An Improved Dissonance Measure Based on Auditory Memory

DEFF Research Database (Denmark)

Jensen, Kristoffer; Hjortkjær, Jens

2012-01-01

Dissonance is an important feature in music audio analysis. We present here a dissonance model that accounts for the temporal integration of dissonant events in auditory short term memory. We compare the memory-based dissonance extracted from musical audio sequences to the response of human...... listeners. In a number of tests, the memory model predicts listener’s response better than traditional dissonance measures....

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

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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.

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,…

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).

Elements of episodic-like memory in animal models.

Science.gov (United States)

Crystal, Jonathon D

2009-03-01

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

Likelihood ratio sequential sampling models of recognition memory.

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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.

Data Provenance for Agent-Based Models in a Distributed Memory

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Delmar B. Davis

2018-04-01

Full Text Available Agent-Based Models (ABMs assist with studying emergent collective behavior of individual entities in social, biological, economic, network, and physical systems. Data provenance can support ABM by explaining individual agent behavior. However, there is no provenance support for ABMs in a distributed setting. The Multi-Agent Spatial Simulation (MASS library provides a framework for simulating ABMs at fine granularity, where agents and spatial data are shared application resources in a distributed memory. We introduce a novel approach to capture ABM provenance in a distributed memory, called ProvMASS. We evaluate our technique with traditional data provenance queries and performance measures. Our results indicate that a configurable approach can capture provenance that explains coordination of distributed shared resources, simulation logic, and agent behavior while limiting performance overhead. We also show the ability to support practical analyses (e.g., agent tracking and storage requirements for different capture configurations.

An interference model of visual working memory.

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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).

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

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Jenia Jitsev

2009-09-01

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

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

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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.

Modeling soil moisture memory in savanna ecosystems

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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

An SPICE model for phase-change memory simulations

International Nuclear Information System (INIS)

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

2011-01-01

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

An SPICE model for phase-change memory simulations

Energy Technology Data Exchange (ETDEWEB)

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

2011-09-15

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

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.

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

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.

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.

A Memory Hierarchy Model Based on Data Reuse for Full-Search Motion Estimation on High-Definition Digital Videos

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Alba Sandyra Bezerra Lopes

2012-01-01

Full Text Available The motion estimation is the most complex module in a video encoder requiring a high processing throughput and high memory bandwidth, mainly when the focus is high-definition videos. The throughput problem can be solved increasing the parallelism in the internal operations. The external memory bandwidth may be reduced using a memory hierarchy. This work presents a memory hierarchy model for a full-search motion estimation core. The proposed memory hierarchy model is based on a data reuse scheme considering the full search algorithm features. The proposed memory hierarchy expressively reduces the external memory bandwidth required for the motion estimation process, and it provides a very high data throughput for the ME core. This throughput is necessary to achieve real time when processing high-definition videos. When considering the worst bandwidth scenario, this memory hierarchy is able to reduce the external memory bandwidth in 578 times. A case study for the proposed hierarchy, using 32×32 search window and 8×8 block size, was implemented and prototyped on a Virtex 4 FPGA. The results show that it is possible to reach 38 frames per second when processing full HD frames (1920×1080 pixels using nearly 299 Mbytes per second of external memory bandwidth.

The AIP Model of EMDR Therapy and Pathogenic Memories

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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.

A Memory-Based Model of Posttraumatic Stress Disorder: Evaluating Basic Assumptions Underlying the PTSD Diagnosis

Science.gov (United States)

Rubin, David C.; Berntsen, Dorthe; Bohni, Malene Klindt

2008-01-01

In the mnemonic model of posttraumatic stress disorder (PTSD), the current memory of a negative event, not the event itself, determines symptoms. The model is an alternative to the current event-based etiology of PTSD represented in the "Diagnostic and Statistical Manual of Mental Disorders" (4th ed., text rev.; American Psychiatric Association,…

Sequence memory based on coherent spin-interaction neural networks.

Science.gov (United States)

Xia, Min; Wong, W K; Wang, Zhijie

2014-12-01

Sequence information processing, for instance, the sequence memory, plays an important role on many functions of brain. In the workings of the human brain, the steady-state period is alterable. However, in the existing sequence memory models using heteroassociations, the steady-state period cannot be changed in the sequence recall. In this work, a novel neural network model for sequence memory with controllable steady-state period based on coherent spininteraction is proposed. In the proposed model, neurons fire collectively in a phase-coherent manner, which lets a neuron group respond differently to different patterns and also lets different neuron groups respond differently to one pattern. The simulation results demonstrating the performance of the sequence memory are presented. By introducing a new coherent spin-interaction sequence memory model, the steady-state period can be controlled by dimension parameters and the overlap between the input pattern and the stored patterns. The sequence storage capacity is enlarged by coherent spin interaction compared with the existing sequence memory models. Furthermore, the sequence storage capacity has an exponential relationship to the dimension of the neural network.

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

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.

Relaxed memory models: an operational approach

OpenAIRE

Boudol , Gérard; Petri , Gustavo

2009-01-01

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

Discrete-Slots Models of Visual Working-Memory Response Times

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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

Compact modeling of CRS devices based on ECM cells for memory, logic and neuromorphic applications

International Nuclear Information System (INIS)

Linn, E; Ferch, S; Waser, R; Menzel, S

2013-01-01

Dynamic physics-based models of resistive switching devices are of great interest for the realization of complex circuits required for memory, logic and neuromorphic applications. Here, we apply such a model of an electrochemical metallization (ECM) cell to complementary resistive switches (CRSs), which are favorable devices to realize ultra-dense passive crossbar arrays. Since a CRS consists of two resistive switching devices, it is straightforward to apply the dynamic ECM model for CRS simulation with MATLAB and SPICE, enabling study of the device behavior in terms of sweep rate and series resistance variations. Furthermore, typical memory access operations as well as basic implication logic operations can be analyzed, revealing requirements for proper spike and level read operations. This basic understanding facilitates applications of massively parallel computing paradigms required for neuromorphic applications. (paper)

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 ...

On dynamic selection of households for direct marketing based on Markov chain models with memory

NARCIS (Netherlands)

Otter, Pieter W.

A simple, dynamic selection procedure is proposed, based on conditional, expected profits using Markov chain models with memory. The method is easy to apply, only frequencies and mean values have to be calculated or estimated. The method is empirically illustrated using a data set from a charitable

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.

Strategies for memory-based decision making: Modeling behavioral and neural signatures within a cognitive architecture.

Science.gov (United States)

Fechner, Hanna B; Pachur, Thorsten; Schooler, Lael J; Mehlhorn, Katja; Battal, Ceren; Volz, Kirsten G; Borst, Jelmer P

2016-12-01

How do people use memories to make inferences about real-world objects? We tested three strategies based on predicted patterns of response times and blood-oxygen-level-dependent (BOLD) responses: one strategy that relies solely on recognition memory, a second that retrieves additional knowledge, and a third, lexicographic (i.e., sequential) strategy, that considers knowledge conditionally on the evidence obtained from recognition memory. We implemented the strategies as computational models within the Adaptive Control of Thought-Rational (ACT-R) cognitive architecture, which allowed us to derive behavioral and neural predictions that we then compared to the results of a functional magnetic resonance imaging (fMRI) study in which participants inferred which of two cities is larger. Overall, versions of the lexicographic strategy, according to which knowledge about many but not all alternatives is searched, provided the best account of the joint patterns of response times and BOLD responses. These results provide insights into the interplay between recognition and additional knowledge in memory, hinting at an adaptive use of these two sources of information in decision making. The results highlight the usefulness of implementing models of decision making within a cognitive architecture to derive predictions on the behavioral and neural level. Copyright © 2016 Elsevier B.V. All rights reserved.

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...

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…

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.

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.

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.

Dynamics-based sequential memory: Winnerless competition of patterns

International Nuclear Information System (INIS)

Seliger, Philip; Tsimring, Lev S.; Rabinovich, Mikhail I.

2003-01-01

We introduce a biologically motivated dynamical principle of sequential memory which is based on winnerless competition (WLC) of event images. This mechanism is implemented in a two-layer neural model of sequential spatial memory. We present the learning dynamics which leads to the formation of a WLC network. After learning, the system is capable of associative retrieval of prerecorded sequences of patterns

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.

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.

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

Location-based prospective memory.

Science.gov (United States)

O'Rear, Andrea E; Radvansky, Gabriel A

2018-02-01

This study explores location-based prospective memory. People often have to remember to do things when in a particular location, such as buying tissues the next time they are in the supermarket. For event cognition theory, location is important for structuring events. However, because event cognition has not been used to examine prospective memory, the question remains of how multiple events will influence prospective memory performance. In our experiments, people delivered messages from store to store in a virtual shopping mall as an ongoing task. The prospective tasks were to do certain activities in certain stores. For Experiment 1, each trial involved one prospective memory task to be done in a single location at one of three delays. The virtual environment and location cues were effective for prospective memory, and performance was unaffected by delay. For Experiment 2, each trial involved two prospective memory tasks, given in either one or two instruction locations, and to be done in either one or two store locations. There was improved performance when people received instructions from two locations and did both tasks in one location relative to other combinations. This demonstrates that location-based event structure influences how well people perform on prospective memory tasks.

Memory-Based Shallow Parsing

OpenAIRE

Sang, Erik F. Tjong Kim

2002-01-01

We present memory-based learning approaches to shallow parsing and apply these to five tasks: base noun phrase identification, arbitrary base phrase recognition, clause detection, noun phrase parsing and full parsing. We use feature selection techniques and system combination methods for improving the performance of the memory-based learner. Our approach is evaluated on standard data sets and the results are compared with that of other systems. This reveals that our approach works well for ba...

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.

Secure Virtualization Environment Based on Advanced Memory Introspection

Directory of Open Access Journals (Sweden)

Shuhui Zhang

2018-01-01

Full Text Available Most existing virtual machine introspection (VMI technologies analyze the status of a target virtual machine under the assumption that the operating system (OS version and kernel structure information are known at the hypervisor level. In this paper, we propose a model of virtual machine (VM security monitoring based on memory introspection. Using a hardware-based approach to acquire the physical memory of the host machine in real time, the security of the host machine and VM can be diagnosed. Furthermore, a novel approach for VM memory forensics based on the virtual machine control structure (VMCS is put forward. By analyzing the memory of the host machine, the running VMs can be detected and their high-level semantic information can be reconstructed. Then, malicious activity in the VMs can be identified in a timely manner. Moreover, by mutually analyzing the memory content of the host machine and VMs, VM escape may be detected. Compared with previous memory introspection technologies, our solution can automatically reconstruct the comprehensive running state of a target VM without any prior knowledge and is strongly resistant to attacks with high reliability. We developed a prototype system called the VEDefender. Experimental results indicate that our system can handle the VMs of mainstream Linux and Windows OS versions with high efficiency and does not influence the performance of the host machine and VMs.

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

A dynamic model of reasoning and memory.

Science.gov (United States)

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

2016-02-01

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

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.

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).

A neural network model of semantic memory linking feature-based object representation and words.

Science.gov (United States)

Cuppini, C; Magosso, E; Ursino, M

2009-06-01

Recent theories in cognitive neuroscience suggest that semantic memory is a distributed process, which involves many cortical areas and is based on a multimodal representation of objects. The aim of this work is to extend a previous model of object representation to realize a semantic memory, in which sensory-motor representations of objects are linked with words. The model assumes that each object is described as a collection of features, coded in different cortical areas via a topological organization. Features in different objects are segmented via gamma-band synchronization of neural oscillators. The feature areas are further connected with a lexical area, devoted to the representation of words. Synapses among the feature areas, and among the lexical area and the feature areas are trained via a time-dependent Hebbian rule, during a period in which individual objects are presented together with the corresponding words. Simulation results demonstrate that, during the retrieval phase, the network can deal with the simultaneous presence of objects (from sensory-motor inputs) and words (from acoustic inputs), can correctly associate objects with words and segment objects even in the presence of incomplete information. Moreover, the network can realize some semantic links among words representing objects with shared features. These results support the idea that semantic memory can be described as an integrated process, whose content is retrieved by the co-activation of different multimodal regions. In perspective, extended versions of this model may be used to test conceptual theories, and to provide a quantitative assessment of existing data (for instance concerning patients with neural deficits).

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.

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...

Fear memory in a neurodevelopmental model of schizophrenia based on the postnatal blockade of NMDA receptors.

Science.gov (United States)

Latusz, Joachim; Radaszkiewicz, Aleksandra; Bator, Ewelina; Wędzony, Krzysztof; Maćkowiak, Marzena

2017-02-01

Epidemiological data have indicated that memory impairment is observed during adolescence in groups at high risk for schizophrenia and might precede the appearance of schizophrenia symptoms in adulthood. In the present study, we used a neurodevelopmental model of schizophrenia based on the postnatal blockade of N-methyl-d-aspartate (NMDA) receptors in rats to investigate fear memory in adolescence and adulthood. The rats were treated with increasing doses of CGP 37849 (CGP), a competitive antagonist of the NMDA receptor (1.25mg/kg on days 1, 3, 6, 9; 2.5mg/kg on days 12, 15, 18 and 5mg/kg on day 21). Fear memory was analysed in delay and trace fear conditioning. Sensorimotor gating deficit, which is another cognitive symptom of schizophrenia, was also determined in adolescent and adult CGP-treated rats. Postnatal CGP administration disrupted cue- and context-dependent fear memory in adolescent rats in both delay and trace conditioning. In contrast, CGP administration evoked impairment only in cue-dependent fear memory in rats exposed to trace but not delay fear conditioning. The postnatal blockade of NMDA receptors induced sensorimotor gating deficits in adult rats but not in adolescent rats. The postnatal blockade of NMDA receptors induced fear memory impairment in adolescent rats before the onset of neurobehavioral deficits associated with schizophrenia. Copyright © 2016. Published by Elsevier Urban & Partner Sp. z o.o.

Abnormal Fear Memory as a Model for Posttraumatic Stress Disorder.

Science.gov (United States)

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

2015-09-01

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

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.

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.

Resistive content addressable memory based in-memory computation architecture

KAUST Repository

Salama, Khaled N.; Zidan, Mohammed A.; Kurdahi, Fadi; Eltawil, Ahmed M.

2016-01-01

Various examples are provided examples related to resistive content addressable memory (RCAM) based in-memory computation architectures. In one example, a system includes a content addressable memory (CAM) including an array of cells having a memristor based crossbar and an interconnection switch matrix having a gateless memristor array, which is coupled to an output of the CAM. In another example, a method, includes comparing activated bit values stored a key register with corresponding bit values in a row of a CAM, setting a tag bit value to indicate that the activated bit values match the corresponding bit values, and writing masked key bit values to corresponding bit locations in the row of the CAM based on the tag bit value.

Resistive content addressable memory based in-memory computation architecture

KAUST Repository

Salama, Khaled N.

2016-12-08

Various examples are provided examples related to resistive content addressable memory (RCAM) based in-memory computation architectures. In one example, a system includes a content addressable memory (CAM) including an array of cells having a memristor based crossbar and an interconnection switch matrix having a gateless memristor array, which is coupled to an output of the CAM. In another example, a method, includes comparing activated bit values stored a key register with corresponding bit values in a row of a CAM, setting a tag bit value to indicate that the activated bit values match the corresponding bit values, and writing masked key bit values to corresponding bit locations in the row of the CAM based on the tag bit value.

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.

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.

Working memory: theories, models, and controversies.

Science.gov (United States)

Baddeley, Alan

2012-01-01

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

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

CERN Document Server

Khoromskaia, V K

2004-01-01

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

A Memory-based Robot Architecture based on Contextual Information

OpenAIRE

Pratama, Ferdian; Mastrogiovanni, Fulvio; Chong, Nak Young

2014-01-01

In this paper, we present a preliminary conceptual design for a robot long-term memory architecture based on the notion of context. Contextual information is used to organize the data flow between Working Memory (including Perceptual Memory) and Long-Term Memory components. We discuss the major influence of the notion of context within Episodic Memory on Semantic and Procedural Memory, respectively. We address how the occurrence of specific object-related events in time impacts on the semanti...

An Agent-Based Model for the Role of Short-Term Memory Enhancement in the Emergence of Grammatical Agreement.

Science.gov (United States)

Vera, Javier

2018-01-01

What is the influence of short-term memory enhancement on the emergence of grammatical agreement systems in multi-agent language games? Agreement systems suppose that at least two words share some features with each other, such as gender, number, or case. Previous work, within the multi-agent language-game framework, has recently proposed models stressing the hypothesis that the emergence of a grammatical agreement system arises from the minimization of semantic ambiguity. On the other hand, neurobiological evidence argues for the hypothesis that language evolution has mainly related to an increasing of short-term memory capacity, which has allowed the online manipulation of words and meanings participating particularly in grammatical agreement systems. Here, the main aim is to propose a multi-agent language game for the emergence of a grammatical agreement system, under measurable long-range relations depending on the short-term memory capacity. Computer simulations, based on a parameter that measures the amount of short-term memory capacity, suggest that agreement marker systems arise in a population of agents equipped at least with a critical short-term memory capacity.

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

Memory detection 2.0: the first web-based memory detection test.

Science.gov (United States)

Kleinberg, Bennett; Verschuere, Bruno

2015-01-01

There is accumulating evidence that reaction times (RTs) can be used to detect recognition of critical (e.g., crime) information. A limitation of this research base is its reliance upon small samples (average n = 24), and indications of publication bias. To advance RT-based memory detection, we report upon the development of the first web-based memory detection test. Participants in this research (Study1: n = 255; Study2: n = 262) tried to hide 2 high salient (birthday, country of origin) and 2 low salient (favourite colour, favourite animal) autobiographical details. RTs allowed to detect concealed autobiographical information, and this, as predicted, more successfully so than error rates, and for high salient than for low salient items. While much remains to be learned, memory detection 2.0 seems to offer an interesting new platform to efficiently and validly conduct RT-based memory detection research.

Memory detection 2.0: the first web-based memory detection test.

Directory of Open Access Journals (Sweden)

Bennett Kleinberg

Full Text Available There is accumulating evidence that reaction times (RTs can be used to detect recognition of critical (e.g., crime information. A limitation of this research base is its reliance upon small samples (average n = 24, and indications of publication bias. To advance RT-based memory detection, we report upon the development of the first web-based memory detection test. Participants in this research (Study1: n = 255; Study2: n = 262 tried to hide 2 high salient (birthday, country of origin and 2 low salient (favourite colour, favourite animal autobiographical details. RTs allowed to detect concealed autobiographical information, and this, as predicted, more successfully so than error rates, and for high salient than for low salient items. While much remains to be learned, memory detection 2.0 seems to offer an interesting new platform to efficiently and validly conduct RT-based memory detection research.

Comparing vector-based and Bayesian memory models using large-scale datasets: User-generated hashtag and tag prediction on Twitter and Stack Overflow.

Science.gov (United States)

Stanley, Clayton; Byrne, Michael D

2016-12-01

The growth of social media and user-created content on online sites provides unique opportunities to study models of human declarative memory. By framing the task of choosing a hashtag for a tweet and tagging a post on Stack Overflow as a declarative memory retrieval problem, 2 cognitively plausible declarative memory models were applied to millions of posts and tweets and evaluated on how accurately they predict a user's chosen tags. An ACT-R based Bayesian model and a random permutation vector-based model were tested on the large data sets. The results show that past user behavior of tag use is a strong predictor of future behavior. Furthermore, past behavior was successfully incorporated into the random permutation model that previously used only context. Also, ACT-R's attentional weight term was linked to an entropy-weighting natural language processing method used to attenuate high-frequency words (e.g., articles and prepositions). Word order was not found to be a strong predictor of tag use, and the random permutation model performed comparably to the Bayesian model without including word order. This shows that the strength of the random permutation model is not in the ability to represent word order, but rather in the way in which context information is successfully compressed. The results of the large-scale exploration show how the architecture of the 2 memory models can be modified to significantly improve accuracy, and may suggest task-independent general modifications that can help improve model fit to human data in a much wider range of domains. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

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

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

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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.

Preserved memory-based orienting of attention with impaired explicit memory in healthy ageing.

Science.gov (United States)

Salvato, Gerardo; Patai, Eva Z; Nobre, Anna C

2016-01-01

It is increasingly recognised that spatial contextual long-term memory (LTM) prepares neural activity for guiding visuo-spatial attention in a proactive manner. In the current study, we investigated whether the decline in explicit memory observed in healthy ageing would compromise this mechanism. We compared the behavioural performance of younger and older participants on learning new contextual memories, on orienting visual attention based on these learnt contextual associations, and on explicit recall of contextual memories. We found a striking dissociation between older versus younger participants in the relationship between the ability to retrieve contextual memories versus the ability to use these to guide attention to enhance performance on a target-detection task. Older participants showed significant deficits in the explicit retrieval task, but their behavioural benefits from memory-based orienting of attention were equivalent to those in young participants. Furthermore, memory-based orienting correlated significantly with explicit contextual LTM in younger adults but not in older adults. These results suggest that explicit memory deficits in ageing might not compromise initial perception and encoding of events. Importantly, the results also shed light on the mechanisms of memory-guided attention, suggesting that explicit contextual memories are not necessary. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Modeling of SONOS Memory Cell Erase Cycle

Science.gov (United States)

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

2011-01-01

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

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.

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

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

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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.

Single Canonical Model of Reflexive Memory and Spatial Attention

Science.gov (United States)

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

2015-01-01

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

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.

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...

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.

Transfer after process-based object-location memory training in healthy older adults.

Science.gov (United States)

Zimmermann, Kathrin; von Bastian, Claudia C; Röcke, Christina; Martin, Mike; Eschen, Anne

2016-11-01

A substantial part of age-related episodic memory decline has been attributed to the decreasing ability of older adults to encode and retrieve associations among simultaneously processed information units from long-term memory. In addition, this ability seems to share unique variance with reasoning. In this study, we therefore examined whether process-based training of the ability to learn and remember associations has the potential to induce transfer effects to untrained episodic memory and reasoning tasks in healthy older adults (60-75 years). For this purpose, the experimental group (n = 36) completed 30 sessions of process-based object-location memory training, while the active control group (n = 31) practiced visual perception on the same material. Near (spatial episodic memory), intermediate (verbal episodic memory), and far transfer effects (reasoning) were each assessed with multiple tasks at four measurements (before, midway through, immediately after, and 4 months after training). Linear mixed-effects models revealed transfer effects on spatial episodic memory and reasoning that were still observed 4 months after training. These results provide first empirical evidence that process-based training can enhance healthy older adults' associative memory performance and positively affect untrained episodic memory and reasoning abilities. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

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

Science.gov (United States)

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

2014-12-01

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

Operational Semantics of a Weak Memory Model inspired by Go

OpenAIRE

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

2017-01-01

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

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

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

Feedforward-feedback hybrid control for magnetic shape memory alloy actuators based on the Krasnosel'skii-Pokrovskii model.

Directory of Open Access Journals (Sweden)

Miaolei Zhou

Full Text Available As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system.

Feedforward-feedback hybrid control for magnetic shape memory alloy actuators based on the Krasnosel'skii-Pokrovskii model.

Science.gov (United States)

Zhou, Miaolei; Zhang, Qi; Wang, Jingyuan

2014-01-01

As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system.

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…

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.

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

Strategies To Enhance Memory Based on Brain-Research.

Science.gov (United States)

Banikowski, Alison K.; Mehring, Teresa A.

1999-01-01

This article reviews the literature on three aspects of memory: (1) an information processing model of memory (including the sensory register, attention, short-term memory, and long-term memory); (2) instructional strategies designed to enhance memory (which stress gaining students' attention and active involvement); and (3) reasons why…

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

Science.gov (United States)

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

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

Implicit Schemata and Categories in Memory-Based Language Processing

Science.gov (United States)

van den Bosch, Antal; Daelemans, Walter

2013-01-01

Memory-based language processing (MBLP) is an approach to language processing based on exemplar storage during learning and analogical reasoning during processing. From a cognitive perspective, the approach is attractive as a model for human language processing because it does not make any assumptions about the way abstractions are shaped, nor any…

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

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...

Memory-Based Shallow Parsing

NARCIS (Netherlands)

Tjong Kim Sang, E.F.

2002-01-01

We present memory-based learning approaches to shallow parsing and apply these to five tasks: base noun phrase identification, arbitrary base phrase recognition, clause detection, noun phrase parsing and full parsing. We use feature selection techniques and system combination methods for improving

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.

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

Strategies for memory-based decision making : Modeling behavioral and neural signatures within a cognitive architecture

NARCIS (Netherlands)

Fechner, Hanna B; Pachur, Thorsten; Schooler, Lael J; Mehlhorn, Katja; Battal, Ceren; Volz, Kirsten G; Borst, Jelmer P.

2016-01-01

How do people use memories to make inferences about real-world objects? We tested three strategies based on predicted patterns of response times and blood-oxygen-level-dependent (BOLD) responses: one strategy that relies solely on recognition memory, a second that retrieves additional knowledge, and

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

Science.gov (United States)

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

2016-03-01

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

Investigating Phase Transform Behavior in Indium Selenide Based RAM and Its Validation as a Memory Element

Directory of Open Access Journals (Sweden)

Swapnil Sourav

2016-01-01

Full Text Available Phase transform properties of Indium Selenide (In2Se3 based Random Access Memory (RAM have been explored in this paper. Phase change random access memory (PCRAM is an attractive solid-state nonvolatile memory that possesses potential to meet various current technology demands of memory design. Already reported PCRAM models are mainly based upon Germanium-Antimony-Tellurium (Ge2Sb2Te5 or GST materials as their prime constituents. However, PCRAM using GST material lacks some important memory attributes required for memory elements such as larger resistance margin between the highly resistive amorphous and highly conductive crystalline states in phase change materials. This paper investigates various electrical and compositional properties of the Indium Selenide (In2Se3 material and also draws comparison with its counterpart mainly focusing on phase transform properties. To achieve this goal, a SPICE model of In2Se3 based PCRAM model has been reported in this work. The reported model has been also validated to act as a memory cell by associating it with a read/write circuit proposed in this work. Simulation results demonstrate impressive retentivity and low power consumption by requiring a set pulse of 208 μA for a duration of 100 μs to set the PCRAM in crystalline state. Similarly, a reset pulse of 11.7 μA for a duration of 20 ns can set the PCRAM in amorphous state. Modeling of In2Se3 based PCRAM has been done in Verilog-A and simulation results have been extensively verified using SPICE simulator.

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.

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

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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.

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

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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).

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

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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.

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

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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.

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.

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

Model for a flexible motor memory based on a self-active recurrent neural network.

Science.gov (United States)

Boström, Kim Joris; Wagner, Heiko; Prieske, Markus; de Lussanet, Marc

2013-10-01

Using recent recurrent network architecture based on the reservoir computing approach, we propose and numerically simulate a model that is focused on the aspects of a flexible motor memory for the storage of elementary movement patterns into the synaptic weights of a neural network, so that the patterns can be retrieved at any time by simple static commands. The resulting motor memory is flexible in that it is capable to continuously modulate the stored patterns. The modulation consists in an approximately linear inter- and extrapolation, generating a large space of possible movements that have not been learned before. A recurrent network of thousand neurons is trained in a manner that corresponds to a realistic exercising scenario, with experimentally measured muscular activations and with kinetic data representing proprioceptive feedback. The network is "self-active" in that it maintains recurrent flow of activation even in the absence of input, a feature that resembles the "resting-state activity" found in the human and animal brain. The model involves the concept of "neural outsourcing" which amounts to the permanent shifting of computational load from higher to lower-level neural structures, which might help to explain why humans are able to execute learned skills in a fluent and flexible manner without the need for attention to the details of the movement. Copyright © 2013 Elsevier B.V. All rights reserved.

Resource allocation models of auditory working memory.

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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.

About the choice of Gibbs' potential for modelling of FCC ↔ HCP transformation in FeMnSi-based shape memory alloys

Science.gov (United States)

Evard, Margarita E.; Volkov, Aleksandr E.; Belyaev, Fedor S.; Ignatova, Anna D.

2018-05-01

The choice of Gibbs' potential for microstructural modeling of FCC ↔ HCP martensitic transformation in FeMn-based shape memory alloys is discussed. Threefold symmetry of the HCP phase is taken into account on specifying internal variables characterizing volume fractions of martensite variants. Constraints imposed on model constants by thermodynamic equilibrium conditions are formulated.

Spike-based population coding and working memory.

Directory of Open Access Journals (Sweden)

Martin Boerlin

2011-02-01

Full Text Available Compelling behavioral evidence suggests that humans can make optimal decisions despite the uncertainty inherent in perceptual or motor tasks. A key question in neuroscience is how populations of spiking neurons can implement such probabilistic computations. In this article, we develop a comprehensive framework for optimal, spike-based sensory integration and working memory in a dynamic environment. We propose that probability distributions are inferred spike-per-spike in recurrently connected networks of integrate-and-fire neurons. As a result, these networks can combine sensory cues optimally, track the state of a time-varying stimulus and memorize accumulated evidence over periods much longer than the time constant of single neurons. Importantly, we propose that population responses and persistent working memory states represent entire probability distributions and not only single stimulus values. These memories are reflected by sustained, asynchronous patterns of activity which make relevant information available to downstream neurons within their short time window of integration. Model neurons act as predictive encoders, only firing spikes which account for new information that has not yet been signaled. Thus, spike times signal deterministically a prediction error, contrary to rate codes in which spike times are considered to be random samples of an underlying firing rate. As a consequence of this coding scheme, a multitude of spike patterns can reliably encode the same information. This results in weakly correlated, Poisson-like spike trains that are sensitive to initial conditions but robust to even high levels of external neural noise. This spike train variability reproduces the one observed in cortical sensory spike trains, but cannot be equated to noise. On the contrary, it is a consequence of optimal spike-based inference. In contrast, we show that rate-based models perform poorly when implemented with stochastically spiking neurons.

Memory Transmission in Small Groups and Large Networks: An Agent-Based Model.

Science.gov (United States)

Luhmann, Christian C; Rajaram, Suparna

2015-12-01

The spread of social influence in large social networks has long been an interest of social scientists. In the domain of memory, collaborative memory experiments have illuminated cognitive mechanisms that allow information to be transmitted between interacting individuals, but these experiments have focused on small-scale social contexts. In the current study, we took a computational approach, circumventing the practical constraints of laboratory paradigms and providing novel results at scales unreachable by laboratory methodologies. Our model embodied theoretical knowledge derived from small-group experiments and replicated foundational results regarding collaborative inhibition and memory convergence in small groups. Ultimately, we investigated large-scale, realistic social networks and found that agents are influenced by the agents with which they interact, but we also found that agents are influenced by nonneighbors (i.e., the neighbors of their neighbors). The similarity between these results and the reports of behavioral transmission in large networks offers a major theoretical insight by linking behavioral transmission to the spread of information. © The Author(s) 2015.

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

Science.gov (United States)

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

2006-11-22

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

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.

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

International Nuclear Information System (INIS)

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

2016-01-01

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

More than a filter: Feature-based attention regulates the distribution of visual working memory resources.

Science.gov (United States)

Dube, Blaire; Emrich, Stephen M; Al-Aidroos, Naseem

2017-10-01

Across 2 experiments we revisited the filter account of how feature-based attention regulates visual working memory (VWM). Originally drawing from discrete-capacity ("slot") models, the filter account proposes that attention operates like the "bouncer in the brain," preventing distracting information from being encoded so that VWM resources are reserved for relevant information. Given recent challenges to the assumptions of discrete-capacity models, we investigated whether feature-based attention plays a broader role in regulating memory. Both experiments used partial report tasks in which participants memorized the colors of circle and square stimuli, and we provided a feature-based goal by manipulating the likelihood that 1 shape would be probed over the other across a range of probabilities. By decomposing participants' responses using mixture and variable-precision models, we estimated the contributions of guesses, nontarget responses, and imprecise memory representations to their errors. Consistent with the filter account, participants were less likely to guess when the probed memory item matched the feature-based goal. Interestingly, this effect varied with goal strength, even across high probabilities where goal-matching information should always be prioritized, demonstrating strategic control over filter strength. Beyond this effect of attention on which stimuli were encoded, we also observed effects on how they were encoded: Estimates of both memory precision and nontarget errors varied continuously with feature-based attention. The results offer support for an extension to the filter account, where feature-based attention dynamically regulates the distribution of resources within working memory so that the most relevant items are encoded with the greatest precision. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Organic Nonvolatile Memory Devices Based on Ferroelectricity

NARCIS (Netherlands)

Naber, Ronald C. G.; Asadi, Kamal; Blom, Paul W. M.; de Leeuw, Dago M.; de Boer, Bert

2010-01-01

A memory functionality is a prerequisite for many applications of electronic devices. Organic nonvolatile memory devices based on ferroelectricity are a promising approach toward the development of a low-cost memory technology. In this Review Article we discuss the latest developments in this area

Organic nonvolatile memory devices based on ferroelectricity

NARCIS (Netherlands)

Naber, R.C.G.; Asadi, K.; Blom, P.W.M.; Leeuw, D.M. de; Boer, B. de

2010-01-01

A memory functionality is a prerequisite for many applications of electronic devices. Organic nonvolatile memory devices based on ferroelectricity are a promising approach toward the development of a low-cost memory technology. In this Review Article we discuss the latest developments in this area

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

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

Living Memorials: Understanding the Social Meanings of Community-Based Memorials to September 11, 2001

Science.gov (United States)

Erika S. Svendsen; Lindsay K. Campbell

2010-01-01

Living memorials are landscaped spaces created by people to memorialize individuals, places, and events. Hundreds of stewardship groups across the United States of America created living memorials in response to the September 11, 2001 terrorist attacks. This study sought to understand how stewards value, use, and talk about their living, community-based memorials....

3D phenomenological constitutive modeling of shape memory alloys based on microplane theory

International Nuclear Information System (INIS)

Mehrabi, R; Kadkhodaei, M

2013-01-01

This paper concerns 3D phenomenological modeling of shape memory alloys using microplane theory. In the proposed approach, transformation is assumed to be the only source of inelastic strain in 1D constitutive laws considered for any generic plane passing through a material point. 3D constitutive equations are derived by generalizing the 1D equations using a homogenization technique. In the developed model, inelastic strain is explicitly stated in terms of the martensite volume fraction. To compare this approach with incremental constitutive models, such an available model is applied in its 1D integral form to the microplane formulation, and it is shown that both the approaches produce similar results for different uniaxial loadings. A nonproportional loading is then studied, and the results are compared with those obtained from an available model in which the inelastic strain is divided into two separate portions for transformation and reorientation. A good agreement is seen between the results of the two approaches, indicating the capability of the proposed microplane formulation in predicting reorientation phenomena in shape memory alloys. The results of the model are compared with available experimental results for a nonproportional loading path, and a good agreement is seen between the findings. (paper)

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...

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.

My Experience with Ti-Ni-Based and Ti-Based Shape Memory Alloys

Science.gov (United States)

Miyazaki, Shuichi

2017-12-01

The present author has been studying shape memory alloys including Cu-Al-Ni, Ti-Ni-based, and Ni-free Ti-based alloys since 1979. This paper reviews the present author's research results for the latter two materials since 1981. The topics on the Ti-Ni-based alloys include the achievement of superelasticity in Ti-Ni alloys through understanding of the role of microstructures consisting of dislocations and precipitates, followed by the contribution to the development of application market of shape memory effect and superelasticity, characterization of the R-phase and monoclinic martensitic transformations, clarification of the basic characteristics of fatigue properties, development of sputter-deposited shape memory thin films and fabrication of prototypes of microactuators utilizing thin films, development of high temperature shape memory alloys, and so on. The topics of Ni-free Ti-based shape memory alloys include the characterization of the orthorhombic phase martensitic transformation and related shape memory effect and superelasticity, the effects of texture, omega phase and adding elements on the martensitic transformation and shape memory properties, clarification of the unique effects of oxygen addition to induce non-linear large elasticity, Invar effect and heating-induced martensitic transformation, and so on.

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.

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.

Optimizing Memory Usage in L4-Based Microkernel

OpenAIRE

Petre Eftime; Lucian Mogoşanu; Mihai Carabaş; Răzvan Deaconescu; Laura Gheorghe; Valentin Gabriel Voiculescu

2017-01-01

Memory allocation is a critical aspect of any modern operating system kernel because it must run continuously for long periods of time, therefore memory leaks and inefficiency must be eliminated. This paper presents different memory management algorithms and their aplicability to an L4-based microkernel. We aim to reduce memory usage and increase the performance of allocation and deallocation of 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

Music-based memory enhancement in Alzheimer's disease: promise and limitations.

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Simmons-Stern, Nicholas R; Deason, Rebecca G; Brandler, Brian J; Frustace, Bruno S; O'Connor, Maureen K; Ally, Brandon A; Budson, Andrew E

2012-12-01

In a previous study (Simmons-Stern, Budson & Ally, 2010), we found that patients with Alzheimer's disease (AD) better recognized visually presented lyrics when the lyrics were also sung rather than spoken at encoding. The present study sought to further investigate the effects of music on memory in patients with AD by making the content of the song lyrics relevant for the daily life of an older adult and by examining how musical encoding alters several different aspects of episodic memory. Patients with AD and healthy older adults studied visually presented novel song lyrics related to instrumental activities of daily living (IADL) that were accompanied by either a sung or a spoken recording. Overall, participants performed better on a memory test of general lyric content for lyrics that were studied sung as compared to spoken. However, on a memory test of specific lyric content, participants performed equally well for sung and spoken lyrics. We interpret these results in terms of a dual-process model of recognition memory such that the general content questions represent a familiarity-based representation that is preferentially sensitive to enhancement via music, while the specific content questions represent a recollection-based representation unaided by musical encoding. Additionally, in a test of basic recognition memory for the audio stimuli, patients with AD demonstrated equal discrimination for sung and spoken stimuli. We propose that the perceptual distinctiveness of musical stimuli enhanced metamemorial awareness in AD patients via a non-selective distinctiveness heuristic, thereby reducing false recognition while at the same time reducing true recognition and eliminating the mnemonic benefit of music. These results are discussed in the context of potential music-based memory enhancement interventions for the care of patients with AD. Published by Elsevier Ltd.

The Development of Time-Based Prospective Memory in Childhood: The Role of Working Memory Updating

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Voigt, Babett; Mahy, Caitlin E. V.; Ellis, Judi; Schnitzspahn, Katharina; Krause, Ivonne; Altgassen, Mareike; Kliegel, Matthias

2014-01-01

This large-scale study examined the development of time-based prospective memory (PM) across childhood and the roles that working memory updating and time monitoring play in driving age effects in PM performance. One hundred and ninety-seven children aged 5 to 14 years completed a time-based PM task where working memory updating load was…

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

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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.

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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

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

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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.

No Evidence for Improved Associative Memory Performance Following Process-Based Associative Memory Training in Older Adults.

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Bellander, Martin; Eschen, Anne; Lövdén, Martin; Martin, Mike; Bäckman, Lars; Brehmer, Yvonne

2016-01-01

Studies attempting to improve episodic memory performance with strategy instructions and training have had limited success in older adults: their training gains are limited in comparison to those of younger adults and do not generalize to untrained tasks and contexts. This limited success has been partly attributed to age-related impairments in associative binding of information into coherent episodes. We therefore investigated potential training and transfer effects of process-based associative memory training (i.e., repeated practice). Thirty-nine older adults ( M age = 68.8) underwent 6 weeks of either adaptive associative memory training or item recognition training. Both groups improved performance in item memory, spatial memory (object-context binding) and reasoning. A disproportionate effect of associative memory training was only observed for item memory, whereas no training-related performance changes were observed for associative memory. Self-reported strategies showed no signs of spontaneous development of memory-enhancing associative memory strategies. Hence, the results do not support the hypothesis that process-based associative memory training leads to higher associative memory performance in older adults.

A model for visual memory encoding.

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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.

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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.

A mathematical model of capacious and efficient memory that survives trauma

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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.

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 ...

The Effect of Task Duration on Event-Based Prospective Memory: A Multinomial Modeling Approach

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Hongxia Zhang

2017-11-01

Full Text Available Remembering to perform an action when a specific event occurs is referred to as Event-Based Prospective Memory (EBPM. This study investigated how EBPM performance is affected by task duration by having university students (n = 223 perform an EBPM task that was embedded within an ongoing computer-based color-matching task. For this experiment, we separated the overall task’s duration into the filler task duration and the ongoing task duration. The filler task duration is the length of time between the intention and the beginning of the ongoing task, and the ongoing task duration is the length of time between the beginning of the ongoing task and the appearance of the first Prospective Memory (PM cue. The filler task duration and ongoing task duration were further divided into three levels: 3, 6, and 9 min. Two factors were then orthogonally manipulated between-subjects using a multinomial processing tree model to separate the effects of different task durations on the two EBPM components. A mediation model was then created to verify whether task duration influences EBPM via self-reminding or discrimination. The results reveal three points. (1 Lengthening the duration of ongoing tasks had a negative effect on EBPM performance while lengthening the duration of the filler task had no significant effect on it. (2 As the filler task was lengthened, both the prospective and retrospective components show a decreasing and then increasing trend. Also, when the ongoing task duration was lengthened, the prospective component decreased while the retrospective component significantly increased. (3 The mediating effect of discrimination between the task duration and EBPM performance was significant. We concluded that different task durations influence EBPM performance through different components with discrimination being the mediator between task duration and EBPM performance.

Sleep Deprivation and Time-Based Prospective Memory.

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Esposito, Maria José; Occhionero, Miranda; Cicogna, PierCarla

2015-11-01

To evaluate the effect of sleep deprivation on time-based prospective memory performance, that is, realizing delayed intentions at an appropriate time in the future (e.g., to take a medicine in 30 minutes). Between-subjects experimental design. The experimental group underwent 24 h of total sleep deprivation, and the control group had a regular sleep-wake cycle. Participants were tested at 08:00. Laboratory. Fifty healthy young adults (mean age 22 ± 2.1, 31 female). 24 h of total sleep deprivation. Participants were monitored by wrist actigraphy for 3 days before the experimental session. The following cognitive tasks were administered: one time-based prospective memory task and 3 reasoning tasks as ongoing activity. Objective and subjective vigilance was assessed by the psychomotor vigilance task and a visual analog scale, respectively. To measure the time-based prospective memory task we assessed compliance and clock checking behavior (time monitoring). Sleep deprivation negatively affected time-based prospective memory compliance (P sleep deprivation on human behavior, particularly the ability to perform an intended action after a few minutes. Sleep deprivation strongly compromises time-based prospective memory compliance but does not affect time check frequency. Sleep deprivation may impair the mechanism that allows the integration of information related to time monitoring with the prospective intention. © 2015 Associated Professional Sleep Societies, LLC.

EDITORIAL: Non-volatile memory based on nanostructures Non-volatile memory based on nanostructures

Science.gov (United States)

Kalinin, Sergei; Yang, J. Joshua; Demming, Anna

2011-06-01

Non-volatile memory refers to the crucial ability of computers to store information once the power source has been removed. Traditionally this has been achieved through flash, magnetic computer storage and optical discs, and in the case of very early computers paper tape and punched cards. While computers have advanced considerably from paper and punched card memory devices, there are still limits to current non-volatile memory devices that restrict them to use as secondary storage from which data must be loaded and carefully saved when power is shut off. Denser, faster, low-energy non-volatile memory is highly desired and nanostructures are the critical enabler. This special issue on non-volatile memory based on nanostructures describes some of the new physics and technology that may revolutionise future computers. Phase change random access memory, which exploits the reversible phase change between crystalline and amorphous states, also holds potential for future memory devices. The chalcogenide Ge2Sb2Te5 (GST) is a promising material in this field because it combines a high activation energy for crystallization and a relatively low crystallization temperature, as well as a low melting temperature and low conductivity, which accommodates localized heating. Doping is often used to lower the current required to activate the phase change or 'reset' GST but this often aggravates other problems. Now researchers in Korea report in-depth studies of SiO2-doped GST and identify ways of optimising the material's properties for phase-change random access memory [1]. Resistance switching is an area that has attracted a particularly high level of interest for non-volatile memory technology, and a great deal of research has focused on the potential of TiO2 as a model system in this respect. Researchers at HP labs in the US have made notable progress in this field, and among the work reported in this special issue they describe means to control the switch resistance and show

Time-based prospective memory in young children-Exploring executive functions as a developmental mechanism.

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Kretschmer, Anett; Voigt, Babett; Friedrich, Sylva; Pfeiffer, Kathrin; Kliegel, Matthias

2014-01-01

The present study investigated time-based prospective memory (PM) during the transition from kindergarten/preschool to school age and applied mediation models to test the impact of executive functions (working memory, inhibitory control) and time monitoring on time-based PM development. Twenty-five preschool (age: M = 5.75, SD = 0.28) and 22 primary school children (age: M = 7.83, SD = 0.39) participated. To examine time-based PM, children had to play a computer-based driving game requiring them to drive a car on a road without hitting others cars (ongoing task) and to refill the car regularly according to a fuel gauge, which serves as clock equivalent (PM task). The level of gas that was still left in the fuel gauge was not displayed on the screen and children had to monitor it via a button press (time monitoring). Results revealed a developmental increase in time-based PM performance from preschool to school age. Applying the mediation models, only working memory was revealed to influence PM development. Neither inhibitory control alone nor the mediation paths leading from both executive functions to time monitoring could explain the link between age and time-based PM. Thus, results of the present study suggest that working memory may be one key cognitive process driving the developmental growth of time-based PM during the transition from preschool to school age.

Applications of Case Based Organizational Memory Supported by the PAbMM Architecture

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Martín

2017-04-01

Full Text Available In the aim to manage and retrieve the organizational knowledge, in the last years numerous proposals of models and tools for knowledge management and knowledge representation have arisen. However, most of them store knowledge in a non-structured or semi-structured way, hindering the semantic and automatic processing of this knowledge. In this paper we present a more detailed case-based organizational memory ontology, which aims at contributing to the design of an organizational memory based on cases, so that it can be used to learn, reasoning, solve problems, and as support to better decision making as well. The objective of this Organizational Memory is to serve as base for the organizational knowledge exchange in a processing architecture specialized in the measurement and evaluation. In this way, our processing architecture is based on the C-INCAMI framework (Context-Information Need, Concept model, Attribute, Metric and Indicator for defining the measurement projects. Additionally, the proposal architecture uses a big data repository to make available the data for consumption and to manage the Organizational Memory, which allows a feedback mechanism in relation with online processing. In order to illustrate its utility, two practical cases are explained: A pasture predictor system, using the data of the weather radar (WR of the Experimental Agricultural Station (EAS INTA Anguil (La Pampa State, Argentina and an outpatient monitoring scenario. Future trends and concluding remarks are extended.

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

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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…

Modeling Coevolution between Language and Memory Capacity during Language Origin

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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

3D Printed Photoresponsive Devices Based on Shape Memory Composites.

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Yang, Hui; Leow, Wan Ru; Wang, Ting; Wang, Juan; Yu, Jiancan; He, Ke; Qi, Dianpeng; Wan, Changjin; Chen, Xiaodong

2017-09-01

Compared with traditional stimuli-responsive devices with simple planar or tubular geometries, 3D printed stimuli-responsive devices not only intimately meet the requirement of complicated shapes at macrolevel but also satisfy various conformation changes triggered by external stimuli at the microscopic scale. However, their development is limited by the lack of 3D printing functional materials. This paper demonstrates the 3D printing of photoresponsive shape memory devices through combining fused deposition modeling printing technology and photoresponsive shape memory composites based on shape memory polymers and carbon black with high photothermal conversion efficiency. External illumination triggers the shape recovery of 3D printed devices from the temporary shape to the original shape. The effect of materials thickness and light density on the shape memory behavior of 3D printed devices is quantified and calculated. Remarkably, sunlight also triggers the shape memory behavior of these 3D printed devices. This facile printing strategy would provide tremendous opportunities for the design and fabrication of biomimetic smart devices and soft robotics. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Can We Efficiently Check Concurrent Programs Under Relaxed Memory Models in Maude?

DEFF Research Database (Denmark)

Arrahman, Yehia Abd; Andric, Marina; Beggiato, Alessandro

2014-01-01

to the state space explosion. Several techniques have been proposed to mitigate those problems so to make verification under relaxed memory models feasible. We discuss how to adopt some of those techniques in a Maude-based approach to language prototyping, and suggest the use of other techniques that have been......Relaxed memory models offer suitable abstractions of the actual optimizations offered by multi-core architectures and by compilers of concurrent programming languages. Using such abstractions for verification purposes is challenging in part due to their inherent non-determinism which contributes...

Comparing soil moisture memory in satellite observations and models

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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.

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.

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).

Generalized memory associativity in a network model for the neuroses

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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.

Musical Memories: translating evidence-based gerontological nursing into a children's picture book.

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Gerdner, Linda A; Buckwalter, Kathleen C

2013-01-01

Individuals with Alzheimer's disease (AD) are often cared for within multigenerational families. More specifically, 26% of family caregivers have children younger than 18 living with them. This article describes an innovative model for translation of an evidence-based intervention into an engaging, realistic picture book that serves as a teaching tool for children and their families. The book, Musical Memories, focuses on the relationship between a granddaughter and her grandmother who has AD. The story applies basic principles of the Progressively Lowered Stress Threshold model to explain the underlying cause of grandmother's behaviors and models the evidence-based guideline "Individualized Music for Elders with Dementia" to empower the granddaughter in maintaining a relationship with her grandmother. Musical Memories is intended to serve as a valuable resource for families and the gerontological nurses who serve them. Copyright 2013, SLACK Incorporated.

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...

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.

Polynomial constitutive model for shape memory and pseudo elasticity

International Nuclear Information System (INIS)

Savi, M.A.; Kouzak, Z.

1995-01-01

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

Episodic memories predict adaptive value-based decision-making

Science.gov (United States)

Murty, Vishnu; FeldmanHall, Oriel; Hunter, Lindsay E.; Phelps, Elizabeth A; Davachi, Lila

2016-01-01

Prior research illustrates that memory can guide value-based decision-making. For example, previous work has implicated both working memory and procedural memory (i.e., reinforcement learning) in guiding choice. However, other types of memories, such as episodic memory, may also influence decision-making. Here we test the role for episodic memory—specifically item versus associative memory—in supporting value-based choice. Participants completed a task where they first learned the value associated with trial unique lotteries. After a short delay, they completed a decision-making task where they could choose to re-engage with previously encountered lotteries, or new never before seen lotteries. Finally, participants completed a surprise memory test for the lotteries and their associated values. Results indicate that participants chose to re-engage more often with lotteries that resulted in high versus low rewards. Critically, participants not only formed detailed, associative memories for the reward values coupled with individual lotteries, but also exhibited adaptive decision-making only when they had intact associative memory. We further found that the relationship between adaptive choice and associative memory generalized to more complex, ecologically valid choice behavior, such as social decision-making. However, individuals more strongly encode experiences of social violations—such as being treated unfairly, suggesting a bias for how individuals form associative memories within social contexts. Together, these findings provide an important integration of episodic memory and decision-making literatures to better understand key mechanisms supporting adaptive behavior. PMID:26999046

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.

A carrier transport model in the high-resistance state of lead-methylamine iodide-based resistive memory devices

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Yongwoo Kwon

2017-08-01

Full Text Available Methylamine lead iodide (CH3NH3PbI3, which has recently been in the spotlight as a solar cell material, has also recently shown promise for use as an active material in resistive memory cells with ultralow operation voltages, good transparencies, and flexibilities. The material’s defects, which govern its properties, differ vastly depending on the fabrication process. However, the defect chemistry is not yet entirely understood. We have therefore established a macroscopic transport model with defect-related model parameters, such as trap density, trap energy level, and Fermi level, in order to estimate these parameters for fabricated samples based on their electrical data. Our model will serve as an efficient way to analyze the properties of the active material.

Linking agent-based models and stochastic models of financial markets.

Science.gov (United States)

Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H Eugene

2012-05-29

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that "fat" tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting.

Preserved memory-based orienting of attention with impaired explicit memory in healthy ageing.

OpenAIRE

Salvato, G; Patai, EZ; Nobre, AC

2015-01-01

It is increasingly recognised that spatial contextual long-term memory (LTM) prepares neural activity for guiding visuo-spatial attention in a proactive manner. In the current study, we investigated whether the decline in explicit memory observed in healthy ageing would compromise this mechanism. We compared the behavioural performance of younger and older participants on learning new contextual memories, on orienting visual attention based on these learnt contextual associations, and on expl...

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.

Music-Based Memory Enhancement in Alzheimer’s Disease: Promise and Limitations

Science.gov (United States)

Simmons-Stern, Nicholas R.; Deason, Rebecca G.; Brandler, Brian J.; Frustace, Bruno S.; O’Connor, Maureen K.; Ally, Brandon A.; Budson, Andrew E.

2012-01-01

In a previous study (Simmons-Stern, Budson, & Ally 2010), we found that patients with Alzheimer’s disease (AD) better recognized visually presented lyrics when the lyrics were also sung rather than spoken at encoding. The present study sought to further investigate the effects of music on memory in patients with AD by making the content of the song lyrics relevant for the daily life of an older adult and by examining how musical encoding alters several different aspects of episodic memory. Patients with AD and healthy older adults studied visually presented novel song lyrics related to instrumental activities of daily living (IADL) that were accompanied by either a sung or a spoken recording. Overall, participants performed better on a memory test of general lyric content for lyrics that were studied sung as compared to spoken. However, on a memory test of specific lyric content, participants performed equally well for sung and spoken lyrics. We interpret these results in terms of a dual-process model of recognition memory such that the general content questions represent a familiarity-based representation that is preferentially sensitive to enhancement via music, while the specific content questions represent a recollection-based representation unaided by musical encoding. Additionally, in a test of basic recognition memory for the audio stimuli, patients with AD demonstrated equal discrimination for sung and spoken stimuli. We propose that the perceptual distinctiveness of musical stimuli enhanced metamemorial awareness in AD patients via a non-selective distinctiveness heuristic, thereby reducing false recognition while at the same time reducing true recognition and eliminating the mnemonic benefit of music. These results are discussed in the context of potential music-based memory enhancement interventions for the care of patients with AD. PMID:23000133

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.

TiAu based shape memory alloys for high temperature applications

International Nuclear Information System (INIS)

Wadood, Abdul; Yamabe-Mitarai, Yoko; Hosoda, Hideki

2014-01-01

TiAu (equiatomic) exhibits phase transformaion from B2 (ordered bcc) to thermo-elastic orthorhombic B19 martensite at about 875K and thus TiAu is categorized as high temperature shape memory alloy. In this study, recent research and developments related to TiAu based high temperature shape memory alloys will be discussed in the Introduction part. Then some results of our research group related to strengthening of TiAu based high temperature shape memory alloys will be presented. Potential of TiAu based shape memory alloys for high temperature shape memory materials applications will also be discussed

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.

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.

The construction of semantic memory: grammar based representations learned from relational episodic information

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Francesco P Battaglia

2011-08-01

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

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

Science.gov (United States)

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

2011-01-01

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

MeSAP: a fast analytic power model for DRAM memories

NARCIS (Netherlands)

Poddar, S.; Jongerius, R.; Fiorin, L.; Mariani, G.; Dittmann, G.; Anghel, A.; Corporaal, H.

2017-01-01

The design of an energy-efficient memory subsystem is one of the key issues that system architects face today. To achieve this goal, architects usually rely on system simulators and trace-based DRAM power models. However, their long execution time makes the approach infeasible for the design-space

Auditory memory can be object based.

Science.gov (United States)

Dyson, Benjamin J; Ishfaq, Feraz

2008-04-01

Identifying how memories are organized remains a fundamental issue in psychology. Previous work has shown that visual short-term memory is organized according to the object of origin, with participants being better at retrieving multiple pieces of information from the same object than from different objects. However, it is not yet clear whether similar memory structures are employed for other modalities, such as audition. Under analogous conditions in the auditory domain, we found that short-term memories for sound can also be organized according to object, with a same-object advantage being demonstrated for the retrieval of information in an auditory scene defined by two complex sounds overlapping in both space and time. Our results provide support for the notion of an auditory object, in addition to the continued identification of similar processing constraints across visual and auditory domains. The identification of modality-independent organizational principles of memory, such as object-based coding, suggests possible mechanisms by which the human processing system remembers multimodal experiences.

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.

Microplane modelling of shape memory alloys

International Nuclear Information System (INIS)

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

2007-01-01

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

Novel Shape-Memory Polymer with Two Transition Temperature Based on Two Different Memory Mechanism

Institute of Scientific and Technical Information of China (English)

Liu Guoqin; Ding Xiaobing; Cao Yiping; Zheng Zhaohui; Peng Yuxing

2004-01-01

As an important kind of intelligent materials, shape-memory materials have been received increasing attention on account of their interesting properties and potential applications in recent years. Particularly, the rise of shape-memory polymers by far surpasses well-known metallic shape-memory alloys in their shape-memory properties. The advantages of polymers compared to other materials are their easier availability and their wide range of mechanical and physical properties. The polymers designed to exhibit a shape-memory effect require two components on the molecular level: crosslinks to determine the permanent shape and switching segments with Ttrans to fix the temporary shape. Up to now almost all papers on shape-memory polymers introduce switching segments with the covalent linking method. On the other hand, only several cases concern non-covalent interaction. However, the research works mentioned above is based on a single Ttrans (i.e., Tm or Tg).Following our previous work, here, we first report a novel kind of polymer consisted of PMMA-PEG semi-interpenetrating polymer networks (semi-IPN), which exhibiting independently two shape memory effects based on Tm and Tg, respectively. This result can also extend the shape memory polymer categories from one Ttrans to two Ttrans, and the combination of Tm and Tg give rise to an extremely excellent shape-memory effect.Two different shape memory behaviors of this material based on two transition temperatures were evaluated by bending test as follows: a straight strip of the specimen was folded at a temperature above Ttrans and kept in this shape. The so-deformed sample was cooled down to a temperature Tlow＜ Ttrans and the deforming stress were released. When the sample was heated up to the measuring temperature Thigh ＞ Ttrans, it recovered its initial shape. The deformation angle θ f varied as a function of time and the ratio of the recovery was defined as θ f /180. The PMMA-PEG polymer behaved as a hard plastic

Genetic algorithms with memory- and elitism-based immigrants in dynamic environments.

Science.gov (United States)

Yang, Shengxiang

2008-01-01

In recent years the genetic algorithm community has shown a growing interest in studying dynamic optimization problems. Several approaches have been devised. The random immigrants and memory schemes are two major ones. The random immigrants scheme addresses dynamic environments by maintaining the population diversity while the memory scheme aims to adapt genetic algorithms quickly to new environments by reusing historical information. This paper investigates a hybrid memory and random immigrants scheme, called memory-based immigrants, and a hybrid elitism and random immigrants scheme, called elitism-based immigrants, for genetic algorithms in dynamic environments. In these schemes, the best individual from memory or the elite from the previous generation is retrieved as the base to create immigrants into the population by mutation. This way, not only can diversity be maintained but it is done more efficiently to adapt genetic algorithms to the current environment. Based on a series of systematically constructed dynamic problems, experiments are carried out to compare genetic algorithms with the memory-based and elitism-based immigrants schemes against genetic algorithms with traditional memory and random immigrants schemes and a hybrid memory and multi-population scheme. The sensitivity analysis regarding some key parameters is also carried out. Experimental results show that the memory-based and elitism-based immigrants schemes efficiently improve the performance of genetic algorithms in dynamic environments.

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

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.)

Hysteresis modeling of magnetic shape memory alloy actuator based on Krasnosel'skii-Pokrovskii model.

Science.gov (United States)

Zhou, Miaolei; Wang, Shoubin; Gao, Wei

2013-01-01

As a new type of intelligent material, magnetically shape memory alloy (MSMA) has a good performance in its applications in the actuator manufacturing. Compared with traditional actuators, MSMA actuator has the advantages as fast response and large deformation; however, the hysteresis nonlinearity of the MSMA actuator restricts its further improving of control precision. In this paper, an improved Krasnosel'skii-Pokrovskii (KP) model is used to establish the hysteresis model of MSMA actuator. To identify the weighting parameters of the KP operators, an improved gradient correction algorithm and a variable step-size recursive least square estimation algorithm are proposed in this paper. In order to demonstrate the validity of the proposed modeling approach, simulation experiments are performed, simulations with improved gradient correction algorithm and variable step-size recursive least square estimation algorithm are studied, respectively. Simulation results of both identification algorithms demonstrate that the proposed modeling approach in this paper can establish an effective and accurate hysteresis model for MSMA actuator, and it provides a foundation for improving the control precision of MSMA actuator.

Hysteresis Modeling of Magnetic Shape Memory Alloy Actuator Based on Krasnosel'skii-Pokrovskii Model

Directory of Open Access Journals (Sweden)

Miaolei Zhou

2013-01-01

Full Text Available As a new type of intelligent material, magnetically shape memory alloy (MSMA has a good performance in its applications in the actuator manufacturing. Compared with traditional actuators, MSMA actuator has the advantages as fast response and large deformation; however, the hysteresis nonlinearity of the MSMA actuator restricts its further improving of control precision. In this paper, an improved Krasnosel'skii-Pokrovskii (KP model is used to establish the hysteresis model of MSMA actuator. To identify the weighting parameters of the KP operators, an improved gradient correction algorithm and a variable step-size recursive least square estimation algorithm are proposed in this paper. In order to demonstrate the validity of the proposed modeling approach, simulation experiments are performed, simulations with improved gradient correction algorithm and variable step-size recursive least square estimation algorithm are studied, respectively. Simulation results of both identification algorithms demonstrate that the proposed modeling approach in this paper can establish an effective and accurate hysteresis model for MSMA actuator, and it provides a foundation for improving the control precision of MSMA actuator.

A memory-based shallow parser for spoken Dutch

NARCIS (Netherlands)

Canisius, S.V.M.; van den Bosch, A.; Decadt, B.; Hoste, V.; De Pauw, G.

2004-01-01

We describe the development of a Dutch memory-based shallow parser. The availability of large treebanks for Dutch, such as the one provided by the Spoken Dutch Corpus, allows memory-based learners to be trained on examples of shallow parsing taken from the treebank, and act as a shallow parser after

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...

Kinetic memory based on the enzyme-limited competition.

Science.gov (United States)

Hatakeyama, Tetsuhiro S; Kaneko, Kunihiko

2014-08-01

Cellular memory, which allows cells to retain information from their environment, is important for a variety of cellular functions, such as adaptation to external stimuli, cell differentiation, and synaptic plasticity. Although posttranslational modifications have received much attention as a source of cellular memory, the mechanisms directing such alterations have not been fully uncovered. It may be possible to embed memory in multiple stable states in dynamical systems governing modifications. However, several experiments on modifications of proteins suggest long-term relaxation depending on experienced external conditions, without explicit switches over multi-stable states. As an alternative to a multistability memory scheme, we propose "kinetic memory" for epigenetic cellular memory, in which memory is stored as a slow-relaxation process far from a stable fixed state. Information from previous environmental exposure is retained as the long-term maintenance of a cellular state, rather than switches over fixed states. To demonstrate this kinetic memory, we study several models in which multimeric proteins undergo catalytic modifications (e.g., phosphorylation and methylation), and find that a slow relaxation process of the modification state, logarithmic in time, appears when the concentration of a catalyst (enzyme) involved in the modification reactions is lower than that of the substrates. Sharp transitions from a normal fast-relaxation phase into this slow-relaxation phase are revealed, and explained by enzyme-limited competition among modification reactions. The slow-relaxation process is confirmed by simulations of several models of catalytic reactions of protein modifications, and it enables the memorization of external stimuli, as its time course depends crucially on the history of the stimuli. This kinetic memory provides novel insight into a broad class of cellular memory and functions. In particular, applications for long-term potentiation are discussed

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...

Quantum dissipation from power-law memory

International Nuclear Information System (INIS)

Tarasov, Vasily E.

2012-01-01

A new quantum dissipation model based on memory mechanism is suggested. Dynamics of open and closed quantum systems with power-law memory is considered. The processes with power-law memory are described by using integration and differentiation of non-integer orders, by methods of fractional calculus. An example of quantum oscillator with linear friction and power-law memory is considered. - Highlights: ► A new quantum dissipation model based on memory mechanism is suggested. ► The generalization of Lindblad equation is considered. ► An exact solution of generalized Lindblad equation for quantum oscillator with linear friction and power-law memory is derived.

The Development of Time-Based Prospective Memory in Childhood: The Role of Working Memory Updating

NARCIS (Netherlands)

Voigt, B.; Mahy, C.E.V.; Ellis, J.; Schnitzspahn, K.M.; Krause, I.; Altgassen, A.M.; Kliegel, M.

2014-01-01

This large-scale study examined the development of time-based prospective memory (PM) across childhood and the roles that working memory updating and time monitoring play in driving age effects in PM performance. One hundred and ninety-seven children aged 5 to 14 years completed a time-based PM task

Dynamic Memory Model for Non-Stationary Optimization

DEFF Research Database (Denmark)

Bendtsen, Claus Nørgaard; Krink, Thiemo

2002-01-01

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

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

Directory of Open Access Journals (Sweden)

Hui Qian

2013-01-01

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

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.

Hidden long evolutionary memory in a model biochemical network

Science.gov (United States)

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

2018-04-01

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

[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.

Mass Spectrometry-based Approaches to Understand the Molecular Basis of Memory

Directory of Open Access Journals (Sweden)

Arthur Henriques Pontes

2016-10-01

Full Text Available The central nervous system is responsible for an array of cognitive functions such as memory, learning, language and attention. These processes tend to take place in distinct brain regions; yet, they need to be integrated to give rise to adaptive or meaningful behavior. Since cognitive processes result from underlying cellular and molecular changes, genomics and transcriptomics assays have been applied to human and animal models to understand such events. Nevertheless, genes and RNAs are not the end products of most biological functions. In order to gain further insights toward the understanding of brain processes, the field of proteomics has been of increasing importance in the past years. Advancements in liquid chromatography-tandem mass spectrometry (LC-MS/MS have enable the identification and quantification of thousand of proteins with high accuracy and sensitivity, fostering a revolution in the neurosciences. Herein, we review the molecular bases of explicit memory in the hippocampus. We outline the principles of mass spectrometry (MS-based proteomics, highlighting the use of this analytical tool to study memory formation. In addition, we discuss MS-based targeted approaches as the future of protein analysis.

Forward Behavioral Modeling of a Three-Way Amplitude Modulator-Based Transmitter Using an Augmented Memory Polynomial

Directory of Open Access Journals (Sweden)

Jatin Chatrath

2018-03-01

Full Text Available Reconfigurable and multi-standard RF front-ends for wireless communication and sensor networks have gained importance as building blocks for the Internet of Things. Simpler and highly-efficient transmitter architectures, which can transmit better quality signals with reduced impairments, are an important step in this direction. In this regard, mixer-less transmitter architecture, namely, the three-way amplitude modulator-based transmitter, avoids the use of imperfect mixers and frequency up-converters, and their resulting distortions, leading to an improved signal quality. In this work, an augmented memory polynomial-based model for the behavioral modeling of such mixer-less transmitter architecture is proposed. Extensive simulations and measurements have been carried out in order to validate the accuracy of the proposed modeling strategy. The performance of the proposed model is evaluated using normalized mean square error (NMSE for long-term evolution (LTE signals. NMSE for a LTE signal of 1.4 MHz bandwidth with 100,000 samples for digital combining and analog combining are recorded as −36.41 dB and −36.9 dB, respectively. Similarly, for a 5 MHz signal the proposed models achieves −31.93 dB and −32.08 dB NMSE using digital and analog combining, respectively. For further validation of the proposed model, amplitude-to-amplitude (AM-AM, amplitude-to-phase (AM-PM, and the spectral response of the modeled and measured data are plotted, reasonably meeting the desired modeling criteria.

Damage-based life prediction model for uniaxial low-cycle stress fatigue of super-elastic NiTi shape memory alloy microtubes

Science.gov (United States)

Song, Di; Kang, Guozheng; Kan, Qianhua; Yu, Chao; Zhang, Chuanzeng

2015-08-01

Based on the experimental observations for the uniaxial low-cycle stress fatigue failure of super-elastic NiTi shape memory alloy microtubes (Song et al 2015 Smart Mater. Struct. 24 075004) and a new definition of damage variable corresponding to the variation of accumulated dissipation energy, a phenomenological damage model is proposed to describe the damage evolution of the NiTi microtubes during cyclic loading. Then, with a failure criterion of Dc = 1, the fatigue lives of the NiTi microtubes are predicted by the damage-based model, the predicted lives are in good agreement with the experimental ones, and all of the points are located within an error band of 1.5 times.

Damage-based life prediction model for uniaxial low-cycle stress fatigue of super-elastic NiTi shape memory alloy microtubes

International Nuclear Information System (INIS)

Song, Di; Kang, Guozheng; Kan, Qianhua; Yu, Chao; Zhang, Chuanzeng

2015-01-01

Based on the experimental observations for the uniaxial low-cycle stress fatigue failure of super-elastic NiTi shape memory alloy microtubes (Song et al 2015 Smart Mater. Struct. 24 075004) and a new definition of damage variable corresponding to the variation of accumulated dissipation energy, a phenomenological damage model is proposed to describe the damage evolution of the NiTi microtubes during cyclic loading. Then, with a failure criterion of D c = 1, the fatigue lives of the NiTi microtubes are predicted by the damage-based model, the predicted lives are in good agreement with the experimental ones, and all of the points are located within an error band of 1.5 times. (paper)

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…

Hippocampal atrophy in people with memory deficits: results from the population-based IPREA study.

Science.gov (United States)

Ferrarini, Luca; van Lew, Baldur; Reiber, Johan H C; Gandin, Claudia; Galluzzo, Lucia; Scafato, Emanuele; Frisoni, Giovanni B; Milles, Julien; Pievani, Michela

2014-07-01

Clinical studies have shown that hippocampal atrophy is present before dementia in people with memory deficits and can predict dementia development. The question remains whether this association holds in the general population. This is of interest for the possible use of hippocampal atrophy to screen population for preventive interventions. The aim of this study was to assess hippocampal volume and shape abnormalities in elderly adults with memory deficits in a cross-sectional population-based study. We included individuals participating in the Italian Project on the Epidemiology of Alzheimer Disease (IPREA) study: 75 cognitively normal individuals (HC), 31 individuals with memory deficits (MEM), and 31 individuals with memory deficits not otherwise specified (MEMnos). Hippocampal volumes and shape were extracted through manual tracing and the growing and adaptive meshes (GAMEs) shape-modeling algorithm. We investigated between-group differences in hippocampal volume and shape, and correlations with memory deficits. In MEM participants, hippocampal volumes were significantly smaller than in HC and were mildly associated with worse memory scores. Memory-associated shape changes mapped to the anterior hippocampus. Shape-based analysis detected no significant difference between MEM and HC, while MEMnos showed shape changes in the posterior hippocampus compared with HC and MEM groups. These findings support the discriminant validity of hippocampal volumetry as a biomarker of memory impairment in the general population. The detection of shape changes in MEMnos but not in MEM participants suggests that shape-based biomarkers might lack sensitivity to detect Alzheimer's-like pathology in the general population.

Olfactory Memory

Science.gov (United States)

Eichenbaum, Howard; Robitsek, R. Jonathan

2009-01-01

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 electro-physiological 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. PMID:19686208

Neural bases of orthographic long-term memory and working memory in dysgraphia.

Science.gov (United States)

Rapp, Brenda; Purcell, Jeremy; Hillis, Argye E; Capasso, Rita; Miceli, Gabriele

2016-02-01

Spelling a word involves the retrieval of information about the word's letters and their order from long-term memory as well as the maintenance and processing of this information by working memory in preparation for serial production by the motor system. While it is known that brain lesions may selectively affect orthographic long-term memory and working memory processes, relatively little is known about the neurotopographic distribution of the substrates that support these cognitive processes, or the lesions that give rise to the distinct forms of dysgraphia that affect these cognitive processes. To examine these issues, this study uses a voxel-based mapping approach to analyse the lesion distribution of 27 individuals with dysgraphia subsequent to stroke, who were identified on the basis of their behavioural profiles alone, as suffering from deficits only affecting either orthographic long-term or working memory, as well as six other individuals with deficits affecting both sets of processes. The findings provide, for the first time, clear evidence of substrates that selectively support orthographic long-term and working memory processes, with orthographic long-term memory deficits centred in either the left posterior inferior frontal region or left ventral temporal cortex, and orthographic working memory deficits primarily arising from lesions of the left parietal cortex centred on the intraparietal sulcus. These findings also contribute to our understanding of the relationship between the neural instantiation of written language processes and spoken language, working memory and other cognitive skills. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Preservation of memory-based automaticity in reading for older adults.

Science.gov (United States)

Rawson, Katherine A; Touron, Dayna R

2015-12-01

Concerning age-related effects on cognitive skill acquisition, the modal finding is that older adults do not benefit from practice to the same extent as younger adults in tasks that afford a shift from slower algorithmic processing to faster memory-based processing. In contrast, Rawson and Touron (2009) demonstrated a relatively rapid shift to memory-based processing in the context of a reading task. The current research extended beyond this initial study to provide more definitive evidence for relative preservation of memory-based automaticity in reading tasks for older adults. Younger and older adults read short stories containing unfamiliar noun phrases (e.g., skunk mud) followed by disambiguating information indicating the combination's meaning (either the normatively dominant meaning or an alternative subordinate meaning). Stories were repeated across practice blocks, and then the noun phrases were presented in novel sentence frames in a transfer task. Both age groups shifted from computation to retrieval after relatively few practice trials (as evidenced by convergence of reading times for dominant and subordinate items). Most important, both age groups showed strong evidence for memory-based processing of the noun phrases in the transfer task. In contrast, older adults showed minimal shifting to retrieval in an alphabet arithmetic task, indicating that the preservation of memory-based automaticity in reading was task-specific. Discussion focuses on important implications for theories of memory-based automaticity in general and for specific theoretical accounts of age effects on memory-based automaticity, as well as fruitful directions for future research. (c) 2015 APA, all rights reserved).

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…

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.

MULTI: a shared memory approach to cooperative molecular modeling.

Science.gov (United States)

Darden, T; Johnson, P; Smith, H

1991-03-01

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

Memory Based Machine Intelligence Techniques in VLSI hardware

OpenAIRE

James, Alex Pappachen

2012-01-01

We briefly introduce the memory based approaches to emulate machine intelligence in VLSI hardware, describing the challenges and advantages. Implementation of artificial intelligence techniques in VLSI hardware is a practical and difficult problem. Deep architectures, hierarchical temporal memories and memory networks are some of the contemporary approaches in this area of research. The techniques attempt to emulate low level intelligence tasks and aim at providing scalable solutions to high ...

Modeling of strain effects on the device behaviors of ferroelectric memory field-effect transistors

International Nuclear Information System (INIS)

Yang, Feng; Hu, Guangda; Wu, Weibing; Yang, Changhong; Wu, Haitao; Tang, Minghua

2013-01-01

The influence of strains on the channel current–gate voltage behaviors and memory windows of ferroelectric memory field-effect transistors (FeMFETs) were studied using an improved model based on the Landau–Devonshire theory. ‘Channel potential–gate voltage’ ferroelectric polarization and silicon surface potential diagrams were constructed for strained single-domain BaTiO 3 FeMFETs. The compressive strains can increase (or decrease) the amplitude of transistor currents and enlarge memory windows. However, tensile strains only decrease the maximum value of transistor currents and compress memory windows. Mismatch strains were found to have a significant influence on the electrical behaviors of the devices, therefore, they must be considered in FeMFET device designing. (fast track communication)

Memory detection 2.0: The first web-based memory detection test

NARCIS (Netherlands)

Kleinberg, B.; Verschuere, B.

2015-01-01

There is accumulating evidence that reaction times (RTs) can be used to detect recognition of critical (e.g., crime) information. A limitation of this research base is its reliance upon small samples (average n = 24), and indications of publication bias. To advance RT-based memory detection, we

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

Science.gov (United States)

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

2016-01-01

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

A chiral-based magnetic memory device without a permanent magnet.

Science.gov (United States)

Ben Dor, Oren; Yochelis, Shira; Mathew, Shinto P; Naaman, Ron; Paltiel, Yossi

2013-01-01

Several technologies are currently in use for computer memory devices. However, there is a need for a universal memory device that has high density, high speed and low power requirements. To this end, various types of magnetic-based technologies with a permanent magnet have been proposed. Recent charge-transfer studies indicate that chiral molecules act as an efficient spin filter. Here we utilize this effect to achieve a proof of concept for a new type of chiral-based magnetic-based Si-compatible universal memory device without a permanent magnet. More specifically, we use spin-selective charge transfer through a self-assembled monolayer of polyalanine to magnetize a Ni layer. This magnitude of magnetization corresponds to applying an external magnetic field of 0.4 T to the Ni layer. The readout is achieved using low currents. The presented technology has the potential to overcome the limitations of other magnetic-based memory technologies to allow fabricating inexpensive, high-density universal memory-on-chip devices.

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...

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

Science.gov (United States)

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

2011-10-31

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

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.

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)

Memory-based attention capture when multiple items are maintained in visual working memory.

Science.gov (United States)

Hollingworth, Andrew; Beck, Valerie M

2016-07-01

Efficient visual search requires that attention is guided strategically to relevant objects, and most theories of visual search implement this function by means of a target template maintained in visual working memory (VWM). However, there is currently debate over the architecture of VWM-based attentional guidance. We contrasted a single-item-template hypothesis with a multiple-item-template hypothesis, which differ in their claims about structural limits on the interaction between VWM representations and perceptual selection. Recent evidence from van Moorselaar, Theeuwes, and Olivers (2014) indicated that memory-based capture during search, an index of VWM guidance, is not observed when memory set size is increased beyond a single item, suggesting that multiple items in VWM do not guide attention. In the present study, we maximized the overlap between multiple colors held in VWM and the colors of distractors in a search array. Reliable capture was observed when 2 colors were held in VWM and both colors were present as distractors, using both the original van Moorselaar et al. singleton-shape search task and a search task that required focal attention to array elements (gap location in outline square stimuli). In the latter task, memory-based capture was consistent with the simultaneous guidance of attention by multiple VWM representations. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

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.

Electric-field-controlled interface dipole modulation for Si-based memory devices.

Science.gov (United States)

Miyata, Noriyuki

2018-05-31

Various nonvolatile memory devices have been investigated to replace Si-based flash memories or emulate synaptic plasticity for next-generation neuromorphic computing. A crucial criterion to achieve low-cost high-density memory chips is material compatibility with conventional Si technologies. In this paper, we propose and demonstrate a new memory concept, interface dipole modulation (IDM) memory. IDM can be integrated as a Si field-effect transistor (FET) based memory device. The first demonstration of this concept employed a HfO 2 /Si MOS capacitor where the interface monolayer (ML) TiO 2 functions as a dipole modulator. However, this configuration is unsuitable for Si-FET-based devices due to its large interface state density (D it ). Consequently, we propose, a multi-stacked amorphous HfO 2 /1-ML TiO 2 /SiO 2 IDM structure to realize a low D it and a wide memory window. Herein we describe the quasi-static and pulse response characteristics of multi-stacked IDM MOS capacitors and demonstrate flash-type and analog memory operations of an IDM FET device.

All-printed paper-based memory

KAUST Repository

He, Jr-Hau; Lin, Chun-Ho; Lien, Der-Hsien

2016-01-01

All-printed paper-based substrate memory devices are described which can be prepared by a process that includes coating, using a screen printer, one or more areas of a paper substrate (102) with a conductor material (104), such as a carbon paste

Item Memory, Context Memory and the Hippocampus: fMRI Evidence

Science.gov (United States)

Rugg, Michael D.; Vilberg, Kaia L.; Mattson, Julia T.; Yu, Sarah S.; Johnson, Jeffrey D.; Suzuki, Maki

2012-01-01

Dual-process models of recognition memory distinguish between the retrieval of qualitative information about a prior event (recollection), and judgments of prior occurrence based on an acontextual sense of familiarity. fMRI studies investigating the neural correlates of memory encoding and retrieval conducted within the dual-process framework have…

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.

Global sensitivity analysis of a model related to memory formation in synapses: Model reduction based on epistemic parameter uncertainties and related issues.

Science.gov (United States)

Kulasiri, Don; Liang, Jingyi; He, Yao; Samarasinghe, Sandhya

2017-04-21

We investigate the epistemic uncertainties of parameters of a mathematical model that describes the dynamics of CaMKII-NMDAR complex related to memory formation in synapses using global sensitivity analysis (GSA). The model, which was published in this journal, is nonlinear and complex with Ca 2+ patterns with different level of frequencies as inputs. We explore the effects of parameter on the key outputs of the model to discover the most sensitive ones using GSA and partial ranking correlation coefficient (PRCC) and to understand why they are sensitive and others are not based on the biology of the problem. We also extend the model to add presynaptic neurotransmitter vesicles release to have action potentials as inputs of different frequencies. We perform GSA on this extended model to show that the parameter sensitivities are different for the extended model as shown by PRCC landscapes. Based on the results of GSA and PRCC, we reduce the original model to a less complex model taking the most important biological processes into account. We validate the reduced model against the outputs of the original model. We show that the parameter sensitivities are dependent on the inputs and GSA would make us understand the sensitivities and the importance of the parameters. A thorough phenomenological understanding of the relationships involved is essential to interpret the results of GSA and hence for the possible model reduction. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Social importance enhances prospective memory: evidence from an event-based task.

Science.gov (United States)

Walter, Stefan; Meier, Beat

2017-07-01

Prospective memory performance can be enhanced by task importance, for example by promising a reward. Typically, this comes at costs in the ongoing task. However, previous research has suggested that social importance (e.g., providing a social motive) can enhance prospective memory performance without additional monitoring costs in activity-based and time-based tasks. The aim of the present study was to investigate the influence of social importance in an event-based task. We compared four conditions: social importance, promising a reward, both social importance and promising a reward, and standard prospective memory instructions (control condition). The results showed enhanced prospective memory performance for all importance conditions compared to the control condition. Although ongoing task performance was slowed in all conditions with a prospective memory task when compared to a baseline condition with no prospective memory task, additional costs occurred only when both the social importance and reward were present simultaneously. Alone, neither social importance nor promising a reward produced an additional slowing when compared to the cost in the standard (control) condition. Thus, social importance and reward can enhance event-based prospective memory at no additional cost.

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

Threshold switching uniformity in In2Se3 nanowire-based phase change memory

International Nuclear Information System (INIS)

Chen Jian; Du Gang; Liu Xiao-Yan

2015-01-01

The uniformity of threshold voltage and threshold current in the In 2 Se 3 nanowire-based phase change memory (PCM) devices is investigated. Based on the trap-limited transport model, amorphous layer thickness, trap density, and trap depth are considered to clarify their influences upon the threshold voltage and threshold current through simulations. (paper)

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.

Research on Multi - Person Parallel Modeling Method Based on Integrated Model Persistent Storage

Science.gov (United States)

Qu, MingCheng; Wu, XiangHu; Tao, YongChao; Liu, Ying

2018-03-01

This paper mainly studies the multi-person parallel modeling method based on the integrated model persistence storage. The integrated model refers to a set of MDDT modeling graphics system, which can carry out multi-angle, multi-level and multi-stage description of aerospace general embedded software. Persistent storage refers to converting the data model in memory into a storage model and converting the storage model into a data model in memory, where the data model refers to the object model and the storage model is a binary stream. And multi-person parallel modeling refers to the need for multi-person collaboration, the role of separation, and even real-time remote synchronization modeling.

Ketamine alters lateral prefrontal oscillations in a rule-based working memory task.

Science.gov (United States)

Ma, Liya; Skoblenick, Kevin; Johnston, Kevin; Everling, Stefan

2018-02-02

Acute administration of N-methyl-D-aspartate receptor (NMDAR) antagonists in healthy humans and animals produces working memory deficits similar to those observed in schizophrenia. However, it is unclear whether they also lead to altered low-frequency (rule-based prosaccade and antisaccade working memory task, both before and after systemic injections of a subanesthetic dose (delay periods and inter-trial intervals. It also increased task-related alpha-band activities, likely reflecting compromised attention. Beta-band oscillations may be especially relevant to working memory processes, as stronger beta power weakly but significantly predicted shorter saccadic reaction time. Also in beta band, ketamine reduced the performance-related oscillation as well as the rule information encoded in the spectral power. Ketamine also reduced rule information in the spike-field phase consistency in almost all frequencies up to 60Hz. Our findings support NMDAR antagonists in non-human primates as a meaningful model for altered neural oscillations and synchrony, which reflect a disorganized network underlying the working memory deficits in schizophrenia. SIGNIFICANCE STATEMENT Low doses of ketamine-an NMDA receptor blocker-produce working memory deficits similar to those observed in schizophrenia. In the LPFC, a key brain region for working memory, we found that ketamine altered neural oscillatory activities in similar ways that differentiate schizophrenic patients and healthy subjects, during both task and non-task periods. Ketamine induced stronger gamma (30-60Hz) and weaker beta (13-30Hz) oscillations, reflecting local hyperactivity and reduced long-range communications. Furthermore, ketamine reduced performance-related oscillatory activities, as well as the rule information encoded in the oscillations and in the synchrony between single cell activities and oscillations. The ketamine model helps link the molecular and cellular basis of neural oscillatory changes to the working

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.

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.

Top-down attention based on object representation and incremental memory for knowledge building and inference.

Science.gov (United States)

Kim, Bumhwi; Ban, Sang-Woo; Lee, Minho

2013-10-01

Humans can efficiently perceive arbitrary visual objects based on an incremental learning mechanism with selective attention. This paper proposes a new task specific top-down attention model to locate a target object based on its form and color representation along with a bottom-up saliency based on relativity of primitive visual features and some memory modules. In the proposed model top-down bias signals corresponding to the target form and color features are generated, which draw the preferential attention to the desired object by the proposed selective attention model in concomitance with the bottom-up saliency process. The object form and color representation and memory modules have an incremental learning mechanism together with a proper object feature representation scheme. The proposed model includes a Growing Fuzzy Topology Adaptive Resonance Theory (GFTART) network which plays two important roles in object color and form biased attention; one is to incrementally learn and memorize color and form features of various objects, and the other is to generate a top-down bias signal to localize a target object by focusing on the candidate local areas. Moreover, the GFTART network can be utilized for knowledge inference which enables the perception of new unknown objects on the basis of the object form and color features stored in the memory during training. Experimental results show that the proposed model is successful in focusing on the specified target objects, in addition to the incremental representation and memorization of various objects in natural scenes. In addition, the proposed model properly infers new unknown objects based on the form and color features of previously trained objects. Copyright © 2013 Elsevier Ltd. All rights reserved.

Adult age differences in perceptually based, but not conceptually based implicit tests of memory.

Science.gov (United States)

Small, B J; Hultsch, D F; Masson, M E

1995-05-01

Implicit tests of memory assess the influence of recent experience without requiring awareness of remembering. Evidence concerning age differences on implicit tests of memory suggests small age differences in favor of younger adults. However, the majority of research examining this issue has relied upon perceptually based implicit tests. Recently, a second type of implicit test, one that relies upon conceptually based processes, has been identified. The pattern of age differences on this second type of implicit test is less clear. In the present study, we examined the pattern of age differences on one conceptually based (fact completion) and one perceptually based (stem completion) implicit test of memory, as well as two explicit tests of memory (fact and word recall). Tasks were administered to 403 adults from three age groups (19-34 years, 58-73 years, 74-89 years). Significant age differences in favor of the young were found on stem completion but not fact completion. Age differences were present for both word and fast recall. Correlational analyses examining the relationship of memory performance to other cognitive variables indicated that the implicit tests were supported by different components than the explicit tests, as well as being different from each other.

Prospective memory, working memory, retrospective memory and self-rated memory performance in persons with intellectual disability

OpenAIRE

Levén, Anna; Lyxell, Björn; Andersson, Jan; Danielsson, Henrik; Rönnberg, Jerker

2008-01-01

The purpose of the present study was to examine the relationship between prospective memory, working memory, retrospective memory and self-rated memory capacity in adults with and without intellectual disability. Prospective memory was investigated by means of a picture-based task. Working memory was measured as performance on span tasks. Retrospective memory was scored as recall of subject performed tasks. Self-ratings of memory performance were based on the prospective and retrospective mem...

Synchronization of map-based neurons with memory and synaptic delay

Energy Technology Data Exchange (ETDEWEB)

Sausedo-Solorio, J.M. [Universidad Autónoma del Estado de Hidalgo, Carretera Pachuca-Tulancingo Km. 4.5, 42074 Pachuca, Hidalgo (Mexico); Pisarchik, A.N., E-mail: apisarch@cio.mx [Centro de Investigaciones en Optica, Loma del Bosque 115, Lomas del Campestre, 37150 Leon, Guanajuato (Mexico); Centre for Biomedical Technology, Technical University of Madrid, Campus Montegancedo, 28223 Pozuelo de Alarcon, Madrid (Spain)

2014-06-13

Synchronization of two synaptically coupled neurons with memory and synaptic delay is studied using the Rulkov map, one of the simplest neuron models which displays specific features inherent to bursting dynamics. We demonstrate a transition from lag to anticipated synchronization as the relationship between the memory duration and the synaptic delay time changes. The neuron maps synchronize either with anticipation, if the memory is longer than the synaptic delay time, or with lag otherwise. The mean anticipation time is equal to the difference between the memory and synaptic delay independently of the coupling strength. Frequency entrainment and phase-locking phenomena as well as a transition from regular spikes to chaos are demonstrated with respect to the coupling strength. - Highlights: • We study synchronization of neurons with memory and synaptic delay in the map model. • Neurons synchronize either with anticipation or with lag depending on delay time. • Mean anticipation time is equal to the difference between memory and synaptic delay. • Frequency entrainment and phase locking are studied with respect to the coupling.

Surface Soil Moisture Memory Estimated from Models and SMAP Observations

Science.gov (United States)

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

2017-12-01

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

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.

Development of elastic properties of Cu-based shape memory alloys during martensitic transformation

Czech Academy of Sciences Publication Activity Database

Novák, Václav; Landa, Michal; Šittner, Petr

2004-01-01

Roč. 115, - (2004), s. 363 ISSN 1155-4339 Institutional research plan: CEZ:AV0Z1010914 Keywords : Cu-based shape memory alloy s * elastic properties * elastic constants * modelling Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 0.294, year: 2004

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.

Highly Efficient Coherent Optical Memory Based on Electromagnetically Induced Transparency

Science.gov (United States)

Hsiao, Ya-Fen; Tsai, Pin-Ju; Chen, Hung-Shiue; Lin, Sheng-Xiang; Hung, Chih-Chiao; Lee, Chih-Hsi; Chen, Yi-Hsin; Chen, Yong-Fan; Yu, Ite A.; Chen, Ying-Cheng

2018-05-01

Quantum memory is an important component in the long-distance quantum communication based on the quantum repeater protocol. To outperform the direct transmission of photons with quantum repeaters, it is crucial to develop quantum memories with high fidelity, high efficiency and a long storage time. Here, we achieve a storage efficiency of 92.0 (1.5)% for a coherent optical memory based on the electromagnetically induced transparency scheme in optically dense cold atomic media. We also obtain a useful time-bandwidth product of 1200, considering only storage where the retrieval efficiency remains above 50%. Both are the best record to date in all kinds of schemes for the realization of optical memory. Our work significantly advances the pursuit of a high-performance optical memory and should have important applications in quantum information science.

Concept of dynamic memory in economics

Science.gov (United States)

Tarasova, Valentina V.; Tarasov, Vasily E.

2018-02-01

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

A Working Memory Test Battery: Java-Based Collection of Seven Working Memory Tasks

Directory of Open Access Journals (Sweden)

James M Stone

2015-06-01

Full Text Available Working memory is a key construct within cognitive science. It is an important theory in its own right, but the influence of working memory is enriched due to the widespread evidence that measures of its capacity are linked to a variety of functions in wider cognition. To facilitate the active research environment into this topic, we describe seven computer-based tasks that provide estimates of short-term and working memory incorporating both visuospatial and verbal material. The memory span tasks provided are; digit span, matrix span, arrow span, reading span, operation span, rotation span, and symmetry span. These tasks are built to be simple to use, flexible to adapt to the specific needs of the research design, and are open source. All files can be downloaded from the project website http://www.cognitivetools.uk and the source code is available via Github.

Status and Prospects of ZnO-Based Resistive Switching Memory Devices

Science.gov (United States)

Simanjuntak, Firman Mangasa; Panda, Debashis; Wei, Kung-Hwa; Tseng, Tseung-Yuen

2016-08-01

In the advancement of the semiconductor device technology, ZnO could be a prospective alternative than the other metal oxides for its versatility and huge applications in different aspects. In this review, a thorough overview on ZnO for the application of resistive switching memory (RRAM) devices has been conducted. Various efforts that have been made to investigate and modulate the switching characteristics of ZnO-based switching memory devices are discussed. The use of ZnO layer in different structure, the different types of filament formation, and the different types of switching including complementary switching are reported. By considering the huge interest of transparent devices, this review gives the concrete overview of the present status and prospects of transparent RRAM devices based on ZnO. ZnO-based RRAM can be used for flexible memory devices, which is also covered here. Another challenge in ZnO-based RRAM is that the realization of ultra-thin and low power devices. Nevertheless, ZnO not only offers decent memory properties but also has a unique potential to be used as multifunctional nonvolatile memory devices. The impact of electrode materials, metal doping, stack structures, transparency, and flexibility on resistive switching properties and switching parameters of ZnO-based resistive switching memory devices are briefly compared. This review also covers the different nanostructured-based emerging resistive switching memory devices for low power scalable devices. It may give a valuable insight on developing ZnO-based RRAM and also should encourage researchers to overcome the challenges.

Subtle alterations in memory systems and normal visual attention in the GAERS model of absence epilepsy.

Science.gov (United States)

Marques-Carneiro, J E; Faure, J-B; Barbelivien, A; Nehlig, A; Cassel, J-C

2016-03-01

Even if considered benign, absence epilepsy may alter memory and attention, sometimes subtly. Very little is known on behavior and cognitive functions in the Genetic Absence Epilepsy Rats from Strasbourg (GAERS) model of absence epilepsy. We focused on different memory systems and sustained visual attention, using Non Epileptic Controls (NECs) and Wistars as controls. A battery of cognitive/behavioral tests was used. The functionality of reference, working, and procedural memory was assessed in the Morris water maze (MWM), 8-arm radial maze, T-maze and/or double-H maze. Sustained visual attention was evaluated in the 5-choice serial reaction time task. In the MWM, GAERS showed delayed learning and less efficient working memory. In the 8-arm radial maze and T-maze tests, working memory performance was normal in GAERS, although most GAERS preferred an egocentric strategy (based on proprioceptive/kinesthetic information) to solve the task, but could efficiently shift to an allocentric strategy (based on spatial cues) after protocol alteration. Procedural memory and visual attention were mostly unimpaired. Absence epilepsy has been associated with some learning problems in children. In GAERS, the differences in water maze performance (slower learning of the reference memory task and weak impairment of working memory) and in radial arm maze strategies suggest that cognitive alterations may be subtle, task-specific, and that normal performance can be a matter of strategy adaptation. Altogether, these results strengthen the "face validity" of the GAERS model: in humans with absence epilepsy, cognitive alterations are not easily detectable, which is compatible with subtle deficits. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

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).

Neurophysiological bases of exponential sensory decay and top-down memory retrieval: a model.

Science.gov (United States)

Zylberberg, Ariel; Dehaene, Stanislas; Mindlin, Gabriel B; Sigman, Mariano

2009-01-01

Behavioral observations suggest that multiple sensory elements can be maintained for a short time, forming a perceptual buffer which fades after a few hundred milliseconds. Only a subset of this perceptual buffer can be accessed under top-down control and broadcasted to working memory and consciousness. In turn, single-cell studies in awake-behaving monkeys have identified two distinct waves of response to a sensory stimulus: a first transient response largely determined by stimulus properties and a second wave dependent on behavioral relevance, context and learning. Here we propose a simple biophysical scheme which bridges these observations and establishes concrete predictions for neurophsyiological experiments in which the temporal interval between stimulus presentation and top-down allocation is controlled experimentally. Inspired in single-cell observations, the model involves a first transient response and a second stage of amplification and retrieval, which are implemented biophysically by distinct operational modes of the same circuit, regulated by external currents. We explicitly investigated the neuronal dynamics, the memory trace of a presented stimulus and the probability of correct retrieval, when these two stages were bracketed by a temporal gap. The model predicts correctly the dependence of performance with response times in interference experiments suggesting that sensory buffering does not require a specific dedicated mechanism and establishing a direct link between biophysical manipulations and behavioral observations leading to concrete predictions.

Neurophysiological bases of exponential sensory decay and top-down memory retrieval: a model

Directory of Open Access Journals (Sweden)

Ariel Zylberberg

2009-03-01

Full Text Available Behavioral observations suggest that multiple sensory elements can be maintained for a short time, forming a perceptual buffer which fades after a few hundred milliseconds. Only a subset of this perceptual buffer can be accessed under top-down control and broadcasted to working memory and consciousness. In turn, single-cell studies in awake-behaving monkeys have identified two distinct waves of response to a sensory stimulus: a first transient response largely determined by stimulus properties and a second wave dependent on behavioral relevance, context and learning. Here we propose a simple biophysical scheme which bridges these observations and establishes concrete predictions for neurophsyiological experiments in which the temporal interval between stimulus presentation and top-down allocation is controlled experimentally. Inspired in single-cell observations, the model involves a first transient response and a second stage of amplification and retrieval, which are implemented biophysically by distinct operational modes of the same circuit, regulated by external currents. We explicitly investigated the neuronal dynamics, the memory trace of a presented stimulus and the probability of correct retrieval, when these two stages were bracketed by a temporal gap. The model predicts correctly the dependence of performance with response times in interference experiments suggesting that sensory buffering does not require a specific dedicated mechanism and establishing a direct link between biophysical manipulations and behavioral observations leading to concrete predictions.

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.

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.

FPGA Based Intelligent Co-operative Processor in Memory Architecture

DEFF Research Database (Denmark)

Ahmed, Zaki; Sotudeh, Reza; Hussain, Dil Muhammad Akbar

2011-01-01

benefits of PIM, a concept of Co-operative Intelligent Memory (CIM) was developed by the intelligent system group of University of Hertfordshire, based on the previously developed Co-operative Pseudo Intelligent Memory (CPIM). This paper provides an overview on previous works (CPIM, CIM) and realization......In a continuing effort to improve computer system performance, Processor-In-Memory (PIM) architecture has emerged as an alternative solution. PIM architecture incorporates computational units and control logic directly on the memory to provide immediate access to the data. To exploit the potential...

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

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.

Memory-based snowdrift game on a square lattice

Science.gov (United States)

Shu, Feng; Liu, Xingwen; Fang, Kai; Chen, Hao

2018-04-01

Spatial reciprocity is an effective way widely accepted to facilitate cooperation. In the case of snowdrift game, some researches showed that spatial reciprocity inhibits cooperation for a very wide range of cost-to-benefit ratio r. However, some other researches found that based on the spatial reciprocity, a wider range of r is helpful to achieve a high cooperation level. Thus, how to enlarge the range of r for the purpose of promoting cooperation becomes a hot topic recently. This paper proposes a new memory-based method, in which each individual compares with its own previous payoffs to find out the maximal one as virtual payoff and then randomly compares with one of its neighbours to obtain the optimal strategy according to the given updating rules. It shows the positive effect of spatial reciprocity in the context of memory. Specifically, in this situation, not only the lower ratio can appear a high cooperation level, but also the larger ratio r can emerge a high cooperation level. That is, an expected cooperation level can be achieved simultaneously for small and large r. Furthermore, the scenarios of both constant-size memory and size-varying memory are investigated. An interesting phenomenon is discovered that the cooperation level drops down gradually as the memory size increases.

Quantum memory Write, read and reset

CERN Document Server

Wu Tai Tsun; Wu, Tai Tsun; Yu, Ming Lun

2002-01-01

A model is presented for the quantum memory, the content of which is a pure quantum state. In this model, the fundamental operations of writing on, reading, and resetting the memory are performed through scattering from the memory. The requirement that the quantum memory must remain in a pure state after scattering implies that the scattering is of a special type, and only certain incident waves are admissible. An example, based on the Fermi pseudo-potential in one dimension, is used to demonstrate that the requirements on the scattering process are consistent and can be satisfied. This model is compared with the commonly used model for the quantum memory; the most important difference is that the spatial dimensions and interference play a central role in the present model.

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....

Hardware emulation of Memristor based Ternary Content Addressable Memory

KAUST Repository

Bahloul, Mohamed A.

2017-12-13

MTCAM (Memristor Ternary Content Addressable Memory) is a special purpose storage medium in which data could be retrieved based on the stored content. Using Memristors as the main storage element provides the potential of achieving higher density and more efficient solutions than conventional methods. A key missing item in the validation of such approaches is the wide spread availability of hardware emulation platforms that can provide reliable and repeatable performance statistics. In this paper, we present a hardware MTCAM emulation based on 2-Transistors-2Memristors (2T2M) bit-cell. It builds on a bipolar memristor model with storing and fetching capabilities based on the actual current-voltage behaviour. The proposed design offers a flexible verification environment with quick design revisions, high execution speeds and powerful debugging techniques. The proposed design is modeled using VHDL and prototyped on Xilinx Virtex® FPGA.

Hardware emulation of Memristor based Ternary Content Addressable Memory

KAUST Repository

Bahloul, Mohamed A.; Naous, Rawan; Masmoudi, M.

2017-01-01

MTCAM (Memristor Ternary Content Addressable Memory) is a special purpose storage medium in which data could be retrieved based on the stored content. Using Memristors as the main storage element provides the potential of achieving higher density and more efficient solutions than conventional methods. A key missing item in the validation of such approaches is the wide spread availability of hardware emulation platforms that can provide reliable and repeatable performance statistics. In this paper, we present a hardware MTCAM emulation based on 2-Transistors-2Memristors (2T2M) bit-cell. It builds on a bipolar memristor model with storing and fetching capabilities based on the actual current-voltage behaviour. The proposed design offers a flexible verification environment with quick design revisions, high execution speeds and powerful debugging techniques. The proposed design is modeled using VHDL and prototyped on Xilinx Virtex® FPGA.

Detecting peripheral-based attacks on the host memory

CERN Document Server

Stewin, Patrick

2015-01-01

This work addresses stealthy peripheral-based attacks on host computers and presents a new approach to detecting them. Peripherals can be regarded as separate systems that have a dedicated processor and dedicated runtime memory to handle their tasks. The book addresses the problem that peripherals generally communicate with the host via the host’s main memory, storing cryptographic keys, passwords, opened files and other sensitive data in the process – an aspect attackers are quick to exploit.  Here, stealthy malicious software based on isolated micro-controllers is implemented to conduct an attack analysis, the results of which provide the basis for developing a novel runtime detector. The detector reveals stealthy peripheral-based attacks on the host’s main memory by exploiting certain hardware properties, while a permanent and resource-efficient measurement strategy ensures that the detector is also capable of detecting transient attacks, which can otherwise succeed when the applied strategy only me...

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

Science.gov (United States)

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

2008-09-01

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

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.

Reward associations magnify memory-based biases on perception.

Science.gov (United States)

Doallo, Sonia; Patai, Eva Zita; Nobre, Anna Christina

2013-02-01

Long-term spatial contextual memories are a rich source of predictions about the likely locations of relevant objects in the environment and should enable tuning of neural processing of unfolding events to optimize perception and action. Of particular importance is whether and how the reward outcome of past events can impact perception. We combined behavioral measures with recordings of brain activity with high temporal resolution to test whether the previous reward outcome associated with a memory could modulate the impact of memory-based biases on perception, and if so, the level(s) at which visual neural processing is biased by reward-associated memory-guided attention. Data showed that past rewards potentiate the effects of spatial memories upon the discrimination of target objects embedded within complex scenes starting from early perceptual stages. We show that a single reward outcome of learning impacts on how we perceive events in our complex environments.

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.

Parallel constraint satisfaction in memory-based decisions.

Science.gov (United States)

Glöckner, Andreas; Hodges, Sara D

2011-01-01

Three studies sought to investigate decision strategies in memory-based decisions and to test the predictions of the parallel constraint satisfaction (PCS) model for decision making (Glöckner & Betsch, 2008). Time pressure was manipulated and the model was compared against simple heuristics (take the best and equal weight) and a weighted additive strategy. From PCS we predicted that fast intuitive decision making is based on compensatory information integration and that decision time increases and confidence decreases with increasing inconsistency in the decision task. In line with these predictions we observed a predominant usage of compensatory strategies under all time-pressure conditions and even with decision times as short as 1.7 s. For a substantial number of participants, choices and decision times were best explained by PCS, but there was also evidence for use of simple heuristics. The time-pressure manipulation did not significantly affect decision strategies. Overall, the results highlight intuitive, automatic processes in decision making and support the idea that human information-processing capabilities are less severely bounded than often assumed.

A new DRAM-type memory devices based on polymethacrylate containing pendant 2-methylbenzothiazole

International Nuclear Information System (INIS)

Wang Dong; Li Hua; Li Najun; Zhao Ying; Zhou Qianhao; Xu Qingfeng; Lu Jianmei; Wang Lihua

2012-01-01

Graphical abstract: The devices fabricated with 75 nm and 45 nm thick pBVMA films were both found to exhibit DRAM type memory behaviors, which may indicate that the Al nanoparticles had no penetration into the thin film during the vacuum-deposition process. Highlights: ► The side-functional moieties of pBVMA regularly arranged in film state. ► The device exhibits volatile memory behavior with an ON/OFF current ratio up to 10 5 . ► The film thickness has nothing to do with the device's memory behavior. ► Physical theoretical models and molecular simulation supported the memory mechanism. - Abstract: A polymethacrylate containing pendant 2-methylbenzothiazole (pBVMA) with good thermal stability was synthesized by free radical polymerization. The devices based on pBVMA possess a sandwich structure comprising bottom indium-tin oxide (ITO) electrode and top Al electrode. The as-fabricated device exhibits the dynamic random access memory (DRAM) behavior with an ON/OFF current ratio up to 10 5 and can endure 10 8 read cycles under −1 V pulse voltage. The effect of the film thickness on the device performance was investigated and the devices fabricated with 75 nm and 45 nm thick pBVMA films were both found to exhibit DRAM type memory behaviors, which may indicate that the Al nanoparticles had no penetration into the thin film during the vacuum-deposition process. The molecular simulation and physical theoretical models were analyzed and the mechanism of the DRAM performance may be attributed to the weak electron withdrawing ability of the molecule.

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

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.

Non-volatile memory based on the ferroelectric photovoltaic effect

Science.gov (United States)

Guo, Rui; You, Lu; Zhou, Yang; Shiuh Lim, Zhi; Zou, Xi; Chen, Lang; Ramesh, R.; Wang, Junling

2013-01-01

The quest for a solid state universal memory with high-storage density, high read/write speed, random access and non-volatility has triggered intense research into new materials and novel device architectures. Though the non-volatile memory market is dominated by flash memory now, it has very low operation speed with ~10 μs programming and ~10 ms erasing time. Furthermore, it can only withstand ~105 rewriting cycles, which prevents it from becoming the universal memory. Here we demonstrate that the significant photovoltaic effect of a ferroelectric material, such as BiFeO3 with a band gap in the visible range, can be used to sense the polarization direction non-destructively in a ferroelectric memory. A prototype 16-cell memory based on the cross-bar architecture has been prepared and tested, demonstrating the feasibility of this technique. PMID:23756366

Performance-based empathy mediates the influence of working memory on social competence in schizophrenia.

Science.gov (United States)

Smith, Matthew J; Horan, William P; Cobia, Derin J; Karpouzian, Tatiana M; Fox, Jaclyn M; Reilly, James L; Breiter, Hans C

2014-07-01

Empathic deficits have been linked to poor functioning in schizophrenia, but this work is mostly limited to self-report data. This study examined whether performance-based empathy measures account for incremental variance in social competence and social attainment above and beyond self-reported empathy, neurocognition, and clinical symptoms. Given the importance of working memory in theoretical models of empathy and in the prediction of functioning in schizophrenia, we also examined whether empathy mediates the relationship between working memory and functioning. Sixty outpatients and 45 healthy controls were compared on performance-based measures of 3 key components of empathic responding, including facial affect perception, emotional empathy (affective responsiveness), and cognitive empathy (emotional perspective-taking). Participants also completed measures of self-reported empathy, neurocognition, clinical symptoms, and social competence and attainment. Patients demonstrated lower accuracy than controls across the 3 performance-based empathy measures. Among patients, these measures showed minimal relations to self-reported empathy but significantly correlated with working memory and other neurocognitive functions as well as symptom levels. Furthermore, cognitive empathy explained significant incremental variance in social competence (∆R (2) = .07, P working memory and social competence. Performance-based measures of empathy were sensitive to functionally relevant disturbances in schizophrenia. Working memory deficits appear to have an important effect on these disruptions in empathy. Empathy is emerging as a promising new area for social cognitive research and for novel recovery-oriented treatment development. © The Author 2013. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

A Probabilistic Model of Social Working Memory for Information Retrieval in Social Interactions.

Science.gov (United States)

Li, Liyuan; Xu, Qianli; Gan, Tian; Tan, Cheston; Lim, Joo-Hwee

2018-05-01

Social working memory (SWM) plays an important role in navigating social interactions. Inspired by studies in psychology, neuroscience, cognitive science, and machine learning, we propose a probabilistic model of SWM to mimic human social intelligence for personal information retrieval (IR) in social interactions. First, we establish a semantic hierarchy as social long-term memory to encode personal information. Next, we propose a semantic Bayesian network as the SWM, which integrates the cognitive functions of accessibility and self-regulation. One subgraphical model implements the accessibility function to learn the social consensus about IR-based on social information concept, clustering, social context, and similarity between persons. Beyond accessibility, one more layer is added to simulate the function of self-regulation to perform the personal adaptation to the consensus based on human personality. Two learning algorithms are proposed to train the probabilistic SWM model on a raw dataset of high uncertainty and incompleteness. One is an efficient learning algorithm of Newton's method, and the other is a genetic algorithm. Systematic evaluations show that the proposed SWM model is able to learn human social intelligence effectively and outperforms the baseline Bayesian cognitive model. Toward real-world applications, we implement our model on Google Glass as a wearable assistant for social interaction.

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.

Cognitive components underpinning the development of model-based learning.

Science.gov (United States)

Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A

2017-06-01

Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

A Chinese Chan-based lifestyle intervention improves memory of older adults

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Agnes S. eChan

2014-03-01

Full Text Available This study aims to explore the potential benefits of a Chinese Chan-based lifestyle intervention on enhancing memory in older people with lower memory function. Forty-four aged 60 to 83 adults with various level of memory ability participated in the study. Their memories (including verbal and visual components were assessed before and after a 3-month intervention. The intervention consisted of 12 sessions, with one 90-minute session per week. The intervention involved components of adopting a special vegetarian diet, practicing a type of mind-body exercises and learning self-realization. Elderly with lower memory function at the baseline (i.e., their performance on standardized memory tests was within 25th percentile showed a significant memory improvement after the intervention. Their verbal and visual memory performance has showed 50% and 49% enhancement respectively. In addition, their improvement can be considered as a reliable and clinically significant change as reflected by their significant pre-post differences and reliable change indices. Such robust treatment effect was found to be specific to memory functions, but less influencing on the other cognitive functions. These preliminary encouraging results have shed some light on the potential applicability of the Chinese Chan-based lifestyle intervention as a method for enhancing memory in the elderly population.

A mathematical model for smart functionally graded beam integrated with shape memory alloy actuators

International Nuclear Information System (INIS)

Sepiani, H.; Ebrahimi, F.; Karimipour, H.

2009-01-01

This paper presents a theoretical study of the thermally driven behavior of a shape memory alloy (SMA)/FGM actuator under arbitrary loading and boundary conditions by developing an integrated mathematical model. The model studied is established on the geometric parameters of the three-dimensional laminated composite box beam as an actuator that consists of a functionally graded core integrated with SMA actuator layers with a uniform rectangular cross section. The constitutive equation and linear phase transformation kinetics relations of SMA layers based on Tanaka and Nagaki model are coupled with the governing equation of the actuator to predict the stress history and to model the thermo-mechanical behavior of the smart shape memory alloy/FGM beam. Based on the classical laminated beam theory, the explicit solution to the structural response of the structure, including axial and lateral deflections of the structure, is investigated. As an example, a cantilever box beam subjected to a transverse concentrated load is solved numerically. It is found that the changes in the actuator's responses during the phase transformation due to the strain recovery are significant

Light programmable organic transistor memory device based on hybrid dielectric

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Ren, Xiaochen; Chan, Paddy K. L.

2013-09-01

We have fabricated the transistor memory devices based on SiO2 and polystyrene (PS) hybrid dielectric. The trap states densities with different semiconductors have been investigated and a maximum 160V memory window between programming and erasing is realized. For DNTT based transistor, the trapped electron density is limited by the number of mobile electrons in semiconductor. The charge transport mechanism is verified by light induced Vth shift effect. Furthermore, in order to meet the low operating power requirement of portable electronic devices, we fabricated the organic memory transistor based on AlOx/self-assembly monolayer (SAM)/PS hybrid dielectric, the effective capacitance of hybrid dielectric is 210 nF cm-2 and the transistor can reach saturation state at -3V gate bias. The memory window in transfer I-V curve is around 1V under +/-5V programming and erasing bias.

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

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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.

Cue-dependent memory-based smooth-pursuit in normal human subjects: importance of extra-retinal mechanisms for initial pursuit.

Science.gov (United States)

Ito, Norie; Barnes, Graham R; Fukushima, Junko; Fukushima, Kikuro; Warabi, Tateo

2013-08-01

Using a cue-dependent memory-based smooth-pursuit task previously applied to monkeys, we examined the effects of visual motion-memory on smooth-pursuit eye movements in normal human subjects and compared the results with those of the trained monkeys. These results were also compared with those during simple ramp-pursuit that did not require visual motion-memory. During memory-based pursuit, all subjects exhibited virtually no errors in either pursuit-direction or go/no-go selection. Tracking eye movements of humans and monkeys were similar in the two tasks, but tracking eye movements were different between the two tasks; latencies of the pursuit and corrective saccades were prolonged, initial pursuit eye velocity and acceleration were lower, peak velocities were lower, and time to reach peak velocities lengthened during memory-based pursuit. These characteristics were similar to anticipatory pursuit initiated by extra-retinal components during the initial extinction task of Barnes and Collins (J Neurophysiol 100:1135-1146, 2008b). We suggest that the differences between the two tasks reflect differences between the contribution of extra-retinal and retinal components. This interpretation is supported by two further studies: (1) during popping out of the correct spot to enhance retinal image-motion inputs during memory-based pursuit, pursuit eye velocities approached those during simple ramp-pursuit, and (2) during initial blanking of spot motion during memory-based pursuit, pursuit components appeared in the correct direction. Our results showed the importance of extra-retinal mechanisms for initial pursuit during memory-based pursuit, which include priming effects and extra-retinal drive components. Comparison with monkey studies on neuronal responses and model analysis suggested possible pathways for the extra-retinal mechanisms.

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

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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.

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

Science.gov (United States)

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

1988-01-01

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

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...

Cooperation in memory-based prisoner's dilemma game on interdependent networks

Science.gov (United States)

Luo, Chao; Zhang, Xiaolin; Liu, Hong; Shao, Rui

2016-05-01

Memory or so-called experience normally plays the important role to guide the human behaviors in real world, that is essential for rational decisions made by individuals. Hence, when the evolutionary behaviors of players with bounded rationality are investigated, it is reasonable to make an assumption that players in system are with limited memory. Besides, in order to unravel the intricate variability of complex systems in real world and make a highly integrative understanding of their dynamics, in recent years, interdependent networks as a comprehensive network structure have obtained more attention in this community. In this article, the evolution of cooperation in memory-based prisoner's dilemma game (PDG) on interdependent networks composed by two coupled square lattices is studied. Herein, all or part of players are endowed with finite memory ability, and we focus on the mutual influence of memory effect and interdependent network reciprocity on cooperation of spatial PDG. We show that the density of cooperation can be significantly promoted within an optimal region of memory length and interdependent strength. Furthermore, distinguished by whether having memory ability/external links or not, each kind of players on networks would have distinct evolutionary behaviors. Our work could be helpful to understand the emergence and maintenance of cooperation under the evolution of memory-based players on interdependent networks.

Private Memory Allocation Analysis for Safety-Critical Java

DEFF Research Database (Denmark)

Dalsgaard, Andreas E.; Hansen, René Rydhof; Schoeberl, Martin

2012-01-01

Safety-critical Java (SCJ) avoids garbage collection and uses a scope based memory model. This memory model is based on a restricted version of RTSJ [2] style scopes. The scopes form a clear hierarchy with different lifetimes. Therefore, references between objects in different scopes are only...

Dorsoventral and Proximodistal Hippocampal Processing Account for the Influences of Sleep and Context on Memory (Reconsolidation: A Connectionist Model

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Justin Lines

2017-01-01

Full Text Available The context in which learning occurs is sufficient to reconsolidate stored memories and neuronal reactivation may be crucial to memory consolidation during sleep. The mechanisms of context-dependent and sleep-dependent memory (reconsolidation are unknown but involve the hippocampus. We simulated memory (reconsolidation using a connectionist model of the hippocampus that explicitly accounted for its dorsoventral organization and for CA1 proximodistal processing. Replicating human and rodent (reconsolidation studies yielded the following results. (1 Semantic overlap between memory items and extraneous learning was necessary to explain experimental data and depended crucially on the recurrent networks of dorsal but not ventral CA3. (2 Stimulus-free, sleep-induced internal reactivations of memory patterns produced heterogeneous recruitment of memory items and protected memories from subsequent interference. These simulations further suggested that the decrease in memory resilience when subjects were not allowed to sleep following learning was primarily due to extraneous learning. (3 Partial exposure to the learning context during simulated sleep (i.e., targeted memory reactivation uniformly increased memory item reactivation and enhanced subsequent recall. Altogether, these results show that the dorsoventral and proximodistal organization of the hippocampus may be important components of the neural mechanisms for context-based and sleep-based memory (reconsolidations.

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.

Thermoplastic shape-memory polyurethanes based on natural oils

International Nuclear Information System (INIS)

Saralegi, Ainara; Eceiza, Arantxa; Corcuera, Maria Angeles; Johan Foster, E; Weder, Christoph

2014-01-01

A new family of segmented thermoplastic polyurethanes with thermally activated shape-memory properties was synthesized and characterized. Polyols derived from castor oil with different molecular weights but similar chemical structures and a corn-sugar-based chain extender (propanediol) were used as starting materials in order to maximize the content of carbon from renewable resources in the new materials. The composition was systematically varied to establish a structure–property map and identify compositions with desirable shape-memory properties. The thermal characterization of the new polyurethanes revealed a microphase separated structure, where both the soft (by convention the high molecular weight diol) and the hard phases were highly crystalline. Cyclic thermo-mechanical tensile tests showed that these polymers are excellent candidates for use as thermally activated shape-memory polymers, in which the crystalline soft segments promote high shape fixity values (close to 100%) and the hard segment crystallites ensure high shape recovery values (80–100%, depending on the hard segment content). The high proportion of components from renewable resources used in the polyurethane formulation leads to the synthesis of bio-based polyurethanes with shape-memory properties. (paper)

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.

The Memory State Heuristic: A Formal Model Based on Repeated Recognition Judgments

Science.gov (United States)

Castela, Marta; Erdfelder, Edgar

2017-01-01

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.,…

Ti-Ni-based shape memory alloys as smart materials

International Nuclear Information System (INIS)

Otsuka, K.; Xu, Y.; Ren, X.

2003-01-01

Smart materials consist of three principal materials, ferroelectrics, shape memory alloys (SMA) and electro-active polymers (EAP). Among these SMAs, especially Ti-Ni-based alloys are important, since only they can provide large recoverable strains and high recovery stress. In the present paper the unique characteristics of Ti-Ni-based shape memory alloys are reviewed on an up-to-date basis with the aim of their applications to smart materials and structures. (orig.)

Contextual effects in visual working memory reveal hierarchically structured memory representations.

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Brady, Timothy F; Alvarez, George A

2015-01-01

Influential slot and resource models of visual working memory make the assumption that items are stored in memory as independent units, and that there are no interactions between them. Consequently, these models predict that the number of items to be remembered (the set size) is the primary determinant of working memory performance, and therefore these models quantify memory capacity in terms of the number and quality of individual items that can be stored. Here we demonstrate that there is substantial variance in display difficulty within a single set size, suggesting that limits based on the number of individual items alone cannot explain working memory storage. We asked hundreds of participants to remember the same sets of displays, and discovered that participants were highly consistent in terms of which items and displays were hardest or easiest to remember. Although a simple grouping or chunking strategy could not explain this individual-display variability, a model with multiple, interacting levels of representation could explain some of the display-by-display differences. Specifically, a model that includes a hierarchical representation of items plus the mean and variance of sets of the colors on the display successfully accounts for some of the variability across displays. We conclude that working memory representations are composed only in part of individual, independent object representations, and that a major factor in how many items are remembered on a particular display is interitem representations such as perceptual grouping, ensemble, and texture representations.

Thermoregulatory model of sleep control: losing the heat memory.

Science.gov (United States)

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

1999-12-01

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

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.

A computational model of fMRI activity in the intraparietal sulcus that supports visual working memory.

Science.gov (United States)

Domijan, Dražen

2011-12-01

A computational model was developed to explain a pattern of results of fMRI activation in the intraparietal sulcus (IPS) supporting visual working memory for multiobject scenes. The model is based on the hypothesis that dendrites of excitatory neurons are major computational elements in the cortical circuit. Dendrites enable formation of a competitive queue that exhibits a gradient of activity values for nodes encoding different objects, and this pattern is stored in working memory. In the model, brain imaging data are interpreted as a consequence of blood flow arising from dendritic processing. Computer simulations showed that the model successfully simulates data showing the involvement of inferior IPS in object individuation and spatial grouping through representation of objects' locations in space, along with the involvement of superior IPS in object identification through representation of a set of objects' features. The model exhibits a capacity limit due to the limited dynamic range for nodes and the operation of lateral inhibition among them. The capacity limit is fixed in the inferior IPS regardless of the objects' complexity, due to the normalization of lateral inhibition, and variable in the superior IPS, due to the different encoding demands for simple and complex shapes. Systematic variation in the strength of self-excitation enables an understanding of the individual differences in working memory capacity. The model offers several testable predictions regarding the neural basis of visual working memory.

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

Memristor-based memory: The sneak paths problem and solutions

KAUST Repository

Zidan, Mohammed A.

2012-10-29

In this paper, we investigate the read operation of memristor-based memories. We analyze the sneak paths problem and provide a noise margin metric to compare the various solutions proposed in the literature. We also analyze the power consumption associated with these solutions. Moreover, we study the effect of the aspect ratio of the memory array on the sneak paths. Finally, we introduce a new technique for solving the sneak paths problem by gating the memory cell using a three-terminal memistor device.

Memristor-based memory: The sneak paths problem and solutions

KAUST Repository

Zidan, Mohammed A.; Fahmy, Hossam A.H.; Hussain, Muhammad Mustafa; Salama, Khaled N.

2012-01-01

In this paper, we investigate the read operation of memristor-based memories. We analyze the sneak paths problem and provide a noise margin metric to compare the various solutions proposed in the literature. We also analyze the power consumption associated with these solutions. Moreover, we study the effect of the aspect ratio of the memory array on the sneak paths. Finally, we introduce a new technique for solving the sneak paths problem by gating the memory cell using a three-terminal memistor device.

Copula Regression Analysis of Simultaneously Recorded Frontal Eye Field and Inferotemporal Spiking Activity during Object-Based Working Memory

Science.gov (United States)

Hu, Meng; Clark, Kelsey L.; Gong, Xiajing; Noudoost, Behrad; Li, Mingyao; Moore, Tirin

2015-01-01

Inferotemporal (IT) neurons are known to exhibit persistent, stimulus-selective activity during the delay period of object-based working memory tasks. Frontal eye field (FEF) neurons show robust, spatially selective delay period activity during memory-guided saccade tasks. We present a copula regression paradigm to examine neural interaction of these two types of signals between areas IT and FEF of the monkey during a working memory task. This paradigm is based on copula models that can account for both marginal distribution over spiking activity of individual neurons within each area and joint distribution over ensemble activity of neurons between areas. Considering the popular GLMs as marginal models, we developed a general and flexible likelihood framework that uses the copula to integrate separate GLMs into a joint regression analysis. Such joint analysis essentially leads to a multivariate analog of the marginal GLM theory and hence efficient model estimation. In addition, we show that Granger causality between spike trains can be readily assessed via the likelihood ratio statistic. The performance of this method is validated by extensive simulations, and compared favorably to the widely used GLMs. When applied to spiking activity of simultaneously recorded FEF and IT neurons during working memory task, we observed significant Granger causality influence from FEF to IT, but not in the opposite direction, suggesting the role of the FEF in the selection and retention of visual information during working memory. The copula model has the potential to provide unique neurophysiological insights about network properties of the brain. PMID:26063909

Fe-Mn-Si based shape memory alloys

International Nuclear Information System (INIS)

Hsu, T.Y.

2000-01-01

Characteristics of martensitic transformation fcc(γ)→hcp(ε) in Fe-Mn-Si based alloys are briefly reviewed. By analyzing the influences of constituents and treatments on shape memory effect (SME) in Fe-Mn-Si, the main factors controlling SME are summarized as austenite strengthening, stacking fault energy (probability) and antiferromagnetic temperature. Contribution of thermomechanical training to SME is introduced. The Fe-Mn-Si-RE (rare earth elements) and Fe-Mn-Si-Cr-N alloys are recommended as two novel shape memory alloys with superior SME. (orig.)

Domain-general involvement of the posterior frontolateral cortex in time-based resource-sharing in working memory: An fMRI study

NARCIS (Netherlands)

Vergauwe, E.; Hartstra, E.; Barrouillet, P.; Brass, M.

2015-01-01

Working memory is often defined in cognitive psychology as a system devoted to the simultaneous processing and maintenance of information. In line with the time-based resource-sharing model of working memory (TBRS; Barrouillet and Camos, 2015; Barrouillet et al., 2004), there is accumulating

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

Qualitative Characteristics of Memories for Real, Imagined, and Media-Based Events

Science.gov (United States)

Gordon, Ruthanna; Gerrig, Richard J.; Franklin, Nancy

2009-01-01

People's memories must be able to represent experiences with multiple types of origins--including the real world and our own imaginations, but also printed texts (prose-based media), movies, and television (screen-based media). This study was intended to identify cues that distinguish prose- and screen-based media memories from each other, as well…

Sparse Distributed Memory: understanding the speed and robustness of expert memory

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Marcelo Salhab Brogliato

2014-04-01

Full Text Available How can experts, sometimes in exacting detail, almost immediately and very precisely recall memory items from a vast repertoire? The problem in which we will be interested concerns models of theoretical neuroscience that could explain the speed and robustness of an expert's recollection. The approach is based on Sparse Distributed Memory, which has been shown to be plausible, both in a neuroscientific and in a psychological manner, in a number of ways. A crucial characteristic concerns the limits of human recollection, the `tip-of-tongue' memory event--which is found at a non-linearity in the model. We expand the theoretical framework, deriving an optimization formula to solve to this non-linearity. Numerical results demonstrate how the higher frequency of rehearsal, through work or study, immediately increases the robustness and speed associated with expert memory.

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.

Working memory differences in long-distance dependency resolution

Directory of Open Access Journals (Sweden)

Bruno eNicenboim

2015-03-01

Full Text Available There is a wealth of evidence showing that increasing the distance between an argument and its head leads to more processing effort, namely, locality effects; these are usually associated with constraints in working memory (DLT: Gibson, 2000; activation-based model: Lewis and Vasishth, 2005. In SOV languages, however, the opposite effect has been found: antilocality (see discussion in Levy et al., 2013. Antilocality effects can be explained by the expectation-based approach as proposed by Levy (2008 or by the activation-based model of sentence processing as proposed by Lewis and Vasishth (2005.We report an eye-tracking and a self-paced reading study with sentences in Spanish together with measures of individual differences to examine the distinction between expectation- and memory-based accounts, and within memory-based accounts the further distinction between DLT and the activation-based model. The experiments show that (i antilocality effects as predicted by the expectation account appear only for high-capacity readers; (ii increasing dependency length by interposing material that modifies the head of the dependency (the verb produces stronger facilitation than increasing dependency length with material that does not modify the head; this is in agreement with the activation-based model but not with the expectation account; and (iii a possible outcome of memory load on low-capacity readers is the increase in regressive saccades (locality effects as predicted by memory-based accounts or, surprisingly, a speedup in the self-paced reading task; the latter consistent with good-enough parsing (Ferreira et al., 2002. In sum, the study suggests that individual differences in working memory capacity play a role in dependency resolution, and that some of the aspects of dependency resolution can be best explained with the activation-based model together with a prediction component.

Working memory differences in long-distance dependency resolution

Science.gov (United States)

Nicenboim, Bruno; Vasishth, Shravan; Gattei, Carolina; Sigman, Mariano; Kliegl, Reinhold

2015-01-01

There is a wealth of evidence showing that increasing the distance between an argument and its head leads to more processing effort, namely, locality effects; these are usually associated with constraints in working memory (DLT: Gibson, 2000; activation-based model: Lewis and Vasishth, 2005). In SOV languages, however, the opposite effect has been found: antilocality (see discussion in Levy et al., 2013). Antilocality effects can be explained by the expectation-based approach as proposed by Levy (2008) or by the activation-based model of sentence processing as proposed by Lewis and Vasishth (2005). We report an eye-tracking and a self-paced reading study with sentences in Spanish together with measures of individual differences to examine the distinction between expectation- and memory-based accounts, and within memory-based accounts the further distinction between DLT and the activation-based model. The experiments show that (i) antilocality effects as predicted by the expectation account appear only for high-capacity readers; (ii) increasing dependency length by interposing material that modifies the head of the dependency (the verb) produces stronger facilitation than increasing dependency length with material that does not modify the head; this is in agreement with the activation-based model but not with the expectation account; and (iii) a possible outcome of memory load on low-capacity readers is the increase in regressive saccades (locality effects as predicted by memory-based accounts) or, surprisingly, a speedup in the self-paced reading task; the latter consistent with good-enough parsing (Ferreira et al., 2002). In sum, the study suggests that individual differences in working memory capacity play a role in dependency resolution, and that some of the aspects of dependency resolution can be best explained with the activation-based model together with a prediction component. PMID:25852623

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.

Scientific developments of liquid crystal-based optical memory: a review

Science.gov (United States)

Prakash, Jai; Chandran, Achu; Biradar, Ashok M.

2017-01-01

The memory behavior in liquid crystals (LCs), although rarely observed, has made very significant headway over the past three decades since their discovery in nematic type LCs. It has gone from a mere scientific curiosity to application in variety of commodities. The memory element formed by numerous LCs have been protected by patents, and some commercialized, and used as compensation to non-volatile memory devices, and as memory in personal computers and digital cameras. They also have the low cost, large area, high speed, and high density memory needed for advanced computers and digital electronics. Short and long duration memory behavior for industrial applications have been obtained from several LC materials, and an LC memory with interesting features and applications has been demonstrated using numerous LCs. However, considerable challenges still exist in searching for highly efficient, stable, and long-lifespan materials and methods so that the development of useful memory devices is possible. This review focuses on the scientific and technological approach of fascinating applications of LC-based memory. We address the introduction, development status, novel design and engineering principles, and parameters of LC memory. We also address how the amalgamation of LCs could bring significant change/improvement in memory effects in the emerging field of nanotechnology, and the application of LC memory as the active component for futuristic and interesting memory devices.

Moving target detection based on visual memory model and clustering%基于视觉记忆模型聚类的运动目标检测

Institute of Scientific and Technical Information of China (English)

陈容; 彭力

2015-01-01

In some gradient and repetitive motion modeling scenes, traditional Gaussian mixture background modeling has a good effect. But the algorithm needs a large amount of computation and storage space, and it can neither fit for complex background or background with sudden changes. To solve these problems, a new clustering background modeling based on human memory model is proposed. Combined with human memory model, the algorithm sets up a cluster model for each pixel, and each cluster can be adaptively created, updated and deleted according to background changes. The algorithm makes accurate judgments according to human ultra-short-term memory, short-term memory and long-term memory, and the moving target detection results can meet the judgment of the human sensory organs.%传统的混合高斯背景建模可对存在渐变及重复性运动的场景进行建模，但其运算过程需要足够的计算量和存储空间，不适应在复杂背景下的背景建模，也不能解决场景中存在的突变。针对这些问题，提出了一种基于记忆模型的聚类算法，算法为每个像素点设置一个聚类模型，每个聚类可根据背景的变化结合人类记忆模型自适应的创建、更新和删除。该算法通过人类瞬时记忆、短时记忆和长时记忆做出准确判断，运动目标检测结果更能符合人类感觉器官的判断。

The Effects of Emotion on Episodic Memory for TV Commercials.

Science.gov (United States)

Thorson, Esther; Friestad, Marian

Based on the associational nature of memory, the distinction between episodic and semantic memory, and the notion of memory strength, a model was developed of the role of emotion in the memory of television commercials. The model generated the following hypotheses: (1) emotional commercials will more likely be recalled than nonemotional…

An analytical model for shape memory alloy fiber-reinforced composite thin-walled beam undergoing large deflection

Directory of Open Access Journals (Sweden)

Yongsheng Ren

2015-03-01

Full Text Available The structural model of the thin-walled laminated beams with integral shape memory alloy active fibers and accounting for geometrically nonlinear is presented in this article. The structural modeling is split into two parts: a two-dimensional analysis over the cross section and a geometrically nonlinear analysis of a beam along the beam span. The variational asymptotic method is used to formulate the force–deformation relationship equations taking into account the presence of active shape memory alloy fibers distributed along the cross section of the beam. The geometrically nonlinear governing equations are derived using variational principle and based on the von Kármán-type nonlinear strain–displacement relations. The equations are then solved using Galerkin’s method and an incremental Newton–Raphson method. The validation for the proposed model has been carried out by comparison of the present results with those available in the literature. The results show that significant extension, bending, and twisting coupled nonlinear deflections occur during the phase transformation due to shape memory alloy actuation. The effects of the volume fraction of the shape memory alloy fiber and ply angle are also addressed.

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…

Writing to and reading from a nano-scale crossbar memory based on memristors

International Nuclear Information System (INIS)

Vontobel, Pascal O; Robinett, Warren; Kuekes, Philip J; Stewart, Duncan R; Straznicky, Joseph; Stanley Williams, R

2009-01-01

We present a design study for a nano-scale crossbar memory system that uses memristors with symmetrical but highly nonlinear current-voltage characteristics as memory elements. The memory is non-volatile since the memristors retain their state when un-powered. In order to address the nano-wires that make up this nano-scale crossbar, we use two coded demultiplexers implemented using mixed-scale crossbars (in which CMOS-wires cross nano-wires and in which the crosspoint junctions have one-time configurable memristors). This memory system does not utilize the kind of devices (diodes or transistors) that are normally used to isolate the memory cell being written to and read from in conventional memories. Instead, special techniques are introduced to perform the writing and the reading operation reliably by taking advantage of the nonlinearity of the type of memristors used. After discussing both writing and reading strategies for our memory system in general, we focus on a 64 x 64 memory array and present simulation results that show the feasibility of these writing and reading procedures. Besides simulating the case where all device parameters assume exactly their nominal value, we also simulate the much more realistic case where the device parameters stray around their nominal value: we observe a degradation in margins, but writing and reading is still feasible. These simulation results are based on a device model for memristors derived from measurements of fabricated devices in nano-scale crossbars using Pt and Ti nano-wires and using oxygen-depleted TiO 2 as the switching material.

Neural bases of prospective memory: a meta-analysis and the "Attention to Delayed Intention" (AtoDI) model.

Science.gov (United States)

Cona, Giorgia; Scarpazza, Cristina; Sartori, Giuseppe; Moscovitch, Morris; Bisiacchi, Patrizia Silvia

2015-05-01

Remembering to realize delayed intentions is a multi-phase process, labelled as prospective memory (PM), and involves a plurality of neural networks. The present study utilized the activation likelihood estimation method of meta-analysis to provide a complete overview of the brain regions that are consistently activated in each PM phase. We formulated the 'Attention to Delayed Intention' (AtoDI) model to explain the neural dissociation found between intention maintenance and retrieval phases. The dorsal frontoparietal network is involved mainly in the maintenance phase and seems to mediate the strategic monitoring processes, such as the allocation of top-down attention both towards external stimuli, to monitor for the occurrence of the PM cues, and to internal memory contents, to maintain the intention active in memory. The ventral frontoparietal network is recruited in the retrieval phase and might subserve the bottom-up attention captured externally by the PM cues and, internally, by the intention stored in memory. Together with other brain regions (i.e., insula and posterior cingulate cortex), the ventral frontoparietal network would support the spontaneous retrieval processes. The functional contribution of the anterior prefrontal cortex is discussed extensively for each PM phase. Copyright © 2015 Elsevier Ltd. All rights reserved.

Building a columnar database on shared main memory-based storage

OpenAIRE

Tinnefeld, Christian

2014-01-01

In the field of disk-based parallel database management systems exists a great variety of solutions based on a shared-storage or a shared-nothing architecture. In contrast, main memory-based parallel database management systems are dominated solely by the shared-nothing approach as it preserves the in-memory performance advantage by processing data locally on each server. We argue that this unilateral development is going to cease due to the combination of the following three trends: a) Nowad...

Protein-Based Three-Dimensional Memories and Associative Processors

Science.gov (United States)

Birge, Robert

2008-03-01

The field of bioelectronics has benefited from the fact that nature has often solved problems of a similar nature to those which must be solved to create molecular electronic or photonic devices that operate with efficiency and reliability. Retinal proteins show great promise in bioelectronic devices because they operate with high efficiency (˜0.65%), high cyclicity (>10^7), operate over an extended wavelength range (360 -- 630 nm) and can convert light into changes in voltage, pH, absorption or refractive index. This talk will focus on a retinal protein called bacteriorhodopsin, the proton pump of the organism Halobacterium salinarum. Two memories based on this protein will be described. The first is an optical three-dimensional memory. This memory stores information using volume elements (voxels), and provides as much as a thousand-fold improvement in effective capacity over current technology. A unique branching reaction of a variant of bacteriorhodopsin is used to turn each protein into an optically addressed latched AND gate. Although three working prototypes have been developed, a number of cost/performance and architectural issues must be resolved prior to commercialization. The major issue is that the native protein provides a very inefficient branching reaction. Genetic engineering has improved performance by nearly 500-fold, but a further order of magnitude improvement is needed. Protein-based holographic associative memories will also be discussed. The human brain stores and retrieves information via association, and human intelligence is intimately connected to the nature and enormous capacity of this associative search and retrieval process. To a first order approximation, creativity can be viewed as the association of two seemingly disparate concepts to form a totally new construct. Thus, artificial intelligence requires large scale associative memories. Current computer hardware does not provide an optimal environment for creating artificial

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

Science.gov (United States)

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

2015-01-01

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

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

Science.gov (United States)

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

2013-03-01

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

Normal aging affects movement execution but not visual motion working memory and decision-making delay during cue-dependent memory-based smooth-pursuit.

Science.gov (United States)

Fukushima, Kikuro; Barnes, Graham R; Ito, Norie; Olley, Peter M; Warabi, Tateo

2014-07-01

Aging affects virtually all functions including sensory/motor and cognitive activities. While retinal image motion is the primary input for smooth-pursuit, its efficiency/accuracy depends on cognitive processes. Elderly subjects exhibit gain decrease during initial and steady-state pursuit, but reports on latencies are conflicting. Using a cue-dependent memory-based smooth-pursuit task, we identified important extra-retinal mechanisms for initial pursuit in young adults including cue information priming and extra-retinal drive components (Ito et al. in Exp Brain Res 229:23-35, 2013). We examined aging effects on parameters for smooth-pursuit using the same tasks. Elderly subjects were tested during three task conditions as previously described: memory-based pursuit, simple ramp-pursuit just to follow motion of a single spot, and popping-out of the correct spot during memory-based pursuit to enhance retinal image motion. Simple ramp-pursuit was used as a task that did not require visual motion working memory. To clarify aging effects, we then compared the results with the previous young subject data. During memory-based pursuit, elderly subjects exhibited normal working memory of cue information. Most movement-parameters including pursuit latencies differed significantly between memory-based pursuit and simple ramp-pursuit and also between young and elderly subjects. Popping-out of the correct spot motion was ineffective for enhancing initial pursuit in elderly subjects. However, the latency difference between memory-based pursuit and simple ramp-pursuit in individual subjects, which includes decision-making delay in the memory task, was similar between the two groups. Our results suggest that smooth-pursuit latencies depend on task conditions and that, although the extra-retinal mechanisms were functional for initial pursuit in elderly subjects, they were less effective.

Dorsoventral and Proximodistal Hippocampal Processing Account for the Influences of Sleep and Context on Memory (Re)consolidation: A Connectionist Model.

Science.gov (United States)

Lines, Justin; Nation, Kelsey; Fellous, Jean-Marc

2017-01-01

The context in which learning occurs is sufficient to reconsolidate stored memories and neuronal reactivation may be crucial to memory consolidation during sleep. The mechanisms of context-dependent and sleep-dependent memory (re)consolidation are unknown but involve the hippocampus. We simulated memory (re)consolidation using a connectionist model of the hippocampus that explicitly accounted for its dorsoventral organization and for CA1 proximodistal processing. Replicating human and rodent (re)consolidation studies yielded the following results. (1) Semantic overlap between memory items and extraneous learning was necessary to explain experimental data and depended crucially on the recurrent networks of dorsal but not ventral CA3. (2) Stimulus-free, sleep-induced internal reactivations of memory patterns produced heterogeneous recruitment of memory items and protected memories from subsequent interference. These simulations further suggested that the decrease in memory resilience when subjects were not allowed to sleep following learning was primarily due to extraneous learning. (3) Partial exposure to the learning context during simulated sleep (i.e., targeted memory reactivation) uniformly increased memory item reactivation and enhanced subsequent recall. Altogether, these results show that the dorsoventral and proximodistal organization of the hippocampus may be important components of the neural mechanisms for context-based and sleep-based memory (re)consolidations.

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.

A ‘frozen volume’ transition model and working mechanism for the shape memory effect in amorphous polymers

Science.gov (United States)

Lu, Haibao; Wang, Xiaodong; Yao, Yongtao; Qing Fu, Yong

2018-06-01

Phenomenological models based on frozen volume parameters could well predict shape recovery behavior of shape memory polymers (SMPs), but the physical meaning of using the frozen volume parameters to describe thermomechanical properties has not been well-established. In this study, the fundamental working mechanisms of the shape memory effect (SME) in amorphous SMPs, whose temperature-dependent viscoelastic behavior follows the Eyring equation, have been established with the considerations of both internal stress and its resulted frozen volume. The stress-strain constitutive relation was initially modeled to quantitatively describe effects of internal stresses at the macromolecular scale based on the transient network theory. A phenomenological ‘frozen volume’ model was then established to characterize the macromolecule structure and SME of amorphous SMPs based on a two-site stress-relaxation model. Effects of the internal stress, frozen volume and strain rate on shape memory behavior and thermomechanical properties of the SMP were investigated. Finally, the simulation results were compared with the experimental results reported in the literature, and good agreements between the theoretical and experimental results were achieved. The novelty and key differences of our newly proposed model with respect to the previous reports are (1). The ‘frozen volume’ in our study is caused by the internal stress and governed by the two-site model theory, thus has a good physical meaning. (2). The model can be applied to characterize and predict both the thermal and thermomechanical behaviors of SMPs based on the constitutive relationship with internal stress parameters. It is expected to provide a power tool to investigate the thermomechanical behavior of the SMPs, of which both the macromolecular structure characteristics and SME could be predicted using this ‘frozen volume’ model.

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.

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.

The neurobiological bases of memory formation: from physiological conditions to psychopathology.

Science.gov (United States)

Bisaz, Reto; Travaglia, Alessio; Alberini, Cristina M

2014-01-01

The formation of long-term memories is a function necessary for an adaptive survival. In the last two decades, great progress has been made in the understanding of the biological bases of memory formation. The identification of mechanisms necessary for memory consolidation and reconsolidation, the processes by which the posttraining and postretrieval fragile memory traces become stronger and insensitive to disruption, has indicated new approaches for investigating and treating psychopathologies. In this review, we will discuss some key biological mechanisms found to be critical for memory consolidation and strengthening, the role/s and mechanisms of memory reconsolidation, and how the interference with consolidation and/or reconsolidation can modulate the retention and/or storage of memories that are linked to psychopathologies. © 2014 S. Karger AG, Basel.

Memory hierarchy using row-based compression

Science.gov (United States)

Loh, Gabriel H.; O'Connor, James M.

2016-10-25

A system includes a first memory and a device coupleable to the first memory. The device includes a second memory to cache data from the first memory. The second memory includes a plurality of rows, each row including a corresponding set of compressed data blocks of non-uniform sizes and a corresponding set of tag blocks. Each tag block represents a corresponding compressed data block of the row. The device further includes decompression logic to decompress data blocks accessed from the second memory. The device further includes compression logic to compress data blocks to be stored in the second memory.

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

Directory of Open Access Journals (Sweden)

Agus Wahidi

2017-03-01

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

Topographical memory for newly-learned maps is differentially affected by route-based versus landmark-based learning

DEFF Research Database (Denmark)

Beatty, Erin L.; Muller-Gass, Alexandra; Wojtarowicz, Dorothy

2018-01-01

on their ability to distinguish previously studied 'old' maps from completely unfamiliar 'new' maps under conditions of high and low working memory load in the functional MRI scanner. Viewing old versus new maps was associated with relatively greater activation in a distributed set of regions including bilateral...... inferior temporal gyrus - an important region for recognizing visual objects. Critically, whereas the performance of participants who had followed a route-based strategy dropped to chance level under high working memory load, participants who had followed a landmark-based strategy performed at above chance...... levels under both high and low working memory load - reflected by relatively greater activation in the left inferior parietal lobule (i.e. rostral part of the supramarginal gyrus known as area PFt). Our findings suggest that landmark-based learning may buffer against the effects of working memory load...

Testing the effectiveness of group-based memory rehabilitation in chronic stroke patients.

Science.gov (United States)

Miller, Laurie A; Radford, Kylie

2014-01-01

Memory complaints are common after stroke, yet there have been very few studies of the outcome of memory rehabilitation in these patients. The present study evaluated the effectiveness of a new manualised, group-based memory training programme. Forty outpatients with a single-stroke history and ongoing memory complaints were enrolled. The six-week course involved education and strategy training and was evaluated using a wait-list crossover design, with three assessments conducted 12 weeks apart. Outcome measures included: tests of anterograde memory (Rey Auditory Verbal Learning Test: RAVLT; Complex Figure Test) and prospective memory (Royal Prince Alfred Prospective Memory Test); the Comprehensive Assessment of Prospective Memory (CAPM) questionnaire and self-report of number of strategies used. Significant training-related gains were found on RAVLT learning and delayed recall and on CAPM informant report. Lower baseline scores predicted greater gains for several outcome measures. Patients with higher IQ or level of education showed more gains in number of strategies used. Shorter time since onset was related to gains in prospective memory, but no other stroke-related variables influenced outcome. Our study provides evidence that a relatively brief, group-based training intervention can improve memory functioning in chronic stroke patients and clarified some of the baseline factors that influence outcome.

Study of self-compliance behaviors and internal filament characteristics in intrinsic SiOx-based resistive switching memory

International Nuclear Information System (INIS)

Chang, Yao-Feng; Zhou, Fei; Chen, Ying-Chen; Lee, Jack C.; Fowler, Burt

2016-01-01

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

Neurocognitive architecture of working memory

Science.gov (United States)

Eriksson, Johan; Vogel, Edward K.; Lansner, Anders; Bergström, Fredrik; Nyberg, Lars

2015-01-01

The crucial role of working memory for temporary information processing and guidance of complex behavior has been recognized for many decades. There is emerging consensus that working memory maintenance results from the interactions among long-term memory representations and basic processes, including attention, that are instantiated as reentrant loops between frontal and posterior cortical areas, as well as subcortical structures. The nature of such interactions can account for capacity limitations, lifespan changes, and restricted transfer after working-memory training. Recent data and models indicate that working memory may also be based on synaptic plasticity, and that working memory can operate on non-consciously perceived information. PMID:26447571

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...

The Interplay of Hippocampus and Ventromedial Prefrontal Cortex in Memory-Based Decision Making

Directory of Open Access Journals (Sweden)

Regina A. Weilbächer

2016-12-01

Full Text Available Episodic memory and value-based decision making are two central and intensively studied research domains in cognitive neuroscience, but we are just beginning to understand how they interact to enable memory-based decisions. The two brain regions that have been associated with episodic memory and value-based decision making are the hippocampus and the ventromedial prefrontal cortex, respectively. In this review article, we first give an overview of these brain–behavior associations and then focus on the mechanisms of potential interactions between the hippocampus and ventromedial prefrontal cortex that have been proposed and tested in recent neuroimaging studies. Based on those possible interactions, we discuss several directions for future research on the neural and cognitive foundations of memory-based decision making.

Interfering with theories of sleep and memory: sleep, declarative memory, and associative interference.

Science.gov (United States)

Ellenbogen, Jeffrey M; Hulbert, Justin C; Stickgold, Robert; Dinges, David F; Thompson-Schill, Sharon L

2006-07-11

Mounting behavioral evidence in humans supports the claim that sleep leads to improvements in recently acquired, nondeclarative memories. Examples include motor-sequence learning; visual-discrimination learning; and perceptual learning of a synthetic language. In contrast, there are limited human data supporting a benefit of sleep for declarative (hippocampus-mediated) memory in humans (for review, see). This is particularly surprising given that animal models (e.g.,) and neuroimaging studies (e.g.,) predict that sleep facilitates hippocampus-based memory consolidation. We hypothesized that we could unmask the benefits of sleep by challenging the declarative memory system with competing information (interference). This is the first study to demonstrate that sleep protects declarative memories from subsequent associative interference, and it has important implications for understanding the neurobiology of memory consolidation.

Adaptive Digital Predistortion Schemes to Linearize RF Power Amplifiers with Memory Effects

Institute of Scientific and Technical Information of China (English)

ZHANG Peng; WU Si-liang; ZHANG Qin

2008-01-01

To compensate for nonlinear distortion introduced by RF power amplifiers (PAs) with memory effects, two correlated models, namely an extended memory polynomial (EMP) model and a memory lookup table (LUT) model, are proposed for predistorter design. Two adaptive digital predistortion (ADPD) schemes with indirect learning architecture are presented. One adopts the EMP model and the recursive least square (RLS) algorithm, and the other utilizes the memory LUT model and the least mean square (LMS) algorithm. Simulation results demonstrate that the EMP-based ADPD yields the best linearization performance in terms of suppressing spectral regrowth. It is also shown that the ADPD based on memory LUT makes optimum tradeoff between performance and computational complexity.