

2013-01-01

Acquired brain injuries (ABI) may display cognitive impairments and lead to long-term disabilities including prospective memory (PM) failure. Prospective memory serves to remember to execute an intended action in the future. PM problems would be a challenge to an ABI patient's successful community reintegration. While retrospective memory (RM) has been extensively studied, treatment programs for prospective memory are rarely reported. The development of a treatment program for PM, which is considered timely, can be cost-effective and appropriate to the patient's environment. A 12-session virtual reality (VR)-based cognitive rehabilitation program was developed using everyday PM activities as training content. 37 subjects were recruited to participate in a pretest-posttest control experimental study to evaluate its treatment effectiveness. Results suggest that significantly better changes were seen in both VR-based and real-life PM outcome measures, related cognitive attributes such as frontal lobe functions and semantic fluency. VR-based training may be well accepted by ABI patients as encouraging improvement has been shown. Large-scale studies of a virtual reality-based prospective memory (VRPM) training program are indicated.

Main Memory

NARCIS (Netherlands)

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

2008-01-01

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

VHDL-based programming environment for Floating-Gate analog memory cell

Directory of Open Access Journals (Sweden)

Carlos Alberto dos Reis Filho

2005-02-01

Full Text Available An implementation in CMOS technology of a Floating-Gate Analog Memory Cell and Programming Environment is presented. A digital closed-loop control compares a reference value set by user and the memory output and after cycling, the memory output is updated and the new value stored. The circuit can be used as analog trimming for VLSI applications where mechanical trimming associated with postprocessing chip is prohibitive due to high costs.

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

Science.gov (United States)

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

2013-12-01

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

A program of positive intervention in the elderly: memories, gratitude and forgiveness.

Science.gov (United States)

Ramírez, Encarnación; Ortega, Ana Raquel; Chamorro, Alberto; Colmenero, José María

2014-05-01

The main goal of this study has been to increase the quality of life in people of over 60 years through a positive psychology intervention. We employed a program which consists of training based on autobiographical memory, forgiveness and gratitude. The sample consisted of 46 participants aged 60-93 years. State and trait anxiety, depression, general memory, specific memories, life satisfaction and subjective happiness were measured. The results revealed that participants who followed the program (experimental group) showed a significant decrease in state anxiety and depression as well as an increase in specific memories, life satisfaction and subjective happiness, compared with the placebo group. Our program offers promising results and provides new evidence for the effectiveness of positive interventions in the field of psychogerontology, helping increase subjective well-being and quality of life in older adults by focusing interventions on the enhancement of personal and social resources for being happy.

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

Science.gov (United States)

Taha, Badie A.; Standley, Hilda M.

1989-01-01

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

A simplified computational memory model from information processing.

Science.gov (United States)

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

2016-11-23

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

Modeling soil moisture memory in savanna ecosystems

Science.gov (United States)

Gou, S.; Miller, G. R.

2011-12-01

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

Reagent-Free Programming of Shape-Memory Behavior in Gelatin by Electron Beams: Experiments and Modeling

Science.gov (United States)

Riedel, Stefanie; Mayr, Stefan G.

2018-02-01

Recent years have seen a paradigm shift in biomaterials toward stimuli-responsive switchable systems that actively interact with their environment. This work demonstrates how to turn the ubiquitous off-the-shelf material gelatin into such a smart biomaterial. This is achieved by realizing the shape-memory effect, viz., a temperature-induced transition from a secondary into a primary shape that has been programmed in the first place merely by exposure to energetic electrons without addition of potentially hazardous cross-linkers. While this scenario is experimentally quantified for exemplary actuators, a theoretical framework capable of unraveling the molecular foundations and predicting experiments is also presented. It particularly employs molecular dynamics modeling based on force fields that are also derived within this work. Implementing this functionality into a highly accepted material, these findings open an avenue for large-scale application in a broad range of areas.

An interference model of visual working memory.

Science.gov (United States)

Oberauer, Klaus; Lin, Hsuan-Yu

2017-01-01

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

A simplified computational memory model from information processing

Science.gov (United States)

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

2016-01-01

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

What we remember affects how we see: spatial working memory steers saccade programming.

Science.gov (United States)

Wong, Jason H; Peterson, Matthew S

2013-02-01

Relationships between visual attention, saccade programming, and visual working memory have been hypothesized for over a decade. Awh, Jonides, and Reuter-Lorenz (Journal of Experimental Psychology: Human Perception and Performance 24(3):780-90, 1998) and Awh et al. (Psychological Science 10(5):433-437, 1999) proposed that rehearsing a location in memory also leads to enhanced attentional processing at that location. In regard to eye movements, Belopolsky and Theeuwes (Attention, Perception & Psychophysics 71(3):620-631, 2009) found that holding a location in working memory affects saccade programming, albeit negatively. In three experiments, we attempted to replicate the findings of Belopolsky and Theeuwes (Attention, Perception & Psychophysics 71(3):620-631, 2009) and determine whether the spatial memory effect can occur in other saccade-cuing paradigms, including endogenous central arrow cues and exogenous irrelevant singletons. In the first experiment, our results were the opposite of those in Belopolsky and Theeuwes (Attention, Perception & Psychophysics 71(3):620-631, 2009), in that we found facilitation (shorter saccade latencies) instead of inhibition when the saccade target matched the region in spatial working memory. In Experiment 2, we sought to determine whether the spatial working memory effect would generalize to other endogenous cuing tasks, such as a central arrow that pointed to one of six possible peripheral locations. As in Experiment 1, we found that saccade programming was facilitated when the cued location coincided with the saccade target. In Experiment 3, we explored how spatial memory interacts with other types of cues, such as a peripheral color singleton target or irrelevant onset. In both cases, the eyes were more likely to go to either singleton when it coincided with the location held in spatial working memory. On the basis of these results, we conclude that spatial working memory and saccade programming are likely to share common

Elements of episodic-like memory in animal models.

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Crystal, Jonathon D

2009-03-01

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

An Investigation of Unified Memory Access Performance in CUDA

Science.gov (United States)

Landaverde, Raphael; Zhang, Tiansheng; Coskun, Ayse K.; Herbordt, Martin

2015-01-01

Managing memory between the CPU and GPU is a major challenge in GPU computing. A programming model, Unified Memory Access (UMA), has been recently introduced by Nvidia to simplify the complexities of memory management while claiming good overall performance. In this paper, we investigate this programming model and evaluate its performance and programming model simplifications based on our experimental results. We find that beyond on-demand data transfers to the CPU, the GPU is also able to request subsets of data it requires on demand. This feature allows UMA to outperform full data transfer methods for certain parallel applications and small data sizes. We also find, however, that for the majority of applications and memory access patterns, the performance overheads associated with UMA are significant, while the simplifications to the programming model restrict flexibility for adding future optimizations. PMID:26594668

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

Science.gov (United States)

Schweppe, Judith; Rummer, Ralf

2014-01-01

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

Sensory Dissonance Using Memory Model

DEFF Research Database (Denmark)

Jensen, Karl Kristoffer

2015-01-01

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

A Bayesian Model of the Memory Colour Effect.

Science.gov (United States)

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

2018-01-01

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

Main Memory

OpenAIRE

Boncz, Peter; Liu, Lei; Özsu, M.

2008-01-01

htmlabstractPrimary storage, presently known as main memory, is the largest memory directly accessible to the CPU in the prevalent Von Neumann model and stores both data and instructions (program code). The CPU continuously reads instructions stored there and executes them. It is also called Random Access Memory (RAM), to indicate that load/store instructions can access data at any location at the same cost, is usually implemented using DRAM chips, which are connected to the CPU and other per...

Thermomechanical macroscopic model of shape memory alloys

International Nuclear Information System (INIS)

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

2003-01-01

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

Hypergraph-Based Recognition Memory Model for Lifelong Experience

Science.gov (United States)

2014-01-01

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

Memory Management for Safety-Critical Java

DEFF Research Database (Denmark)

Schoeberl, Martin

2011-01-01

Safety-Critical Java (SCJ) is based on the Real-Time Specification for Java. To simplify the certification of Java programs, SCJ supports only a restricted scoped memory model. Individual threads share only immortal memory and the newly introduced mission memory. All other scoped memories...... implementation is evaluated on an embedded Java processor....

Cognitive Training Program to Improve Working Memory in Older Adults with MCI.

Science.gov (United States)

Hyer, Lee; Scott, Ciera; Atkinson, Mary Michael; Mullen, Christine M; Lee, Anna; Johnson, Aaron; Mckenzie, Laura C

2016-01-01

Deficits in working memory (WM) are associated with age-related decline. We report findings from a clinical trial that examined the effectiveness of Cogmed, a computerized program that trains WM. We compare this program to a Sham condition in older adults with Mild Cognitive Impairment (MCI). Older adults (N = 68) living in the community were assessed. Participants reported memory impairment and met criteria for MCI, either by poor delayed memory or poor performance in other cognitive areas. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS, Delayed Memory Index) and the Clinical Dementia Rating scale (CDR) were utilized. All presented with normal Mini Mental State Exams (MMSE) and activities of daily living (ADLs). Participants were randomized to Cogmed or a Sham computer program. Twenty-five sessions were completed over five to seven weeks. Pre, post, and follow-up measures included a battery of cognitive measures (three WM tests), a subjective memory scale, and a functional measure. Both intervention groups improved over time. Cogmed significantly outperformed Sham on Span Board and exceeded in subjective memory reports at follow-up as assessed by the Cognitive Failures Questionnaire (CFQ). The Cogmed group demonstrated better performance on the Functional Activities Questionnaire (FAQ), a measure of adjustment and far transfer, at follow-up. Both groups, especially Cogmed, enjoyed the intervention. Results suggest that WM was enhanced in both groups of older adults with MCI. Cogmed was better on one core WM measure and had higher ratings of satisfaction. The Sham condition declined on adjustment.

Understanding Notional Machines through Traditional Teaching with Conceptual Contraposition and Program Memory Tracing

Directory of Open Access Journals (Sweden)

Jeisson Hidalgo-Céspedes

2016-08-01

Full Text Available A correct understanding about how computers run code is mandatory in order to effectively learn to program. Lectures have historically been used in programming courses to teach how computers execute code, and students are assessed through traditional evaluation methods, such as exams. Constructivism learning theory objects to students’ passiveness during lessons, and traditional quantitative methods for evaluating a complex cognitive process such as understanding. Constructivism proposes complimentary techniques, such as conceptual contraposition and colloquies. We enriched lectures of a “Programming II” (CS2 course combining conceptual contraposition with program memory tracing, then we evaluated students’ understanding of programming concepts through colloquies. Results revealed that these techniques applied to the lecture are insufficient to help students develop satisfactory mental models of the C++ notional machine, and colloquies behaved as the most comprehensive traditional evaluations conducted in the course.

Weak Memory Models: Balancing Definitional Simplicity and Implementation Flexibility

OpenAIRE

Zhang, Sizhuo; Vijayaraghavan, Muralidaran; Arvind

2017-01-01

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

Dynamic intersectoral models with power-law memory

Science.gov (United States)

Tarasova, Valentina V.; Tarasov, Vasily E.

2018-01-01

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

The AIP Model of EMDR Therapy and Pathogenic Memories

Directory of Open Access Journals (Sweden)

Michael Hase

2017-09-01

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

Episodic and Semantic Memories of a Residential Environmental Education Program

Science.gov (United States)

Knapp, Doug; Benton, Gregory M.

2006-01-01

This study used a phenomenological approach to investigate the recollections of participants of an environmental education (EE) residential program. Ten students who participated in a residential EE program in the fall of 2001 were interviewed in the fall of 2002. Three major themes relating to the participants' long-term memory of the residential…

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

Science.gov (United States)

Cunha, Rodrigo A; Agostinho, Paula M

2010-01-01

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

Automatically Proving Termination and Memory Safety for Programs with Pointer Arithmetic

DEFF Research Database (Denmark)

Ströder, Thomas; Giesl, Jürgen; Brockschmidt, Marc

2017-01-01

While automated verification of imperative programs has been studied intensively, proving termination of programs with explicit pointer arithmetic fully automatically was still an open problem. To close this gap, we introduce a novel abstract domain that can track allocated memory in detail. We use...

A Memory-Based Model of Hick's Law

Science.gov (United States)

Schneider, Darryl W.; Anderson, John R.

2011-01-01

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

A bio-inspired memory model for structural health monitoring

International Nuclear Information System (INIS)

Zheng, Wei; Zhu, Yong

2009-01-01

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

A bio-inspired memory model for structural health monitoring

Science.gov (United States)

Zheng, Wei; Zhu, Yong

2009-04-01

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

Adolescent development, hypothalamic-pituitary-adrenal function, and programming of adult learning and memory.

Science.gov (United States)

McCormick, Cheryl M; Mathews, Iva Z

2010-06-30

Chronic exposure to stress is known to affect learning and memory in adults through the release of glucocorticoid hormones by the hypothalamic-pituitary-adrenal (HPA) axis. In adults, glucocorticoids alter synaptic structure and function in brain regions that express high levels of glucocorticoid receptors and that mediate goal-directed behaviour and learning and memory. In contrast to relatively transient effects of stress on cognitive function in adulthood, exposure to high levels of glucocorticoids in early life can produce enduring changes through substantial remodeling of the developing nervous system. Adolescence is another time of significant brain development and maturation of the HPA axis, thereby providing another opportunity for glucocorticoids to exert programming effects on neurocircuitry involved in learning and memory. These topics are reviewed, as is the emerging research evidence in rodent models highlighting that adolescence may be a period of increased vulnerability compared to adulthood in which exposure to high levels of glucocorticoids results in enduring changes in adult cognitive function. Copyright 2009 Elsevier Inc. All rights reserved.

A low-voltage flash memory cell utilizing the gate-injection program/erase method with a recessed channel structure

International Nuclear Information System (INIS)

Wu Dake; Huang Ru; Wang Pengfei; Tang Poren; Wang Yangyuan

2008-01-01

In this paper, a low-voltage recessed channel SONOS flash memory using the gate-injection program/erase method is proposed and investigated for NAND application. It is shown that the proposed flash memory can achieve 8 V lower programming voltage compared with planar flash memory, due to the effective capacitance coupling and the electric-field enhancement by combining the recessed channel structure and the gate-injection program/erase method. In addition, more than 30% larger threshold voltage window and improved short channel effects can be obtained in the proposed flash memory

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

Energy Technology Data Exchange (ETDEWEB)

Campbell, Philip Montgomery; Wix, Steven D.

2017-04-01

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

Likelihood ratio sequential sampling models of recognition memory.

Science.gov (United States)

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

2017-02-01

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

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

Science.gov (United States)

Shanks, David R; Berry, Christopher J

2012-01-01

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

GIGMF - A statistical model program

International Nuclear Information System (INIS)

Vladuca, G.; Deberth, C.

1978-01-01

The program GIGMF computes the differential and integrated statistical model cross sections for the reactions proceeding through a compound nuclear stage. The computational method is based on the Hauser-Feshbach-Wolfenstein theory, modified to include the modern version of Tepel et al. Although the program was written for a PDP-15 computer, with 16K high speed memory, many reaction channels can be taken into account with the following restrictions: the pro ectile spin must be less than 2, the maximum spin momenta of the compound nucleus can not be greater than 10. These restrictions are due solely to the storage allotments and may be easily relaxed. The energy of the impinging particle, the target and projectile masses, the spin and paritjes of the projectile, target, emergent and residual nuclei the maximum orbital momentum and transmission coefficients for each reaction channel are the input parameters of the program. (author)

A model for visual memory encoding.

Directory of Open Access Journals (Sweden)

Rodolphe Nenert

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

A model for visual memory encoding.

Science.gov (United States)

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

2014-01-01

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

Feasibility study of current pulse induced 2-bit/4-state multilevel programming in phase-change memory

Science.gov (United States)

Liu, Yan; Fan, Xi; Chen, Houpeng; Wang, Yueqing; Liu, Bo; Song, Zhitang; Feng, Songlin

2017-08-01

In this brief, multilevel data storage for phase-change memory (PCM) has attracted more attention in the memory market to implement high capacity memory system and reduce cost-per-bit. In this work, we present a universal programing method of SET stair-case current pulse in PCM cells, which can exploit the optimum programing scheme to achieve 2-bit/ 4state resistance-level with equal logarithm interval. SET stair-case waveform can be optimized by TCAD real time simulation to realize multilevel data storage efficiently in an arbitrary phase change material. Experimental results from 1 k-bit PCM test-chip have validated the proposed multilevel programing scheme. This multilevel programming scheme has improved the information storage density, robustness of resistance-level, energy efficient and avoiding process complexity.

Weak Memory Models with Matching Axiomatic and Operational Definitions

OpenAIRE

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

2017-01-01

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

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

Science.gov (United States)

Zhao, Yue; Kang, Jinsheng; Wright, David

2010-01-01

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

Attention-based Memory Selection Recurrent Network for Language Modeling

OpenAIRE

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

2016-01-01

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

Programs for Testing Processor-in-Memory Computing Systems

Science.gov (United States)

Katz, Daniel S.

2006-01-01

The Multithreaded Microbenchmarks for Processor-In-Memory (PIM) Compilers, Simulators, and Hardware are computer programs arranged in a series for use in testing the performances of PIM computing systems, including compilers, simulators, and hardware. The programs at the beginning of the series test basic functionality; the programs at subsequent positions in the series test increasingly complex functionality. The programs are intended to be used while designing a PIM system, and can be used to verify that compilers, simulators, and hardware work correctly. The programs can also be used to enable designers of these system components to examine tradeoffs in implementation. Finally, these programs can be run on non-PIM hardware (either single-threaded or multithreaded) using the POSIX pthreads standard to verify that the benchmarks themselves operate correctly. [POSIX (Portable Operating System Interface for UNIX) is a set of standards that define how programs and operating systems interact with each other. pthreads is a library of pre-emptive thread routines that comply with one of the POSIX standards.

Effects of a Memory and Visual-Motor Integration Program for Older Adults Based on Self-Efficacy Theory.

Science.gov (United States)

Kim, Eun Hwi; Suh, Soon Rim

2017-06-01

This study was conducted to verify the effects of a memory and visual-motor integration program for older adults based on self-efficacy theory. A non-equivalent control group pretest-posttest design was implemented in this quasi-experimental study. The participants were 62 older adults from senior centers and older adult welfare facilities in D and G city (Experimental group=30, Control group=32). The experimental group took part in a 12-session memory and visual-motor integration program over 6 weeks. Data regarding memory self-efficacy, memory, visual-motor integration, and depression were collected from July to October of 2014 and analyzed with independent t-test and Mann-Whitney U test using PASW Statistics (SPSS) 18.0 to determine the effects of the interventions. Memory self-efficacy (t=2.20, p=.031), memory (Z=-2.92, p=.004), and visual-motor integration (Z=-2.49, p=.013) increased significantly in the experimental group as compared to the control group. However, depression (Z=-0.90, p=.367) did not decrease significantly. This program is effective for increasing memory, visual-motor integration, and memory self-efficacy in older adults. Therefore, it can be used to improve cognition and prevent dementia in older adults. © 2017 Korean Society of Nursing Science

Comparing soil moisture memory in satellite observations and models

Science.gov (United States)

Stacke, Tobias; Hagemann, Stefan; Loew, Alexander

2013-04-01

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

Logistic map with memory from economic model

International Nuclear Information System (INIS)

Tarasova, Valentina V.; Tarasov, Vasily E.

2017-01-01

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

Generalized memory associativity in a network model for the neuroses

Science.gov (United States)

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

2009-03-01

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

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

Science.gov (United States)

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

2017-11-01

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

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

Science.gov (United States)

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

2015-03-02

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

Guidance system operations plan for manned CSM earth orbital and lunar missions using program COLOSSUS 3. Section 7: Erasable memory programs

Science.gov (United States)

Hamilton, M. H.

1972-01-01

Erasable-memory programs designed for guidance computers used in command and lunar modules are presented. The purpose, functional description, assumptions, restrictions, and imitations are given for each program.

Silver Memories: implementation and evaluation of a unique radio program for older people.

Science.gov (United States)

Travers, Catherine; Bartlett, Helen P

2011-03-01

A unique radio program, Silver Memories, specifically designed to address social isolation and loneliness in older people by broadcasting music (primarily), serials and other programs relevant to the period when older people grew up--the 1920-1950s--first aired in Brisbane, Australia, in April 2008. The impact of the program upon older listeners' mood, quality of life (QOL) and self-reported loneliness was independently evaluated. One hundred and thirteen community-dwelling persons and residents of residential care facilities, aged 60 years and older participated in a three month evaluation of Silver Memories. They were asked to listen to the program daily and baseline and follow-up measures of depression, QOL and loneliness were obtained. Participants were also asked for their opinions regarding the program's quality and appeal. The results showed a statistically significant improvement in measures of depression and QOL from baseline to follow-up but there was no change on the measure of loneliness. The results did not vary by living situation (community vs. residential care), whether the participant was lonely or not lonely, socially isolated or not isolated, or whether there had been any important changes in the participant's health or social circumstances throughout the evaluation. It was concluded that listening to Silver Memories appears to improve the QOL and mood of older people and is an inexpensive intervention that is flexible and readily implemented.

Toxin-Induced Experimental Models of Learning and Memory Impairment.

Science.gov (United States)

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

2016-09-01

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

Modeling Confidence and Response Time in Recognition Memory

Science.gov (United States)

Ratcliff, Roger; Starns, Jeffrey J.

2009-01-01

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

Thermodynamic modelling of shape memory behaviour: some examples

International Nuclear Information System (INIS)

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

1995-01-01

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

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

OpenAIRE

Kopfová, J.; Krejčí, P. (Pavel)

2011-01-01

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

Virtual memory support for distributed computing environments using a shared data object model

Science.gov (United States)

Huang, F.; Bacon, J.; Mapp, G.

1995-12-01

Conventional storage management systems provide one interface for accessing memory segments and another for accessing secondary storage objects. This hinders application programming and affects overall system performance due to mandatory data copying and user/kernel boundary crossings, which in the microkernel case may involve context switches. Memory-mapping techniques may be used to provide programmers with a unified view of the storage system. This paper extends such techniques to support a shared data object model for distributed computing environments in which good support for coherence and synchronization is essential. The approach is based on a microkernel, typed memory objects, and integrated coherence control. A microkernel architecture is used to support multiple coherence protocols and the addition of new protocols. Memory objects are typed and applications can choose the most suitable protocols for different types of object to avoid protocol mismatch. Low-level coherence control is integrated with high-level concurrency control so that the number of messages required to maintain memory coherence is reduced and system-wide synchronization is realized without severely impacting the system performance. These features together contribute a novel approach to the support for flexible coherence under application control.

Phone Routing using the Dynamic Memory Model

DEFF Research Database (Denmark)

Bendtsen, Claus Nicolaj; Krink, Thiemo

2002-01-01

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

Long Memory Models to Generate Synthetic Hydrological Series

Directory of Open Access Journals (Sweden)

Guilherme Armando de Almeida Pereira

2014-01-01

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

Neural network modeling of associative memory: Beyond the Hopfield model

Science.gov (United States)

Dasgupta, Chandan

1992-07-01

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

Spatial memory tasks in rodents: what do they model?

Science.gov (United States)

Morellini, Fabio

2013-10-01

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

Comparative Evaluation and Case Studies of Shared-Memory and Data-Parallel Execution Patterns

Directory of Open Access Journals (Sweden)

Xiaodong Zhang

1999-01-01

Full Text Available Shared‐memory and data‐parallel programming models are two important paradigms for scientific applications. Both models provide high‐level program abstractions, and simple and uniform views of network structures. The common features of the two models significantly simplify program coding and debugging for scientific applications. However, the underlining execution and overhead patterns are significantly different between the two models due to their programming constraints, and due to different and complex structures of interconnection networks and systems which support the two models. We performed this experimental study to present implications and comparisons of execution patterns on two commercial architectures. We implemented a standard electromagnetic simulation program (EM and a linear system solver using the shared‐memory model on the KSR‐1 and the data‐parallel model on the CM‐5. Our objectives are to examine the execution pattern changes required for an implementation transformation between the two models; to study memory access patterns; to address scalability issues; and to investigate relative costs and advantages/disadvantages of using the two models for scientific computations. Our results indicate that the EM program tends to become computation‐intensive in the KSR‐1 shared‐memory system, and memory‐demanding in the CM‐5 data‐parallel system when the systems and the problems are scaled. The EM program, a highly data‐parallel program performed extremely well, and the linear system solver, a highly control‐structured program suffered significantly in the data‐parallel model on the CM‐5. Our study provides further evidence that matching execution patterns of algorithms to parallel architectures would achieve better performance.

Parallel phase model : a programming model for high-end parallel machines with manycores.

Energy Technology Data Exchange (ETDEWEB)

Wu, Junfeng (Syracuse University, Syracuse, NY); Wen, Zhaofang; Heroux, Michael Allen; Brightwell, Ronald Brian

2009-04-01

This paper presents a parallel programming model, Parallel Phase Model (PPM), for next-generation high-end parallel machines based on a distributed memory architecture consisting of a networked cluster of nodes with a large number of cores on each node. PPM has a unified high-level programming abstraction that facilitates the design and implementation of parallel algorithms to exploit both the parallelism of the many cores and the parallelism at the cluster level. The programming abstraction will be suitable for expressing both fine-grained and coarse-grained parallelism. It includes a few high-level parallel programming language constructs that can be added as an extension to an existing (sequential or parallel) programming language such as C; and the implementation of PPM also includes a light-weight runtime library that runs on top of an existing network communication software layer (e.g. MPI). Design philosophy of PPM and details of the programming abstraction are also presented. Several unstructured applications that inherently require high-volume random fine-grained data accesses have been implemented in PPM with very promising results.

A Comparison of Two Paradigms for Distributed Shared Memory

NARCIS (Netherlands)

Levelt, W.G.; Kaashoek, M.F.; Bal, H.E.; Tanenbaum, A.S.

1992-01-01

Two paradigms for distributed shared memory on loosely‐coupled computing systems are compared: the shared data‐object model as used in Orca, a programming language specially designed for loosely‐coupled computing systems, and the shared virtual memory model. For both paradigms two systems are

Apollo guidance, navigation and control: Guidance system operations plans for manned LM earth orbital and lunar missions using Program COLOSSUS 3. Section 7: Erasable memory programs

Science.gov (United States)

Hamilton, M. H.

1972-01-01

Erasable-memory programs (EMPs) designed for the guidance computers used in the command (CMC) and lunar modules (LGC) are described. CMC programs are designated COLOSSUS 3, and the associated EMPs are identified by a three-digit number beginning with 5. LGC programs are designated LUMINARY 1E, and the associated EMPs are identified, with one exception, by a three-digit number beginning with 1. The exception is EMP 99. The EMPs vary in complexity from a simple flagbit setting to a long and intricate logical structure. They all, however, cause the computer to behave in a way not intended in the original design of the programs; they accomplish this off-nominal behavior by some alteration of erasable memory to interface with existing fixed-memory programs to effect a desired result.

Ising formulation of associative memory models and quantum annealing recall

Science.gov (United States)

Santra, Siddhartha; Shehab, Omar; Balu, Radhakrishnan

2017-12-01

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

Projected phase-change memory devices.

Science.gov (United States)

Koelmans, Wabe W; Sebastian, Abu; Jonnalagadda, Vara Prasad; Krebs, Daniel; Dellmann, Laurent; Eleftheriou, Evangelos

2015-09-03

Nanoscale memory devices, whose resistance depends on the history of the electric signals applied, could become critical building blocks in new computing paradigms, such as brain-inspired computing and memcomputing. However, there are key challenges to overcome, such as the high programming power required, noise and resistance drift. Here, to address these, we present the concept of a projected memory device, whose distinguishing feature is that the physical mechanism of resistance storage is decoupled from the information-retrieval process. We designed and fabricated projected memory devices based on the phase-change storage mechanism and convincingly demonstrate the concept through detailed experimentation, supported by extensive modelling and finite-element simulations. The projected memory devices exhibit remarkably low drift and excellent noise performance. We also demonstrate active control and customization of the programming characteristics of the device that reliably realize a multitude of resistance states.

Music Genre Classification using an Auditory Memory Model

DEFF Research Database (Denmark)

Jensen, Kristoffer

2011-01-01

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

Short-Term Memory and Its Biophysical Model

Science.gov (United States)

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

1996-12-01

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

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

Science.gov (United States)

Jarrold, C; Baddeley, A D

2001-10-01

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

COMBINING LONG MEMORY AND NONLINEAR MODEL OUTPUTS FOR INFLATION FORECAST

OpenAIRE

Heri Kuswanto; Irhamah Alimuhajin; Laylia Afidah

2014-01-01

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

Behavioural Models of Motor Control and Short-Term Memory

OpenAIRE

Imanaka, Kuniyasu; Funase, Kozo; Yamauchi, Masaki

1995-01-01

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

Generic database cost models for hierarchical memory systems

NARCIS (Netherlands)

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

2002-01-01

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

A phenomenological memristor model for synaptic memory and learning behaviors

Institute of Scientific and Technical Information of China (English)

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

2017-01-01

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

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

Science.gov (United States)

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

2003-12-01

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

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

Science.gov (United States)

Sánchez-Ramón, Silvia; Faure, Florence

2016-01-01

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

Generic Database Cost Models for Hierarchical Memory Systems

NARCIS (Netherlands)

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

2002-01-01

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

Introduction to parallel programming

CERN Document Server

Brawer, Steven

1989-01-01

Introduction to Parallel Programming focuses on the techniques, processes, methodologies, and approaches involved in parallel programming. The book first offers information on Fortran, hardware and operating system models, and processes, shared memory, and simple parallel programs. Discussions focus on processes and processors, joining processes, shared memory, time-sharing with multiple processors, hardware, loops, passing arguments in function/subroutine calls, program structure, and arithmetic expressions. The text then elaborates on basic parallel programming techniques, barriers and race

Modeling Recognition Memory Using the Similarity Structure of Natural Input

Science.gov (United States)

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

2006-01-01

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

Generic Database Cost Models for Hierarchical Memory Systems

OpenAIRE

Manegold, Stefan; Boncz, Peter; Kersten, Martin

2002-01-01

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

Discrete-Slots Models of Visual Working-Memory Response Times

Science.gov (United States)

Donkin, Christopher; Nosofsky, Robert M.; Gold, Jason M.; Shiffrin, Richard M.

2014-01-01

Much recent research has aimed to establish whether visual working memory (WM) is better characterized by a limited number of discrete all-or-none slots or by a continuous sharing of memory resources. To date, however, researchers have not considered the response-time (RT) predictions of discrete-slots versus shared-resources models. To complement the past research in this field, we formalize a family of mixed-state, discrete-slots models for explaining choice and RTs in tasks of visual WM change detection. In the tasks under investigation, a small set of visual items is presented, followed by a test item in 1 of the studied positions for which a change judgment must be made. According to the models, if the studied item in that position is retained in 1 of the discrete slots, then a memory-based evidence-accumulation process determines the choice and the RT; if the studied item in that position is missing, then a guessing-based accumulation process operates. Observed RT distributions are therefore theorized to arise as probabilistic mixtures of the memory-based and guessing distributions. We formalize an analogous set of continuous shared-resources models. The model classes are tested on individual subjects with both qualitative contrasts and quantitative fits to RT-distribution data. The discrete-slots models provide much better qualitative and quantitative accounts of the RT and choice data than do the shared-resources models, although there is some evidence for “slots plus resources” when memory set size is very small. PMID:24015956

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

Science.gov (United States)

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

2000-01-01

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

Relaxed Operational Semantics of Concurrent Programming Languages

Directory of Open Access Journals (Sweden)

Gustavo Petri

2012-08-01

Full Text Available We propose a novel, operational framework to formally describe the semantics of concurrent programs running within the context of a relaxed memory model. Our framework features a "temporary store" where the memory operations issued by the threads are recorded, in program order. A memory model then specifies the conditions under which a pending operation from this sequence is allowed to be globally performed, possibly out of order. The memory model also involves a "write grain," accounting for architectures where a thread may read a write that is not yet globally visible. Our formal model is supported by a software simulator, allowing us to run litmus tests in our semantics.

Meta-analysis of the research impact of Baddeley’s multicomponent working memory model and Cowan’s embedded-processes model of working memory : a bibliometric mapping approach

OpenAIRE

Gruszka-Gosiewska, Aleksandra; Orzechowski, Jarosław

2016-01-01

In this study bibliometric mapping method was employed to visualise the current research trends and the impact of the two most influential models of working memory, namely: A. D. Baddeley and G. J. Hitch’s (1974) multicomponent working memory model and N. Cowan’s (1988) embedded-processes model of working memory. Using VOSviewer software two maps were generated based on the index-term words extracted from the research papers citing Baddeley (2000) and Cowan (2001), respectively. The maps repr...

Resonator memories and optical novelty filters

Science.gov (United States)

Anderson, Dana Z.; Erle, Marie C.

Optical resonators having holographic elements are potential candidates for storing information that can be accessed through content addressable or associative recall. Closely related to the resonator memory is the optical novelty filter, which can detect the differences between a test object and a set of reference objects. We discuss implementations of these devices using continuous optical media such as photorefractive materials. The discussion is framed in the context of neural network models. There are both formal and qualitative similarities between the resonator memory and optical novelty filter and network models. Mode competition arises in the theory of the resonator memory, much as it does in some network models. We show that the role of the phenomena of "daydreaming" in the real-time programmable optical resonator is very much akin to the role of "unlearning" in neural network memories. The theory of programming the real-time memory for a single mode is given in detail. This leads to a discussion of the optical novelty filter. Experimental results for the resonator memory, the real-time programmable memory, and the optical tracking novelty filter are reviewed. We also point to several issues that need to be addressed in order to implement more formal models of neural networks.

A unitary signal-detection model of implicit and explicit memory.

Science.gov (United States)

Berry, Christopher J; Shanks, David R; Henson, Richard N A

2008-10-01

Do dissociations imply independent systems? In the memory field, the view that there are independent implicit and explicit memory systems has been predominantly supported by dissociation evidence. Here, we argue that many of these dissociations do not necessarily imply distinct memory systems. We review recent work with a single-system computational model that extends signal-detection theory (SDT) to implicit memory. SDT has had a major influence on research in a variety of domains. The current work shows that it can be broadened even further in its range of application. Indeed, the single-system model that we present does surprisingly well in accounting for some key dissociations that have been taken as evidence for independent implicit and explicit memory systems.

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

Science.gov (United States)

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

2010-08-01

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

Asymmetric Programming: A Highly Reliable Metadata Allocation Strategy for MLC NAND Flash Memory-Based Sensor Systems

Science.gov (United States)

Huang, Min; Liu, Zhaoqing; Qiao, Liyan

2014-01-01

While the NAND flash memory is widely used as the storage medium in modern sensor systems, the aggressive shrinking of process geometry and an increase in the number of bits stored in each memory cell will inevitably degrade the reliability of NAND flash memory. In particular, it's critical to enhance metadata reliability, which occupies only a small portion of the storage space, but maintains the critical information of the file system and the address translations of the storage system. Metadata damage will cause the system to crash or a large amount of data to be lost. This paper presents Asymmetric Programming, a highly reliable metadata allocation strategy for MLC NAND flash memory storage systems. Our technique exploits for the first time the property of the multi-page architecture of MLC NAND flash memory to improve the reliability of metadata. The basic idea is to keep metadata in most significant bit (MSB) pages which are more reliable than least significant bit (LSB) pages. Thus, we can achieve relatively low bit error rates for metadata. Based on this idea, we propose two strategies to optimize address mapping and garbage collection. We have implemented Asymmetric Programming on a real hardware platform. The experimental results show that Asymmetric Programming can achieve a reduction in the number of page errors of up to 99.05% with the baseline error correction scheme. PMID:25310473

Asymmetric Programming: A Highly Reliable Metadata Allocation Strategy for MLC NAND Flash Memory-Based Sensor Systems

Directory of Open Access Journals (Sweden)

Min Huang

2014-10-01

Full Text Available While the NAND flash memory is widely used as the storage medium in modern sensor systems, the aggressive shrinking of process geometry and an increase in the number of bits stored in each memory cell will inevitably degrade the reliability of NAND flash memory. In particular, it’s critical to enhance metadata reliability, which occupies only a small portion of the storage space, but maintains the critical information of the file system and the address translations of the storage system. Metadata damage will cause the system to crash or a large amount of data to be lost. This paper presents Asymmetric Programming, a highly reliable metadata allocation strategy for MLC NAND flash memory storage systems. Our technique exploits for the first time the property of the multi-page architecture of MLC NAND flash memory to improve the reliability of metadata. The basic idea is to keep metadata in most significant bit (MSB pages which are more reliable than least significant bit (LSB pages. Thus, we can achieve relatively low bit error rates for metadata. Based on this idea, we propose two strategies to optimize address mapping and garbage collection. We have implemented Asymmetric Programming on a real hardware platform. The experimental results show that Asymmetric Programming can achieve a reduction in the number of page errors of up to 99.05% with the baseline error correction scheme.

Working memory training and poetry-based stimulation programs: are there differences in cognitive outcome in healthy older adults?

Science.gov (United States)

Zimmermann, Nicolle; Netto, Tania Maria; Amodeo, Maria Teresa; Ska, Bernadette; Fonseca, Rochele Paz

2014-01-01

Neuropsychological interventions have been mainly applied with clinical populations, in spite of the need of preventing negative changes across life span. Among the few studies of cognitive stimulation in elderly, surprisingly there is no enough research comparing direct and indirect active stimulation programs. This study aims to verify wheter there are differences between two cognitive interventions approaches in older adults: a structured Working Memory (WM) Training Program versus a Poetry-based Stimulation Program. Fourteen older adults were randomly assigned to participate into one of the two intervention groups. The assessed neurocognitive components were attention, episodic and working memory, communicative and executive functions. WM Training activities were based on Baddeley's model; Poetry-based Stimulation Program was composed by general language activities. Data were analyzed with one-way ANCOVA with Delta scores and pre and post-training tests raw scores. WM group improved performance on WM, inhibition, and cognitive flexibility measures, while Poetry group improved on verbal fluency and narrative discourse tasks. Both approaches presented benefits; however WM Training improved its target function with transfer effects to executive functions, being useful for future studies with a variety of dementias. Poetry-based Stimulation also improved complex linguistic abilities. Both approaches may be helpful as strategies to prevent dysfunctional aging changes.

Modeling recognition memory using the similarity structure of natural input

NARCIS (Netherlands)

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

2006-01-01

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

Lower Bounds in the Asymmetric External Memory Model

DEFF Research Database (Denmark)

Jacob, Riko; Sitchinava, Nodari

2017-01-01

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

Colored noise and memory effects on formal spiking neuron models

Science.gov (United States)

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

2015-06-01

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

Thermomechanical model for NiTi shape memory wires

International Nuclear Information System (INIS)

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

2010-01-01

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

Scopes describe frames : A uniform model for memory layout in dynamic semantics

NARCIS (Netherlands)

Poulsen, C.B.; Neron, P.J.M.; Tolmach, Andrew; Visser, Eelco; Krishnamurthi, Shriram; Lerner, Benjamin S.

2016-01-01

Semantic specifications do not make a systematic connection between the names and scopes in the static structure of a program and memory layout, and access during its execution. In this paper we introduce a systematic approach to the alignment of names in static semantics and memory in dynamic

Memory Effects in the Two-Level Model for Glasses

Science.gov (United States)

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

2008-07-01

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

A program for undergraduate research into the mechanisms of sensory coding and memory decay

Energy Technology Data Exchange (ETDEWEB)

Calin-Jageman, R J

2010-09-28

This is the final technical report for this DOE project, entitltled "A program for undergraduate research into the mechanisms of sensory coding and memory decay". The report summarizes progress on the three research aims: 1) to identify phyisological and genetic correlates of long-term habituation, 2) to understand mechanisms of olfactory coding, and 3) to foster a world-class undergraduate neuroscience program. Progress on the first aim has enabled comparison of learning-regulated transcripts across closely related learning paradigms and species, and results suggest that only a small core of transcripts serve truly general roles in long-term memory. Progress on the second aim has enabled testing of several mutant phenotypes for olfactory behaviors, and results show that responses are not fully consistent with the combinitoral coding hypothesis. Finally, 14 undergraduate students participated in this research, the neuroscience program attracted extramural funding, and we completed a successful summer program to enhance transitions for community-college students into 4-year colleges to persue STEM fields.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Silvia eSánchez-Ramón

2016-02-01

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

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

Science.gov (United States)

Sánchez-Ramón, Silvia; Faure, Florence

2016-01-01

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

Addiction memory as a specific, individually learned memory imprint.

Science.gov (United States)

Böning, J

2009-05-01

The construct of "addiction memory" (AM) and its importance for relapse occurrence has been the subject of discussion for the past 30 years. Neurobiological findings from "social neuroscience" and biopsychological learning theory, in conjunction with construct-valid behavioral pharmacological animal models, can now also provide general confirmation of addiction memory as a pathomorphological correlate of addiction disorders. Under multifactorial influences, experience-driven neuronal learning and memory processes of emotional and cognitive processing patterns in the specific individual "set" and "setting" play an especially pivotal role in this connection. From a neuropsychological perspective, the episodic (biographical) memory, located at the highest hierarchical level, is of central importance for the formation of the AM in certain structural and functional areas of the brain and neuronal networks. Within this context, neuronal learning and conditioning processes take place more or less unconsciously and automatically in the preceding long-term-memory systems (in particular priming and perceptual memory). They then regulate the individually programmed addiction behavior implicitly and thus subsequently stand for facilitated recollection of corresponding, previously stored cues or context situations. This explains why it is so difficult to treat an addiction memory, which is embedded above all in the episodic memory, from the molecular carrier level via the neuronal pattern level through to the psychological meaning level, and has thus meanwhile become a component of personality.

Transactional Memory

CERN Document Server

Harris, Tim; Rajwar, Ravi

2010-01-01

The advent of multicore processors has renewed interest in the idea of incorporating transactions into the programming model used to write parallel programs.This approach, known as transactional memory, offers an alternative, and hopefully better, way to coordinate concurrent threads. The ACI(atomicity, consistency, isolation) properties of transactions provide a foundation to ensure that concurrent reads and writes of shared data do not produce inconsistent or incorrect results. At a higher level, a computation wrapped in a transaction executes atomically - either it completes successfullyand

A Four–Component Model of Age–Related Memory Change

Science.gov (United States)

Healey, M. Karl; Kahana, Michael J.

2015-01-01

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

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

Science.gov (United States)

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

2013-09-01

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

The ASC Sequoia Programming Model

Energy Technology Data Exchange (ETDEWEB)

Seager, M

2008-08-06

In the late 1980's and early 1990's, Lawrence Livermore National Laboratory was deeply engrossed in determining the next generation programming model for the Integrated Design Codes (IDC) beyond vectorization for the Cray 1s series of computers. The vector model, developed in mid 1970's first for the CDC 7600 and later extended from stack based vector operation to memory to memory operations for the Cray 1s, lasted approximately 20 years (See Slide 5). The Cray vector era was deemed an extremely long lived era as it allowed vector codes to be developed over time (the Cray 1s were faster in scalar mode than the CDC 7600) with vector unit utilization increasing incrementally over time. The other attributes of the Cray vector era at LLNL were that we developed, supported and maintained the Operating System (LTSS and later NLTSS), communications protocols (LINCS), Compilers (Civic Fortran77 and Model), operating system tools (e.g., batch system, job control scripting, loaders, debuggers, editors, graphics utilities, you name it) and math and highly machine optimized libraries (e.g., SLATEC, and STACKLIB). Although LTSS was adopted by Cray for early system generations, they later developed COS and UNICOS operating systems and environment on their own. In the late 1970s and early 1980s two trends appeared that made the Cray vector programming model (described above including both the hardware and system software aspects) seem potentially dated and slated for major revision. These trends were the appearance of low cost CMOS microprocessors and their attendant, departmental and mini-computers and later workstations and personal computers. With the wide spread adoption of Unix in the early 1980s, it appeared that LLNL (and the other DOE Labs) would be left out of the mainstream of computing without a rapid transition to these 'Killer Micros' and modern OS and tools environments. The other interesting advance in the period is that systems were being

A Java Reference Model of Transacted Memory for Smart Cards

NARCIS (Netherlands)

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

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

A Java Reference Model of Transacted Memory for Smart Cards

NARCIS (Netherlands)

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

2002-01-01

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

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

Science.gov (United States)

Broekaert, Jan B.; Busemeyer, Jerome R.

2017-06-01

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

Aplikasi Bidirectional Assosiatif Memori (BAM) Network pada Pengenalan Model

OpenAIRE

Iskandar, Iskhaq

2001-01-01

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

Mechanisms of memory storage in a model perirhinal network.

Science.gov (United States)

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

2017-01-01

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

A four-component model of age-related memory change.

Science.gov (United States)

Healey, M Karl; Kahana, Michael J

2016-01-01

We develop a novel, computationally explicit, theory of age-related memory change within the framework of the context maintenance and retrieval (CMR2) model of memory search. We introduce a set of benchmark findings from the free recall and recognition tasks that include aspects of memory performance that show both age-related stability and decline. We test aging theories by lesioning the corresponding mechanisms in a model fit to younger adult free recall data. When effects are considered in isolation, many theories provide an adequate account, but when all effects are considered simultaneously, the existing theories fail. We develop a novel theory by fitting the full model (i.e., allowing all parameters to vary) to individual participants and comparing the distributions of parameter values for older and younger adults. This theory implicates 4 components: (a) the ability to sustain attention across an encoding episode, (b) the ability to retrieve contextual representations for use as retrieval cues, (c) the ability to monitor retrievals and reject intrusions, and (d) the level of noise in retrieval competitions. We extend CMR2 to simulate a recognition memory task using the same mechanisms the free recall model uses to reject intrusions. Without fitting any additional parameters, the 4-component theory that accounts for age differences in free recall predicts the magnitude of age differences in recognition memory accuracy. Confirming a prediction of the model, free recall intrusion rates correlate positively with recognition false alarm rates. Thus, we provide a 4-component theory of a complex pattern of age differences across 2 key laboratory tasks. (c) 2015 APA, all rights reserved).

A three-dimensional constitutive model for shape memory alloy

International Nuclear Information System (INIS)

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

2009-01-01

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

Optical Associative Memory Model With Threshold Modification Using Complementary Vector

Science.gov (United States)

Bian, Shaoping; Xu, Kebin; Hong, Jing

1989-02-01

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

Medical Music Therapy: A Model Program for Clinical Practice, Education, Training and Research

Science.gov (United States)

Standley, Jayne

2005-01-01

This monograph evolved from the unique, innovative partnership between the Florida State University Music Therapy Program and Tallahassee Memorial HealthCare. Its purpose is to serve as a model for music therapy educators, students, clinicians, and the hospital administrators who might employ them. This book should prove a valuable resource for…

Nonlinear Model of Pseudoelastic Shape Memory Alloy Damper Considering Residual Martensite Strain Effect

Directory of Open Access Journals (Sweden)

Y. M. Parulekar

2012-01-01

Full Text Available Recently, there has been increasing interest in using superelastic shape memory alloys for applications in seismic resistant-design. Shape memory alloys (SMAs have a unique property by which they can recover their original shape after experiencing large strains up to 8% either by heating (shape memory effect or removing stress (pseudoelastic effect. Many simplified shape memory alloy models are suggested in the past literature for capturing the pseudoelastic response of SMAs in passive vibration control of structures. Most of these models do not consider the cyclic effects of SMA's and resulting residual martensite deformation. Therefore, a suitable constitutive model of shape memory alloy damper which represents the nonlinear hysterical dynamic system appropriately is essential. In this paper a multilinear hysteretic model incorporating residual martensite strain effect of pseudoelastic shape memory alloy damper is developed and experimentally validated using SMA wire, based damper device. A sensitivity analysis is done using the proposed model along with three other simplified SMA models. The models are implemented on a steel frame representing an SDOF system and the comparison of seismic response of structure with all the models is made in the numerical study.

MaMR: High-performance MapReduce programming model for material cloud applications

Science.gov (United States)

Jing, Weipeng; Tong, Danyu; Wang, Yangang; Wang, Jingyuan; Liu, Yaqiu; Zhao, Peng

2017-02-01

With the increasing data size in materials science, existing programming models no longer satisfy the application requirements. MapReduce is a programming model that enables the easy development of scalable parallel applications to process big data on cloud computing systems. However, this model does not directly support the processing of multiple related data, and the processing performance does not reflect the advantages of cloud computing. To enhance the capability of workflow applications in material data processing, we defined a programming model for material cloud applications that supports multiple different Map and Reduce functions running concurrently based on hybrid share-memory BSP called MaMR. An optimized data sharing strategy to supply the shared data to the different Map and Reduce stages was also designed. We added a new merge phase to MapReduce that can efficiently merge data from the map and reduce modules. Experiments showed that the model and framework present effective performance improvements compared to previous work.

Constitutive Models for Shape Memory Alloy Polycrystals

Science.gov (United States)

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

1996-01-01

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

Distributed-memory matrix computations

DEFF Research Database (Denmark)

Balle, Susanne Mølleskov

1995-01-01

The main goal of this project is to investigate, develop, and implement algorithms for numerical linear algebra on parallel computers in order to acquire expertise in methods for parallel computations. An important motivation for analyzaing and investigating the potential for parallelism in these......The main goal of this project is to investigate, develop, and implement algorithms for numerical linear algebra on parallel computers in order to acquire expertise in methods for parallel computations. An important motivation for analyzaing and investigating the potential for parallelism...... in these algorithms is that many scientific applications rely heavily on the performance of the involved dense linear algebra building blocks. Even though we consider the distributed-memory as well as the shared-memory programming paradigm, the major part of the thesis is dedicated to distributed-memory architectures....... We emphasize distributed-memory massively parallel computers - such as the Connection Machines model CM-200 and model CM-5/CM-5E - available to us at UNI-C and at Thinking Machines Corporation. The CM-200 was at the time this project started one of the few existing massively parallel computers...

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

Science.gov (United States)

Sato, Naoyuki; Yamaguchi, Yoko

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

Modeling spatial-temporal operations with context-dependent associative memories.

Science.gov (United States)

Mizraji, Eduardo; Lin, Juan

2015-10-01

We organize our behavior and store structured information with many procedures that require the coding of spatial and temporal order in specific neural modules. In the simplest cases, spatial and temporal relations are condensed in prepositions like "below" and "above", "behind" and "in front of", or "before" and "after", etc. Neural operators lie beneath these words, sharing some similarities with logical gates that compute spatial and temporal asymmetric relations. We show how these operators can be modeled by means of neural matrix memories acting on Kronecker tensor products of vectors. The complexity of these memories is further enhanced by their ability to store episodes unfolding in space and time. How does the brain scale up from the raw plasticity of contingent episodic memories to the apparent stable connectivity of large neural networks? We clarify this transition by analyzing a model that flexibly codes episodic spatial and temporal structures into contextual markers capable of linking different memory modules.

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

Science.gov (United States)

Brady, Timothy F.; Tenenbaum, Joshua B.

2013-01-01

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

Physicochemical analog for modeling superimposed and coded memories

Science.gov (United States)

Ensanian, Minas

1992-07-01

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

Models of wave memory

CERN Document Server

Kashchenko, Serguey

2015-01-01

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

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

Science.gov (United States)

Simmering, Vanessa R

2016-09-01

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

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

Science.gov (United States)

Orban de Xivry, Jean-Jacques; Lefèvre, Philippe

2015-04-01

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

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

Science.gov (United States)

Camina, Eduardo; Güell, Francisco

2017-01-01

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

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

Science.gov (United States)

Camina, Eduardo; Güell, Francisco

2017-01-01

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

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

Directory of Open Access Journals (Sweden)

Eduardo Camina

2017-06-01

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

Towards Modeling False Memory With Computational Knowledge Bases.

Science.gov (United States)

Li, Justin; Kohanyi, Emma

2017-01-01

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

Calibration of Chaboche Model with a Memory Surface

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Radim HALAMA

2013-06-01

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

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

Science.gov (United States)

Berry, Christopher J; Kessels, Roy P C; Wester, Arie J; Shanks, David R

2014-08-13

We challenge the claim that there are distinct neural systems for explicit and implicit memory by demonstrating that a formal single-system model predicts the pattern of recognition memory (explicit) and repetition priming (implicit) in amnesia. In the current investigation, human participants with amnesia categorized pictures of objects at study and then, at test, identified fragmented versions of studied (old) and nonstudied (new) objects (providing a measure of priming), and made a recognition memory judgment (old vs new) for each object. Numerous results in the amnesic patients were predicted in advance by the single-system model, as follows: (1) deficits in recognition memory and priming were evident relative to a control group; (2) items judged as old were identified at greater levels of fragmentation than items judged new, regardless of whether the items were actually old or new; and (3) the magnitude of the priming effect (the identification advantage for old vs new items) overall was greater than that of items judged new. Model evidence measures also favored the single-system model over two formal multiple-systems models. The findings support the single-system model, which explains the pattern of recognition and priming in amnesia primarily as a reduction in the strength of a single dimension of memory strength, rather than a selective explicit memory system deficit. Copyright © 2014 the authors 0270-6474/14/3410963-12$15.00/0.

The memory state heuristic: A formal model based on repeated recognition judgments.

Science.gov (United States)

Castela, Marta; Erdfelder, Edgar

2017-02-01

The recognition heuristic (RH) theory predicts that, in comparative judgment tasks, if one object is recognized and the other is not, the recognized one is chosen. The memory-state heuristic (MSH) extends the RH by assuming that choices are not affected by recognition judgments per se, but by the memory states underlying these judgments (i.e., recognition certainty, uncertainty, or rejection certainty). Specifically, the larger the discrepancy between memory states, the larger the probability of choosing the object in the higher state. The typical RH paradigm does not allow estimation of the underlying memory states because it is unknown whether the objects were previously experienced or not. Therefore, we extended the paradigm by repeating the recognition task twice. In line with high threshold models of recognition, we assumed that inconsistent recognition judgments result from uncertainty whereas consistent judgments most likely result from memory certainty. In Experiment 1, we fitted 2 nested multinomial models to the data: an MSH model that formalizes the relation between memory states and binary choices explicitly and an approximate model that ignores the (unlikely) possibility of consistent guesses. Both models provided converging results. As predicted, reliance on recognition increased with the discrepancy in the underlying memory states. In Experiment 2, we replicated these results and found support for choice consistency predictions of the MSH. Additionally, recognition and choice latencies were in agreement with the MSH in both experiments. Finally, we validated critical parameters of our MSH model through a cross-validation method and a third experiment. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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

Science.gov (United States)

Eustache, Francis; Viard, Armelle; Desgranges, Béatrice

2016-07-01

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

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

Science.gov (United States)

Qingtao, Zhai; Hongxia, Ge; Rongjun, Cheng

2018-01-01

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

Nonvolatile Memory Technology for Space Applications

Science.gov (United States)

Oldham, Timothy R.; Irom, Farokh; Friendlich, Mark; Nguyen, Duc; Kim, Hak; Berg, Melanie; LaBel, Kenneth A.

2010-01-01

This slide presentation reviews several forms of nonvolatile memory for use in space applications. The intent is to: (1) Determine inherent radiation tolerance and sensitivities, (2) Identify challenges for future radiation hardening efforts, (3) Investigate new failure modes and effects, and technology modeling programs. Testing includes total dose, single event (proton, laser, heavy ion), and proton damage (where appropriate). Test vehicles are expected to be a variety of non-volatile memory devices as available including Flash (NAND and NOR), Charge Trap, Nanocrystal Flash, Magnetic Memory (MRAM), Phase Change--Chalcogenide, (CRAM), Ferroelectric (FRAM), CNT, and Resistive RAM.

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

Science.gov (United States)

Repovs, G; Baddeley, A

2006-04-28

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

Spatial Impairment and Memory in Genetic Disorders: Insights from Mouse Models

Directory of Open Access Journals (Sweden)

Sang Ah Lee

2017-02-01

Full Text Available Research across the cognitive and brain sciences has begun to elucidate some of the processes that guide navigation and spatial memory. Boundary geometry and featural landmarks are two distinct classes of environmental cues that have dissociable neural correlates in spatial representation and follow different patterns of learning. Consequently, spatial navigation depends both on the type of cue available and on the type of learning provided. We investigated this interaction between spatial representation and memory by administering two different tasks (working memory, reference memory using two different environmental cues (rectangular geometry, striped landmark in mouse models of human genetic disorders: Prader-Willi syndrome (PWScrm+/p− mice, n = 12 and Beta-catenin mutation (Thr653Lys-substituted mice, n = 12. This exploratory study provides suggestive evidence that these models exhibit different abilities and impairments in navigating by boundary geometry and featural landmarks, depending on the type of memory task administered. We discuss these data in light of the specific deficits in cognitive and brain function in these human syndromes and their animal model counterparts.

System of programming units for the K556RT4 and K556RT5 fixed programmed memory devices

International Nuclear Information System (INIS)

Bobkov, S.G.; Ermolin, Yu.V.; Kantserov, V.A.; Strigin, V.B.

1983-01-01

The programming system of constant programmable memory devices K556RT4 and K556RT5 that consist of two units (a programming device and an electrothermotraining unit) is described. The modules are made in the KAMAK standard. The programming device takes up 2 normal places, while the electrothermotraining block takes up 1 place. As information recording is done using a computer the time for programming is reduced and the possibility of errors is limited as compared with the manual method. The computer introduces the whole word to be recorded, not the separate parts, in the programming device. The transition to a new digit of a given word in the programming device is done automatically. This reduces the expense of computer time and accelerates the programming of microdiagrams

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

Science.gov (United States)

Smorti, Andrea; Fioretti, Chiara

2016-06-01

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

Past, Present and Future. Dull Knife Memorial College (Indian Action Program Inc.).

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1978

Five vocational training programs as well as academic coursework are offered on the Northern Cheyenne Reservation by Dull Knife Memorial College. Established and operated by the Northern Cheyenne, and located in Lame Deer, Montana, the college was chartered by a tribal ordinance in 1975. Approximately 75 trainees are currently involved in the…

Single Canonical Model of Reflexive Memory and Spatial Attention

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

2015-01-01

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

Single Canonical Model of Reflexive Memory and Spatial Attention.

Science.gov (United States)

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

2015-10-23

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

Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models

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Shelton Peiris

2017-12-01

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

Abnormal Fear Memory as a Model for Posttraumatic Stress Disorder.

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

2015-09-01

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

Adiabatic Quantum Optimization for Associative Memory Recall

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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.

Adiabatic Quantum Optimization for Associative Memory Recall

Directory of Open Access Journals (Sweden)

Hadayat eSeddiqi

2014-12-01

Full Text Available 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.

Thermoregulatory model of sleep control: losing the heat memory.

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

1999-12-01

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

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

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

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

Deception and Cognitive Load: Expanding our Horizon with a Working Memory Model

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Siegfried Ludwig Sporer

2016-04-01

Full Text Available Deception and Cognitive Load: Expanding our Horizon with a Working Memory ModelAbstractRecently, studies on deception and its detection have increased dramatically. Many of these studies rely on the cognitive load approach as the sole explanatory principle to understand deception. These studies have been exclusively on lies about negative actions (usually lies of suspects of [mock] crimes. Instead, we need to re-focus more generally on the cognitive processes involved in generating both lies and truths, not just on manipulations of cognitive load. Using Baddeley's (2000, 2007, 2012 working memory model, which integrates verbal and visual processes in working memory with retrieval from long-term memory and control of action, not only verbal content cues but also nonverbal, paraverbal and linguistic cues can be investigated within a single framework. The proposed model considers long-term semantic, episodic and autobiographical memory and their connections with working memory and action. It also incorporates ironic processes of mental control (Wegner, 1994, 2009, the role of scripts and schemata and retrieval cues and retrieval processes. Specific predictions of the model are outlined and support from selective studies is presented. The model is applicable to different types of reports, particularly about lies and truths about complex events, and to different modes of production (oral, hand-written, typed. Predictions regarding several moderator variables and methods to investigate them are proposed.

Memory and learning in a class of neural network models

International Nuclear Information System (INIS)

Wallace, D.J.

1986-01-01

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

A dynamic model of reasoning and memory.

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

2016-02-01

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

Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models

NARCIS (Netherlands)

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

2016-01-01

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

Working memory: theories, models, and controversies.

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Baddeley, Alan

2012-01-01

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

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

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

2006-11-22

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

A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation

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Fiebig, Florian

2017-01-01

A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. SIGNIFICANCE STATEMENT Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and

Generalized transport model for phase transition with memory

International Nuclear Information System (INIS)

Chen, Chi; Ciucci, Francesco

2013-01-01

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

Silicon Carbide Defect Qubits/Quantum Memory with Field-Tuning: OSD Quantum Science and Engineering Program (QSEP)

Science.gov (United States)

2017-08-01

TECHNICAL REPORT 3073 August 2017 Silicon Carbide Defect Qubits/Quantum Memory with Field-tuning: OSD Quantum Science and Engineering Program...Quantum Science and Engineering Program) by the Advanced Concepts and Applied Research Branch (Code 71730), the Energy and Environmental Sustainability...the Secretary of Defense (OSD) Quantum Science and Engineering Program (QSEP). Their collaboration topic was to examine the effect of electric-field

Randomized controlled trial of a healthy brain ageing cognitive training program: effects on memory, mood, and sleep.

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Diamond, Keri; Mowszowski, Loren; Cockayne, Nicole; Norrie, Louisa; Paradise, Matthew; Hermens, Daniel F; Lewis, Simon J G; Hickie, Ian B; Naismith, Sharon L

2015-01-01

With the rise in the ageing population and absence of a cure for dementia, cost-effective prevention strategies for those 'at risk' of dementia including those with depression and/or mild cognitive impairment are urgently required. This study evaluated the efficacy of a multifaceted Healthy Brain Ageing Cognitive Training (HBA-CT) program for older adults 'at risk' of dementia. Using a single-blinded design, 64 participants (mean age = 66.5 years, SD = 8.6) were randomized to an immediate treatment (HBA-CT) or treatment-as-usual control arm. The HBA-CT intervention was conducted twice-weekly for seven weeks and comprised group-based psychoeducation about cognitive strategies and modifiable lifestyle factors pertaining to healthy brain ageing, and computerized cognitive training. In comparison to the treatment-as-usual control arm, the HBA-CT program was associated with improvements in verbal memory (p = 0.03), self-reported memory (p = 0.03), mood (p = 0.01), and sleep (p = 0.01). While the improvements in memory (p = 0.03) and sleep (p = 0.02) remained after controlling for improvements in mood, only a trend in verbal memory improvement was apparent after controlling for sleep. The HBA-CT program improves cognitive, mood, and sleep functions in older adults 'at risk' of dementia, and therefore offers promise as a secondary prevention strategy.

Benefits of a Classroom Based Instrumental Music Program on Verbal Memory of Primary School Children: A Longitudinal Study

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Rickard, Nikki S.; Vasquez, Jorge T.; Murphy, Fintan; Gill, Anneliese; Toukhsati, Samia R.

2010-01-01

Previous research has demonstrated a benefit of music training on a number of cognitive functions including verbal memory performance. The impact of school-based music programs on memory processes is however relatively unknown. The current study explored the effect of increasing frequency and intensity of classroom-based instrumental training…

A Buffer Model of Memory Encoding and Temporal Correlations in Retrieval

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Lehman, Melissa; Malmberg, Kenneth J.

2013-01-01

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

Retrieval-induced NMDA receptor-dependent Arc expression in two models of cocaine-cue memory.

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Alaghband, Yasaman; O'Dell, Steven J; Azarnia, Siavash; Khalaj, Anna J; Guzowski, John F; Marshall, John F

2014-12-01

The association of environmental cues with drugs of abuse results in persistent drug-cue memories. These memories contribute significantly to relapse among addicts. While conditioned place preference (CPP) is a well-established paradigm frequently used to examine the modulation of drug-cue memories, very few studies have used the non-preference-based model conditioned activity (CA) for this purpose. Here, we used both experimental approaches to investigate the neural substrates of cocaine-cue memories. First, we directly compared, in a consistent setting, the involvement of cortical and subcortical brain regions in cocaine-cue memory retrieval by quantifying activity-regulated cytoskeletal-associated (Arc) protein expression in both the CPP and CA models. Second, because NMDA receptor activation is required for Arc expression, we investigated the NMDA receptor dependency of memory persistence using the CA model. In both the CPP and CA models, drug-paired animals showed significant increases in Arc immunoreactivity in regions of the frontal cortex and amygdala compared to unpaired controls. Additionally, administration of a NMDA receptor antagonist (MK-801 or memantine) immediately after cocaine-CA memory reactivation impaired the subsequent conditioned locomotion associated with the cocaine-paired environment. The enhanced Arc expression evident in a subset of corticolimbic regions after retrieval of a cocaine-context memory, observed in both the CPP and CA paradigms, likely signifies that these regions: (i) are activated during retrieval of these memories irrespective of preference-based decisions, and (ii) undergo neuroplasticity in order to update information about cues previously associated with cocaine. This study also establishes the involvement of NMDA receptors in maintaining memories established using the CA model, a characteristic previously demonstrated using CPP. Overall, these results demonstrate the utility of the CA model for studies of cocaine

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

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

2015-01-01

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

Modeling learning and memory using verbal learning tests: results from ACTIVE.

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Gross, Alden L; Rebok, George W; Brandt, Jason; Tommet, Doug; Marsiske, Michael; Jones, Richard N

2013-03-01

To investigate the influence of memory training on initial recall and learning. The Advanced Cognitive Training for Independent and Vital Elderly study of community-dwelling adults older than age 65 (n = 1,401). We decomposed trial-level recall in the Auditory Verbal Learning Test (AVLT) and Hopkins Verbal Learning Test (HVLT) into initial recall and learning across trials using latent growth models. Trial-level increases in words recalled in the AVLT and HVLT at each follow-up visit followed an approximately logarithmic shape. Over the 5-year study period, memory training was associated with slower decline in Trial 1 AVLT recall (Cohen's d = 0.35, p = .03) and steep pre- and posttraining acceleration in learning (d = 1.56, p learning, d = 3.10, p memory-trained group had a higher level of recall than the control group through the end of the 5-year study period despite faster decline in learning. This study contributes to the understanding of the mechanisms by which training benefits memory and expands current knowledge by reporting long-term changes in initial recall and learning, as measured from growth models and by characterization of the impact of memory training on these components. Results reveal that memory training delays the worsening of memory span and boosts learning.

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

Science.gov (United States)

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

2011-07-01

The present review discusses the current state of research on the clinical neuropsychology of prospective memory in Parkinson's disease. To do so the paper is divided in two sections. In the first section, we briefly outline key features of the (partly implicit) rationale underlying the available literature on the clinical neuropsychology of prospective memory. Here, we present a conceptual model that guides our approach to the clinical neuropsychology of prospective memory in general and to the effects of Parkinson's disease on prospective memory in particular. In the second section, we use this model to guide our review of the available literature and suggest some open issues and future directions motivated by previous findings and the proposed conceptual model. The review suggests that certain phases of the prospective memory process (intention formation und initiation) are particularly impaired by Parkinson's disease. In addition, it is argued that prospective memory may be preserved when tasks involve specific features (e.g., focal cues) that reduce the need for strategic monitoring processes. In terms of suggestions for future directions, it is noted that intervention studies are needed which target the specific phases of the prospective memory process that are impaired in Parkinson's disease, such as planning interventions. Moreover, it is proposed that prospective memory deficits in Parkinson's disease should be explored in the context of a general impairment in the ability to form an intention and plan or coordinate an appropriate series of actions. Copyright © 2011 Elsevier Ltd. All rights reserved.

Effects of a school-based instrumental music program on verbal and visual memory in primary school children: a longitudinal study

Directory of Open Access Journals (Sweden)

Ingo eRoden

2012-12-01

Full Text Available This study examined the effects of a school-based instrumental training program on the development of verbal and visual memory skills in primary school children. Participants either took part in a music program with weekly 45 minutes sessions of instrumental lessons in small groups at school, or they received extended natural science training. A third group of children did not receive additional training. Each child completed verbal and visual memory tests for three times over a period of 18 months. Significant Group by Time interactions were found in the measures of verbal memory. Children in the music group showed greater improvements than children in the control groups after controlling for children's socio-economic background, age and IQ. No differences between groups were found in the visual memory tests. These findings are consistent with and extend previous research by suggesting that children receiving music training may benefit from improvements in their verbal memory skills.

Effects of a school-based instrumental music program on verbal and visual memory in primary school children: a longitudinal study.

Science.gov (United States)

Roden, Ingo; Kreutz, Gunter; Bongard, Stephan

2012-01-01

This study examined the effects of a school-based instrumental training program on the development of verbal and visual memory skills in primary school children. Participants either took part in a music program with weekly 45 min sessions of instrumental lessons in small groups at school, or they received extended natural science training. A third group of children did not receive additional training. Each child completed verbal and visual memory tests three times over a period of 18 months. Significant Group by Time interactions were found in the measures of verbal memory. Children in the music group showed greater improvements than children in the control groups after controlling for children's socio-economic background, age, and IQ. No differences between groups were found in the visual memory tests. These findings are consistent with and extend previous research by suggesting that children receiving music training may benefit from improvements in their verbal memory skills.

Effects of a School-Based Instrumental Music Program on Verbal and Visual Memory in Primary School Children: A Longitudinal Study

Science.gov (United States)

Roden, Ingo; Kreutz, Gunter; Bongard, Stephan

2012-01-01

This study examined the effects of a school-based instrumental training program on the development of verbal and visual memory skills in primary school children. Participants either took part in a music program with weekly 45 min sessions of instrumental lessons in small groups at school, or they received extended natural science training. A third group of children did not receive additional training. Each child completed verbal and visual memory tests three times over a period of 18 months. Significant Group by Time interactions were found in the measures of verbal memory. Children in the music group showed greater improvements than children in the control groups after controlling for children’s socio-economic background, age, and IQ. No differences between groups were found in the visual memory tests. These findings are consistent with and extend previous research by suggesting that children receiving music training may benefit from improvements in their verbal memory skills. PMID:23267341

A Cognitive Attachment Model of prolonged grief: integrating attachments, memory, and identity.

Science.gov (United States)

Maccallum, Fiona; Bryant, Richard A

2013-08-01

Prolonged grief (PG), otherwise known as complicated grief, has attracted much attention in recent years as a potentially debilitating condition that affects approximately 10% of bereaved people. We propose a model of PG that integrates processes of attachment, self-identity, and autobiographical memory. The paper commences with a discussion of the PG construct and reviews current evidence regarding the distinctiveness of PG from other bereavement related-outcomes. We then review the evidence regarding the dysfunctional attachments, appraisals, and coping styles that people with PG display. Recent evidence pertaining to the patterns of autobiographical memory in PG is described in the context of the self-memory system. This system provides a unifying framework to understand the roles of personal memories, identity, attachments, and coping responses in PG. The proposed model places emphasis on how one's sense of identity influences yearning, memories of the deceased, appraisals, and coping strategies, to maintain a focus on the loss. The model is discussed in relation to existing models of PG. The potential for shaping treatment strategies to shift perceptions of the self is then outlined. Finally, we outline future directions to test propositions stemming from the model and enhance our understanding of the mechanisms underlying PG. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

Directory of Open Access Journals (Sweden)

Sparsh Mittal

2017-09-01

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

Resource allocation models of auditory working memory.

Science.gov (United States)

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

2016-06-01

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

Superdiffusion in a non-Markovian random walk model with a Gaussian memory profile

Science.gov (United States)

Borges, G. M.; Ferreira, A. S.; da Silva, M. A. A.; Cressoni, J. C.; Viswanathan, G. M.; Mariz, A. M.

2012-09-01

Most superdiffusive Non-Markovian random walk models assume that correlations are maintained at all time scales, e.g., fractional Brownian motion, Lévy walks, the Elephant walk and Alzheimer walk models. In the latter two models the random walker can always "remember" the initial times near t = 0. Assuming jump size distributions with finite variance, the question naturally arises: is superdiffusion possible if the walker is unable to recall the initial times? We give a conclusive answer to this general question, by studying a non-Markovian model in which the walker's memory of the past is weighted by a Gaussian centered at time t/2, at which time the walker had one half the present age, and with a standard deviation σt which grows linearly as the walker ages. For large widths we find that the model behaves similarly to the Elephant model, but for small widths this Gaussian memory profile model behaves like the Alzheimer walk model. We also report that the phenomenon of amnestically induced persistence, known to occur in the Alzheimer walk model, arises in the Gaussian memory profile model. We conclude that memory of the initial times is not a necessary condition for generating (log-periodic) superdiffusion. We show that the phenomenon of amnestically induced persistence extends to the case of a Gaussian memory profile.

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

DEFF Research Database (Denmark)

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

2013-01-01

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

Introducing memory and association mechanism into a biologically inspired visual model.

Science.gov (United States)

Qiao, Hong; Li, Yinlin; Tang, Tang; Wang, Peng

2014-09-01

A famous biologically inspired hierarchical model (HMAX model), which was proposed recently and corresponds to V1 to V4 of the ventral pathway in primate visual cortex, has been successfully applied to multiple visual recognition tasks. The model is able to achieve a set of position- and scale-tolerant recognition, which is a central problem in pattern recognition. In this paper, based on some other biological experimental evidence, we introduce the memory and association mechanism into the HMAX model. The main contributions of the work are: 1) mimicking the active memory and association mechanism and adding the top down adjustment to the HMAX model, which is the first try to add the active adjustment to this famous model and 2) from the perspective of information, algorithms based on the new model can reduce the computation storage and have a good recognition performance. The new model is also applied to object recognition processes. The primary experimental results show that our method is efficient with a much lower memory requirement.

"Shape function + memory mechanism"-based hysteresis modeling of magnetorheological fluid actuators

Science.gov (United States)

Qian, Li-Jun; Chen, Peng; Cai, Fei-Long; Bai, Xian-Xu

2018-03-01

A hysteresis model based on "shape function + memory mechanism" is presented and its feasibility is verified through modeling the hysteresis behavior of a magnetorheological (MR) damper. A hysteresis phenomenon in resistor-capacitor (RC) circuit is first presented and analyzed. In the hysteresis model, the "memory mechanism" originating from the charging and discharging processes of the RC circuit is constructed by adopting a virtual displacement variable and updating laws for the reference points. The "shape function" is achieved and generalized from analytical solutions of the simple semi-linear Duhem model. Using the approach, the memory mechanism reveals the essence of specific Duhem model and the general shape function provides a direct and clear means to fit the hysteresis loop. In the frame of the structure of a "Restructured phenomenological model", the original hysteresis operator, i.e., the Bouc-Wen operator, is replaced with the new hysteresis operator. The comparative work with the Bouc-Wen operator based model demonstrates superior performances of high computational efficiency and comparable accuracy of the new hysteresis operator-based model.

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

Science.gov (United States)

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

2013-03-01

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

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

OpenAIRE

Geisler, J.; Scheben, C.

2007-01-01

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

A phenomenological memristor model for short-term/long-term memory

International Nuclear Information System (INIS)

Chen, Ling; Li, Chuandong; Huang, Tingwen; Ahmad, Hafiz Gulfam; Chen, Yiran

2014-01-01

Memristor is considered to be a natural electrical synapse because of its distinct memory property and nanoscale. In recent years, more and more similar behaviors are observed between memristors and biological synapse, e.g., short-term memory (STM) and long-term memory (LTM). The traditional mathematical models are unable to capture the new emerging behaviors. In this article, an updated phenomenological model based on the model of the Hewlett–Packard (HP) Labs has been proposed to capture such new behaviors. The new dynamical memristor model with an improved ion diffusion term can emulate the synapse behavior with forgetting effect, and exhibit the transformation between the STM and the LTM. Further, this model can be used in building new type of neural networks with forgetting ability like biological systems, and it is verified by our experiment with Hopfield neural network. - Highlights: • We take the Fick diffusion and the Soret diffusion into account in the ion drift theory. • We develop a new model based on the old HP model. • The new model can describe the forgetting effect and the spike-rate-dependent property of memristor. • The new model can solve the boundary effect of all window functions discussed in [13]. • A new Hopfield neural network with the forgetting ability is built by the new memristor model

A cognitive psychometric model for the psychodiagnostic assessment of memory-related deficits.

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Alexander, Gregory E; Satalich, Timothy A; Shankle, W Rodman; Batchelder, William H

2016-03-01

Clinical tests used for psychodiagnostic purposes, such as the well-known Alzheimer's Disease Assessment Scale: Cognitive subscale (ADAS-Cog), include a free-recall task. The free-recall task taps into latent cognitive processes associated with learning and memory components of human cognition, any of which might be impaired with the progression of Alzheimer's disease (AD). A Hidden Markov model of free recall is developed to measure latent cognitive processes used during the free-recall task. In return, these cognitive measurements give us insight into the degree to which normal cognitive functions are differentially impaired by medical conditions, such as AD and related disorders. The model is used to analyze the free-recall data obtained from healthy elderly participants, participants diagnosed as having mild cognitive impairment, and participants diagnosed with early AD. The model is specified hierarchically to handle item differences because of the serial position curve in free recall, as well as within-group individual differences in participants' recall abilities. Bayesian hierarchical inference is used to estimate the model. The model analysis suggests that the impaired patients have the following: (1) long-term memory encoding deficits, (2) short-term memory (STM) retrieval deficits for all but very short time intervals, (3) poorer transfer into long-term memory for items successfully retrieved from STM, and (4) poorer retention of items encoded into long-term memory after longer delays. Yet, impaired patients appear to have no deficit in immediate recall of encoded words in long-term memory or for very short time intervals in STM. (c) 2016 APA, all rights reserved).

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

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Pechmann, T; Mohr, G

1992-05-01

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

Programming Robots with Associative Memories

Energy Technology Data Exchange (ETDEWEB)

Touzet, C

1999-07-10

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

Programming Robots with Associative Memories

International Nuclear Information System (INIS)

Touzet, C.

1999-01-01

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

Contention Modeling for Multithreaded Distributed Shared Memory Machines: The Cray XMT

Energy Technology Data Exchange (ETDEWEB)

Secchi, Simone; Tumeo, Antonino; Villa, Oreste

2011-07-27

Distributed Shared Memory (DSM) machines are a wide class of multi-processor computing systems where a large virtually-shared address space is mapped on a network of physically distributed memories. High memory latency and network contention are two of the main factors that limit performance scaling of such architectures. Modern high-performance computing DSM systems have evolved toward exploitation of massive hardware multi-threading and fine-grained memory hashing to tolerate irregular latencies, avoid network hot-spots and enable high scaling. In order to model the performance of such large-scale machines, parallel simulation has been proved to be a promising approach to achieve good accuracy in reasonable times. One of the most critical factors in solving the simulation speed-accuracy trade-off is network modeling. The Cray XMT is a massively multi-threaded supercomputing architecture that belongs to the DSM class, since it implements a globally-shared address space abstraction on top of a physically distributed memory substrate. In this paper, we discuss the development of a contention-aware network model intended to be integrated in a full-system XMT simulator. We start by measuring the effects of network contention in a 128-processor XMT machine and then investigate the trade-off that exists between simulation accuracy and speed, by comparing three network models which operate at different levels of accuracy. The comparison and model validation is performed by executing a string-matching algorithm on the full-system simulator and on the XMT, using three datasets that generate noticeably different contention patterns.

A three-dimensional ground-water-flow model modified to reduce computer-memory requirements and better simulate confining-bed and aquifer pinchouts

Science.gov (United States)

Leahy, P.P.

1982-01-01

The Trescott computer program for modeling groundwater flow in three dimensions has been modified to (1) treat aquifer and confining bed pinchouts more realistically and (2) reduce the computer memory requirements needed for the input data. Using the original program, simulation of aquifer systems with nonrectangular external boundaries may result in a large number of nodes that are not involved in the numerical solution of the problem, but require computer storage. (USGS)

A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation.

Science.gov (United States)

Fiebig, Florian; Lansner, Anders

2017-01-04

A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and neurophysiology of the underlying

Electrophysiological Evidence for a Sensory Recruitment Model of Somatosensory Working Memory.

Science.gov (United States)

Katus, Tobias; Grubert, Anna; Eimer, Martin

2015-12-01

Sensory recruitment models of working memory assume that information storage is mediated by the same cortical areas that are responsible for the perceptual processing of sensory signals. To test this assumption, we measured somatosensory event-related brain potentials (ERPs) during a tactile delayed match-to-sample task. Participants memorized a tactile sample set at one task-relevant hand to compare it with a subsequent test set on the same hand. During the retention period, a sustained negativity (tactile contralateral delay activity, tCDA) was elicited over primary somatosensory cortex contralateral to the relevant hand. The amplitude of this component increased with memory load and was sensitive to individual limitations in memory capacity, suggesting that the tCDA reflects the maintenance of tactile information in somatosensory working memory. The tCDA was preceded by a transient negativity (N2cc component) with a similar contralateral scalp distribution, which is likely to reflect selection of task-relevant tactile stimuli at the encoding stage. The temporal sequence of N2cc and tCDA components mirrors previous observations from ERP studies of working memory in vision. The finding that the sustained somatosensory delay period activity varies as a function of memory load supports a sensory recruitment model for spatial working memory in touch. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A new shared-memory programming paradigm for molecular dynamics simulations on the Intel Paragon

International Nuclear Information System (INIS)

D'Azevedo, E.F.; Romine, C.H.

1994-12-01

This report describes the use of shared memory emulation with DOLIB (Distributed Object Library) to simplify parallel programming on the Intel Paragon. A molecular dynamics application is used as an example to illustrate the use of the DOLIB shared memory library. SOTON-PAR, a parallel molecular dynamics code with explicit message-passing using a Lennard-Jones 6-12 potential, is rewritten using DOLIB primitives. The resulting code has no explicit message primitives and resembles a serial code. The new code can perform dynamic load balancing and achieves better performance than the original parallel code with explicit message-passing

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

Science.gov (United States)

Sporer, Siegfried L

2016-01-01

Recently, studies on deception and its detection have increased dramatically. Many of these studies rely on the "cognitive load approach" as the sole explanatory principle to understand deception. These studies have been exclusively on lies about negative actions (usually lies of suspects of [mock] crimes). Instead, we need to re-focus more generally on the cognitive processes involved in generating both lies and truths, not just on manipulations of cognitive load. Using Baddeley's (2000, 2007, 2012) working memory model, which integrates verbal and visual processes in working memory with retrieval from long-term memory and control of action, not only verbal content cues but also nonverbal, paraverbal, and linguistic cues can be investigated within a single framework. The proposed model considers long-term semantic, episodic and autobiographical memory and their connections with working memory and action. It also incorporates ironic processes of mental control (Wegner, 1994, 2009), the role of scripts and schemata and retrieval cues and retrieval processes. Specific predictions of the model are outlined and support from selective studies is presented. The model is applicable to different types of reports, particularly about lies and truths about complex events, and to different modes of production (oral, hand-written, typed). Predictions regarding several moderator variables and methods to investigate them are proposed.

Modeling High Frequency Data with Long Memory and Structural Change: A-HYEGARCH Model

Directory of Open Access Journals (Sweden)

Yanlin Shi

2018-03-01

Full Text Available In this paper, we propose an Adaptive Hyperbolic EGARCH (A-HYEGARCH model to estimate the long memory of high frequency time series with potential structural breaks. Based on the original HYGARCH model, we use the logarithm transformation to ensure the positivity of conditional variance. The structural change is further allowed via a flexible time-dependent intercept in the conditional variance equation. To demonstrate its effectiveness, we perform a range of Monte Carlo studies considering various data generating processes with and without structural changes. Empirical testing of the A-HYEGARCH model is also conducted using high frequency returns of S&P 500, FTSE 100, ASX 200 and Nikkei 225. Our simulation and empirical evidence demonstrate that the proposed A-HYEGARCH model outperforms various competing specifications and can effectively control for structural breaks. Therefore, our model may provide more reliable estimates of long memory and could be a widely useful tool for modelling financial volatility in other contexts.

A long-memory model of motor learning in the saccadic system: a regime-switching approach.

Science.gov (United States)

Wong, Aaron L; Shelhamer, Mark

2013-08-01

Maintenance of movement accuracy relies on motor learning, by which prior errors guide future behavior. One aspect of this learning process involves the accurate generation of predictions of movement outcome. These predictions can, for example, drive anticipatory movements during a predictive-saccade task. Predictive saccades are rapid eye movements made to anticipated future targets based on error information from prior movements. This predictive process exhibits long-memory (fractal) behavior, as suggested by inter-trial fluctuations. Here, we model this learning process using a regime-switching approach, which avoids the computational complexities associated with true long-memory processes. The resulting model demonstrates two fundamental characteristics. First, long-memory behavior can be mimicked by a system possessing no true long-term memory, producing model outputs consistent with human-subjects performance. In contrast, the popular two-state model, which is frequently used in motor learning, cannot replicate these findings. Second, our model suggests that apparent long-term memory arises from the trade-off between correcting for the most recent movement error and maintaining consistent long-term behavior. Thus, the model surprisingly predicts that stronger long-memory behavior correlates to faster learning during adaptation (in which systematic errors drive large behavioral changes); greater apparent long-term memory indicates more effective incorporation of error from the cumulative history across trials.

Effects of a School-Based Instrumental Music Program on Verbal and Visual Memory in Primary School Children: A Longitudinal Study

OpenAIRE

Roden, Ingo; Kreutz, Gunter; Bongard, Stephan

2012-01-01

This study examined the effects of a school-based instrumental training program on the development of verbal and visual memory skills in primary school children. Participants either took part in a music program with weekly 45 minutes sessions of instrumental lessons in small groups at school, or they received extended natural science training. A third group of children did not receive additional training. Each child completed verbal and visual memory tests for three times over a period of 18 ...

Modeling Coevolution between Language and Memory Capacity during Language Origin

Science.gov (United States)

Gong, Tao; Shuai, Lan

2015-01-01

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

On the Use of Memory Models in Audio Features

DEFF Research Database (Denmark)

Jensen, Karl Kristoffer

2011-01-01

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

Phase-change memory: A continuous multilevel compact model of subthreshold conduction and threshold switching

Science.gov (United States)

Pigot, Corentin; Gilibert, Fabien; Reyboz, Marina; Bocquet, Marc; Zuliani, Paola; Portal, Jean-Michel

2018-04-01

Phase-change memory (PCM) compact modeling of the threshold switching based on a thermal runaway in Poole–Frenkel conduction is proposed. Although this approach is often used in physical models, this is the first time it is implemented in a compact model. The model accuracy is validated by a good correlation between simulations and experimental data collected on a PCM cell embedded in a 90 nm technology. A wide range of intermediate states is measured and accurately modeled with a single set of parameters, allowing multilevel programing. A good convergence is exhibited even in snapback simulation owing to this fully continuous approach. Moreover, threshold properties extraction indicates a thermally enhanced switching, which validates the basic hypothesis of the model. Finally, it is shown that this model is compliant with a new drift-resilient cell-state metric. Once enriched with a phase transition module, this compact model is ready to be implemented in circuit simulators.

Laser memory (hologram) and coincident redundant multiplex memory (CRM-memory)

International Nuclear Information System (INIS)

Ostojic, Branko

1975-01-01

It is shown that besides the memory which remembers the object by memorising of the phases of the interferenting waves of the light (i.e. hologram) it is possible to construct the memory which remembers the object by memorising of the phases of the interferenting impulses (CFM-memory). It is given the mathematical description of the memory, based on the experimental model. Although in the paper only the technical aspect of CRM memory is given. It is mentioned the possibility that the human memory has the same principle and that the invention of CRM memory is due to cybernetical analysis of the system human eye-visual cortex

Working Memory in Written Composition: An Evaluation of the 1996 Model

Directory of Open Access Journals (Sweden)

Ronald T. Kellogg, , , &

2013-10-01

Full Text Available A model of how working memory, as conceived by Baddeley (1986, supports the planning of ideas, translating ideas into written sentences, and reviewing the ideas and text already produced was proposed by Kellogg (1996. A progress report based on research from the past 17 years shows strong support for the core assumption that planning, translating, and reviewing are all dependent on the central executive. Similarly, the translation of ideas into a sentence does in fact require also verbal working memory, but the claim that editing makes no demands on the phonological loop is tenuous. As predicted by the model, planning also engages the visuo-spatial sketchpad. However, it turns out to do so only in planning with concrete concepts that elicit mental imagery. Abstract concepts do not require visuo-spatial resources, a point not anticipated by the original model. Moreover, it is unclear the extent to which planning involves spatial as opposed to visual working memory. Contrary to Baddeley’s original model, these are now known to be independent stores of working memory; the specific role of the spatial store in writing is uncertain based on the existing literature. The implications of this body of research for the instruction of writing are considered in the final section of the paper.

High Performance Programming Using Explicit Shared Memory Model on the Cray T3D

Science.gov (United States)

Saini, Subhash; Simon, Horst D.; Lasinski, T. A. (Technical Monitor)

1994-01-01

The Cray T3D is the first-phase system in Cray Research Inc.'s (CRI) three-phase massively parallel processing program. In this report we describe the architecture of the T3D, as well as the CRAFT (Cray Research Adaptive Fortran) programming model, and contrast it with PVM, which is also supported on the T3D We present some performance data based on the NAS Parallel Benchmarks to illustrate both architectural and software features of the T3D.

Modeling Students' Memory for Application in Adaptive Educational Systems

Science.gov (United States)

Pelánek, Radek

2015-01-01

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

A heuristic model for working memory deficit in schizophrenia.

Science.gov (United States)

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

2016-11-01

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

Dynamic effects of memory in a cobweb model with competing technologies

Science.gov (United States)

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.

A mathematical model of capacious and efficient memory that survives trauma

Science.gov (United States)

Srivastava, Vipin; Edwards, S. F.

2004-02-01

The brain's memory system can store without any apparent constraint, it recalls stored information efficiently and it is robust against lesion. Existing models of memory do not fully account for all these features. The model due to Hopfield (Proc. Natl. Acad. Sci. USA 79 (1982) 2554) based on Hebbian learning (The Organization of Behaviour, Wiley, New York, 1949) shows an early saturation of memory with the retrieval from memory becoming slow and unreliable before collapsing at this limit. Our hypothesis (Physica A 276 (2000) 352) that the brain might store orthogonalized information improved the situation in many ways but was still constrained in that the information to be stored had to be linearly independent, i.e., signals that could be expressed as linear combinations of others had to be excluded. Here we present a model that attempts to address the problem quite comprehensively in the background of the above attributes of the brain. We demonstrate that if the brain devolves incoming signals in analogy with Fourier analysis, the noise created by interference of stored signals diminishes systematically (which yields prompt retrieval) and most importantly it can withstand partial damages to the brain.

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

Directory of Open Access Journals (Sweden)

Dun C

2016-07-01

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

PMCAP: A Threat Model of Process Memory Data on the Windows Operating System

Directory of Open Access Journals (Sweden)

Jiaye Pan

2017-01-01

Full Text Available Research on endpoint security involves both traditional PC platform and prevalent mobile platform, among which the analysis of software vulnerability and malware is one of the important contents. For researchers, it is necessary to carry out nonstop exploration of the insecure factors in order to better protect the endpoints. Driven by this motivation, we propose a new threat model named Process Memory Captor (PMCAP on the Windows operating system which threatens the live process volatile memory data. Compared with other threats, PMCAP aims at dynamic data in the process memory and uses a noninvasive approach for data extraction. In this paper we describe and analyze the model and then give a detailed implementation taking four popular web browsers IE, Edge, Chrome, and Firefox as examples. Finally, the model is verified through real experiments and case studies. Compared with existing technologies, PMCAP can extract valuable data at a lower cost; some techniques in the model are also suitable for memory forensics and malware analysis.

Computational modelling of memory retention from synapse to behaviour

Science.gov (United States)

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

2013-03-01

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

Computational modelling of memory retention from synapse to behaviour

International Nuclear Information System (INIS)

Van Rossum, Mark C W; Shippi, Maria

2013-01-01

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

Memory rehabilitation for the working memory of patients with multiple sclerosis (MS).

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Mousavi, Shokoufeh; Zare, Hossein; Etemadifar, Masoud; Taher Neshatdoost, Hamid

2018-05-01

The main cognitive impairments in multiple sclerosis (MS) affect the working memory, processing speed, and performances that are in close interaction with one another. Cognitive problems in MS are influenced to a lesser degree by disease recovery medications or treatments,but cognitive rehabilitation is considered one of the promising methods for cure. There is evidence regarding the effectiveness of cognitive rehabilitation for MS patients in various stages of the disease. Since the impairment in working memory is one of the main MS deficits, a particular training that affects this cognitive domain can be of a great value. This study aims to determine the effectiveness of memory rehabilitation on the working memory performance of MS patients. Sixty MS patients with cognitive impairment and similar in terms of demographic characteristics, duration of disease, neurological problems, and mental health were randomly assigned to three groups: namely, experimental, placebo, and control. Patients' cognitive evaluation incorporated baseline assessments immediately post-intervention and 5 weeks post-intervention. The experimental group received a cognitive rehabilitation program in one-hour sessions on a weekly basis for 8 weeks. The placebo group received relaxation techniques on a weekly basis; the control group received no intervention. The results of this study showed that the cognitive rehabilitation program had a positive effect on the working memory performance of patients with MS in the experimental group. These results were achieved in immediate evaluation (post-test) and follow-up 5 weeks after intervention. There was no significant difference in working memory performance between the placebo group and the control group. According to the study, there is evidence for the effectiveness of a memory rehabilitation program for the working memory of patients with MS. Cognitive rehabilitation can improve working memory disorders and have a positive effect on the

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

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

2016-09-15

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

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

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

2009-01-01

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

Improvement and speed optimization of numerical tsunami modelling program using OpenMP technology

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Chernov, A.; Zaytsev, A.; Yalciner, A.; Kurkin, A.

2009-04-01

Currently, the basic problem of tsunami modeling is low speed of calculations which is unacceptable for services of the operative notification. Existing algorithms of numerical modeling of hydrodynamic processes of tsunami waves are developed without taking the opportunities of modern computer facilities. There is an opportunity to have considerable acceleration of process of calculations by using parallel algorithms. We discuss here new approach to parallelization tsunami modeling code using OpenMP Technology (for multiprocessing systems with the general memory). Nowadays, multiprocessing systems are easily accessible for everyone. The cost of the use of such systems becomes much lower comparing to the costs of clusters. This opportunity also benefits all programmers to apply multithreading algorithms on desktop computers of researchers. Other important advantage of the given approach is the mechanism of the general memory - there is no necessity to send data on slow networks (for example Ethernet). All memory is the common for all computing processes; it causes almost linear scalability of the program and processes. In the new version of NAMI DANCE using OpenMP technology and multi-threading algorithm provide 80% gain in speed in comparison with the one-thread version for dual-processor unit. The speed increased and 320% gain was attained for four core processor unit of PCs. Thus, it was possible to reduce considerably time of performance of calculations on the scientific workstations (desktops) without complete change of the program and user interfaces. The further modernization of algorithms of preparation of initial data and processing of results using OpenMP looks reasonable. The final version of NAMI DANCE with the increased computational speed can be used not only for research purposes but also in real time Tsunami Warning Systems.

Increasing dimension of structures by 4D printing shape memory polymers via fused deposition modeling

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Hu, G. F.; Damanpack, A. R.; Bodaghi, M.; Liao, W. H.

2017-12-01

The main objective of this paper is to introduce a 4D printing method to program shape memory polymers (SMPs) during fabrication process. Fused deposition modeling (FDM) as a filament-based printing method is employed to program SMPs during depositing the material. This method is implemented to fabricate complicated polymeric structures by self-bending features without need of any post-programming. Experiments are conducted to demonstrate feasibility of one-dimensional (1D)-to 2D and 2D-to-3D self-bending. It is shown that 3D printed plate structures can transform into masonry-inspired 3D curved shell structures by simply heating. Good reliability of SMP programming during printing process is also demonstrated. A 3D macroscopic constitutive model is established to simulate thermo-mechanical features of the printed SMPs. Governing equations are also derived to simulate programming mechanism during printing process and shape change of self-bending structures. In this respect, a finite element formulation is developed considering von-Kármán geometric nonlinearity and solved by implementing iterative Newton-Raphson scheme. The accuracy of the computational approach is checked with experimental results. It is demonstrated that the theoretical model is able to replicate the main characteristics observed in the experiments. This research is likely to advance the state of the art FDM 4D printing, and provide pertinent results and computational tool that are instrumental in design of smart materials and structures with self-bending features.

A visual LISP program for voxelizing AutoCAD solid models

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Marschallinger, Robert; Jandrisevits, Carmen; Zobl, Fritz

2015-01-01

AutoCAD solid models are increasingly recognized in geological and geotechnical 3D modeling. In order to bridge the currently existing gap between AutoCAD solid models and the grid modeling realm, a Visual LISP program is presented that converts AutoCAD solid models into voxel arrays. Acad2Vox voxelizer works on a 3D-model that is made up of arbitrary non-overlapping 3D-solids. After definition of the target voxel array geometry, 3D-solids are scanned at grid positions and properties are streamed to an ASCII output file. Acad2Vox has a novel voxelization strategy that combines a hierarchical reduction of sampling dimensionality with an innovative use of AutoCAD-specific methods for a fast and memory-saving operation. Acad2Vox provides georeferenced, voxelized analogs of 3D design data that can act as regions-of-interest in later geostatistical modeling and simulation. The Supplement includes sample geological solid models with instructions for practical work with Acad2Vox.

The Vast Universe of T Cell Diversity: Subsets of Memory Cells and Their Differentiation.

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Jandus, Camilla; Usatorre, Amaia Martínez; Viganò, Selena; Zhang, Lianjun; Romero, Pedro

2017-01-01

The T cell receptor confers specificity for antigen recognition to T cells. By the first encounter with the cognate antigen, reactive T cells initiate a program of expansion and differentiation that will define not only the ultimate quantity of specific cells that will be generated, but more importantly their quality and functional heterogeneity. Recent achievements using mouse model infection systems have helped to shed light into the complex network of factors that dictate and sustain memory T cell differentiation, ranging from antigen load, TCR signal strength, metabolic fitness, transcriptional programs, and proliferative potential. The different models of memory T cell differentiation are discussed in this chapter, and key phenotypic and functional attributes of memory T cell subsets are presented, both for mouse and human cells. Therapeutic manipulation of memory T cell generation is expected to provide novel unique ways to optimize current immunotherapies, both in infection and cancer.

A Probabilistic Palimpsest Model of Visual Short-term Memory

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

2015-01-01

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

Low-voltage high-speed programming gate-all-around floating gate memory cell with tunnel barrier engineering

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Hamzah, Afiq; Ezaila Alias, N.; Ismail, Razali

2018-06-01

The aim of this study is to investigate the memory performances of gate-all-around floating gate (GAA-FG) memory cell implementing engineered tunnel barrier concept of variable oxide thickness (VARIOT) of low-k/high-k for several high-k (i.e., Si3N4, Al2O3, HfO2, and ZrO2) with low-k SiO2 using three-dimensional (3D) simulator Silvaco ATLAS. The simulation work is conducted by initially determining the optimized thickness of low-k/high-k barrier-stacked and extracting their Fowler–Nordheim (FN) coefficients. Based on the optimized parameters the device performances of GAA-FG for fast program operation and data retention are assessed using benchmark set by 6 and 8 nm SiO2 tunnel layer respectively. The programming speed has been improved and wide memory window with 30% increment from conventional SiO2 has been obtained using SiO2/Al2O3 tunnel layer due to its thin low-k dielectric thickness. Furthermore, given its high band edges only 1% of charge-loss is expected after 10 years of ‑3.6/3.6 V gate stress.

Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model

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Orth, Rene; Koster, Randal Dean; Seneviratne, Sonia I.

2013-01-01

Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.

A cross-lagged model of the reciprocal associations of loneliness and memory functioning.

Science.gov (United States)

Ayalon, Liat; Shiovitz-Ezra, Sharon; Roziner, Ilan

2016-05-01

The study was designed to evaluate the reciprocal associations of loneliness and memory functioning using a cross-lagged model. The study was based on the psychosocial questionnaire of the Health and Retirement Study, which is a U.S. nationally representative survey of individuals over the age of 50 and their spouses of any age. A total of 1,225 respondents had complete data on the loneliness measure in 2004 and at least in 1 of the subsequent waves (e.g., 2008, 2012) and were maintained for analysis. A cross-lagged model was estimated to examine the reciprocal associations of loneliness and memory functioning, controlling for age, gender, education, depressive symptoms, number of medical conditions, and the number of close social relationships. The model had adequate fit indices: χ2(860, N = 1,225) = 1,401.54, p memory functioning was nonsignificant, B(SE) = -.11(.08), p = .15, whereas the lagged effect of memory functioning on loneliness was significant, B(SE) = -.06(.02), p = .01, indicating that lower levels of memory functioning precede higher levels of loneliness 4 years afterward. Further research is required to better understand the mechanisms responsible for the temporal association between reduced memory functioning and increased loneliness. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

An approach to modeling tensile–compressive asymmetry for martensitic shape memory alloys

International Nuclear Information System (INIS)

Zaki, Wael

2010-01-01

In this paper, the asymmetric tensile–compressive behavior of shape memory alloys is modeled based on the mathematical framework of Raniecki and Mróz (2008 Acta Mech. 195 81–102). The framework allows the definition of smooth, non-symmetric, pressure-insensitive yield functions that are used here to incorporate tensile–compressive modeling capabilities into the Zaki–Moumni (ZM) model for shape memory materials. It is found that, despite some increased complexity, the generalized model is capable of producing satisfactory results that agree with uniaxial experimental data taken from the literature

An Evaluation of a Teacher Training Program at the United States Holocaust Memorial Museum

Science.gov (United States)

DeBerry, LaMonnia Edge

2015-01-01

The purpose of this mixed methods study was to explore the effects of the United States Holocaust Memorial Museum's work in partnering with professors from universities across the United States during a 1-year collaborative partnership through an educational program referred to as Belfer First Step Holocaust Institute for Teacher Educators (BFS…

Dynamic State Space Partitioning for External Memory Model Checking

DEFF Research Database (Denmark)

Evangelista, Sami; Kristensen, Lars Michael

2009-01-01

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

Reactivation in working memory: an attractor network model of free recall.

Science.gov (United States)

Lansner, Anders; Marklund, Petter; Sikström, Sverker; Nilsson, Lars-Göran

2013-01-01

The dynamic nature of human working memory, the general-purpose system for processing continuous input, while keeping no longer externally available information active in the background, is well captured in immediate free recall of supraspan word-lists. Free recall tasks produce several benchmark memory phenomena, like the U-shaped serial position curve, reflecting enhanced memory for early and late list items. To account for empirical data, including primacy and recency as well as contiguity effects, we propose here a neurobiologically based neural network model that unifies short- and long-term forms of memory and challenges both the standard view of working memory as persistent activity and dual-store accounts of free recall. Rapidly expressed and volatile synaptic plasticity, modulated intrinsic excitability, and spike-frequency adaptation are suggested as key cellular mechanisms underlying working memory encoding, reactivation and recall. Recent findings on the synaptic and molecular mechanisms behind early LTP and on spiking activity during delayed-match-to-sample tasks support this view.

Reactivation in working memory: an attractor network model of free recall.

Directory of Open Access Journals (Sweden)

Anders Lansner

Full Text Available The dynamic nature of human working memory, the general-purpose system for processing continuous input, while keeping no longer externally available information active in the background, is well captured in immediate free recall of supraspan word-lists. Free recall tasks produce several benchmark memory phenomena, like the U-shaped serial position curve, reflecting enhanced memory for early and late list items. To account for empirical data, including primacy and recency as well as contiguity effects, we propose here a neurobiologically based neural network model that unifies short- and long-term forms of memory and challenges both the standard view of working memory as persistent activity and dual-store accounts of free recall. Rapidly expressed and volatile synaptic plasticity, modulated intrinsic excitability, and spike-frequency adaptation are suggested as key cellular mechanisms underlying working memory encoding, reactivation and recall. Recent findings on the synaptic and molecular mechanisms behind early LTP and on spiking activity during delayed-match-to-sample tasks support this view.

Reactivation in Working Memory: An Attractor Network Model of Free Recall

Science.gov (United States)

Lansner, Anders; Marklund, Petter; Sikström, Sverker; Nilsson, Lars-Göran

2013-01-01

The dynamic nature of human working memory, the general-purpose system for processing continuous input, while keeping no longer externally available information active in the background, is well captured in immediate free recall of supraspan word-lists. Free recall tasks produce several benchmark memory phenomena, like the U-shaped serial position curve, reflecting enhanced memory for early and late list items. To account for empirical data, including primacy and recency as well as contiguity effects, we propose here a neurobiologically based neural network model that unifies short- and long-term forms of memory and challenges both the standard view of working memory as persistent activity and dual-store accounts of free recall. Rapidly expressed and volatile synaptic plasticity, modulated intrinsic excitability, and spike-frequency adaptation are suggested as key cellular mechanisms underlying working memory encoding, reactivation and recall. Recent findings on the synaptic and molecular mechanisms behind early LTP and on spiking activity during delayed-match-to-sample tasks support this view. PMID:24023690

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

Science.gov (United States)

de Ribaupierre, Anik; Bailleux, Christine

2000-01-01

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

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

Science.gov (United States)

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.

Fechner’s law in metacognition: a quantitative model of visual working memory confidence

Science.gov (United States)

van den Berg, Ronald; Yoo, Aspen H.; Ma, Wei Ji

2016-01-01

Although visual working memory (VWM) has been studied extensively, it is unknown how people form confidence judgments about their memories. Peirce (1878) speculated that Fechner’s law – which states that sensation is proportional to the logarithm of stimulus intensity – might apply to confidence reports. Based on this idea, we hypothesize that humans map the precision of their VWM contents to a confidence rating through Fechner’s law. We incorporate this hypothesis into the best available model of VWM encoding and fit it to data from a delayed-estimation experiment. The model provides an excellent account of human confidence rating distributions as well as the relation between performance and confidence. Moreover, the best-fitting mapping in a model with a highly flexible mapping closely resembles the logarithmic mapping, suggesting that no alternative mapping exists that accounts better for the data than Fechner's law. We propose a neural implementation of the model and find that this model also fits the behavioral data well. Furthermore, we find that jointly fitting memory errors and confidence ratings boosts the power to distinguish previously proposed VWM encoding models by a factor of 5.99 compared to fitting only memory errors. Finally, we show that Fechner's law also accounts for metacognitive judgments in a word recognition memory task, which is a first indication that it may be a general law in metacognition. Our work presents the first model to jointly account for errors and confidence ratings in VWM and could lay the groundwork for understanding the computational mechanisms of metacognition. PMID:28221087

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

Science.gov (United States)

Ullman, Michael T.; Lovelett, Jarrett T.

2018-01-01

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

Programming Models in HPC

Energy Technology Data Exchange (ETDEWEB)

Shipman, Galen M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-06-13

These are the slides for a presentation on programming models in HPC, at the Los Alamos National Laboratory's Parallel Computing Summer School. The following topics are covered: Flynn's Taxonomy of computer architectures; single instruction single data; single instruction multiple data; multiple instruction multiple data; address space organization; definition of Trinity (Intel Xeon-Phi is a MIMD architecture); single program multiple data; multiple program multiple data; ExMatEx workflow overview; definition of a programming model, programming languages, runtime systems; programming model and environments; MPI (Message Passing Interface); OpenMP; Kokkos (Performance Portable Thread-Parallel Programming Model); Kokkos abstractions, patterns, policies, and spaces; RAJA, a systematic approach to node-level portability and tuning; overview of the Legion Programming Model; mapping tasks and data to hardware resources; interoperability: supporting task-level models; Legion S3D execution and performance details; workflow, integration of external resources into the programming model.

A buffer model of memory encoding and temporal correlations in retrieval.

Science.gov (United States)

Lehman, Melissa; Malmberg, Kenneth J

2013-01-01

Atkinson and Shiffrin's (1968) dual-store model of memory includes structural aspects of memory along with control processes. The rehearsal buffer is a process by which items are kept in mind and long-term episodic traces are formed. The model has been both influential and controversial. Here, we describe a novel variant of Atkinson and Shiffrin's buffer model within the framework of the retrieving effectively from memory theory (REM; Shiffrin & Steyvers, 1997) that accounts for findings previously thought to be difficult for such models to explain. This model assumes a limited-capacity buffer where information is stored about items, along with information about associations between items and between items and the context in which they are studied. The strength of association between items and context is limited by the number of items simultaneously occupying the buffer (Lehman & Malmberg, 2009). The contents of the buffer are managed by complementary processes of rehearsal and compartmentalization (Lehman & Malmberg, 2011). New findings that directly test a priori predictions of the model are reported, including serial position effects and conditional and first recall probabilities in immediate and delayed free recall, in a continuous distractor paradigm, and in experiments using list-length manipulations of single-item and paired-item study lists.

A Neuroanatomical Model of Prefrontal Inhibitory Modulation of Memory Retrieval

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Depue, Brendan E.

2012-01-01

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

Activation and Binding in Verbal Working Memory: A Dual-Process Model for the Recognition of Nonwords

Science.gov (United States)

Oberauer, Klauss; Lange, Elke B.

2009-01-01

The article presents a mathematical model of short-term recognition based on dual-process models and the three-component theory of working memory [Oberauer, K. (2002). Access to information in working memory: Exploring the focus of attention. "Journal of Experimental Psychology: Learning, Memory, and Cognition, 28", 411-421]. Familiarity arises…

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

Science.gov (United States)

Sundstrøm, Martin

2011-07-01

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

A simplified memory network model based on pattern formations

Science.gov (United States)

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

2014-12-01

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

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

Science.gov (United States)

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

2017-06-01

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

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

Science.gov (United States)

Başar, Erol

2005-01-01

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

Working Memory Training in Children with Mild Intellectual Disability, Through Designed Computerized Program

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Mona Delavarian

2015-12-01

Full Text Available Objectives: The aim of this research is designing a computerized program, in game format, for working memory training in mild intellectual disabled children. Methods: 24 students participated as test and control groups. The auditory and visual-spatial WM were assessed by primary test, which included computerized Wechsler numerical forward and backward sub- tests, and secondary tests, which contained three parts: dual visual-spatial test, auditory test, and a one-syllable word recalling test. Results: The results showed significant differnces between working memory capacity in the intellectually disabled children and normal ones (P-value<0.00001. After using the computerized working memory training, Visual-spatial WM, auditory WM, and speaking were improved in the trained group. The mentioned four tests showed significant differences between pre-test and post-test. The trained group showed more improvements in forward tasks. The trained participant’s processing speed increased with training. Discussion: According to the results, comprehensive human-computer interfaces and the aplication of computer in children training, especially in traing of intellectual disabled children with impairements in visual and auditory perceptions, could be more effective and vaulable.

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

Science.gov (United States)

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

2011-01-01

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

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

NARCIS (Netherlands)

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

2013-01-01

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

Effect of quantum learning model in improving creativity and memory

Science.gov (United States)

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

2018-04-01

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

Time Series with Long Memory

OpenAIRE

西埜, 晴久

2004-01-01

The paper investigates an application of long-memory processes to economic time series. We show properties of long-memory processes, which are motivated to model a long-memory phenomenon in economic time series. An FARIMA model is described as an example of long-memory model in statistical terms. The paper explains basic limit theorems and estimation methods for long-memory processes in order to apply long-memory models to economic time series.

Avalanches and generalized memory associativity in a network model for conscious and unconscious mental functioning

Science.gov (United States)

Siddiqui, Maheen; Wedemann, Roseli S.; Jensen, Henrik Jeldtoft

2018-01-01

We explore statistical characteristics of avalanches associated with the dynamics of a complex-network model, where two modules corresponding to sensorial and symbolic memories interact, representing unconscious and conscious mental processes. The model illustrates Freud's ideas regarding the neuroses and that consciousness is related with symbolic and linguistic memory activity in the brain. It incorporates the Stariolo-Tsallis generalization of the Boltzmann Machine in order to model memory retrieval and associativity. In the present work, we define and measure avalanche size distributions during memory retrieval, in order to gain insight regarding basic aspects of the functioning of these complex networks. The avalanche sizes defined for our model should be related to the time consumed and also to the size of the neuronal region which is activated, during memory retrieval. This allows the qualitative comparison of the behaviour of the distribution of cluster sizes, obtained during fMRI measurements of the propagation of signals in the brain, with the distribution of avalanche sizes obtained in our simulation experiments. This comparison corroborates the indication that the Nonextensive Statistical Mechanics formalism may indeed be more well suited to model the complex networks which constitute brain and mental structure.

Self-defining memories, scripts, and the life story: narrative identity in personality and psychotherapy.

Science.gov (United States)

Singer, Jefferson A; Blagov, Pavel; Berry, Meredith; Oost, Kathryn M

2013-12-01

An integrative model of narrative identity builds on a dual memory system that draws on episodic memory and a long-term self to generate autobiographical memories. Autobiographical memories related to critical goals in a lifetime period lead to life-story memories, which in turn become self-defining memories when linked to an individual's enduring concerns. Self-defining memories that share repetitive emotion-outcome sequences yield narrative scripts, abstracted templates that filter cognitive-affective processing. The life story is the individual's overarching narrative that provides unity and purpose over the life course. Healthy narrative identity combines memory specificity with adaptive meaning-making to achieve insight and well-being, as demonstrated through a literature review of personality and clinical research, as well as new findings from our own research program. A clinical case study drawing on this narrative identity model is also presented with implications for treatment and research. © 2012 Wiley Periodicals, Inc.

Nanographene charge trapping memory with a large memory window

International Nuclear Information System (INIS)

Meng, Jianling; Yang, Rong; Zhao, Jing; He, Congli; Wang, Guole; Shi, Dongxia; Zhang, Guangyu

2015-01-01

Nanographene is a promising alternative to metal nanoparticles or semiconductor nanocrystals for charge trapping memory. In general, a high density of nanographene is required in order to achieve high charge trapping capacity. Here, we demonstrate a strategy of fabrication for a high density of nanographene for charge trapping memory with a large memory window. The fabrication includes two steps: (1) direct growth of continuous nanographene film; and (2) isolation of the as-grown film into high-density nanographene by plasma etching. Compared with directly grown isolated nanographene islands, abundant defects and edges are formed in nanographene under argon or oxygen plasma etching, i.e. more isolated nanographene islands are obtained, which provides more charge trapping sites. As-fabricated nanographene charge trapping memory shows outstanding memory properties with a memory window as wide as ∼9 V at a relative low sweep voltage of ±8 V, program/erase speed of ∼1 ms and robust endurance of >1000 cycles. The high-density nanographene charge trapping memory provides an outstanding alternative for downscaling technology beyond the current flash memory. (paper)

Memory Reconsolidation and Computational Learning

Science.gov (United States)

2010-03-01

Siegelmann-Danieli and H.T. Siegelmann, "Robust Artificial Life Via Artificial Programmed Death," Artificial Inteligence 172(6-7), April 2008: 884-898. F...STATEMENT Unrestricted 13. SUPPLEMENTARY NOTES 20100402019 14. ABSTRACT Memory models are central to Artificial Intelligence and Machine...beyond [1]. The advances cited are a significant step toward creating Artificial Intelligence via neural networks at the human level. Our network

Determination of memory performance

International Nuclear Information System (INIS)

Gopych, P.M.

1999-01-01

Within the scope of testing statistical hypotheses theory a model definition and a computer method for model calculation of widely used in neuropsychology human memory performance (free recall, cued recall, and recognition probabilities), a model definition and a computer method for model calculation of intensities of cues used in experiments for testing human memory quality are proposed. Models for active and passive traces of memory and their relations are found. It was shown that autoassociative memory unit in the form of short two-layer artificial neural network with (or without) damages can be used for model description of memory performance in subjects with (or without) local brain lesions

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

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Masahiro Nakagawa

2010-01-01

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

Canonical Cortical Circuit Model Explains Rivalry, Intermittent Rivalry, and Rivalry Memory.

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Shashaank Vattikuti

2016-05-01

Full Text Available It has been shown that the same canonical cortical circuit model with mutual inhibition and a fatigue process can explain perceptual rivalry and other neurophysiological responses to a range of static stimuli. However, it has been proposed that this model cannot explain responses to dynamic inputs such as found in intermittent rivalry and rivalry memory, where maintenance of a percept when the stimulus is absent is required. This challenges the universality of the basic canonical cortical circuit. Here, we show that by including an overlooked realistic small nonspecific background neural activity, the same basic model can reproduce intermittent rivalry and rivalry memory without compromising static rivalry and other cortical phenomena. The background activity induces a mutual-inhibition mechanism for short-term memory, which is robust to noise and where fine-tuning of recurrent excitation or inclusion of sub-threshold currents or synaptic facilitation is unnecessary. We prove existence conditions for the mechanism and show that it can explain experimental results from the quartet apparent motion illusion, which is a prototypical intermittent rivalry stimulus.

Combining thermodynamic principles with Preisach models for superelastic shape memory alloy wires

International Nuclear Information System (INIS)

Doraiswamy, S; Rao, A; Srinivasa, A R

2011-01-01

We present a simple model for simulating the response of a superelastic shape memory alloy wire based on the thermodynamics of irreversible processes, which can simulate the full thermomechanical response including internal hysteresis loops, at different temperatures, with minimal data input. The key idea is to separate the dissipative response and the elastic response of shape memory alloys using a Gibbs potential based formulation, and then use a Preisach model for the dissipative part of the response. This enables better handling of the features observed in the superelastic response such as those due to changes in temperature and internal hysteresis loops. We compare the predicted response with experiments performed on 0.75 mm NiTi shape memory alloy wires at three different temperatures

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

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Florian eFiebig

2014-07-01

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

Constitutive modeling of SMA SMP multifunctional high performance smart adaptive shape memory composite

International Nuclear Information System (INIS)

Jarali, Chetan S; Raja, S; Upadhya, A R

2010-01-01

Materials design involving the thermomechanical constitutive modeling of shape memory alloy (SMA) and shape memory polymer (SMP) composites is a key topic in the development of smart adaptive shape memory composites (SASMC). In this work, a constitutive model for SASMC is developed. First, a one-dimensional SMA model, which can simulate the pseudoelastic (PE) and shape memory effects (SME) is presented. Subsequently, a one-dimensional SMP model able to reproduce the SME is addressed. Both SMA and SMP models are based on a single internal state variable, namely the martensite fraction and the frozen fraction, which can be expressed as a function of temperature. A consistent form of the analytical solution for the SMP model is obtained using the fourth-order Runge–Kutta method. Finally, the SASMC constitutive model is proposed, following two analytical homogenization approaches. One approach is based on an equivalent inclusion method and the other approach is the rule of mixtures. The SMA and SMP constitutive models are validated independently with experimental results. However, the validation of the composite model is performed using the two homogenization approaches and a close agreement in results is observed. Results regarding the isothermal and thermomechanical stress–strain responses are analyzed as a function of SMA volume fraction. Further, it is concluded that the proposed composite model is able to reproduce consistently the overall composite response by taking into consideration not only the phase transformations, variable modulus and transformation stresses in SMA but also the variable modulus, the evolution of stored strain and thermal strain in the SMP

Associative memory model with spontaneous neural activity

Science.gov (United States)

Kurikawa, Tomoki; Kaneko, Kunihiko

2012-05-01

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

Barkley's Parent Training Program, Working Memory Training and their Combination for Children with ADHD: Attention Deficit Hyperactivity Disorder.

Directory of Open Access Journals (Sweden)

Zahra Hosainzadeh Maleki

2014-06-01

Full Text Available The aim of the current study was to examine the effectiveness of Barkley's parent training program, working memory training and the combination of these two interventions for children with Attention deficit hyperactivity disorder (ADHD.In this study, 36 participants with ADHD (aged 6 to 12 years were selected by convenience sampling. Revision of the Swanson, Nolan and Pelham (SNAP questionnaire (SNAP-IV, Child Behavior Checklist (CBCL and clinical interviews were employed to diagnose ADHD. Wechsler Intelligence Scale for Children-Fourth Edition was also implemented. The participants were randomly assigned to the three intervention groups of Barkley's parent training program, working memory training and the combined group. SNAP-IV and CBCL were used as pre-tests and post-tests across all three groups. Data were analyzed using MANCOVA (SPSS version18.There was a significant difference (p< 0.05 in the decline of attention deficit and hyperactivity /impulsivity symptoms between the combined treatment group and working memory training group and also between the combined treatment group and the parent training group in SNAP. In terms of attention problems (experience-based subscales of CBCL, there was a significant difference (p< 0.001 between the combined treatment group and working memory training group. Furthermore, compared to the working memory training and parent training groups, the combined group demonstrated a significant decline (p< 0.01 in clinical symptoms of ADHD (based on DSM.It was revealed that combined treatment in comparison with the other two methods suppressed the clinical symptoms of ADHD more significantly.

An ACL2 Mechanization of an Axiomatic Framework for Weak Memory

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Benjamin Selfridge

2014-06-01

Full Text Available Proving the correctness of programs written for multiple processors is a challenging problem, due in no small part to the weaker memory guarantees afforded by most modern architectures. In particular, the existence of store buffers means that the programmer can no longer assume that writes to different locations become visible to all processors in the same order. However, all practical architectures do provide a collection of weaker guarantees about memory consistency across processors, which enable the programmer to write provably correct programs in spite of a lack of full sequential consistency. In this work, we present a mechanization in the ACL2 theorem prover of an axiomatic weak memory model (introduced by Alglave et al.. In the process, we provide a new proof of an established theorem involving these axioms.

Evaluating Multicore Algorithms on the Unified Memory Model

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John E. Savage

2009-01-01

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

A dependability modeling of software under memory faults for digital system in nuclear power plants

International Nuclear Information System (INIS)

Choi, J. G.; Seong, P. H.

1997-01-01

In this work, an analytic approach to the dependability of software in the operational phase is suggested with special attention to the hardware fault effects on the software behavior : The hardware faults considered are memory faults and the dependability measure in question is the reliability. The model is based on the simple reliability theory and the graph theory which represents the software with graph composed of nodes and arcs. Through proper transformation, the graph can be reduced to a simple two-node graph and the software reliability is derived from this graph. Using this model, we predict the reliability of an application software in the digital system (ILS) in the nuclear power plant and show the sensitivity of the software reliability to the major physical parameters which affect the software failure in the normal operation phase. We also found that the effects of the hardware faults on the software failure should be considered for predicting the software dependability accurately in operation phase, especially for the software which is executed frequently. This modeling method is particularly attractive for the medium size programs such as the microprocessor-based nuclear safety logic program. (author)

Modeling the behaviour of shape memory materials under large deformations

Science.gov (United States)

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

2017-06-01

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

A model of shape memory materials with hierarchical twinning: statics and dynamics

International Nuclear Information System (INIS)

Saxena, A.; Bishop, A.R.; Wu, Y.; Lookman, T.

1995-01-01

We consider a model of shape memory materials in which hierarchical twinning near the habit plane (austenite-martensite interface) is a new and crucial ingredient. The model includes (1) a triple-well potential (φ 6 model) in local shear strain, (2) strain gradient terms up to second order in strain and fourth order in gradient, and (3) all symmetry allowed compositional fluctuation-induced strain gradient terms. The last term favors hierarchy which enables communication between macroscopic (cm) and microscopic (A) regions essential for shape memory. Hierarchy also stabilizes tweed formation (criss-cross patterns of twins). External stress or pressure modulates (''patterns'') the spacing of domain walls. Therefore the ''pattern'' is encoded in the modulated hierarchical variation of the depth and width of the twins. This hierarchy of length scales provides a related hierarchy of time scales and thus the possibility of non-exponential decay. The four processes of the complete shape memory cycle-write, record, erase and recall-are explained within this model. Preliminary results based on 2D molecular dynamics are shown for tweed and hierarchy formation. (orig.)

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

International Nuclear Information System (INIS)

Ngai, K.L.; Hsia, Y.

1982-01-01

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

The Effect of Programmed Physical Exercise to Attention and Working Memory Score in Medical Students

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Kevin Fachri Muhammad

2015-06-01

Full Text Available Background: Attention and working memory are two cognitive domain crucial for activities of daily living. Physical exercise increases the level of BDNF, IGF-1, and VEGF which contributes in attention and working memory processes.This study was conducted to analyze improvement of attention and working memory after programmed physical exercise of Pendidikan Dasar XXI Atlas Medical Pioneer (Pendas XXI AMP. Methods: An analytic observational study was conducted on 47 students from Faculty of Medicine, Universitas Padjadjaran during September-November 2012. Attention was assessed using digit span backward test, stroop test, visual search task, and trail making test. Working memory was assessed using digit span forward test and digit symbol test. Assessment was done on the 11th and 19th week of Pendas XXI AMP. Data distribution was tested first using a test of normality, and then analyzed using T-Dependent Test and Wilcoxon Test Results: Significant improvement was noted for attention in males based on working time for stroop test (26.50±5.66 to 22.03±3.78 seconds, working memory in males based on digit symbol test score (43.96±6.14 to 53.36±5.26 points, attention in females based on reaction time of visual search task for target absent (0.92±0.07 to 0.87±0.07 seconds, and working memory in females based on digit span forward score (5.42±1.30 to 6.63±1.07 points and digit symbol test score (42.47±5.95 to 53.84±5.33 points. Conclusions: Exercise in Pendas XXI AMP improves attention and working memory for college students in Faculty of Medicine Universitas Padjadjaran.

Cycle accurate and cycle reproducible memory for an FPGA based hardware accelerator

Science.gov (United States)

Asaad, Sameh W.; Kapur, Mohit

2016-03-15

A method, system and computer program product are disclosed for using a Field Programmable Gate Array (FPGA) to simulate operations of a device under test (DUT). The DUT includes a device memory having a number of input ports, and the FPGA is associated with a target memory having a second number of input ports, the second number being less than the first number. In one embodiment, a given set of inputs is applied to the device memory at a frequency Fd and in a defined cycle of time, and the given set of inputs is applied to the target memory at a frequency Ft. Ft is greater than Fd and cycle accuracy is maintained between the device memory and the target memory. In an embodiment, a cycle accurate model of the DUT memory is created by separating the DUT memory interface protocol from the target memory storage array.

Limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method for the parameter estimation on geographically weighted ordinal logistic regression model (GWOLR)

Science.gov (United States)

Saputro, Dewi Retno Sari; Widyaningsih, Purnami

2017-08-01

In general, the parameter estimation of GWOLR model uses maximum likelihood method, but it constructs a system of nonlinear equations, making it difficult to find the solution. Therefore, an approximate solution is needed. There are two popular numerical methods: the methods of Newton and Quasi-Newton (QN). Newton's method requires large-scale time in executing the computation program since it contains Jacobian matrix (derivative). QN method overcomes the drawback of Newton's method by substituting derivative computation into a function of direct computation. The QN method uses Hessian matrix approach which contains Davidon-Fletcher-Powell (DFP) formula. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is categorized as the QN method which has the DFP formula attribute of having positive definite Hessian matrix. The BFGS method requires large memory in executing the program so another algorithm to decrease memory usage is needed, namely Low Memory BFGS (LBFGS). The purpose of this research is to compute the efficiency of the LBFGS method in the iterative and recursive computation of Hessian matrix and its inverse for the GWOLR parameter estimation. In reference to the research findings, we found out that the BFGS and LBFGS methods have arithmetic operation schemes, including O(n2) and O(nm).

A memory-based model of posttraumatic stress disorder

DEFF Research Database (Denmark)

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

2008-01-01

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

Structural Breaks and Long Memory Property in Korean Won Exchange Rates: Adaptive FIGARCH Model

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Young Wook Han

2011-06-01

Full Text Available This paper explores the issue of structural breaks and long memory property in the conditional variance process of the Korean exchange rates. To analyze the above in detail, this paper examines the dynamics of the structural breaks and the long memory in the conditional variance process of the Korean exchange returns by using the daily KRW-USD and KRW-JPY exchange rates for the period from 2000 through 2007. In particular, this paper employs the Adaptive FIGARCH model of Baillie and Morana (2009 which account for the structural breaks and the long memory property together. This paper also finds that the new Adaptive FIGARCH model outperforms the usual FIGARCH model of Baillie et al. (1996 when the structural breaks are present and that the long memory property in the conditional variance process of the Korean exchange returns is significantly reduced after the structural breaks are accounted for. Thus, these results suggest that the upward biased long memory property observed in the conditional variance process of the Korean exchange returns could partially have been imparted as a result of neglecting the structural breaks.

Bayesian Inference on the Memory Parameter for Gamma-Modulated Regression Models

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Plinio Andrade

2015-09-01

Full Text Available In this work, we propose a Bayesian methodology to make inferences for the memory parameter and other characteristics under non-standard assumptions for a class of stochastic processes. This class generalizes the Gamma-modulated process, with trajectories that exhibit long memory behavior, as well as decreasing variability as time increases. Different values of the memory parameter influence the speed of this decrease, making this heteroscedastic model very flexible. Its properties are used to implement an approximate Bayesian computation and MCMC scheme to obtain posterior estimates. We test and validate our method through simulations and real data from the big earthquake that occurred in 2010 in Chile.

Model checking a cache coherence protocol for a Java DSM implementation

NARCIS (Netherlands)

J. Pang; W.J. Fokkink (Wan); R. Hofman (Rutger); R. Veldema

2007-01-01

textabstractJackal is a fine-grained distributed shared memory implementation of the Java programming language. It aims to implement Java's memory model and allows multithreaded Java programs to run unmodified on a distributed memory system. It employs a multiple-writer cache coherence

Modelling Long Memory Volatility in Agricultural Commodity Futures Returns

NARCIS (Netherlands)

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

2009-01-01

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

Modelling Long Memory Volatility in Agricultural Commodity Futures Returns

NARCIS (Netherlands)

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

2012-01-01

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

Effects on locomotion and memory in 2 models of cerebral hypoperfusion in male Wistar rats.

Science.gov (United States)

Martínez-Díaz, J A; García, L I; Hernández, M E; Aranda-Abreu, G E

2015-09-01

Cerebral ischaemia is one of the most common neurological diseases worldwide. Its many sequelae range from motor and sensory symptoms to cognitive decline and dementia. Animal models of cerebral ischaemia/hypoperfusion elicit effects on long term memory; however, the effects of these procedures on short term memory are not clearly understood and effects induced by alternative hypoperfusion models are completely unknown. We evaluated the effects of 2 cerebral hyperperfusion models on memory in 3-month-old male rats. Episodic memory and working memory were assessed using the new object recognition test and the spontaneous alteration test, respectively. Neurological assessment was also performed, along with an open field test to evaluate locomotor activity. Rats in both hyperperfusion models displayed no cognitive changes. Rats with unilateral left-sided ligation plus temporary ligation of the right carotid tended to show slightly impaired performance on the new object recognition test on the second day after the procedure. In contrast, the group with permanent unilateral ligation tended to display alterations in working and episodic memory 9 days after the procedure, but they subsequently recovered. Despite these differences, both hypoperfusion groups displayed clear signs of motor impairment 2 days after the procedure, as reflected by their decreased locomotor activity during the open field test. Copyright © 2014 Sociedad Española de Neurología. Published by Elsevier España, S.L.U. All rights reserved.

A Neural Network Model of the Visual Short-Term Memory

DEFF Research Database (Denmark)

Petersen, Anders; Kyllingsbæk, Søren; Hansen, Lars Kai

2009-01-01

In this paper a neural network model of Visual Short-Term Memory (VSTM) is presented. The model links closely with Bundesen’s (1990) well-established mathematical theory of visual attention. We evaluate the model’s ability to fit experimental data from a classical whole and partial report study...

Performance analysis and comparison of a minimum interconnections direct storage model with traditional neural bidirectional memories.

Science.gov (United States)

Bhatti, A Aziz

2009-12-01

This study proposes an efficient and improved model of a direct storage bidirectional memory, improved bidirectional associative memory (IBAM), and emphasises the use of nanotechnology for efficient implementation of such large-scale neural network structures at a considerable lower cost reduced complexity, and less area required for implementation. This memory model directly stores the X and Y associated sets of M bipolar binary vectors in the form of (MxN(x)) and (MxN(y)) memory matrices, requires O(N) or about 30% of interconnections with weight strength ranging between +/-1, and is computationally very efficient as compared to sequential, intraconnected and other bidirectional associative memory (BAM) models of outer-product type that require O(N(2)) complex interconnections with weight strength ranging between +/-M. It is shown that it is functionally equivalent to and possesses all attributes of a BAM of outer-product type, and yet it is simple and robust in structure, very large scale integration (VLSI), optical and nanotechnology realisable, modular and expandable neural network bidirectional associative memory model in which the addition or deletion of a pair of vectors does not require changes in the strength of interconnections of the entire memory matrix. The analysis of retrieval process, signal-to-noise ratio, storage capacity and stability of the proposed model as well as of the traditional BAM has been carried out. Constraints on and characteristics of unipolar and bipolar binaries for improved storage and retrieval are discussed. The simulation results show that it has log(e) N times higher storage capacity, superior performance, faster convergence and retrieval time, when compared to traditional sequential and intraconnected bidirectional memories.

Early programming and late-acting checkpoints governing the development of CD4 T cell memory.

Science.gov (United States)

Dhume, Kunal; McKinstry, K Kai

2018-04-27

CD4 T cells contribute to protection against pathogens through numerous mechanisms. Incorporating the goal of memory CD4 T cell generation into vaccine strategies thus offers a powerful approach to improve their efficacy, especially in situations where humoral responses alone cannot confer long-term immunity. These threats include viruses such as influenza that mutate coat proteins to avoid neutralizing antibodies, but that are targeted by T cells that recognize more conserved protein epitopes shared by different strains. A major barrier in the design of such vaccines is that the mechanisms controlling the efficiency with which memory cells form remain incompletely understood. Here, we discuss recent insights into fate decisions controlling memory generation. We focus on the importance of three general cues: interleukin-2, antigen, and costimulatory interactions. It is increasingly clear that these signals have a powerful influence on the capacity of CD4 T cells to form memory during two distinct phases of the immune response. First, through 'programming' that occurs during initial priming, and second, through 'checkpoints' that operate later during the effector stage. These findings indicate that novel vaccine strategies must seek to optimize cognate interactions, during which interleukin-2-, antigen, and costimulation-dependent signals are tightly linked, well beyond initial antigen encounter to induce robust memory CD4 T cells. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Model-Driven Study of Visual Memory

National Research Council Canada - National Science Library

Sekuler, Robert

2004-01-01

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

Constitutive model for a stress- and thermal-induced phase transition in a shape memory polymer

International Nuclear Information System (INIS)

Guo, Xiaogang; Liu, Liwu; Liu, Yanju; Zhou, Bo; Leng, Jinsong

2014-01-01

Recently, increasing applications of shape memory polymers have pushed forward the development of appropriate constitutive models for smart materials such as the shape memory polymer. During the heating process, the phase transition, which is a continuous time-dependent process, happens in the shape memory polymer, and various individual phases will form at different configuration temperatures. In addition, these phases can generally be divided into two parts: the frozen and active phase (Liu Y et al 2006 Int. J. Plast. 22 279–313). During the heating or cooling process, the strain will be stored or released with the occurring phase transition between these two parts. Therefore, a shape memory effect emerges. In this paper, a new type of model was developed to characterize the variation of the volume fraction in a shape memory polymer during the phase transition. In addition to the temperature variation, the applied stress was also taken as a significant influence factor on the phase transition. Based on the experimental results, an exponential equation was proposed to describe the relationship between the stress and phase transition temperature. For the sake of describing the mechanical behaviors of the shape memory polymer, a three-dimensional constitutive model was established. Also, the storage strain, which was the key factor of the shape memory effect, was also discussed in detail. Similar to previous works, we first explored the effect of applied stress on storage strain. Through comparisons with the DMA and the creep experimental results, the rationality and accuracy of the new phase transition and constitutive model were finally verified. (paper)

Why are you telling me that? A conceptual model of the social function of autobiographical memory.

Science.gov (United States)

Alea, Nicole; Bluck, Susan

2003-03-01

In an effort to stimulate and guide empirical work within a functional framework, this paper provides a conceptual model of the social functions of autobiographical memory (AM) across the lifespan. The model delineates the processes and variables involved when AMs are shared to serve social functions. Components of the model include: lifespan contextual influences, the qualitative characteristics of memory (emotionality and level of detail recalled), the speaker's characteristics (age, gender, and personality), the familiarity and similarity of the listener to the speaker, the level of responsiveness during the memory-sharing process, and the nature of the social relationship in which the memory sharing occurs (valence and length of the relationship). These components are shown to influence the type of social function served and/or, the extent to which social functions are served. Directions for future empirical work to substantiate the model and hypotheses derived from the model are provided.

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

Science.gov (United States)

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

2017-12-13

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

Memory operation mechanism of fullerene-containing polymer memory

Energy Technology Data Exchange (ETDEWEB)

Nakajima, Anri, E-mail: anakajima@hiroshima-u.ac.jp; Fujii, Daiki [Research Institute for Nanodevice and Bio Systems, Hiroshima University, 1-4-2 Kagamiyama, Higashihiroshima, Hiroshima 739-8527 (Japan)

2015-03-09

The memory operation mechanism in fullerene-containing nanocomposite gate insulators was investigated while varying the kind of fullerene in a polymer gate insulator. It was cleared what kind of traps and which positions in the nanocomposite the injected electrons or holes are stored in. The reason for the difference in the easiness of programming was clarified taking the role of the charging energy of an injected electron into account. The dependence of the carrier dynamics on the kind of fullerene molecule was investigated. A nonuniform distribution of injected carriers occurred after application of a large magnitude programming voltage due to the width distribution of the polystyrene barrier between adjacent fullerene molecules. Through the investigations, we demonstrated a nanocomposite gate with fullerene molecules having excellent retention characteristics and a programming capability. This will lead to the realization of practical organic memories with fullerene-containing polymer nanocomposites.

Development of an engineering model for ferromagnetic shape memory alloys

International Nuclear Information System (INIS)

Tani, Yoshiaki; Todaka, Takashi; Enokizono, Masato

2008-01-01

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

The role of memory in the relationship between attention toward thin-ideal media and body dissatisfaction.

Science.gov (United States)

Jiang, Michelle Y W; Vartanian, Lenny R

2016-03-01

This study examined the causal relationship between attention and memory bias toward thin-body images, and the indirect effect of attending to thin-body images on women's body dissatisfaction via memory. In a 2 (restrained vs. unrestrained eaters) × 2 (long vs. short exposure) quasi-experimental design, female participants (n = 90) were shown images of thin models for either 7 s or 150 ms, and then completed a measure of body dissatisfaction and a recognition test to assess their memory for the images. Both restrained and unrestrained eaters in the long exposure condition had better recognition memory for images of thin models than did those in the short exposure condition. Better recognition memory for images of thin models was associated with lower body dissatisfaction. Finally, exposure duration to images of thin models had an indirect effect on body dissatisfaction through recognition memory. These findings suggest that memory for body-related information may be more critical in influencing women's body image than merely the exposure itself, and that targeting memory bias might enhance the effectiveness of cognitive bias modification programs.

A thermodynamically consistent model of shape-memory alloys

Czech Academy of Sciences Publication Activity Database

Benešová, Barbora

2011-01-01

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

Model checking a cache coherence protocol of a Java DSM implementation

NARCIS (Netherlands)

Pang, J.; Fokkink, W.J.; Hofman, R.; Veldema, R.S.

2007-01-01

Jackal is a fine-grained distributed shared memory implementation of the Java programming language. It aims to implement Java's memory model and allows multithreaded Java programs to run unmodified on a distributed memory system. It employs a multiple-writer cache coherence protocol. In this paper,

Extending and implementing the Self-adaptive Virtual Processor for distributed memory architectures

NARCIS (Netherlands)

van Tol, M.W.; Koivisto, J.

2011-01-01

Many-core architectures of the future are likely to have distributed memory organizations and need fine grained concurrency management to be used effectively. The Self-adaptive Virtual Processor (SVP) is an abstract concurrent programming model which can provide this, but the model and its current

[Artificial intelligence meeting neuropsychology. Semantic memory in normal and pathological aging].

Science.gov (United States)

Aimé, Xavier; Charlet, Jean; Maillet, Didier; Belin, Catherine

2015-03-01

Artificial intelligence (IA) is the subject of much research, but also many fantasies. It aims to reproduce human intelligence in its learning capacity, knowledge storage and computation. In 2014, the Defense Advanced Research Projects Agency (DARPA) started the restoring active memory (RAM) program that attempt to develop implantable technology to bridge gaps in the injured brain and restore normal memory function to people with memory loss caused by injury or disease. In another IA's field, computational ontologies (a formal and shared conceptualization) try to model knowledge in order to represent a structured and unambiguous meaning of the concepts of a target domain. The aim of these structures is to ensure a consensual understanding of their meaning and a univariant use (the same concept is used by all to categorize the same individuals). The first representations of knowledge in the AI's domain are largely based on model tests of semantic memory. This one, as a component of long-term memory is the memory of words, ideas, concepts. It is the only declarative memory system that resists so remarkably to the effects of age. In contrast, non-specific cognitive changes may decrease the performance of elderly in various events and instead report difficulties of access to semantic representations that affect the semantics stock itself. Some dementias, like semantic dementia and Alzheimer's disease, are linked to alteration of semantic memory. We propose in this paper, using the computational ontologies model, a formal and relatively thin modeling, in the service of neuropsychology: 1) for the practitioner with decision support systems, 2) for the patient as cognitive prosthesis outsourced, and 3) for the researcher to study semantic memory.

Thermoviscoelastic shape memory behavior for epoxy-shape memory polymer

International Nuclear Information System (INIS)

Chen, Jianguo; Liu, Liwu; Liu, Yanju; Leng, Jinsong

2014-01-01

There are various applications for shape memory polymer (SMP) in the smart materials and structures field due to its large recoverable strain and controllable driving method. The mechanical shape memory deformation mechanism is so obscure that many samples and test schemes have to be tried in order to verify a final design proposal for a smart structure system. This paper proposes a simple and very useful method to unambiguously analyze the thermoviscoelastic shape memory behavior of SMP smart structures. First, experiments under different temperature and loading conditions are performed to characterize the large deformation and thermoviscoelastic behavior of epoxy-SMP. Then, a rheological constitutive model, which is composed of a revised standard linear solid (SLS) element and a thermal expansion element, is proposed for epoxy-SMP. The thermomechanical coupling effect and nonlinear viscous flowing rules are considered in the model. Then, the model is used to predict the measured rubbery and time-dependent response of the material, and different thermomechanical loading histories are adopted to verify the shape memory behavior of the model. The results of the calculation agree with experiments satisfactorily. The proposed shape memory model is practical for the design of SMP smart structures. (paper)

Working memory load and the retro-cue effect: A diffusion model account.

Science.gov (United States)

Shepherdson, Peter; Oberauer, Klaus; Souza, Alessandra S

2018-02-01

Retro-cues (i.e., cues presented between the offset of a memory array and the onset of a probe) have consistently been found to enhance performance in working memory tasks, sometimes ameliorating the deleterious effects of increased memory load. However, the mechanism by which retro-cues exert their influence remains a matter of debate. To inform this debate, we applied a hierarchical diffusion model to data from 4 change detection experiments using single item, location-specific probes (i.e., a local recognition task) with either visual or verbal memory stimuli. Results showed that retro-cues enhanced the quality of information entering the decision process-especially for visual stimuli-and decreased the time spent on nondecisional processes. Further, cues interacted with memory load primarily on nondecision time, decreasing or abolishing load effects. To explain these findings, we propose an account whereby retro-cues act primarily to reduce the time taken to access the relevant representation in memory upon probe presentation, and in addition protect cued representations from visual interference. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Memories as Useful Outcomes of Residential Outdoor Environmental Education

Science.gov (United States)

Liddicoat, Kendra R.; Krasny, Marianne E.

2014-01-01

Residential outdoor environmental education (ROEE) programs for youth have been shown to yield lasting autobiographical episodic memories. This article explores how past program participants have used such memories, and draws on the memory psychology literature to offer a new perspective on the long-term impacts of environmental education.…

Animal Model of Methylphenidate's Longterm Memory-Enhancing Effects

Science.gov (United States)

Carmack, Stephanie A.; Howell, Kristin K.; Rasaei, Kleou; Reas, Emilie T.; Anagnostaras, Stephan G.

2014-01-01

Methylphenidate (MPH), introduced more than 60 years ago, accounts for two-thirds of current prescriptions for attention deficit hyperactivity disorder (ADHD). Although many studies have modeled MPH's effect on executive function, almost none have directly modeled its effect on long-term memory (LTM), even though improvement in LTM is a…

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

Science.gov (United States)

Rovee-Collier, Carolyn; Cuevas, Kimberly

2009-01-01

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

Memory-induced resonancelike suppression of spike generation in a resonate-and-fire neuron model

Science.gov (United States)

Mankin, Romi; Paekivi, Sander

2018-01-01

The behavior of a stochastic resonate-and-fire neuron model based on a reduction of a fractional noise-driven generalized Langevin equation (GLE) with a power-law memory kernel is considered. The effect of temporally correlated random activity of synaptic inputs, which arise from other neurons forming local and distant networks, is modeled as an additive fractional Gaussian noise in the GLE. Using a first-passage-time formulation, in certain system parameter domains exact expressions for the output interspike interval (ISI) density and for the survival probability (the probability that a spike is not generated) are derived and their dependence on input parameters, especially on the memory exponent, is analyzed. In the case of external white noise, it is shown that at intermediate values of the memory exponent the survival probability is significantly enhanced in comparison with the cases of strong and weak memory, which causes a resonancelike suppression of the probability of spike generation as a function of the memory exponent. Moreover, an examination of the dependence of multimodality in the ISI distribution on input parameters shows that there exists a critical memory exponent αc≈0.402 , which marks a dynamical transition in the behavior of the system. That phenomenon is illustrated by a phase diagram describing the emergence of three qualitatively different structures of the ISI distribution. Similarities and differences between the behavior of the model at internal and external noises are also discussed.

Exploring memory hierarchy design with emerging memory technologies

CERN Document Server

Sun, Guangyu

2014-01-01

This book equips readers with tools for computer architecture of high performance, low power, and high reliability memory hierarchy in computer systems based on emerging memory technologies, such as STTRAM, PCM, FBDRAM, etc.  The techniques described offer advantages of high density, near-zero static power, and immunity to soft errors, which have the potential of overcoming the “memory wall.”  The authors discuss memory design from various perspectives: emerging memory technologies are employed in the memory hierarchy with novel architecture modification;  hybrid memory structure is introduced to leverage advantages from multiple memory technologies; an analytical model named “Moguls” is introduced to explore quantitatively the optimization design of a memory hierarchy; finally, the vulnerability of the CMPs to radiation-based soft errors is improved by replacing different levels of on-chip memory with STT-RAMs.   ·         Provides a holistic study of using emerging memory technologies i...

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

Science.gov (United States)

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

2016-01-01

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

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

Science.gov (United States)

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

2016-09-01

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

Memory-efficient dynamic programming backtrace and pairwise local sequence alignment.

Science.gov (United States)

Newberg, Lee A

2008-08-15

A backtrace through a dynamic programming algorithm's intermediate results in search of an optimal path, or to sample paths according to an implied probability distribution, or as the second stage of a forward-backward algorithm, is a task of fundamental importance in computational biology. When there is insufficient space to store all intermediate results in high-speed memory (e.g. cache) existing approaches store selected stages of the computation, and recompute missing values from these checkpoints on an as-needed basis. Here we present an optimal checkpointing strategy, and demonstrate its utility with pairwise local sequence alignment of sequences of length 10,000. Sample C++-code for optimal backtrace is available in the Supplementary Materials. Supplementary data is available at Bioinformatics online.

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

International Nuclear Information System (INIS)

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

1987-01-01

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

The storage capacity of Potts models for semantic memory retrieval

Science.gov (United States)

Kropff, Emilio; Treves, Alessandro

2005-08-01

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

First Principles Modelling of Shape Memory Alloys Molecular Dynamics Simulations

CERN Document Server

Kastner, Oliver

2012-01-01

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

An A.P.L. micro-programmed machine: implementation on a Multi-20 mini-computer, memory organization, micro-programming and flowcharts

International Nuclear Information System (INIS)

Granger, Jean-Louis

1975-01-01

This work deals with the presentation of an APL interpreter implemented on an MULTI 20 mini-computer. It includes a left to right syntax analyser, a recursive routine for generation and execution. This routine uses a beating method for array processing. Moreover, during the execution of all APL statements, dynamic memory allocation is used. Execution of basic operations has been micro-programmed. The basic APL interpreter has a length of 10 K bytes. It uses overlay methods. (author) [fr

GPAW optimized for Blue Gene/P using hybrid programming

DEFF Research Database (Denmark)

Kristensen, Mads Ruben Burgdorff; Happe, Hans Henrik; Vinter, Brian

2009-01-01

In this work we present optimizations of a Grid-based projector-augmented wave method software, GPAW for the Blue Gene/P architecture. The improvements are achieved by exploring the advantage of shared and distributed memory programming also known as hybrid programming. The work focuses on optimi......In this work we present optimizations of a Grid-based projector-augmented wave method software, GPAW for the Blue Gene/P architecture. The improvements are achieved by exploring the advantage of shared and distributed memory programming also known as hybrid programming. The work focuses...... on optimizing a very time consuming operation in GPAW, the finite-different stencil operation, and different hybrid programming approaches are evaluated. The work succeeds in demonstrating a hybrid programming model which is clearly beneficial compared to the original flat programming model. In total...... an improvement of 1.94 compared to the original implementation is obtained. The results we demonstrate here are reasonably general and may be applied to other finite difference codes....

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

Directory of Open Access Journals (Sweden)

Flavie eDarcet

2014-05-01

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

Frequent Statement and Dereference Elimination for Imperative and Object-Oriented Distributed Programs

Science.gov (United States)

El-Zawawy, Mohamed A.

2014-01-01

This paper introduces new approaches for the analysis of frequent statement and dereference elimination for imperative and object-oriented distributed programs running on parallel machines equipped with hierarchical memories. The paper uses languages whose address spaces are globally partitioned. Distributed programs allow defining data layout and threads writing to and reading from other thread memories. Three type systems (for imperative distributed programs) are the tools of the proposed techniques. The first type system defines for every program point a set of calculated (ready) statements and memory accesses. The second type system uses an enriched version of types of the first type system and determines which of the ready statements and memory accesses are used later in the program. The third type system uses the information gather so far to eliminate unnecessary statement computations and memory accesses (the analysis of frequent statement and dereference elimination). Extensions to these type systems are also presented to cover object-oriented distributed programs. Two advantages of our work over related work are the following. The hierarchical style of concurrent parallel computers is similar to the memory model used in this paper. In our approach, each analysis result is assigned a type derivation (serves as a correctness proof). PMID:24892098

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

OpenAIRE

Zilli, Eric A.; Hasselmo, Michael E.

2008-01-01

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

Design, fabrication, testing and delivery of a feasibility model laminated ferrite memory

Science.gov (United States)

Heckler, H. C.

1973-01-01

The effect of using multiword addressing with laminated ferrite arrays was made. Both a reduction in the number of components, and a reduction in power consumption was obtained for memory capacities between one million bits and one million words. An investigation into the effect of variations in the processing steps resulted in a number of process modifications that improved the quality of the arrays. A feasibility model laminated ferrite memory system was constructed by modifying a commercial plated wire memory system to operate with laminated ferrite arrays. To provide flexibility for the testing of the laminated ferrite memory, an exerciser has been constructed to automatically control the loading and recirculation of arbitrary size checkerboard patterns of one's and zero's and to display the patterns of stored information on a CRT screen.

Generalized nucleation and looping model for epigenetic memory of histone modifications

Science.gov (United States)

Erdel, Fabian; Greene, Eric C.

2016-01-01

Histone modifications can redistribute along the genome in a sequence-independent manner, giving rise to chromatin position effects and epigenetic memory. The underlying mechanisms shape the endogenous chromatin landscape and determine its response to ectopically targeted histone modifiers. Here, we simulate linear and looping-driven spreading of histone modifications and compare both models to recent experiments on histone methylation in fission yeast. We find that a generalized nucleation-and-looping mechanism describes key observations on engineered and endogenous methylation domains including intrinsic spatial confinement, independent regulation of domain size and memory, variegation in the absence of antagonists, and coexistence of short- and long-term memory at loci with weak and strong constitutive nucleation. These findings support a straightforward relationship between the biochemical properties of chromatin modifiers and the spatiotemporal modification pattern. The proposed mechanism gives rise to a phase diagram for cellular memory that may be generally applicable to explain epigenetic phenomena across different species. PMID:27382173

Test data generation for LRU cache-memory testing

OpenAIRE

Evgeni, Kornikhin

2009-01-01

System functional testing of microprocessors deals with many assembly programs of given behavior. The paper proposes new constraint-based algorithm of initial cache-memory contents generation for given behavior of assembly program (with cache misses and hits). Although algorithm works for any types of cache-memory, the paper describes algorithm in detail for basis types of cache-memory only: fully associative cache and direct mapped cache.

A grey NGM(1,1, k) self-memory coupling prediction model for energy consumption prediction.

Science.gov (United States)

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

2014-01-01

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

Meta-analysis of the research impact of Baddeley’s multicomponent working memory model and Cowan’s embedded-processes model of working memory: A bibliometric mapping approach

Directory of Open Access Journals (Sweden)

Gruszka Aleksandra

2016-04-01

Full Text Available In this study bibliometric mapping method was employed to visualise the current research trends and the impact of the two most influential models of working memory, namely: A. D. Baddeley and G. J. Hitch’s (1974 multicomponent working memory model and N. Cowan’s (1988 embedded-processes model of working memory. Using VOSviewer software two maps were generated based on the index-term words extracted from the research papers citing Baddeley (2000 and Cowan (2001, respectively. The maps represent networks of co-occurrences of index terms and can be interpreted as an indication of the main research fields related to the examined models of WM. The results of the analysis revealed that the spheres of influence of the two main conceptualisations of WM are rather different than similar. Although the first two clusters, i.e. “brain mapping” and “higher-level cognition and development” are present in both maps, their relative importance varies. The remaining clusters are unique to each map. Baddeley’s theory seems to have a greater influence on “neuropsychology”, while Cowan’s theory - on basic research on “biological systems”, including the nervous system in humans and animals. The second difference between these theories concerns their relations to functions and dysfunctions associated with particular sensory modalities: in Baddelay’s theory with the “auditory modality” cluster, and in Cowan’s - with the “visual modality” one.

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

Science.gov (United States)

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

2015-08-01

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

A memory module for experimental data handling

Science.gov (United States)

De Blois, J.

1985-02-01

A compact CAMAC memory module for experimental data handling was developed to eliminate the need of direct memory access in computer controlled measurements. When using autonomous controllers it also makes measurements more independent of the program and enlarges the available space for programs in the memory of the micro-computer. The memory module has three modes of operation: an increment-, a list- and a fifo mode. This is achieved by connecting the main parts, being: the memory (MEM), the fifo buffer (FIFO), the address buffer (BUF), two counters (AUX and ADDR) and a readout register (ROR), by an internal 24-bit databus. The time needed for databus operations is 1 μs, for measuring cycles as well as for CAMAC cycles. The FIFO provides temporary data storage during CAMAC cycles and separates the memory part from the application part. The memory is variable from 1 to 64K (24 bits) by using different types of memory chips. The application part, which forms 1/3 of the module, will be specially designed for each application and is added to the memory chian internal connector. The memory unit will be used in Mössbauer experiments and in thermal neutron scattering experiments.

Cross-scale Efficient Tensor Contractions for Coupled Cluster Computations Through Multiple Programming Model Backends

Energy Technology Data Exchange (ETDEWEB)

Ibrahim, Khaled Z. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Epifanovsky, Evgeny [Q-Chem, Inc., Pleasanton, CA (United States); Williams, Samuel W. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Krylov, Anna I. [Univ. of Southern California, Los Angeles, CA (United States). Dept. of Chemistry

2016-07-26

Coupled-cluster methods provide highly accurate models of molecular structure by explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix-matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts to extend the Libtensor framework to work in the distributed memory environment in a scalable and energy efficient manner. We achieve up to 240 speedup compared with the best optimized shared memory implementation. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures, (Cray XC30&XC40, BlueGene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance. Nevertheless, we preserve a uni ed interface to both programming models to maintain the productivity of computational quantum chemists.

Protective effects of cultured and fermented ginseng extracts against scopolamine-induced memory loss in a mouse model.

Science.gov (United States)

Han, Song-Hee; Kim, Sung-June; Yun, Young Won; Nam, Sang Yoon; Lee, Hu-Jang; Lee, Beom-Jun

2018-03-01

This study was performed to investigate the effect of a concentrate of fermented wild ginseng root culture (HLJG0701) on memory improvement in the scopolamine (SPL)-induced memory-deficient mouse model. Eight-week-old male ICR mice were used to evaluate the protective effect of HLJG0701 against the SPL-induced memory loss animal model. The Morris water maze test, which measures hippocampus-dependent learning ability, and the Y-maze test, a short-term memory assessment test, were performed and related markers were analyzed. HLJG0701-treated groups displayed significantly reduced acetylcholinesterase activity and increased acetylcholine level compared with the SPL-administered group (SPL-G) ( P memory loss by inhibiting acetylcholinesterase activity and preventing acetylcholine deficiency.

Memory Effects and Coverage Dependence of Surface Diffusion in a Model Adsorption System

DEFF Research Database (Denmark)

Vattulainen, Ilpo Tapio; Ying, S. C.; Ala-Nissila, T.

1999-01-01

in tracer and collective diffusion. We show that memory effects can be very pronounced deep inside the ordered phases and in regions close to first and second order phase transition boundaries. Particular attention is paid to the details of the time dependence of memory effects. The memory effect in tracer......We study the coverage dependence of surface diffusion coefficients for a strongly interacting adsorption system O/W(110) via Monte Carlo simulations of a lattice-gas model. In particular, we consider the nature and emergence of memory effects as contained in the corresponding correlation factors...... diffusion is found to decay following a power law after an initial transient period. This behavior persists until the hydrodynamic regime is reached, after which the memory effect decays exponentially. The time required to reach the hydrodynamical regime and the related exponential decay is strongly...

Models of verbal working memory capacity: what does it take to make them work?

Science.gov (United States)

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

2012-07-01

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

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

NARCIS (Netherlands)

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

2011-01-01

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

Retrieval-induced NMDA receptor-dependent Arc expression in two models of cocaine-cue memory

OpenAIRE

Alaghband, Yasaman; O'Dell, Steven J.; Azarnia, Siavash; Khalaj, Anna J.; Guzowski, John F.; Marshall, John F.

2014-01-01

The association of environmental cues with drugs of abuse results in persistent drug-cue memories. These memories contribute significantly to relapse among addicts. While conditioned place preference (CPP) is a well-established paradigm frequently used to examine the modulation of drug-cue memories, very few studies have used the non-preference-based model conditioned activity (CA) for this purpose. Here, we used both experimental approaches to investigate the neural substrates of cocaine-cue...

Los Alamos Programming Models

Energy Technology Data Exchange (ETDEWEB)

Bergen, Benjamin Karl [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-07-07

This is the PDF of a powerpoint presentation from a teleconference on Los Alamos programming models. It starts by listing their assumptions for the programming models and then details a hierarchical programming model at the System Level and Node Level. Then it details how to map this to their internal nomenclature. Finally, a list is given of what they are currently doing in this regard.

Olfactory memory: a bridge between humans and animals in models of cognitive aging.

Science.gov (United States)

Eichenbaum, Howard; Robitsek, R Jonathan

2009-07-01

Odor-recognition memory in rodents may provide a valuable model of cognitive aging. In a recent study we used signal detection analyses to distinguish odor recognition based on recollection versus that based on familiarity. Aged rats were selectively impaired in recollection, with relative sparing of familiarity, and the deficits in recollection were correlated with spatial memory impairments. These results complement electrophysiological findings indicating age-associated deficits in the ability of hippocampal neurons to differentiate contextual information, and this information-processing impairment may underlie the common age-associated decline in olfactory and spatial memory.

An analytical study of physical models with inherited temporal and spatial memory

Science.gov (United States)

Jaradat, Imad; Alquran, Marwan; Al-Khaled, Kamel

2018-04-01

Du et al. (Sci. Reb. 3, 3431 (2013)) demonstrated that the fractional derivative order can be physically interpreted as a memory index by fitting the test data of memory phenomena. The aim of this work is to study analytically the joint effect of the memory index on time and space coordinates simultaneously. For this purpose, we introduce a novel bivariate fractional power series expansion that is accompanied by twofold fractional derivatives ordering α, β\\in(0,1]. Further, some convergence criteria concerning our expansion are presented and an analog of the well-known bivariate Taylor's formula in the sense of mixed fractional derivatives is obtained. Finally, in order to show the functionality and efficiency of this expansion, we employ the corresponding Taylor's series method to obtain closed-form solutions of various physical models with inherited time and space memory.

Program scheme using common source lines in channel stacked NAND flash memory with layer selection by multilevel operation

Science.gov (United States)

Kim, Do-Bin; Kwon, Dae Woong; Kim, Seunghyun; Lee, Sang-Ho; Park, Byung-Gook

2018-02-01

To obtain high channel boosting potential and reduce a program disturbance in channel stacked NAND flash memory with layer selection by multilevel (LSM) operation, a new program scheme using boosted common source line (CSL) is proposed. The proposed scheme can be achieved by applying proper bias to each layer through its own CSL. Technology computer-aided design (TCAD) simulations are performed to verify the validity of the new method in LSM. Through TCAD simulation, it is revealed that the program disturbance characteristics is effectively improved by the proposed scheme.

A stress-induced phase transition model for semi-crystallize shape memory polymer

Science.gov (United States)

Guo, Xiaogang; Zhou, Bo; Liu, Liwu; Liu, Yanju; Leng, Jinsong

2014-03-01

The developments of constitutive models for shape memory polymer (SMP) have been motivated by its increasing applications. During cooling or heating process, the phase transition which is a continuous time-dependent process happens in semi-crystallize SMP and the various individual phases form at different temperature and in different configuration. Then, the transformation between these phases occurred and shape memory effect will emerge. In addition, stress applied on SMP is an important factor for crystal melting during phase transition. In this theory, an ideal phase transition model considering stress or pre-strain is the key to describe the behaviors of shape memory effect. So a normal distributed model was established in this research to characterize the volume fraction of each phase in SMP during phase transition. Generally, the experiment results are partly backward (in heating process) or forward (in cooling process) compared with the ideal situation considering delay effect during phase transition. So, a correction on the normal distributed model is needed. Furthermore, a nonlinear relationship between stress and phase transition temperature Tg is also taken into account for establishing an accurately normal distributed phase transition model. Finally, the constitutive model which taking the stress as an influence factor on phase transition was also established. Compared with the other expressions, this new-type model possesses less parameter and is more accurate. For the sake of verifying the rationality and accuracy of new phase transition and constitutive model, the comparisons between the simulated and experimental results were carried out.

A short executive function training program improves preschoolers’ working memory

Directory of Open Access Journals (Sweden)

Emma eBlakey

2015-11-01

Full Text Available Cognitive training has been shown to improve executive functions in middle childhood and adulthood. However, fewer studies have targeted the preschool years – a time when executive functions undergo rapid development. The present study tested the effects of a short four session executive function training program in 54 four-year-olds. The training group significantly improved their working memory from pre-training relative to an active control group. Notably, this effect extended to a task sharing few surface features with the trained tasks, and continued to be apparent three months later. In addition, the benefits of training extended to a measure of mathematical reasoning three months later, indicating that training executive functions during the preschool years has the potential to convey benefits that are both long-lasting and wide-ranging.

Short-Term Memory for Serial Order: A Recurrent Neural Network Model

Science.gov (United States)

Botvinick, Matthew M.; Plaut, David C.

2006-01-01

Despite a century of research, the mechanisms underlying short-term or working memory for serial order remain uncertain. Recent theoretical models have converged on a particular account, based on transient associations between independent item and context representations. In the present article, the authors present an alternative model, according…

Working memory capacity and overgeneral autobiographical memory in young and older adults.

Science.gov (United States)

Ros, Laura; Latorre, José Miguel; Serrano, Juan Pedro

2010-01-01

The objectives of this study are to compare the Autobiographical Memory Test (AMT) performance of two healthy samples of younger and older adults and to analyse the relationship between overgeneral memory (OGM) and working memory executive processes (WMEP) using a structural equation modelling with latent variables. The AMT and sustained attention, short-term memory and working memory tasks were administered to a group of young adults (N = 50) and a group of older adults (N = 46). On the AMT, the older adults recalled a greater number of categorical memories (p = .000) and fewer specific memories (p = .000) than the young adults, confirming that OGM occurs in the normal population and increases with age. WMEP was measured by reading span and a working memory with sustained attention load task. Structural equation modelling reflects that WMEP shows a strong relationship with OGM: lower scores on WMEP reflect an OGM phenomenon characterized by higher categorical and lower specific memories.

Alternative conceptions, memory, & mental models in physics education

Science.gov (United States)

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

2005-09-01

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

A single-trace dual-process model of episodic memory: a novel computational account of familiarity and recollection.

Science.gov (United States)

Greve, Andrea; Donaldson, David I; van Rossum, Mark C W

2010-02-01

Dual-process theories of episodic memory state that retrieval is contingent on two independent processes: familiarity (providing a sense of oldness) and recollection (recovering events and their context). A variety of studies have reported distinct neural signatures for familiarity and recollection, supporting dual-process theory. One outstanding question is whether these signatures reflect the activation of distinct memory traces or the operation of different retrieval mechanisms on a single memory trace. We present a computational model that uses a single neuronal network to store memory traces, but two distinct and independent retrieval processes access the memory. The model is capable of performing familiarity and recollection-based discrimination between old and new patterns, demonstrating that dual-process models need not to rely on multiple independent memory traces, but can use a single trace. Importantly, our putative familiarity and recollection processes exhibit distinct characteristics analogous to those found in empirical data; they diverge in capacity and sensitivity to sparse and correlated patterns, exhibit distinct ROC curves, and account for performance on both item and associative recognition tests. The demonstration that a single-trace, dual-process model can account for a range of empirical findings highlights the importance of distinguishing between neuronal processes and the neuronal representations on which they operate.

A new pattern associative memory model for image recognition based on Hebb rules and dot product

Science.gov (United States)

Gao, Mingyue; Deng, Limiao; Wang, Yanjiang

2018-04-01

A great number of associative memory models have been proposed to realize information storage and retrieval inspired by human brain in the last few years. However, there is still much room for improvement for those models. In this paper, we extend a binary pattern associative memory model to accomplish real-world image recognition. The learning process is based on the fundamental Hebb rules and the retrieval is implemented by a normalized dot product operation. Our proposed model can not only fulfill rapid memory storage and retrieval for visual information but also have the ability on incremental learning without destroying the previous learned information. Experimental results demonstrate that our model outperforms the existing Self-Organizing Incremental Neural Network (SOINN) and Back Propagation Neuron Network (BPNN) on recognition accuracy and time efficiency.

Quantitative Analysis of Memristance Defined Exponential Model for Multi-bits Titanium Dioxide Memristor Memory Cell

Directory of Open Access Journals (Sweden)

DAOUD, A. A. D.

2016-05-01

Full Text Available The ability to store multiple bits in a single memristor based memory cell is a key feature for high-capacity memory packages. Studying multi-bit memristor circuits requires high accuracy in modelling the memristance change. A memristor model based on a novel definition of memristance is proposed. A design of a single memristor memory cell using the proposed model for the platinum electrodes titanium dioxide memristor is illustrated. A specific voltage pulse is used with varying its parameters (amplitude or pulse width to store different number of states in a single memristor. New state variation parameters associated with the utilized model are provided and their effects on write and read processes of memristive multi-states are analysed. PSPICE simulations are also held, and they show a good agreement with the data obtained from the analysis.

Languages, compilers and run-time environments for distributed memory machines

CERN Document Server

Saltz, J

1992-01-01

Papers presented within this volume cover a wide range of topics related to programming distributed memory machines. Distributed memory architectures, although having the potential to supply the very high levels of performance required to support future computing needs, present awkward programming problems. The major issue is to design methods which enable compilers to generate efficient distributed memory programs from relatively machine independent program specifications. This book is the compilation of papers describing a wide range of research efforts aimed at easing the task of programmin

Capacity and precision in an animal model of visual short-term memory.

Science.gov (United States)

Lara, Antonio H; Wallis, Jonathan D

2012-03-14

Temporary storage of information in visual short-term memory (VSTM) is a key component of many complex cognitive abilities. However, it is highly limited in capacity. Understanding the neurophysiological nature of this capacity limit will require a valid animal model of VSTM. We used a multiple-item color change detection task to measure macaque monkeys' VSTM capacity. Subjects' performance deteriorated and reaction times increased as a function of the number of items in memory. Additionally, we measured the precision of the memory representations by varying the distance between sample and test colors. In trials with similar sample and test colors, subjects made more errors compared to trials with highly discriminable colors. We modeled the error distribution as a Gaussian function and used this to estimate the precision of VSTM representations. We found that as the number of items in memory increases the precision of the representations decreases dramatically. Additionally, we found that focusing attention on one of the objects increases the precision with which that object is stored and degrades the precision of the remaining. These results are in line with recent findings in human psychophysics and provide a solid foundation for understanding the neurophysiological nature of the capacity limit of VSTM.

[A neuropsychoanalytic freudian model of psychic trauma and memory. Theoretical and clinical applications].

Science.gov (United States)

Cohen, Diego; Basili, Rubén; Sharpin de Basili, Isabel

2009-01-01

The traumatic memory is conceptualized by means of an amplified Freudian neuropsychoanalytic model using a contemporary memory system based on its contents, conscious and unconscious recollection (explicit and implicit memories) highlighting the validity of the Freudian discoveries. This is then related to the psychoanalytical theories of consciousness, affects and thinking. Particular importance is given to Freud's seduction theory, its relation to memory and the clinical application of these concepts to the basic organization of the personality, together with the relation to Bowlby's concept of emotional deprivation. The development and working trough of trauma is postulated as a vector to make "real" or phantasized trauma unconscious through repression in neurosis, splitting in borderline personality organization, and primitive mechanisms of projection in psychosis.

Analysis and modeling of resistive switching mechanism oriented to fault tolerance of resistive memory based on memristor

International Nuclear Information System (INIS)

Huang Da; Wu Jun-Jie; Tang Yu-Hua

2014-01-01

With the progress of the semiconductor industry, resistive memories, especially the memristor, have drawn increasing attention. The resistive memory based on memrsitor has not been commercialized mainly because of data error. Currently, there are more studies focused on fault tolerance of resistive memory. This paper studies the resistive switching mechanism which may have time-varying characteristics. Resistive switching mechanism is analyzed and its respective circuit model is established based on the memristor Spice model

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

Science.gov (United States)

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

2017-01-01

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

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

Science.gov (United States)

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

2017-09-01

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

Models of Working Memory

National Research Council Canada - National Science Library

Miyake, Akira

1997-01-01

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

Comparison of Three Models Dealing with Working Memory and Its Dimensions in Second Language Acquisition

Directory of Open Access Journals (Sweden)

Abdulaziz Alshahrani

2017-12-01

Full Text Available The current status of research on working memory (WM and its components in second language acquisition (SLA was examined in this review. Literature search was done on four aspects using search terms in Google Scholar. Hence, the review results are given and introduced. 1. In the definition of WM, some confusion exists on whether short term memory (STM or recent memory is the same as WM or different. 2. In this review, three main models have been discussed elaborately, as they are the only ones discussed in literature. They are: multicomponent model of Baddeley (2000, embedded process model of Cowan (2005 and attention control model of Engle and Kane (2003. 3. The phonological and executive components of WM were examined in more detail, as these determine the two basic aspects of language acquisition: language characteristics and acquisition methods (Wen, 2012. Overall, the variables related to phonological and executive working memories are evident from published research, but their interactive relationships and affecting factors are not entirely clear. 4. Admittedly, several diverse internal and external factors affect WM in relation to SLA. Some practically useful interventions are indicated by certain findings.

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

Science.gov (United States)

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

2014-01-01

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

MINI-TRAC code: a driver program for assessment of constitutive equations of two-fluid model

International Nuclear Information System (INIS)

Akimoto, Hajime; Abe, Yutaka; Ohnuki, Akira; Murao, Yoshio

1991-05-01

MINI-TRAC code, a driver program for assessment of constitutive equations of two-fluid model, has been developed to perform assessment and improvement of constitutive equations of two-fluid model widely and efficiently. The MINI-TRAC code uses one-dimensional conservation equations for mass, momentum and energy based on the two-fluid model. The code can work on a personal computer because it can be operated with a core memory size less than 640 KB. The MINI-TRAC code includes constitutive equations of TRAC-PF1/MOD1 code, TRAC-BF1 code and RELAP5/MOD2 code. The code is modulated so that one can easily change constitutive equations to perform a test calculation. This report is a manual of the MINI-TRAC code. The basic equations, numerics, constitutive, equations included in the MINI-TRAC code will be described. The user's manual such as input description will be presented. The program structure and contents of main variables will also be mentioned in this report. (author)

Relating Memory To Functional Performance In Normal Aging to Dementia Using Hierarchical Bayesian Cognitive Processing Models

Science.gov (United States)

Shankle, William R.; Pooley, James P.; Steyvers, Mark; Hara, Junko; Mangrola, Tushar; Reisberg, Barry; Lee, Michael D.

2012-01-01

Determining how cognition affects functional abilities is important in Alzheimer’s disease and related disorders (ADRD). 280 patients (normal or ADRD) received a total of 1,514 assessments using the Functional Assessment Staging Test (FAST) procedure and the MCI Screen (MCIS). A hierarchical Bayesian cognitive processing (HBCP) model was created by embedding a signal detection theory (SDT) model of the MCIS delayed recognition memory task into a hierarchical Bayesian framework. The SDT model used latent parameters of discriminability (memory process) and response bias (executive function) to predict, simultaneously, recognition memory performance for each patient and each FAST severity group. The observed recognition memory data did not distinguish the six FAST severity stages, but the latent parameters completely separated them. The latent parameters were also used successfully to transform the ordinal FAST measure into a continuous measure reflecting the underlying continuum of functional severity. HBCP models applied to recognition memory data from clinical practice settings accurately translated a latent measure of cognition to a continuous measure of functional severity for both individuals and FAST groups. Such a translation links two levels of brain information processing, and may enable more accurate correlations with other levels, such as those characterized by biomarkers. PMID:22407225

A model considering mechanical anisotropy of magnetic-field-induced superelastic strain in magnetic shape memory alloys

International Nuclear Information System (INIS)

Zhu, Yuping; Yu, Kai

2013-01-01

Highlights: ► The model analyzes mechanical anisotropy of magnetic shape memory alloy. ► The numerical evaluation of Eshelby tensor of shape memory alloy is obtained. ► Interaction energy of magnetic shape memory alloy is analyzed. - Abstract: Under applied mechanical load and magnetic field, a micromechanics-based thermodynamic model taking account of mechanical anisotropy of magnetic shape memory alloys (MSMAs) is developed in this work. Considering the crystallographic and magnetic microstructure, the internal state variables are chosen and the model can capture the magnetic shape memory effect caused by the martensitic variant reorientation process. It is assumed that the Gibbs free energy is consisted of the mechanical potential energy of anisotropic matrix, the Zeeman energy and the magnetocrystalline anisotropy energy in the model. In terms of the balance between the thermodynamic driving force derived from the reduction of Gibbs free energy and the resistive force for the variant reorientation, the kinetic equation is established and the Eshelby tensor of anisotropic MSMAs is then obtained by using numerical evaluation. At last, the effects of the anisotropy on interaction energy and macroscopic strain are discussed. The assumption of isotropy tends to underestimate interaction energy and macroscopic strain. The results considering mechanical anisotropy are in good agreement with the experimental data.

A memory module for experimental data handling

International Nuclear Information System (INIS)

Blois, J. de

1985-01-01

A compact CAMAC memory module for experimental data handling was developed to eliminate the need of direct memory access in computer controlled measurements. When using autonomous controllers it also makes measurements more independent of the program and enlarges the available space for programs in the memory of the micro-computer. The memory module has three modes of operation: an increment-, a list- and a fifo mode. This is achieved by connecting the main parts, being: the memory (MEM), the fifo buffer (FIFO), the address buffer (BUF), two counters (AUX and ADDR) and a readout register (ROR), by an internal 24-bit databus. The time needed for databus operations is 1 μs, for measuring cycles as well as for CAMAC cycles. The FIFO provides temporary data storage during CAMAC cycles and separates the memory part from the application part. The memory is variable from 1 to 64K (24 bits) by using different types of memory chips. The application part, which forms 1/3 of the module, will be specially designed for each application and is added to the memory by an internal connector. The memory unit will be used in Moessbauer experiments and in thermal neutron scattering experiments. (orig.)