Dopamine D1 signaling organizes network dynamics underlying working memory.

PubMed

Roffman, Joshua L; Tanner, Alexandra S; Eryilmaz, Hamdi; Rodriguez-Thompson, Anais; Silverstein, Noah J; Ho, New Fei; Nitenson, Adam Z; Chonde, Daniel B; Greve, Douglas N; Abi-Dargham, Anissa; Buckner, Randy L; Manoach, Dara S; Rosen, Bruce R; Hooker, Jacob M; Catana, Ciprian

2016-06-01

Local prefrontal dopamine signaling supports working memory by tuning pyramidal neurons to task-relevant stimuli. Enabled by simultaneous positron emission tomography-magnetic resonance imaging (PET-MRI), we determined whether neuromodulatory effects of dopamine scale to the level of cortical networks and coordinate their interplay during working memory. Among network territories, mean cortical D1 receptor densities differed substantially but were strongly interrelated, suggesting cross-network regulation. Indeed, mean cortical D1 density predicted working memory-emergent decoupling of the frontoparietal and default networks, which respectively manage task-related and internal stimuli. In contrast, striatal D1 predicted opposing effects within these two networks but no between-network effects. These findings specifically link cortical dopamine signaling to network crosstalk that redirects cognitive resources to working memory, echoing neuromodulatory effects of D1 signaling on the level of cortical microcircuits.

CoNNeCT Baseband Processor Module

NASA Technical Reports Server (NTRS)

Yamamoto, Clifford K; Jedrey, Thomas C.; Gutrich, Daniel G.; Goodpasture, Richard L.

2011-01-01

A document describes the CoNNeCT Baseband Processor Module (BPM) based on an updated processor, memory technology, and field-programmable gate arrays (FPGAs). The BPM was developed from a requirement to provide sufficient computing power and memory storage to conduct experiments for a Software Defined Radio (SDR) to be implemented. The flight SDR uses the AT697 SPARC processor with on-chip data and instruction cache. The non-volatile memory has been increased from a 20-Mbit EEPROM (electrically erasable programmable read only memory) to a 4-Gbit Flash, managed by the RTAX2000 Housekeeper, allowing more programs and FPGA bit-files to be stored. The volatile memory has been increased from a 20-Mbit SRAM (static random access memory) to a 1.25-Gbit SDRAM (synchronous dynamic random access memory), providing additional memory space for more complex operating systems and programs to be executed on the SPARC. All memory is EDAC (error detection and correction) protected, while the SPARC processor implements fault protection via TMR (triple modular redundancy) architecture. Further capability over prior BPM designs includes the addition of a second FPGA to implement features beyond the resources of a single FPGA. Both FPGAs are implemented with Xilinx Virtex-II and are interconnected by a 96-bit bus to facilitate data exchange. Dedicated 1.25- Gbit SDRAMs are wired to each Xilinx FPGA to accommodate high rate data buffering for SDR applications as well as independent SpaceWire interfaces. The RTAX2000 manages scrub and configuration of each Xilinx.

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

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-29

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

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

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-01

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

A microprocessor card software server to support the Quebec health microprocessor card project.

PubMed

Durant, P; Bérubé, J; Lavoie, G; Gamache, A; Ardouin, P; Papillon, M J; Fortin, J P

1995-01-01

The Quebec Health Smart Card Project is advocating the use of a memory card software server[1] (SCAM) to implement a portable medical record (PMR) on a smart card. The PMR is viewed as an object that can be manipulated by SCAM's services. In fact, we can talk about a pseudo-object-oriented approach. This software architecture provides a flexible and evolutive way to manage and optimize the PMR. SCAM is a generic software server; it can manage smart cards as well as optical (laser) cards or other types of memory cards. But, in the specific case of the Quebec Health Card Project, SCAM is used to provide services between physicians' or pharmacists' software and IBM smart card technology. We propose to expose the concepts and techniques used to provide a generic environment to deal with smart cards (and more generally with memory cards), to obtain a dynamic an evolutive PMR, to raise the system global security level and the data integrity, to optimize significantly the management of the PMR, and to provide statistic information about the use of the PMR.

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

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-27

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

Temperature and leakage aware techniques to improve cache reliability

NASA Astrophysics Data System (ADS)

Akaaboune, Adil

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

Dopamine D1 signaling organizes network dynamics underlying working memory

PubMed Central

Roffman, Joshua L.; Tanner, Alexandra S.; Eryilmaz, Hamdi; Rodriguez-Thompson, Anais; Silverstein, Noah J.; Ho, New Fei; Nitenson, Adam Z.; Chonde, Daniel B.; Greve, Douglas N.; Abi-Dargham, Anissa; Buckner, Randy L.; Manoach, Dara S.; Rosen, Bruce R.; Hooker, Jacob M.; Catana, Ciprian

2016-01-01

Local prefrontal dopamine signaling supports working memory by tuning pyramidal neurons to task-relevant stimuli. Enabled by simultaneous positron emission tomography–magnetic resonance imaging (PET-MRI), we determined whether neuromodulatory effects of dopamine scale to the level of cortical networks and coordinate their interplay during working memory. Among network territories, mean cortical D1 receptor densities differed substantially but were strongly interrelated, suggesting cross-network regulation. Indeed, mean cortical D1 density predicted working memory–emergent decoupling of the frontoparietal and default networks, which respectively manage task-related and internal stimuli. In contrast, striatal D1 predicted opposing effects within these two networks but no between-network effects. These findings specifically link cortical dopamine signaling to network crosstalk that redirects cognitive resources to working memory, echoing neuromodulatory effects of D1 signaling on the level of cortical microcircuits. PMID:27386561

Dynamic intersectoral models with power-law memory

NASA Astrophysics Data System (ADS)

Tarasova, Valentina V.; Tarasov, Vasily E.

2018-01-01

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

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

PubMed

Yang, Shengxiang

2008-01-01

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

Generic, Type-Safe and Object Oriented Computer Algebra Software

NASA Astrophysics Data System (ADS)

Kredel, Heinz; Jolly, Raphael

Advances in computer science, in particular object oriented programming, and software engineering have had little practical impact on computer algebra systems in the last 30 years. The software design of existing systems is still dominated by ad-hoc memory management, weakly typed algorithm libraries and proprietary domain specific interactive expression interpreters. We discuss a modular approach to computer algebra software: usage of state-of-the-art memory management and run-time systems (e.g. JVM) usage of strongly typed, generic, object oriented programming languages (e.g. Java) and usage of general purpose, dynamic interactive expression interpreters (e.g. Python) To illustrate the workability of this approach, we have implemented and studied computer algebra systems in Java and Scala. In this paper we report on the current state of this work by presenting new examples.

Memory effects in nanoparticle dynamics and transport

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

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

PubMed

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

2017-01-11

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

Stable and Dynamic Coding for Working Memory in Primate Prefrontal Cortex

PubMed Central

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

2017-01-01

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

The Dynamics of Memory: Context-Dependent Updating

ERIC Educational Resources Information Center

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

2008-01-01

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

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

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-13

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

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

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-07

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

Memory-induced nonlinear dynamics of excitation in cardiac diseases.

PubMed

Landaw, Julian; Qu, Zhilin

2018-04-01

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

Memory-induced nonlinear dynamics of excitation in cardiac diseases

NASA Astrophysics Data System (ADS)

Landaw, Julian; Qu, Zhilin

2018-04-01

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

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

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-25

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

Altered Brain Dynamics in Patients With Type 1 Diabetes During Working Memory Processing.

PubMed

Embury, Christine M; Wiesman, Alex I; Proskovec, Amy L; Heinrichs-Graham, Elizabeth; McDermott, Timothy J; Lord, Grace H; Brau, Kaitlin L; Drincic, Andjela T; Desouza, Cyrus V; Wilson, Tony W

2018-06-01

It is now generally accepted that diabetes increases the risk for cognitive impairment, but the precise mechanisms are poorly understood. A critical problem in linking diabetes to cognitive impairment is that patients often have multiple comorbidities (e.g., obesity, hypertension) that have been independently linked to cognitive deficits. In the study reported here we focused on young adults with and without type 1 diabetes who were virtually free of such comorbidities. The two groups were matched on major health and demographic factors, and all participants completed a verbal working memory task during magnetoencephalographic brain imaging. We hypothesized that patients would have altered neural dynamics in verbal working memory processing and that these differences would directly relate to clinical disease measures. Accordingly, we found that patients had significantly stronger neural responses in the superior parietal cortices during memory encoding and significantly weaker activity in parietal-occipital regions during maintenance compared with control subjects. Moreover, disease duration and glycemic control were both significantly correlated with neural responses in various brain regions. In conclusion, young healthy adults with type 1 diabetes already have aberrant neural processing relative to their peers without diabetes, using compensatory responses to perform the task, and glucose management and duration may play a central role. © 2018 by the American Diabetes Association.

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

ERIC Educational Resources Information Center

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

2010-01-01

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

Endocannabinoid signaling and memory dynamics: A synaptic perspective.

PubMed

Drumond, Ana; Madeira, Natália; Fonseca, Rosalina

2017-02-01

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

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

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-28

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

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

PubMed

Sato, Naoyuki; Yamaguchi, Yoko

2007-03-26

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

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

NASA Astrophysics Data System (ADS)

Sasaki, Hironori

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

Elements of the cellular metabolic structure

PubMed Central

De la Fuente, Ildefonso M.

2015-01-01

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

Digital item for digital human memory--television commerce application: family tree albuming system

NASA Astrophysics Data System (ADS)

Song, Jaeil; Lee, Hyejoo; Hong, JinWoo

2004-01-01

Technical advance in creating, storing digital media in daily life enables computers to capture human life and remember it as people do. A critical point with digitizing human life is how to recall bits of experience that are associated by semantic information. This paper proposes a technique for structuring dynamic digital object based on MPEG-21 Digital Item (DI) in order to recall human"s memory and providing interactive TV service on family tree albuming system as one of its applications. DIs are a dynamically reconfigurable, uniquely identified, described by a descriptor language, logical unit for structuring relationship among multiple media resources. Digital Item Processing (DIP) provides the means to interact with DIs to remind context to user, with active properties where objects have executable properties. Each user can adapt DIs" active properties to tailor the behavior of DIs to match his/her own specific needs. DIs" technologies in Intellectual Property Management and Protection (IPMP) can be used for privacy protection. In the interaction between the social space and technological space, the internal dynamics of family life fits well sharing family albuming service via family television. Family albuming service can act as virtual communities builders for family members. As memory is shared between family members, multiple annotations (including active properties on contextual information) will be made with snowballing value.

Flash memory management system and method utilizing multiple block list windows

NASA Technical Reports Server (NTRS)

Chow, James (Inventor); Gender, Thomas K. (Inventor)

2005-01-01

The present invention provides a flash memory management system and method with increased performance. The flash memory management system provides the ability to efficiently manage and allocate flash memory use in a way that improves reliability and longevity, while maintaining good performance levels. The flash memory management system includes a free block mechanism, a disk maintenance mechanism, and a bad block detection mechanism. The free block mechanism provides efficient sorting of free blocks to facilitate selecting low use blocks for writing. The disk maintenance mechanism provides for the ability to efficiently clean flash memory blocks during processor idle times. The bad block detection mechanism provides the ability to better detect when a block of flash memory is likely to go bad. The flash status mechanism stores information in fast access memory that describes the content and status of the data in the flash disk. The new bank detection mechanism provides the ability to automatically detect when new banks of flash memory are added to the system. Together, these mechanisms provide a flash memory management system that can improve the operational efficiency of systems that utilize flash memory.

Gilgamesh: A Multithreaded Processor-In-Memory Architecture for Petaflops Computing

NASA Technical Reports Server (NTRS)

Sterling, T. L.; Zima, H. P.

2002-01-01

Processor-in-Memory (PIM) architectures avoid the von Neumann bottleneck in conventional machines by integrating high-density DRAM and CMOS logic on the same chip. Parallel systems based on this new technology are expected to provide higher scalability, adaptability, robustness, fault tolerance and lower power consumption than current MPPs or commodity clusters. In this paper we describe the design of Gilgamesh, a PIM-based massively parallel architecture, and elements of its execution model. Gilgamesh extends existing PIM capabilities by incorporating advanced mechanisms for virtualizing tasks and data and providing adaptive resource management for load balancing and latency tolerance. The Gilgamesh execution model is based on macroservers, a middleware layer which supports object-based runtime management of data and threads allowing explicit and dynamic control of locality and load balancing. The paper concludes with a discussion of related research activities and an outlook to future work.

Memory and betweenness preference in temporal networks induced from time series

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Statistical Computations Underlying the Dynamics of Memory Updating

PubMed Central

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

2014-01-01

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

Scaling properties in time-varying networks with memory

NASA Astrophysics Data System (ADS)

Kim, Hyewon; Ha, Meesoon; Jeong, Hawoong

2015-12-01

The formation of network structure is mainly influenced by an individual node's activity and its memory, where activity can usually be interpreted as the individual inherent property and memory can be represented by the interaction strength between nodes. In our study, we define the activity through the appearance pattern in the time-aggregated network representation, and quantify the memory through the contact pattern of empirical temporal networks. To address the role of activity and memory in epidemics on time-varying networks, we propose temporal-pattern coarsening of activity-driven growing networks with memory. In particular, we focus on the relation between time-scale coarsening and spreading dynamics in the context of dynamic scaling and finite-size scaling. Finally, we discuss the universality issue of spreading dynamics on time-varying networks for various memory-causality tests.

Robot Evolutionary Localization Based on Attentive Visual Short-Term Memory

PubMed Central

Vega, Julio; Perdices, Eduardo; Cañas, José M.

2013-01-01

Cameras are one of the most relevant sensors in autonomous robots. However, two of their challenges are to extract useful information from captured images, and to manage the small field of view of regular cameras. This paper proposes implementing a dynamic visual memory to store the information gathered from a moving camera on board a robot, followed by an attention system to choose where to look with this mobile camera, and a visual localization algorithm that incorporates this visual memory. The visual memory is a collection of relevant task-oriented objects and 3D segments, and its scope is wider than the current camera field of view. The attention module takes into account the need to reobserve objects in the visual memory and the need to explore new areas. The visual memory is useful also in localization tasks, as it provides more information about robot surroundings than the current instantaneous image. This visual system is intended as underlying technology for service robot applications in real people's homes. Several experiments have been carried out, both with simulated and real Pioneer and Nao robots, to validate the system and each of its components in office scenarios. PMID:23337333

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

PubMed Central

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

2013-01-01

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

Promoting and maintaining diversity in contemporary hardwood forests: Confronting contemporary drivers of change and the loss of ecological memory

Treesearch

Christopher R. Webster; Yvette L. Dickinson; Julia I. Burton; Lee E. Frelich; Michael A. Jenkins; Christel C. Kern; Patricia Raymond; Michael R. Saunders; Michael B. Walters; John L. Willis

2018-01-01

Declines in the diversity of herbaceous and woody plant species in the understory of eastern North American hardwood forests are increasingly common. Forest managers are tasked with maintaining and/or promoting species diversity and resilience; however, the success of these efforts depends on a robust understanding of past and future system dynamics and identification...

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

PubMed Central

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

2009-01-01

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

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

ERIC Educational Resources Information Center

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

2014-01-01

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

Oscillations in Spurious States of the Associative Memory Model with Synaptic Depression

NASA Astrophysics Data System (ADS)

Murata, Shin; Otsubo, Yosuke; Nagata, Kenji; Okada, Masato

2014-12-01

The associative memory model is a typical neural network model that can store discretely distributed fixed-point attractors as memory patterns. When the network stores the memory patterns extensively, however, the model has other attractors besides the memory patterns. These attractors are called spurious memories. Both spurious states and memory states are in equilibrium, so there is little difference between their dynamics. Recent physiological experiments have shown that the short-term dynamic synapse called synaptic depression decreases its efficacy of transmission to postsynaptic neurons according to the activities of presynaptic neurons. Previous studies revealed that synaptic depression destabilizes the memory states when the number of memory patterns is finite. However, it is very difficult to study the dynamical properties of the spurious states if the number of memory patterns is proportional to the number of neurons. We investigate the effect of synaptic depression on spurious states by Monte Carlo simulation. The results demonstrate that synaptic depression does not affect the memory states but mainly destabilizes the spurious states and induces periodic oscillations.

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

PubMed

Brown, Paul A; Messina, Michael

2016-03-03

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

Antiferromagnetic CuMnAs multi-level memory cell with microelectronic compatibility

NASA Astrophysics Data System (ADS)

Olejník, K.; Schuler, V.; Marti, X.; Novák, V.; Kašpar, Z.; Wadley, P.; Campion, R. P.; Edmonds, K. W.; Gallagher, B. L.; Garces, J.; Baumgartner, M.; Gambardella, P.; Jungwirth, T.

2017-05-01

Antiferromagnets offer a unique combination of properties including the radiation and magnetic field hardness, the absence of stray magnetic fields, and the spin-dynamics frequency scale in terahertz. Recent experiments have demonstrated that relativistic spin-orbit torques can provide the means for an efficient electric control of antiferromagnetic moments. Here we show that elementary-shape memory cells fabricated from a single-layer antiferromagnet CuMnAs deposited on a III-V or Si substrate have deterministic multi-level switching characteristics. They allow for counting and recording thousands of input pulses and responding to pulses of lengths downscaled to hundreds of picoseconds. To demonstrate the compatibility with common microelectronic circuitry, we implemented the antiferromagnetic bit cell in a standard printed circuit board managed and powered at ambient conditions by a computer via a USB interface. Our results open a path towards specialized embedded memory-logic applications and ultra-fast components based on antiferromagnets.

A dynamic case-based planning system for space station application

NASA Technical Reports Server (NTRS)

Oppacher, F.; Deugo, D.

1988-01-01

We are currently investigating the use of a case-based reasoning approach to develop a dynamic planning system. The dynamic planning system (DPS) is designed to perform resource management, i.e., to efficiently schedule tasks both with and without failed components. This approach deviates from related work on scheduling and on planning in AI in several aspects. In particular, an attempt is made to equip the planner with an ability to cope with a changing environment by dynamic replanning, to handle resource constraints and feedback, and to achieve some robustness and autonomy through plan learning by dynamic memory techniques. We briefly describe the proposed architecture of DPS and its four major components: the PLANNER, the plan EXECUTOR, the dynamic REPLANNER, and the plan EVALUATOR. The planner, which is implemented in Smalltalk, is being evaluated for use in connection with the Space Station Mobile Service System (MSS).

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

PubMed

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

2017-09-01

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

Robust sequential working memory recall in heterogeneous cognitive networks

PubMed Central

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

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

Optimal Foraging in Semantic Memory

ERIC Educational Resources Information Center

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

2012-01-01

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

The Response Dynamics of Recognition Memory: Sensitivity and Bias

ERIC Educational Resources Information Center

Koop, Gregory J.; Criss, Amy H.

2016-01-01

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

Spaceborne Processor Array

NASA Technical Reports Server (NTRS)

Chow, Edward T.; Schatzel, Donald V.; Whitaker, William D.; Sterling, Thomas

2008-01-01

A Spaceborne Processor Array in Multifunctional Structure (SPAMS) can lower the total mass of the electronic and structural overhead of spacecraft, resulting in reduced launch costs, while increasing the science return through dynamic onboard computing. SPAMS integrates the multifunctional structure (MFS) and the Gilgamesh Memory, Intelligence, and Network Device (MIND) multi-core in-memory computer architecture into a single-system super-architecture. This transforms every inch of a spacecraft into a sharable, interconnected, smart computing element to increase computing performance while simultaneously reducing mass. The MIND in-memory architecture provides a foundation for high-performance, low-power, and fault-tolerant computing. The MIND chip has an internal structure that includes memory, processing, and communication functionality. The Gilgamesh is a scalable system comprising multiple MIND chips interconnected to operate as a single, tightly coupled, parallel computer. The array of MIND components shares a global, virtual name space for program variables and tasks that are allocated at run time to the distributed physical memory and processing resources. Individual processor- memory nodes can be activated or powered down at run time to provide active power management and to configure around faults. A SPAMS system is comprised of a distributed Gilgamesh array built into MFS, interfaces into instrument and communication subsystems, a mass storage interface, and a radiation-hardened flight computer.

Managing Chemotherapy Side Effects: Memory Changes

MedlinePlus

... C ancer I nstitute Managing Chemotherapy Side Effects Memory Changes What is causing these changes? Your doctor ... thinking or remembering things Managing Chemotherapy Side Effects: Memory Changes Get help to remember things. Write down ...

Extended memory management under RTOS

NASA Technical Reports Server (NTRS)

Plummer, M.

1981-01-01

A technique for extended memory management in ROLM 1666 computers using FORTRAN is presented. A general software system is described for which the technique can be ideally applied. The memory manager interface with the system is described. The protocols by which the manager is invoked are presented, as well as the methods used by the manager.

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

PubMed

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

2018-04-20

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

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

PubMed

Dent, Kevin

2010-01-01

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

Socio-hydrological modelling of floods: investigating community resilience, adaptation capacity and risk

NASA Astrophysics Data System (ADS)

Ciullo, Alessio; Viglione, Alberto; Castellarin, Attilio

2016-04-01

Changes in flood risk occur because of changes in climate and hydrology, and in societal exposure and vulnerability. Research on change in flood risk has demonstrated that the mutual interactions and continuous feedbacks between floods and societies has to be taken into account in flood risk management. The present work builds on an existing conceptual model of an hypothetical city located in the proximity of a river, along whose floodplains the community evolves over time. The model reproduces the dynamic co-evolution of four variables: flooding, population density of the flooplain, amount of structural protection measures and memory of floods. These variables are then combined in a way to mimic the temporal change of community resilience, defined as the (inverse of the) amount of time for the community to recover from a shock, and adaptation capacity, defined as ratio between damages due to subsequent events. Also, temporal changing exposure, vulnerability and probability of flooding are also modelled, which results in a dynamically varying flood-risk. Examples are provided that show how factors such as collective memory and risk taking attitude influence the dynamics of community resilience, adaptation capacity and risk.

Dynamical class of a two-dimensional plasmonic Dirac system.

PubMed

Silva, Érica de Mello

2015-10-01

A current goal in plasmonic science and technology is to figure out how to manage the relaxational dynamics of surface plasmons in graphene since its damping constitutes a hinder for the realization of graphene-based plasmonic devices. In this sense we believe it might be of interest to enlarge the knowledge on the dynamical class of two-dimensional plasmonic Dirac systems. According to the recurrence relations method, different systems are said to be dynamically equivalent if they have identical relaxation functions at all times, and such commonality may lead to deep connections between seemingly unrelated physical systems. We employ the recurrence relations approach to obtain relaxation and memory functions of density fluctuations and show that a two-dimensional plasmonic Dirac system at long wavelength and zero temperature belongs to the same dynamical class of standard two-dimensional electron gas and classical harmonic oscillator chain with an impurity mass.

Integrating Cache Performance Modeling and Tuning Support in Parallelization Tools

NASA Technical Reports Server (NTRS)

Waheed, Abdul; Yan, Jerry; Saini, Subhash (Technical Monitor)

1998-01-01

With the resurgence of distributed shared memory (DSM) systems based on cache-coherent Non Uniform Memory Access (ccNUMA) architectures and increasing disparity between memory and processors speeds, data locality overheads are becoming the greatest bottlenecks in the way of realizing potential high performance of these systems. While parallelization tools and compilers facilitate the users in porting their sequential applications to a DSM system, a lot of time and effort is needed to tune the memory performance of these applications to achieve reasonable speedup. In this paper, we show that integrating cache performance modeling and tuning support within a parallelization environment can alleviate this problem. The Cache Performance Modeling and Prediction Tool (CPMP), employs trace-driven simulation techniques without the overhead of generating and managing detailed address traces. CPMP predicts the cache performance impact of source code level "what-if" modifications in a program to assist a user in the tuning process. CPMP is built on top of a customized version of the Computer Aided Parallelization Tools (CAPTools) environment. Finally, we demonstrate how CPMP can be applied to tune a real Computational Fluid Dynamics (CFD) application.

Network resiliency through memory health monitoring and proactive management

DOEpatents

Andrade Costa, Carlos H.; Cher, Chen-Yong; Park, Yoonho; Rosenburg, Bryan S.; Ryu, Kyung D.

2017-11-21

A method for managing a network queue memory includes receiving sensor information about the network queue memory, predicting a memory failure in the network queue memory based on the sensor information, and outputting a notification through a plurality of nodes forming a network and using the network queue memory, the notification configuring communications between the nodes.

Dynamic Search and Working Memory in Social Recall

ERIC Educational Resources Information Center

Hills, Thomas T.; Pachur, Thorsten

2012-01-01

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

The Dynamics of Access to Groups in Working Memory

ERIC Educational Resources Information Center

Farrell, Simon; Lelievre, Anna

2012-01-01

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

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

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-20

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

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

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

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

Jin, Shuangshuang; Chen, Yousu; Wu, Di

2015-12-09

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

Dynamic search and working memory in social recall.

PubMed

Hills, Thomas T; Pachur, Thorsten

2012-01-01

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

Faithful Solid State Optical Memory with Dynamically Decoupled Spin Wave Storage

NASA Astrophysics Data System (ADS)

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

2013-07-01

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

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

PubMed

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

2013-07-12

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

Memory Dynamics and Decision Making in Younger and Older Adults

ERIC Educational Resources Information Center

Lechuga, M. Teresa; Gomez-Ariza, Carlos J.; Iglesias-Parro, Sergio; Pelegrina, Santiago

2012-01-01

The main aim of this research was to study whether memory dynamics influence older people's choices to the same extent as younger's ones. To do so, we adapted the retrieval-practice paradigm to produce variations in memory accessibility of information on which decisions were made later. Based on previous results, we expected to observe…

Dynamic Forest: An Efficient Index Structure for NAND Flash Memory

NASA Astrophysics Data System (ADS)

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

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

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

ERIC Educational Resources Information Center

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

2008-01-01

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

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

ERIC Educational Resources Information Center

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

2012-01-01

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

Dynamic effects of memory in a cobweb model with competing technologies

NASA Astrophysics Data System (ADS)

Agliari, Anna; Naimzada, Ahmad; Pecora, Nicolò

2017-02-01

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

Memory dynamics under stress.

PubMed

Quaedflieg, Conny W E M; Schwabe, Lars

2018-03-01

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

Memory management in genome-wide association studies

PubMed Central

2009-01-01

Genome-wide association is a powerful tool for the identification of genes that underlie common diseases. Genome-wide association studies generate billions of genotypes and pose significant computational challenges for most users including limited computer memory. We applied a recently developed memory management tool to two analyses of North American Rheumatoid Arthritis Consortium studies and measured the performance in terms of central processing unit and memory usage. We conclude that our memory management approach is simple, efficient, and effective for genome-wide association studies. PMID:20018047

Prospective memory in schizophrenia: relationship to medication management skills, neurocognition, and symptoms in individuals with schizophrenia.

PubMed

Raskin, Sarah A; Maye, Jacqueline; Rogers, Alexandra; Correll, David; Zamroziewicz, Marta; Kurtz, Matthew

2014-05-01

Impaired adherence to medication regimens is a serious concern for individuals with schizophrenia linked to relapse and poorer outcomes. One possible reason for poor adherence to medication is poor ability to remember future intentions, labeled prospective memory skills. It has been demonstrated in several studies that individuals with schizophrenia have impairments in prospective memory that are linked to everyday life skills. However, there have been no studies, to our knowledge, examining the relationship of a clinical measure of prospective memory to medication management skills, a key element of successful adherence. In this Study 41 individuals with schizophrenia and 25 healthy adults were administered a standardized test battery that included measures of prospective memory, medication management skills, neurocognition, and symptoms. Individuals with schizophrenia demonstrated impairments in prospective memory (both time and event-based) relative to healthy controls. Performance on the test of prospective memory was correlated with the standardized measure of medication management in individuals with schizophrenia. Moreover, the test of prospective memory predicted skills in medication adherence even after measures of neurocognition were accounted for. This suggests that prospective memory may play a key role in medication management skills and thus should be a target of cognitive remediation programs.

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

PubMed

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

2014-11-06

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

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

PubMed

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

2018-05-01

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

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

PubMed

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

2013-01-01

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

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

PubMed

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

2018-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Evolving technologies drive the new roles of Biomedical Engineering.

PubMed

Frisch, P H; St Germain, J; Lui, W

2008-01-01

Rapidly changing technology coupled with the financial impact of organized health care, has required hospital Biomedical Engineering organizations to augment their traditional operational and business models to increase their role in developing enhanced clinical applications utilizing new and evolving technologies. The deployment of these technology based applications has required Biomedical Engineering organizations to re-organize to optimize the manner in which they provide and manage services. Memorial Sloan-Kettering Cancer Center has implemented a strategy to explore evolving technologies integrating them into enhanced clinical applications while optimally utilizing the expertise of the traditional Biomedical Engineering component (Clinical Engineering) to provide expanded support in technology / equipment management, device repair, preventive maintenance and integration with legacy clinical systems. Specifically, Biomedical Engineering is an integral component of the Medical Physics Department which provides comprehensive and integrated support to the Center in advanced physical, technical and engineering technology. This organizational structure emphasizes the integration and collaboration between a spectrum of technical expertise for clinical support and equipment management roles. The high cost of clinical equipment purchases coupled with the increasing cost of service has driven equipment management responsibilities to include significant business and financial aspects to provide a cost effective service model. This case study details the dynamics of these expanded roles, future initiatives and benefits for Biomedical Engineering and Memorial Sloan Kettering Cancer Center.

Hard Real-Time: C++ Versus RTSJ

NASA Technical Reports Server (NTRS)

Dvorak, Daniel L.; Reinholtz, William K.

2004-01-01

In the domain of hard real-time systems, which language is better: C++ or the Real-Time Specification for Java (RTSJ)? Although ordinary Java provides a more productive programming environment than C++ due to its automatic memory management, that benefit does not apply to RTSJ when using NoHeapRealtimeThread and non-heap memory areas. As a result, RTSJ programmers must manage non-heap memory explicitly. While that's not a deterrent for veteran real-time programmers-where explicit memory management is common-the lack of certain language features in RTSJ (and Java) makes that manual memory management harder to accomplish safely than in C++. This paper illustrates the problem for practitioners in the context of moving data and managing memory in a real-time producer/consumer pattern. The relative ease of implementation and safety of the C++ programming model suggests that RTSJ has a struggle ahead in the domain of hard real-time applications, despite its other attractive features.

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

PubMed

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

2010-12-31

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

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

PubMed Central

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

2010-01-01

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

Memory Dynamics in Cross-linked Actin Networks

NASA Astrophysics Data System (ADS)

Scheff, Danielle; Majumdar, Sayantan; Gardel, Margaret

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

A self-defining hierarchical data system

NASA Technical Reports Server (NTRS)

Bailey, J.

1992-01-01

The Self-Defining Data System (SDS) is a system which allows the creation of self-defining hierarchical data structures in a form which allows the data to be moved between different machine architectures. Because the structures are self-defining they can be used for communication between independent modules in a distributed system. Unlike disk-based hierarchical data systems such as Starlink's HDS, SDS works entirely in memory and is very fast. Data structures are created and manipulated as internal dynamic structures in memory managed by SDS itself. A structure may then be exported into a caller supplied memory buffer in a defined external format. This structure can be written as a file or sent as a message to another machine. It remains static in structure until it is reimported into SDS. SDS is written in portable C and has been run on a number of different machine architectures. Structures are portable between machines with SDS looking after conversion of byte order, floating point format, and alignment. A Fortran callable version is also available for some machines.

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

PubMed

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

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

A class Hierarchical, object-oriented approach to virtual memory management

NASA Technical Reports Server (NTRS)

Russo, Vincent F.; Campbell, Roy H.; Johnston, Gary M.

1989-01-01

The Choices family of operating systems exploits class hierarchies and object-oriented programming to facilitate the construction of customized operating systems for shared memory and networked multiprocessors. The software is being used in the Tapestry laboratory to study the performance of algorithms, mechanisms, and policies for parallel systems. Described here are the architectural design and class hierarchy of the Choices virtual memory management system. The software and hardware mechanisms and policies of a virtual memory system implement a memory hierarchy that exploits the trade-off between response times and storage capacities. In Choices, the notion of a memory hierarchy is captured by abstract classes. Concrete subclasses of those abstractions implement a virtual address space, segmentation, paging, physical memory management, secondary storage, and remote (that is, networked) storage. Captured in the notion of a memory hierarchy are classes that represent memory objects. These classes provide a storage mechanism that contains encapsulated data and have methods to read or write the memory object. Each of these classes provides specializations to represent the memory hierarchy.

Cholinergic modulation of cognitive processing: insights drawn from computational models

PubMed Central

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

2012-01-01

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

Impact of emotionality on memory and meta-memory in schizophrenia using video sequences.

PubMed

Peters, Maarten J V; Hauschildt, Marit; Moritz, Steffen; Jelinek, Lena

2013-03-01

A vast amount of memory and meta-memory research in schizophrenia shows that these patients perform worse on memory accuracy and hold false information with strong conviction compared to healthy controls. So far, studies investigating these effects mainly used traditional static stimulus material like word lists or pictures. The question remains whether these memory and meta-memory effects are also present in (1) more near-life dynamic situations (i.e., using standardized videos) and (2) whether emotionality has an influence on memory and meta-memory deficits (i.e., response confidence) in schizophrenia compared to healthy controls. Twenty-seven schizophrenia patients and 24 healthy controls were administered a newly developed emotional video paradigm with five videos differing in emotionality (positive, two negative, neutral, and delusional related). After each video, a recognition task required participants to make old-new discriminations along with confidence ratings, investigating memory accuracy and meta-memory deficits in more dynamic settings. For all but the positively valenced video, patients recognized fewer correct items compared to healthy controls, and did not differ with regard to the number of false memories for related items. In line with prior findings, schizophrenia patients showed more high-confident responses for misses and false memories for related items but displayed underconfidence for hits when compared to healthy controls, independent of emotionality. Limited sample size and control group; combined valence and arousal indicator for emotionality; general psychopathology indicator. Emotionality differentially moderated memory accuracy, biases in schizophrenia patients compared to controls. Moreover, the meta-memory deficits identified in static paradigms also manifest in more dynamic settings near-life settings and seem to be independent of emotionality. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

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

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

2015-12-28

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

Prospective memory in schizophrenia: Relationship to medication management skills, neurocognition and symptoms in individuals with schizophrenia

PubMed Central

Raskin, S.; Maye, J.; Rogers, A.; Correll, D.; Zamroziewicz, M.; Kurtz, M.

2014-01-01

Objective Impaired adherence to medication regimens is a serious concern for individuals with schizophrenia linked to relapse and poorer outcomes. One possible reason for poor adherence to medication is poor ability to remember future intentions, labeled prospective memory skills. It has been demonstrated in several studies that individuals with schizophrenia have impairments in prospective memory that are linked to everyday life skills. However, there have been no studies, to our knowledge, examining the relationship of a clinical measure of prospective memory to medication management skills, a key element of successful adherence. Methods In this study 41 individuals with schizophrenia and 25 healthy adults were administered a standardized test battery that included measures of prospective memory, medication management skills, neurocognition and symptoms. Results Individuals with schizophrenia demonstrated impairments in prospective memory (both time and event-based) relative to healthy controls. Performance on the test of prospective memory was correlated with the standardized measure of medication management in individuals with schizophrenia. Moreover, the test of prospective memory predicted skills in medication adherence even after measures of neurocognition were accounted for. Conclusions This suggests that prospective memory may play a key role in medication management skills and thus should be a target of cognitive remediation programs. PMID:24188118

HIV dynamics linked to memory CD4+ T cell homeostasis.

PubMed

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

2017-01-01

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

Radiation-Hardened Solid-State Drive

NASA Technical Reports Server (NTRS)

Sheldon, Douglas J.

2010-01-01

A method is provided for a radiationhardened (rad-hard) solid-state drive for space mission memory applications by combining rad-hard and commercial off-the-shelf (COTS) non-volatile memories (NVMs) into a hybrid architecture. The architecture is controlled by a rad-hard ASIC (application specific integrated circuit) or a FPGA (field programmable gate array). Specific error handling and data management protocols are developed for use in a rad-hard environment. The rad-hard memories are smaller in overall memory density, but are used to control and manage radiation-induced errors in the main, and much larger density, non-rad-hard COTS memory devices. Small amounts of rad-hard memory are used as error buffers and temporary caches for radiation-induced errors in the large COTS memories. The rad-hard ASIC/FPGA implements a variety of error-handling protocols to manage these radiation-induced errors. The large COTS memory is triplicated for protection, and CRC-based counters are calculated for sub-areas in each COTS NVM array. These counters are stored in the rad-hard non-volatile memory. Through monitoring, rewriting, regeneration, triplication, and long-term storage, radiation-induced errors in the large NV memory are managed. The rad-hard ASIC/FPGA also interfaces with the external computer buses.

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

ERIC Educational Resources Information Center

Tobias, Robert

2009-01-01

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

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

PubMed Central

Michelmann, Sebastian; Bowman, Howard; Hanslmayr, Simon

2016-01-01

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

Dynamic modulation of innate immunity programming and memory.

PubMed

Yuan, Ruoxi; Li, Liwu

2016-01-01

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

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

PubMed

Takahama, Sachiko; Miyauchi, Satoru; Saiki, Jun

2010-02-15

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

Working-Memory Load and Temporal Myopia in Dynamic Decision Making

ERIC Educational Resources Information Center

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

2012-01-01

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

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

PubMed

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

2016-11-01

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

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

ERIC Educational Resources Information Center

Schutte, Anne R.; Spencer, John P.

2009-01-01

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

Synapsin Is Selectively Required for Anesthesia-Sensitive Memory

ERIC Educational Resources Information Center

Knapek, Stephan; Gerber, Bertram; Tanimoto, Hiromu

2010-01-01

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

Effect of water table dynamics on land surface hydrologic memory

NASA Astrophysics Data System (ADS)

Lo, Min-Hui; Famiglietti, James S.

2010-11-01

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

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

PubMed

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

2010-02-01

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

A microkernel design for component-based parallel numerical software systems.

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

Balay, S.

1999-01-13

What is the minimal software infrastructure and what type of conventions are needed to simplify development of sophisticated parallel numerical application codes using a variety of software components that are not necessarily available as source code? We propose an opaque object-based model where the objects are dynamically loadable from the file system or network. The microkernel required to manage such a system needs to include, at most: (1) a few basic services, namely--a mechanism for loading objects at run time via dynamic link libraries, and consistent schemes for error handling and memory management; and (2) selected methods that all objectsmore » share, to deal with object life (destruction, reference counting, relationships), and object observation (viewing, profiling, tracing). We are experimenting with these ideas in the context of extensible numerical software within the ALICE (Advanced Large-scale Integrated Computational Environment) project, where we are building the microkernel to manage the interoperability among various tools for large-scale scientific simulations. This paper presents some preliminary observations and conclusions from our work with microkernel design.« less

Computer memory management system

DOEpatents

Kirk, III, Whitson John

2002-01-01

A computer memory management system utilizing a memory structure system of "intelligent" pointers in which information related to the use status of the memory structure is designed into the pointer. Through this pointer system, The present invention provides essentially automatic memory management (often referred to as garbage collection) by allowing relationships between objects to have definite memory management behavior by use of coding protocol which describes when relationships should be maintained and when the relationships should be broken. In one aspect, the present invention system allows automatic breaking of strong links to facilitate object garbage collection, coupled with relationship adjectives which define deletion of associated objects. In another aspect, The present invention includes simple-to-use infinite undo/redo functionality in that it has the capability, through a simple function call, to undo all of the changes made to a data model since the previous `valid state` was noted.

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

ERIC Educational Resources Information Center

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

2009-01-01

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

Collective Langevin dynamics of conformational motions in proteins

NASA Astrophysics Data System (ADS)

Lange, Oliver F.; Grubmüller, Helmut

2006-06-01

Functionally relevant slow conformational motions of proteins are, at present, in most cases inaccessible to molecular dynamics (MD) simulations. The main reason is that the major part of the computational effort is spend for the accurate description of a huge number of high frequency motions of the protein and the surrounding solvent. The accumulated influence of these fluctuations is crucial for a correct treatment of the conformational dynamics; however, their details can be considered irrelevant for most purposes. To accurately describe long time protein dynamics we here propose a reduced dimension approach, collective Langevin dynamics (CLD), which evolves the dynamics of the system within a small subspace of relevant collective degrees of freedom. The dynamics within the low-dimensional conformational subspace is evolved via a generalized Langevin equation which accounts for memory effects via memory kernels also extracted from short explicit MD simulations. To determine the memory kernel with differing levels of regularization, we propose and evaluate two methods. As a first test, CLD is applied to describe the conformational motion of the peptide neurotensin. A drastic dimension reduction is achieved by considering one single curved conformational coordinate. CLD yielded accurate thermodynamical and dynamical behaviors. In particular, the rate of transitions between two conformational states agreed well with a rate obtained from a 150ns reference molecular dynamics simulation, despite the fact that the time scale of the transition (˜50ns) was much longer than the 1ns molecular dynamics simulation from which the memory kernel was extracted.

A New Role for Attentional Corticopetal Acetylcholine in Cortical Memory Dynamics

NASA Astrophysics Data System (ADS)

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

2011-09-01

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

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

NASA Astrophysics Data System (ADS)

Ma, Lina; Li, Xiantao; Liu, Chun

2016-11-01

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

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

PubMed Central

Stokes, Mark G.

2015-01-01

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

Cognitive Rehabilitation of Episodic Memory Disorders: From Theory to Practice

PubMed Central

Ptak, Radek; der Linden, Martial Van; Schnider, Armin

2010-01-01

Memory disorders are among the most frequent and most debilitating cognitive impairments following acquired brain damage. Cognitive remediation strategies attempt to restore lost memory capacity, provide compensatory techniques or teach the use of external memory aids. Memory rehabilitation has strongly been influenced by memory theory, and the interaction between both has stimulated the development of techniques such as spaced retrieval, vanishing cues or errorless learning. These techniques partly rely on implicit memory and therefore enable even patients with dense amnesia to acquire new information. However, knowledge acquired in this way is often strongly domain-specific and inflexible. In addition, individual patients with amnesia respond differently to distinct interventions. The factors underlying these differences have not yet been identified. Behavioral management of memory failures therefore often relies on a careful description of environmental factors and measurement of associated behavioral disorders such as unawareness of memory failures. The current evidence suggests that patients with less severe disorders benefit from self-management techniques and mnemonics whereas rehabilitation of severely amnesic patients should focus on behavior management, the transmission of domain-specific knowledge through implicit memory processes and the compensation for memory deficits with memory aids. PMID:20700383

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

NASA Astrophysics Data System (ADS)

Comlekoglu, T.; Weinberg, S. H.

2017-09-01

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

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

PubMed

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

2016-04-01

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

Method and apparatus for managing access to a memory

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

DeBenedictis, Erik

A method and apparatus for managing access to a memory of a computing system. A controller transforms a plurality of operations that represent a computing job into an operational memory layout that reduces a size of a selected portion of the memory that needs to be accessed to perform the computing job. The controller stores the operational memory layout in a plurality of memory cells within the selected portion of the memory. The controller controls a sequence by which a processor in the computing system accesses the memory to perform the computing job using the operational memory layout. The operationalmore » memory layout reduces an amount of energy consumed by the processor to perform the computing job.« less

Dynamic Organization of Hierarchical Memories

PubMed Central

Kurikawa, Tomoki; Kaneko, Kunihiko

2016-01-01

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

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

PubMed Central

Savin, Cristina; Dayan, Peter; Lengyel, Máté

2014-01-01

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

Groundwater-fed irrigation impacts spatially distributed temporal scaling behavior of the natural system: a spatio-temporal framework for understanding water management impacts

NASA Astrophysics Data System (ADS)

Condon, Laura E.; Maxwell, Reed M.

2014-03-01

Regional scale water management analysis increasingly relies on integrated modeling tools. Much recent work has focused on groundwater-surface water interactions and feedbacks. However, to our knowledge, no study has explicitly considered impacts of management operations on the temporal dynamics of the natural system. Here, we simulate twenty years of hourly moisture dependent, groundwater-fed irrigation using a three-dimensional, fully integrated, hydrologic model (ParFlow-CLM). Results highlight interconnections between irrigation demand, groundwater oscillation frequency and latent heat flux variability not previously demonstrated. Additionally, the three-dimensional model used allows for novel consideration of spatial patterns in temporal dynamics. Latent heat flux and water table depth both display spatial organization in temporal scaling, an important finding given the spatial homogeneity and weak scaling observed in atmospheric forcings. Pumping and irrigation amplify high frequency (sub-annual) variability while attenuating low frequency (inter-annual) variability. Irrigation also intensifies scaling within irrigated areas, essentially increasing temporal memory in both the surface and the subsurface. These findings demonstrate management impacts that extend beyond traditional water balance considerations to the fundamental behavior of the system itself. This is an important step to better understanding groundwater’s role as a buffer for natural variability and the impact that water management has on this capacity.

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

PubMed Central

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

2016-01-01

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

Fractional-order leaky integrate-and-fire model with long-term memory and power law dynamics.

PubMed

Teka, Wondimu W; Upadhyay, Ranjit Kumar; Mondal, Argha

2017-09-01

Pyramidal neurons produce different spiking patterns to process information, communicate with each other and transform information. These spiking patterns have complex and multiple time scale dynamics that have been described with the fractional-order leaky integrate-and-Fire (FLIF) model. Models with fractional (non-integer) order differentiation that generalize power law dynamics can be used to describe complex temporal voltage dynamics. The main characteristic of FLIF model is that it depends on all past values of the voltage that causes long-term memory. The model produces spikes with high interspike interval variability and displays several spiking properties such as upward spike-frequency adaptation and long spike latency in response to a constant stimulus. We show that the subthreshold voltage and the firing rate of the fractional-order model make transitions from exponential to power law dynamics when the fractional order α decreases from 1 to smaller values. The firing rate displays different types of spike timing adaptation caused by changes on initial values. We also show that the voltage-memory trace and fractional coefficient are the causes of these different types of spiking properties. The voltage-memory trace that represents the long-term memory has a feedback regulatory mechanism and affects spiking activity. The results suggest that fractional-order models might be appropriate for understanding multiple time scale neuronal dynamics. Overall, a neuron with fractional dynamics displays history dependent activities that might be very useful and powerful for effective information processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multimodal properties and dynamics of gradient echo quantum memory.

PubMed

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

2008-11-14

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

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

PubMed

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

2013-02-01

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

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

PubMed

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

2014-01-22

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

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Debates—Perspectives on socio-hydrology: Modeling flood risk as a public policy problem

NASA Astrophysics Data System (ADS)

Gober, Patricia; Wheater, Howard S.

2015-06-01

Socio-hydrology views human activities as endogenous to water system dynamics; it is the interaction between human and biophysical processes that threatens the viability of current water systems through positive feedbacks and unintended consequences. Di Baldassarre et al. implement socio-hydrology as a flood risk problem using the concept of social memory as a vehicle to link human perceptions to flood damage. Their mathematical model has heuristic value in comparing potential flood damages in green versus technological societies. It can also support communities in exploring the potential consequences of policy decisions and evaluating critical policy tradeoffs, for example, between flood protection and economic development. The concept of social memory does not, however, adequately capture the social processes whereby public perceptions are translated into policy action, including the pivotal role played by the media in intensifying or attenuating perceived flood risk, the success of policy entrepreneurs in keeping flood hazard on the public agenda during short windows of opportunity for policy action, and different societal approaches to managing flood risk that derive from cultural values and economic interests. We endorse the value of seeking to capture these dynamics in a simplified conceptual framework, but favor a broader conceptualization of socio-hydrology that includes a knowledge exchange component, including the way modeling insights and scientific results are communicated to floodplain managers. The social processes used to disseminate the products of socio-hydrological research are as important as the research results themselves in determining whether modeling is used for real-world decision making.

POLARIS: Agent-based modeling framework development and implementation for integrated travel demand and network and operations simulations

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

Auld, Joshua; Hope, Michael; Ley, Hubert

This paper discusses the development of an agent-based modelling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations. A description is given of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine, and memory allocator, as well as a number of ancillary utilities: visualization library, database IO library, and scenario manager. The overall framework emphasizes the design goals of: generality, code agility, and high performance. This framework allows the modeling of several aspects of transportation system that are typicallymore » done with separate stand-alone software applications, in a high-performance and extensible manner. The issue of integrating such models as dynamic traffic assignment and disaggregate demand models has been a long standing issue for transportation modelers. The integrated approach shows a possible way to resolve this difficulty. The simulation model built from the POLARIS framework is a single, shared-memory process for handling all aspects of the integrated urban simulation. The resulting gains in computational efficiency and performance allow planning models to be extended to include previously separate aspects of the urban system, enhancing the utility of such models from the planning perspective. Initial tests with case studies involving traffic management center impacts on various network events such as accidents, congestion and weather events, show the potential of the system.« less

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

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

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

PubMed Central

Fiebig, Florian; Lansner, Anders

2014-01-01

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

Event-induced theta responses as a window on the dynamics of memory.

PubMed

Bastiaansen, Marcel; Hagoort, Peter

2003-01-01

An important, but often ignored distinction in the analysis of EEG signals is that between evoked activity and induced activity. Whereas evoked activity reflects the summation of transient post-synaptic potentials triggered by an event, induced activity, which is mainly oscillatory in nature, is thought to reflect changes in parameters controlling dynamic interactions within and between brain structures. We hypothesize that induced activity may yield information about the dynamics of cell assembly formation, activation and subsequent uncoupling, which may play a prominent role in different types of memory operations. We then describe a number of analysis tools that can be used to study the reactivity of induced rhythmic activity, both in terms of amplitude changes and of phase variability. We briefly discuss how alpha, gamma and theta rhythms are thought to be generated, paying special attention to the hypothesis that the theta rhythm reflects dynamic interactions between the hippocampal system and the neocortex. This hypothesis would imply that studying the reactivity of scalp-recorded theta may provide a window on the contribution of the hippocampus to memory functions. We review studies investigating the reactivity of scalp-recorded theta in paradigms engaging episodic memory, spatial memory and working memory. In addition, we review studies that relate theta reactivity to processes at the interface of memory and language. Despite many unknowns, the experimental evidence largely supports the hypothesis that theta activity plays a functional role in cell assembly formation, a process which may constitute the neural basis of memory formation and retrieval. The available data provide only highly indirect support for the hypothesis that scalp-recorded theta yields information about hippocampal functioning. It is concluded that studying induced rhythmic activity holds promise as an additional important way to study brain function.

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

PubMed

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

2014-02-01

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

Field Test of Boiler Primary Loop Temperature Controller

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

Glanville, P.; Rowley, P.; Schroeder, D.

Beyond these initial system efficiency upgrades are an emerging class of Advanced Load Monitoring (ALM) aftermarket controllers that dynamically respond to the boiler load, with claims of 10% to 30% of fuel savings over a heating season. For hydronic boilers specifically, these devices perform load monitoring, with continuous measurement of supply and, in some cases, return water temperatures. Energy savings from these ALM controllers are derived from dynamic management of the boiler differential, where a microprocessor with memory of past boiler cycles prevents the boiler from firing for a period of time, to limit cycling losses and inefficient operation duringmore » perceived low load conditions. These differ from OTR controllers, which vary boiler setpoint temperatures with ambient conditions while maintaining a fixed differential.« less

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

PubMed

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

2016-04-13

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

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2017-08-22

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

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

PubMed

Mizuhara, Hiroaki; Sato, Naoyuki; Yamaguchi, Yoko

2015-05-01

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

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

PubMed

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

2018-01-01

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

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

PubMed Central

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

2018-01-01

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

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

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

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

2016-07-14

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

Changing disturbance regimes, ecological memory, and forest resilience

USGS Publications Warehouse

Johnstone, Jill F.; Allen, Craig D.; Franklin, Jerry F.; Frelich, Lee E.; Harvey, Brian J.; Higuera, Philip E.; Mack, Michelle C.; Meentemeyer, Ross K.; Metz, Margaret R.; Perry, George LW; Schoennagel, Tania; Turner, Monica G.

2016-01-01

Ecological memory is central to how ecosystems respond to disturbance and is maintained by two types of legacies – information and material. Species life-history traits represent an adaptive response to disturbance and are an information legacy; in contrast, the abiotic and biotic structures (such as seeds or nutrients) produced by single disturbance events are material legacies. Disturbance characteristics that support or maintain these legacies enhance ecological resilience and maintain a “safe operating space” for ecosystem recovery. However, legacies can be lost or diminished as disturbance regimes and environmental conditions change, generating a “resilience debt” that manifests only after the system is disturbed. Strong effects of ecological memory on post-disturbance dynamics imply that contingencies (effects that cannot be predicted with certainty) of individual disturbances, interactions among disturbances, and climate variability combine to affect ecosystem resilience. We illustrate these concepts and introduce a novel ecosystem resilience framework with examples of forest disturbances, primarily from North America. Identifying legacies that support resilience in a particular ecosystem can help scientists and resource managers anticipate when disturbances may trigger abrupt shifts in forest ecosystems, and when forests are likely to be resilient.

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

ERIC Educational Resources Information Center

Loft, Shayne; Remington, Roger W.

2010-01-01

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

Swarming UAS II

DTIC Science & Technology

2010-05-05

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

Common chromosomal fragile sites (CFS) may be involved in normal and traumatic cognitive stress memory consolidation and altered nervous system immunity.

PubMed

Gericke, G S

2010-05-01

Previous reports of specific patterns of increased fragility at common chromosomal fragile sites (CFS) found in association with certain neurobehavioural disorders did not attract attention at the time due to a shift towards molecular approaches to delineate neuropsychiatric disorder candidate genes. Links with miRNA, altered methylation and the origin of copy number variation indicate that CFS region characteristics may be part of chromatinomic mechanisms that are increasingly linked with neuroplasticity and memory. Current reports of large-scale double-stranded DNA breaks in differentiating neurons and evidence of ongoing DNA demethylation of specific gene promoters in adult hippocampus may shed new light on the dynamic epigenetic changes that are increasingly appreciated as contributing to long-term memory consolidation. The expression of immune recombination activating genes in key stress-induced memory regions suggests the adoption by the brain of this ancient pattern recognition and memory system to establish a structural basis for long-term memory through controlled chromosomal breakage at highly specific genomic regions. It is furthermore considered that these mechanisms for management of epigenetic information related to stress memory could be linked, in some instances, with the transfer of the somatically acquired information to the germline. Here, rearranged sequences can be subjected to further selection and possible eventual retrotranscription to become part of the more stable coding machinery if proven to be crucial for survival and reproduction. While linkage of cognitive memory with stress and fear circuitry and memory establishment through structural DNA modification is proposed as a normal process, inappropriate activation of immune-like genomic rearrangement processes through traumatic stress memory may have the potential to lead to undesirable activation of neuro-inflammatory processes. These theories could have a significant impact on the interpretation of risks posed by heredity and the environment and the search for neuropsychiatric candidate genes.

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

NASA Astrophysics Data System (ADS)

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

1996-02-01

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

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

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

Molecular dynamics simulations through GPU video games technologies

PubMed Central

Loukatou, Styliani; Papageorgiou, Louis; Fakourelis, Paraskevas; Filntisi, Arianna; Polychronidou, Eleftheria; Bassis, Ioannis; Megalooikonomou, Vasileios; Makałowski, Wojciech; Vlachakis, Dimitrios; Kossida, Sophia

2016-01-01

Bioinformatics is the scientific field that focuses on the application of computer technology to the management of biological information. Over the years, bioinformatics applications have been used to store, process and integrate biological and genetic information, using a wide range of methodologies. One of the most de novo techniques used to understand the physical movements of atoms and molecules is molecular dynamics (MD). MD is an in silico method to simulate the physical motions of atoms and molecules under certain conditions. This has become a state strategic technique and now plays a key role in many areas of exact sciences, such as chemistry, biology, physics and medicine. Due to their complexity, MD calculations could require enormous amounts of computer memory and time and therefore their execution has been a big problem. Despite the huge computational cost, molecular dynamics have been implemented using traditional computers with a central memory unit (CPU). A graphics processing unit (GPU) computing technology was first designed with the goal to improve video games, by rapidly creating and displaying images in a frame buffer such as screens. The hybrid GPU-CPU implementation, combined with parallel computing is a novel technology to perform a wide range of calculations. GPUs have been proposed and used to accelerate many scientific computations including MD simulations. Herein, we describe the new methodologies developed initially as video games and how they are now applied in MD simulations. PMID:27525251

Spintronic Nanodevices for Bioinspired Computing

PubMed Central

Grollier, Julie; Querlioz, Damien; Stiles, Mark D.

2016-01-01

Bioinspired hardware holds the promise of low-energy, intelligent, and highly adaptable computing systems. Applications span from automatic classification for big data management, through unmanned vehicle control, to control for biomedical prosthesis. However, one of the major challenges of fabricating bioinspired hardware is building ultra-high-density networks out of complex processing units interlinked by tunable connections. Nanometer-scale devices exploiting spin electronics (or spintronics) can be a key technology in this context. In particular, magnetic tunnel junctions (MTJs) are well suited for this purpose because of their multiple tunable functionalities. One such functionality, non-volatile memory, can provide massive embedded memory in unconventional circuits, thus escaping the von-Neumann bottleneck arising when memory and processors are located separately. Other features of spintronic devices that could be beneficial for bioinspired computing include tunable fast nonlinear dynamics, controlled stochasticity, and the ability of single devices to change functions in different operating conditions. Large networks of interacting spintronic nanodevices can have their interactions tuned to induce complex dynamics such as synchronization, chaos, soliton diffusion, phase transitions, criticality, and convergence to multiple metastable states. A number of groups have recently proposed bioinspired architectures that include one or several types of spintronic nanodevices. In this paper, we show how spintronics can be used for bioinspired computing. We review the different approaches that have been proposed, the recent advances in this direction, and the challenges toward fully integrated spintronics complementary metal–oxide–semiconductor (CMOS) bioinspired hardware. PMID:27881881

Deterministic ripple-spreading model for complex networks.

PubMed

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

2011-04-01

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

Molecular dynamics of conformational substates for a simplified protein model

NASA Astrophysics Data System (ADS)

Grubmüller, Helmut; Tavan, Paul

1994-09-01

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

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

PubMed Central

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

2013-01-01

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

Adiabatic quantum optimization for associative memory recall

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

Seddiqi, Hadayat; Humble, Travis S.

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

Adiabatic Quantum Optimization for Associative Memory Recall

NASA Astrophysics Data System (ADS)

Seddiqi, Hadayat; Humble, Travis

2014-12-01

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

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

PubMed

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

2013-10-01

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

Dynamics of memory-guided choice behavior in Drosophila

PubMed Central

ICHINOSE, Toshiharu; TANIMOTO, Hiromu

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

Adiabatic quantum optimization for associative memory recall

DOE PAGES

Seddiqi, Hadayat; Humble, Travis S.

2014-12-22

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

APOLLO II

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

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

1988-11-01

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

Theory of the dynamical thermal conductivity of metals

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

A processing architecture for associative short-term memory in electronic noses

NASA Astrophysics Data System (ADS)

Pioggia, G.; Ferro, M.; Di Francesco, F.; DeRossi, D.

2006-11-01

Electronic nose (e-nose) architectures usually consist of several modules that process various tasks such as control, data acquisition, data filtering, feature selection and pattern analysis. Heterogeneous techniques derived from chemometrics, neural networks, and fuzzy rules used to implement such tasks may lead to issues concerning module interconnection and cooperation. Moreover, a new learning phase is mandatory once new measurements have been added to the dataset, thus causing changes in the previously derived model. Consequently, if a loss in the previous learning occurs (catastrophic interference), real-time applications of e-noses are limited. To overcome these problems this paper presents an architecture for dynamic and efficient management of multi-transducer data processing techniques and for saving an associative short-term memory of the previously learned model. The architecture implements an artificial model of a hippocampus-based working memory, enabling the system to be ready for real-time applications. Starting from the base models available in the architecture core, dedicated models for neurons, maps and connections were tailored to an artificial olfactory system devoted to analysing olive oil. In order to verify the ability of the processing architecture in associative and short-term memory, a paired-associate learning test was applied. The avoidance of catastrophic interference was observed.

Dynamic frontotemporal systems process space and time in working memory

PubMed Central

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

2018-01-01

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

Quantifying memory in complex physiological time-series.

PubMed

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

2013-01-01

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

Quantifying Memory in Complex Physiological Time-Series

PubMed Central

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2008-03-01

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

Understanding human dynamics in microblog posting activities

NASA Astrophysics Data System (ADS)

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

2013-02-01

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

HTMT-class Latency Tolerant Parallel Architecture for Petaflops Scale Computation

NASA Technical Reports Server (NTRS)

Sterling, Thomas; Bergman, Larry

2000-01-01

Computational Aero Sciences and other numeric intensive computation disciplines demand computing throughputs substantially greater than the Teraflops scale systems only now becoming available. The related fields of fluids, structures, thermal, combustion, and dynamic controls are among the interdisciplinary areas that in combination with sufficient resolution and advanced adaptive techniques may force performance requirements towards Petaflops. This will be especially true for compute intensive models such as Navier-Stokes are or when such system models are only part of a larger design optimization computation involving many design points. Yet recent experience with conventional MPP configurations comprising commodity processing and memory components has shown that larger scale frequently results in higher programming difficulty and lower system efficiency. While important advances in system software and algorithms techniques have had some impact on efficiency and programmability for certain classes of problems, in general it is unlikely that software alone will resolve the challenges to higher scalability. As in the past, future generations of high-end computers may require a combination of hardware architecture and system software advances to enable efficient operation at a Petaflops level. The NASA led HTMT project has engaged the talents of a broad interdisciplinary team to develop a new strategy in high-end system architecture to deliver petaflops scale computing in the 2004/5 timeframe. The Hybrid-Technology, MultiThreaded parallel computer architecture incorporates several advanced technologies in combination with an innovative dynamic adaptive scheduling mechanism to provide unprecedented performance and efficiency within practical constraints of cost, complexity, and power consumption. The emerging superconductor Rapid Single Flux Quantum electronics can operate at 100 GHz (the record is 770 GHz) and one percent of the power required by convention semiconductor logic. Wave Division Multiplexing optical communications can approach a peak per fiber bandwidth of 1 Tbps and the new Data Vortex network topology employing this technology can connect tens of thousands of ports providing a bi-section bandwidth on the order of a Petabyte per second with latencies well below 100 nanoseconds, even under heavy loads. Processor-in-Memory (PIM) technology combines logic and memory on the same chip exposing the internal bandwidth of the memory row buffers at low latency. And holographic storage photorefractive storage technologies provide high-density memory with access a thousand times faster than conventional disk technologies. Together these technologies enable a new class of shared memory system architecture with a peak performance in the range of a Petaflops but size and power requirements comparable to today's largest Teraflops scale systems. To achieve high-sustained performance, HTMT combines an advanced multithreading processor architecture with a memory-driven coarse-grained latency management strategy called "percolation", yielding high efficiency while reducing the much of the parallel programming burden. This paper will present the basic system architecture characteristics made possible through this series of advanced technologies and then give a detailed description of the new percolation approach to runtime latency management.

Implementing a bubble memory hierarchy system

NASA Technical Reports Server (NTRS)

Segura, R.; Nichols, C. D.

1979-01-01

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

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

PubMed Central

Souza, Pamela; Arehart, Kathryn; Neher, Tobias

2015-01-01

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

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2016-01-15

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

Chemical Memory Reactions Induced Bursting Dynamics in Gene Expression

PubMed Central

Tian, Tianhai

2013-01-01

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

Chemical memory reactions induced bursting dynamics in gene expression.

PubMed

Tian, Tianhai

2013-01-01

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

Dynamic switching between semantic and episodic memory systems.

PubMed

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

2009-09-01

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

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

PubMed Central

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

2011-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

Dynamic reconfiguration of frontal brain networks during executive cognition in humans

PubMed Central

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

2015-01-01

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

Reservoir Computing Beyond Memory-Nonlinearity Trade-off.

PubMed

Inubushi, Masanobu; Yoshimura, Kazuyuki

2017-08-31

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

An Adaptive Memory Interface Controller for Improving Bandwidth Utilization of Hybrid and Reconfigurable Systems

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

Castellana, Vito G.; Tumeo, Antonino; Ferrandi, Fabrizio

Emerging applications such as data mining, bioinformatics, knowledge discovery, social network analysis are irregular. They use data structures based on pointers or linked lists, such as graphs, unbalanced trees or unstructures grids, which generates unpredictable memory accesses. These data structures usually are large, but difficult to partition. These applications mostly are memory bandwidth bounded and have high synchronization intensity. However, they also have large amounts of inherent dynamic parallelism, because they potentially perform a task for each one of the element they are exploring. Several efforts are looking at accelerating these applications on hybrid architectures, which integrate general purpose processorsmore » with reconfigurable devices. Some solutions, which demonstrated significant speedups, include custom-hand tuned accelerators or even full processor architectures on the reconfigurable logic. In this paper we present an approach for the automatic synthesis of accelerators from C, targeted at irregular applications. In contrast to typical High Level Synthesis paradigms, which construct a centralized Finite State Machine, our approach generates dynamically scheduled hardware components. While parallelism exploitation in typical HLS-generated accelerators is usually bound within a single execution flow, our solution allows concurrently running multiple execution flow, thus also exploiting the coarser grain task parallelism of irregular applications. Our approach supports multiple, multi-ported and distributed memories, and atomic memory operations. Its main objective is parallelizing as many memory operations as possible, independently from their execution time, to maximize the memory bandwidth utilization. This significantly differs from current HLS flows, which usually consider a single memory port and require precise scheduling of memory operations. A key innovation of our approach is the generation of a memory interface controller, which dynamically maps concurrent memory accesses to multiple ports. We present a case study on a typical irregular kernel, Graph Breadth First search (BFS), exploring different tradeoffs in terms of parallelism and number of memories.« less

Dynamic Reconfiguration of Security Policies in Wireless Sensor Networks

PubMed Central

Pinto, Mónica; Gámez, Nadia; Fuentes, Lidia; Amor, Mercedes; Horcas, José Miguel; Ayala, Inmaculada

2015-01-01

Providing security and privacy to wireless sensor nodes (WSNs) is very challenging, due to the heterogeneity of sensor nodes and their limited capabilities in terms of energy, processing power and memory. The applications for these systems run in a myriad of sensors with different low-level programming abstractions, limited capabilities and different routing protocols. This means that applications for WSNs need mechanisms for self-adaptation and for self-protection based on the dynamic adaptation of the algorithms used to provide security. Dynamic software product lines (DSPLs) allow managing both variability and dynamic software adaptation, so they can be considered a key technology in successfully developing self-protected WSN applications. In this paper, we propose a self-protection solution for WSNs based on the combination of the INTER-TRUST security framework (a solution for the dynamic negotiation and deployment of security policies) and the FamiWare middleware (a DSPL approach to automatically configure and reconfigure instances of a middleware for WSNs). We evaluate our approach using a case study from the intelligent transportation system domain. PMID:25746093

Chaotic patterns of autonomic activity during hypnotic recall.

PubMed

Bob, Petr; Siroka, Ivana; Susta, Marek

2009-01-01

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

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

PubMed Central

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

PubMed

Oikawa, Shuichi

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Forensic Analysis of Window’s(Registered) Virtual Memory Incorporating the System’s Page-File

DTIC Science & Technology

2008-12-01

Management and Budget, Paperwork Reduction Project (0704-0188) Washington DC 20503. 1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE December...data in a meaningful way. One reason for this is how memory is managed by the operating system. Data belonging to one process can be distributed...way. One reason for this is how memory is managed by the operating system. Data belonging to one process can be distributed arbitrarily across

Dementia

MedlinePlus

... living. Functions affected include memory, language skills, visual perception, problem solving, self-management, and the ability to ... living. Functions affected include memory, language skills, visual perception, problem solving, self-management, and the ability to ...

Scale factor management in the studies of affine models of shockproof garment elements

NASA Astrophysics Data System (ADS)

Denisov, Oleg; Pleshko, Mikhail; Ponomareva, Irina; Merenyashev, Vitaliy

2018-03-01

New samples of protective garment for performing construction work at height require numerous tests in conditions close to real conditions of extreme vital activity. The article presents some results of shockproof garment element studies and a description of a patented prototype. The tests were carried out on a model which geometric dimensions were convenient for manufacturing it in a limited batch. In addition, the used laboratory equipment (for example, a unique power pendulum), blanks made of a titanium-nickel alloy with a shape memory effect also imposed their limitations. The problem of the adequacy of the obtained experimental results transfer to mass-produced products was solved using tools of the classical similarity theory. Scale factor management influence in the affine modeling of the shockproof element, studied on the basis of the equiatomic titanium-nickel alloy with the shape memory effect, allowed us to assume, with a sufficient degree of reliability, the technical possibility of extrapolating the results of experimental studies to full-scale objects for the formation of the initial data of the mathematical model of shockproof garment dynamics elastoplastic deformation (while observing the similarity of the features of external loading).

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

ERIC Educational Resources Information Center

Reinhart, Paul N.; Souza, Pamela E.

2016-01-01

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

Dynamic overset grid communication on distributed memory parallel processors

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

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

ERIC Educational Resources Information Center

Swanson, H. Lee

2011-01-01

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

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

ERIC Educational Resources Information Center

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

2012-01-01

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

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

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

Jelinek, D.A.

1992-03-01

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

From Contextual Fear to a Dynamic View of Memory Systems

PubMed Central

Fanselow, Michael S

2009-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2008-11-01

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

Understanding original antigenic sin in influenza with a dynamical system.

PubMed

Pan, Keyao

2011-01-01

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

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

ERIC Educational Resources Information Center

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

2014-01-01

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

Memory Transformation Enhances Reinforcement Learning in Dynamic Environments.

PubMed

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

2016-11-30

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

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

PubMed Central

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

2008-01-01

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

Healthcare knowledge management through building and operationalising healthcare enterprise memory.

PubMed

Cheah, Y N; Abidi, S S

1999-01-01

In this paper we suggest that the healthcare enterprise needs to be more conscious of its vast knowledge resources vis-à-vis the exploitation of knowledge management techniques to efficiently manage its knowledge. The development of healthcare enterprise memory is suggested as a solution, together with a novel approach advocating the operationalisation of healthcare enterprise memories leading to the modelling of healthcare processes for strategic planning. As an example, we present a simulation of Service Delivery Time in a hospital's OPD.

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

DTIC Science & Technology

2014-09-24

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

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

PubMed Central

You, Hongzhi; Wang, Da-Hui

2017-01-01

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

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

PubMed

You, Hongzhi; Wang, Da-Hui

2017-01-01

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

Significantly enhanced memory effect in metallic glass by multistep training

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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

PubMed

Sheremata, Summer L; Shomstein, Sarah

2017-08-01

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

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

PubMed

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

2016-07-19

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

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

The structure and dynamics of interactive documents

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

Rocha, J.T.

1999-04-01

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

Ancient Approaches to the Age-old Problem of Water - How Archaeology Can Contribute to the Water Management Discourse of Socio-Hydrology

NASA Astrophysics Data System (ADS)

Egerer, Kyle

2017-04-01

As "the study of old things", archaeology is concerned with material remnants of the human past. At first glance, archaeology may not appear to align well with the purpose of socio-hydrology. Archaeologists attempt to understand past society by analyzing the materials and architecture that provide them with evidence of how people lived and organized their lives. One aspiration of doing so is to gain a contextualized perspective of how contemporary society became the way it is. Human interaction with water is recorded - among other forms of material evidence - in forms of infrastructure and architecture that people construct to control water's flow and preserve this life-supporting resource in times of human need. Building structures, such as water canals or reservoirs, represent society's endeavor to reconcile nature's incalculable influence on society while subtly revealing humanity's penetration into the natural hydrological cycle. Thus, a bi-directional - or reciprocal - relationship between society and nature exists. Socio-hydrological approaches to water management also attempt to understand this relationship. This contribution introduces an archaeological example of how to conceptualize the human-nature dynamic that can be used to understand the socio-political aspects that envelope water management. To evaluate how the Hittite civilization of Late Bronze Age Anatolia (ca. 1600-1200 B.C.) controlled water resources, the author adopts a socio-ecological approach informed by theories of socio-cultural memory and geomorphological analysis. Critical assessment of Hittite written and cultural evidence are compared with hydraulic infrastructure installations to determine how the Hittites used knowledge of their physical landscape to their advantage. In doing so, a framework for interpreting water management practices is formulated that indicates that solutions to water collection and storage were case-based and highly contextualized. Furthermore, legitimate congruencies between archaeology, socio-hydrology and methodologies of integrated water resource management (IWRM) are presented. This primary research ultimately attempts to ameliorate the theoretical and methodological incongruences of such a highly interdisciplinary field such as socio-hydrology. This approach will fuel a debate within the IWRM discipline about how an archaeological approach for analyzing water management strategies of the past can be used in modern water-management-related issues that encompass human-infrastructural, human-irrigational and human-agricultural systems. Keywords: Socio-hydrology, Bronze Age Archaeology of Anatolia, Hittites, Water Management, Integrated Water Resource Management, Socio-cultural Memory, Perception, Phenomenology, Vulnerability, Human-environment dynamics

Dynamics of social contagions with memory of nonredundant information

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

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

PubMed Central

Miller, Brian T.; D'Esposito, Mark

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-02-01

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

Reconsolidation of a Well-Learned Instrumental Memory

ERIC Educational Resources Information Center

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

2014-01-01

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

Aging, memory, and nonhierarchical energy landscape of spin jam

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

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

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

Jelinek, D.A.

1992-03-01

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

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

NASA Astrophysics Data System (ADS)

Jablonski, Piotr; Poe, Gina; Zochowski, Michal

2007-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2007-01-01

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

Individual Differences in Dynamic Functional Brain Connectivity across the Human Lifespan

PubMed Central

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

2016-01-01

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

The Fritz Roethlisberger Memorial Award Goes to "Using Leadered Groups in Organizational Behavior and Management Survey Courses"

ERIC Educational Resources Information Center

Amoroso, Lisa M.; Loyd, Denise Lewin; Hoobler, Jenny M.

2012-01-01

The Fritz J. Roethlisberger Memorial Award for the best article in the 2011 "Journal of Management Education" goes to Rae Andre for her article, Using Leadered Groups in Organizational Behavior and Management Survey Courses ("Journal of Management Education," Volume 35, Number 5, pp. 596-619). In keeping with Roethlisberger's legacy, this year's…

Multi-language naming game

NASA Astrophysics Data System (ADS)

Zhou, Jianfeng; Lou, Yang; Chen, Guanrong; Tang, Wallace K. S.

2018-04-01

Naming game is a simulation-based experiment used to study the evolution of languages. The conventional naming game focuses on a single language. In this paper, a novel naming game model named multi-language naming game (MLNG) is proposed, where the agents are different-language speakers who cannot communicate with each other without a translator (interpreter) in between. The MLNG model is general, capable of managing k different languages with k ≥ 2. For illustration, the paper only discusses the MLNG with two different languages, and studies five representative network topologies, namely random-graph, WS small-world, NW small-world, scale-free, and random-triangle topologies. Simulation and analysis results both show that: 1) using the network features and based on the proportion of translators the probability of establishing a conversation between two or three agents can be theoretically estimated; 2) the relationship between the convergence speed and the proportion of translators has a power-law-like relation; 3) different agents require different memory sizes, thus a local memory allocation rule is recommended for saving memory resources. The new model and new findings should be useful for further studies of naming games and for better understanding of languages evolution from a dynamical network perspective.

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

PubMed

Alyahya, Mohammad

2012-02-01

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

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

PubMed Central

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

2012-01-01

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

Centrally managed unified shared virtual address space

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

Wilkes, John

Systems, apparatuses, and methods for managing a unified shared virtual address space. A host may execute system software and manage a plurality of nodes coupled to the host. The host may send work tasks to the nodes, and for each node, the host may externally manage the node's view of the system's virtual address space. Each node may have a central processing unit (CPU) style memory management unit (MMU) with an internal translation lookaside buffer (TLB). In one embodiment, the host may be coupled to a given node via an input/output memory management unit (IOMMU) interface, where the IOMMU frontendmore » interface shares the TLB with the given node's MMU. In another embodiment, the host may control the given node's view of virtual address space via memory-mapped control registers.« less

Temporal Dynamics of Recovery from Extinction Shortly after Extinction Acquisition

ERIC Educational Resources Information Center

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

2013-01-01

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

A Principal Components Analysis of Dynamic Spatial Memory Biases

ERIC Educational Resources Information Center

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

2008-01-01

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

Ferroelectric memory evaluation and development system

NASA Astrophysics Data System (ADS)

Bondurant, David W.

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

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

NASA Astrophysics Data System (ADS)

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

2013-06-01

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

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

ERIC Educational Resources Information Center

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

2002-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization

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

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

2012-10-01

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

Stochastic dynamics of time correlation in complex systems with discrete time

NASA Astrophysics Data System (ADS)

Yulmetyev, Renat; Hänggi, Peter; Gafarov, Fail

2000-11-01

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

Resummed memory kernels in generalized system-bath master equations

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

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

2014-08-07

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

Short-term action potential memory and electrical restitution: A cellular computational study on the stability of cardiac repolarization under dynamic pacing

PubMed Central

2018-01-01

Electrical restitution (ER) is a major determinant of repolarization stability and, under fast pacing rate, it reveals memory properties of the cardiac action potential (AP), whose dynamics have never been fully elucidated, nor their ionic mechanisms. Previous studies have looked at ER mainly in terms of changes in AP duration (APD) when the preceding diastolic interval (DI) changes and described dynamic conditions where this relationship shows hysteresis which, in turn, has been proposed as a marker of short-term AP memory and repolarization stability. By means of numerical simulations of a non-propagated human ventricular AP, we show here that measuring ER as APD versus the preceding cycle length (CL) provides additional information on repolarization dynamics which is not contained in the companion formulation. We focus particularly on fast pacing rate conditions with a beat-to-beat variable CL, where memory properties emerge from APD vs CL and not from APD vs DI and should thus be stored in APD and not in DI. We provide an ion-currents characterization of such conditions under periodic and random CL variability, and show that the memory stored in APD plays a stabilizing role on AP repolarization under pacing rate perturbations. The gating kinetics of L-type calcium current seems to be the main determinant of this safety mechanism. We also show that, at fast pacing rate and under otherwise identical pacing conditions, a periodically beat-to-beat changing CL is more effective than a random one in stabilizing repolarization. In summary, we propose a novel view of short-term AP memory, differentially stored between systole and diastole, which opens a number of methodological and theoretical implications for the understanding of arrhythmia development. PMID:29494628

Memory Compression Techniques for Network Address Management in MPI

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

Guo, Yanfei; Archer, Charles J.; Blocksome, Michael

MPI allows applications to treat processes as a logical collection of integer ranks for each MPI communicator, while internally translating these logical ranks into actual network addresses. In current MPI implementations the management and lookup of such network addresses use memory sizes that are proportional to the number of processes in each communicator. In this paper, we propose a new mechanism, called AV-Rankmap, for managing such translation. AV-Rankmap takes advantage of logical patterns in rank-address mapping that most applications naturally tend to have, and it exploits the fact that some parts of network address structures are naturally more performance criticalmore » than others. It uses this information to compress the memory used for network address management. We demonstrate that AV-Rankmap can achieve performance similar to or better than that of other MPI implementations while using significantly less memory.« less

Inductive Game Theory and the Dynamics of Animal Conflict

PubMed Central

DeDeo, Simon; Krakauer, David C.; Flack, Jessica C.

2010-01-01

Conflict destabilizes social interactions and impedes cooperation at multiple scales of biological organization. Of fundamental interest are the causes of turbulent periods of conflict. We analyze conflict dynamics in an monkey society model system. We develop a technique, Inductive Game Theory, to extract directly from time-series data the decision-making strategies used by individuals and groups. This technique uses Monte Carlo simulation to test alternative causal models of conflict dynamics. We find individuals base their decision to fight on memory of social factors, not on short timescale ecological resource competition. Furthermore, the social assessments on which these decisions are based are triadic (self in relation to another pair of individuals), not pairwise. We show that this triadic decision making causes long conflict cascades and that there is a high population cost of the large fights associated with these cascades. These results suggest that individual agency has been over-emphasized in the social evolution of complex aggregates, and that pair-wise formalisms are inadequate. An appreciation of the empirical foundations of the collective dynamics of conflict is a crucial step towards its effective management. PMID:20485557

Inductive game theory and the dynamics of animal conflict.

PubMed

DeDeo, Simon; Krakauer, David C; Flack, Jessica C

2010-05-13

Conflict destabilizes social interactions and impedes cooperation at multiple scales of biological organization. Of fundamental interest are the causes of turbulent periods of conflict. We analyze conflict dynamics in an monkey society model system. We develop a technique, Inductive Game Theory, to extract directly from time-series data the decision-making strategies used by individuals and groups. This technique uses Monte Carlo simulation to test alternative causal models of conflict dynamics. We find individuals base their decision to fight on memory of social factors, not on short timescale ecological resource competition. Furthermore, the social assessments on which these decisions are based are triadic (self in relation to another pair of individuals), not pairwise. We show that this triadic decision making causes long conflict cascades and that there is a high population cost of the large fights associated with these cascades. These results suggest that individual agency has been over-emphasized in the social evolution of complex aggregates, and that pair-wise formalisms are inadequate. An appreciation of the empirical foundations of the collective dynamics of conflict is a crucial step towards its effective management.

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

PubMed

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

2017-03-01

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

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

PubMed

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

2012-01-01

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

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

PubMed Central

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

2012-01-01

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

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

PubMed

Eustache, Francis; Viard, Armelle; Desgranges, Béatrice

2016-07-01

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

Two Unipolar Terminal-Attractor-Based Associative Memories

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang; Wu, Chwan-Hwa

1995-01-01

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

Forgetfulness can help you win games.

PubMed

Burridge, James; Gao, Yu; Mao, Yong

2015-09-01

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

Aging, memory, and nonhierarchical energy landscape of spin jam

PubMed Central

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

2016-01-01

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

Minimizing the Disruptive Effects of Prospective Memory in Simulated Air Traffic Control

PubMed Central

Loft, Shayne; Smith, Rebekah E.; Remington, Roger

2015-01-01

Prospective memory refers to remembering to perform an intended action in the future. Failures of prospective memory can occur in air traffic control. In two experiments, we examined the utility of external aids for facilitating air traffic management in a simulated air traffic control task with prospective memory requirements. Participants accepted and handed-off aircraft and detected aircraft conflicts. The prospective memory task involved remembering to deviate from a routine operating procedure when accepting target aircraft. External aids that contained details of the prospective memory task appeared and flashed when target aircraft needed acceptance. In Experiment 1, external aids presented either adjacent or non-adjacent to each of the 20 target aircraft presented over the 40min test phase reduced prospective memory error by 11% compared to a condition without external aids. In Experiment 2, only a single target aircraft was presented a significant time (39min–42min) after presentation of the prospective memory instruction, and the external aids reduced prospective memory error by 34%. In both experiments, costs to the efficiency of non-prospective memory air traffic management (non-target aircraft acceptance response time, conflict detection response time) were reduced by non-adjacent aids compared to no aids or adjacent aids. In contrast, in both experiments, the efficiency of the prospective memory air traffic management (target aircraft acceptance response time) was facilitated by adjacent aids compared to non-adjacent aids. Together, these findings have potential implications for the design of automated alerting systems to maximize multi-task performance in work settings where operators monitor and control demanding perceptual displays. PMID:24059825

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

PubMed

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

2018-04-28

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

PubMed

Cadle, Chelsea E; Zoladz, Phillip R

2015-01-01

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

AKAPS Act in a Two-Step Mechanism of Memory Acquisition

PubMed Central

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

2013-01-01

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

Havens: Explicit Reliable Memory Regions for HPC Applications

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

Hukerikar, Saurabh; Engelmann, Christian

2016-01-01

Supporting error resilience in future exascale-class supercomputing systems is a critical challenge. Due to transistor scaling trends and increasing memory density, scientific simulations are expected to experience more interruptions caused by transient errors in the system memory. Existing hardware-based detection and recovery techniques will be inadequate to manage the presence of high memory fault rates. In this paper we propose a partial memory protection scheme based on region-based memory management. We define the concept of regions called havens that provide fault protection for program objects. We provide reliability for the regions through a software-based parity protection mechanism. Our approach enablesmore » critical program objects to be placed in these havens. The fault coverage provided by our approach is application agnostic, unlike algorithm-based fault tolerance techniques.« less

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

ERIC Educational Resources Information Center

Hogervorst, Susan

2015-01-01

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

Symbolic Model of Perception in Dynamic 3D Environments

DTIC Science & Technology

2006-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

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

PubMed

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

2018-07-01

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

Memories for life: a review of the science and technology

PubMed Central

O'Hara, Kieron; Morris, Richard; Shadbolt, Nigel; Hitch, Graham J; Hall, Wendy; Beagrie, Neil

2006-01-01

This paper discusses scientific, social and technological aspects of memory. Recent developments in our understanding of memory processes and mechanisms, and their digital implementation, have placed the encoding, storage, management and retrieval of information at the forefront of several fields of research. At the same time, the divisions between the biological, physical and the digital worlds seem to be dissolving. Hence, opportunities for interdisciplinary research into memory are being created, between the life sciences, social sciences and physical sciences. Such research may benefit from immediate application into information management technology as a testbed. The paper describes one initiative, memories for life, as a potential common problem space for the various interested disciplines. PMID:16849265

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

ERIC Educational Resources Information Center

Cunningham, David; Nugent, Colleen; Slodden, Caitlin

2010-01-01

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

Short-Term Memory in Orthogonal Neural Networks

NASA Astrophysics Data System (ADS)

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

2004-04-01

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

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

ERIC Educational Resources Information Center

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

2010-01-01

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

General purpose programmable accelerator board

DOEpatents

Robertson, Perry J.; Witzke, Edward L.

2001-01-01

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

On the Law Relating Processing to Storage in Working Memory

ERIC Educational Resources Information Center

Barrouillet, Pierre; Portrat, Sophie; Camos, Valerie

2011-01-01

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

Persistence and memory timescales in root-zone soil moisture dynamics

Treesearch

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

Gupta, Neha; Parihar, Priyanka; Neema, Vaibhav

2018-04-01

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

Memory recall and spike-frequency adaptation

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

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

PubMed Central

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

2016-01-01

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

Unstructured Adaptive Meshes: Bad for Your Memory?

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2003-05-01

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

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

PubMed

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

2018-06-11

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

Post-learning hippocampal dynamics promote preferential retention of rewarding events

PubMed Central

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

2016-01-01

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

Human memory retrieval as Lévy foraging

NASA Astrophysics Data System (ADS)

Rhodes, Theo; Turvey, Michael T.

2007-11-01

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

Electronic implementation of associative memory based on neural network models

NASA Technical Reports Server (NTRS)

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

1987-01-01

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

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

PubMed

Başar, Erol

2005-01-01

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

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

PubMed

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

2018-02-01

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

Cerebellar models of associative memory: Three papers from IEEE COMPCON spring 1989

NASA Technical Reports Server (NTRS)

Raugh, Michael R. (Editor)

1989-01-01

Three papers are presented on the following topics: (1) a cerebellar-model associative memory as a generalized random-access memory; (2) theories of the cerebellum - two early models of associative memory; and (3) intelligent network management and functional cerebellum synthesis.

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

PubMed

Simmering, Vanessa R

2016-09-01

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

Weighing the value of memory loss in the surgical evaluation of left temporal lobe epilepsy: A decision analysis

PubMed Central

Akama-Garren, Elliot H.; Bianchi, Matt T.; Leveroni, Catherine; Cole, Andrew J.; Cash, Sydney S.; Westover, M. Brandon

2016-01-01

SUMMARY Objectives Anterior temporal lobectomy is curative for many patients with disabling medically refractory temporal lobe epilepsy, but carries an inherent risk of disabling verbal memory loss. Although accurate prediction of iatrogenic memory loss is becoming increasingly possible, it remains unclear how much weight such predictions should have in surgical decision making. Here we aim to create a framework that facilitates a systematic and integrated assessment of the relative risks and benefits of surgery versus medical management for patients with left temporal lobe epilepsy. Methods We constructed a Markov decision model to evaluate the probabilistic outcomes and associated health utilities associated with choosing to undergo a left anterior temporal lobectomy versus continuing with medical management for patients with medically refractory left temporal lobe epilepsy. Three base-cases were considered, representing a spectrum of surgical candidates encountered in practice, with varying degrees of epilepsy-related disability and potential for decreased quality of life in response to post-surgical verbal memory deficits. Results For patients with moderately severe seizures and moderate risk of verbal memory loss, medical management was the preferred decision, with increased quality-adjusted life expectancy. However, the preferred choice was sensitive to clinically meaningful changes in several parameters, including quality of life impact of verbal memory decline, quality of life with seizures, mortality rate with medical management, probability of remission following surgery, and probability of remission with medical management. Significance Our decision model suggests that for patients with left temporal lobe epilepsy, quantitative assessment of risk and benefit should guide recommendation of therapy. In particular, risk for and potential impact of verbal memory decline should be carefully weighed against the degree of disability conferred by continued seizures on a patient-by-patient basis. PMID:25244498

Weighing the value of memory loss in the surgical evaluation of left temporal lobe epilepsy: a decision analysis.

PubMed

Akama-Garren, Elliot H; Bianchi, Matt T; Leveroni, Catherine; Cole, Andrew J; Cash, Sydney S; Westover, M Brandon

2014-11-01

Anterior temporal lobectomy is curative for many patients with disabling medically refractory temporal lobe epilepsy, but carries an inherent risk of disabling verbal memory loss. Although accurate prediction of iatrogenic memory loss is becoming increasingly possible, it remains unclear how much weight such predictions should have in surgical decision making. Here we aim to create a framework that facilitates a systematic and integrated assessment of the relative risks and benefits of surgery versus medical management for patients with left temporal lobe epilepsy. We constructed a Markov decision model to evaluate the probabilistic outcomes and associated health utilities associated with choosing to undergo a left anterior temporal lobectomy versus continuing with medical management for patients with medically refractory left temporal lobe epilepsy. Three base-cases were considered, representing a spectrum of surgical candidates encountered in practice, with varying degrees of epilepsy-related disability and potential for decreased quality of life in response to post-surgical verbal memory deficits. For patients with moderately severe seizures and moderate risk of verbal memory loss, medical management was the preferred decision, with increased quality-adjusted life expectancy. However, the preferred choice was sensitive to clinically meaningful changes in several parameters, including quality of life impact of verbal memory decline, quality of life with seizures, mortality rate with medical management, probability of remission following surgery, and probability of remission with medical management. Our decision model suggests that for patients with left temporal lobe epilepsy, quantitative assessment of risk and benefit should guide recommendation of therapy. In particular, risk for and potential impact of verbal memory decline should be carefully weighed against the degree of disability conferred by continued seizures on a patient-by-patient basis. Wiley Periodicals, Inc. © 2014 International League Against Epilepsy.

Memory Management of Multimedia Services in Smart Homes

NASA Astrophysics Data System (ADS)

Kamel, Ibrahim; Muhaureq, Sanaa A.

Nowadays there is a wide spectrum of applications that run in smart home environments. Consequently, home gateway, which is a central component in the smart home, must manage many applications despite limited memory resources. OSGi is a middleware standard for home gateways. OSGi models services as dependent components. Moreover, these applications might differ in their importance. Services collaborate and complement each other to achieve the required results. This paper addresses the following problem: given a home gateway that hosts several applications with different priorities and arbitrary dependencies among them. When the gateway runs out of memory, which application or service will be stopped or kicked out of memory to start a new service. Note that stopping a given service means that all the services that depend on it will be stopped too. Because of the service dependencies, traditional memory management techniques, in the operating system literatures might not be efficient. Our goal is to stop the least important and the least number of services. The paper presents a novel algorithm for home gateway memory management. The proposed algorithm takes into consideration the priority of the application and dependencies between different services, in addition to the amount of memory occupied by each service. We implement the proposed algorithm and performed many experiments to evaluate its performance and execution time. The proposed algorithm is implemented as a part of the OSGi framework (Open Service Gateway initiative). We used best fit and worst fit as yardstick to show the effectiveness of the proposed algorithm.

Working memory management and predicted utility

PubMed Central

Chatham, Christopher H.; Badre, David

2013-01-01

Given the limited capacity of working memory (WM), its resources should be allocated strategically. One strategy is filtering, whereby access to WM is granted preferentially to items with the greatest utility. However, reallocation of WM resources might be required if the utility of maintained information subsequently declines. Here, we present behavioral, computational, and neuroimaging evidence that human participants track changes in the predicted utility of information in WM. First, participants demonstrated behavioral costs when the utility of items already maintained in WM declined and resources should be reallocated. An adapted Q-learning model indicated that these costs scaled with the historical utility of individual items. Finally, model-based neuroimaging demonstrated that frontal cortex tracked the utility of items to be maintained in WM, whereas ventral striatum tracked changes in the utility of items maintained in WM to the degree that these items are no longer useful. Our findings suggest that frontostriatal mechanisms track the utility of information in WM, and that these dynamics may predict delays in the removal of information from WM. PMID:23882196

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

PubMed

Grysman, Azriel; Merrill, Natalie; Fivush, Robyn

2017-03-01

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

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-02-24

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

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

PubMed

Parker, Andrew; Kember, Timothy; Dagnall, Neil

2017-07-01

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

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

PubMed

Hubbard, T L

1995-09-01

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

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

PubMed

Fink, Christian G

2017-01-01

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

Adjusting process count on demand for petascale global optimization

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

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

2012-11-23

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

Digital MOS integrated circuits

NASA Astrophysics Data System (ADS)

Elmasry, M. I.

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

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

PubMed

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

2011-11-30

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

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

PubMed Central

Pedreira, María E.

2013-01-01

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

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

PubMed

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

2013-01-01

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

Goal-Driven Autonomy and Robust Architecture for Long-Duration Missions (Year 1: 1 July 2013 - 31 July 2014)

DTIC Science & Technology

2014-09-30

Mental Domain = Ω Goal Management goal change goal input World =Ψ Memory Mission & Goals( ) World Model (-Ψ) Episodic Memory Semantic Memory ...Activations Trace Meta-Level Control Introspective Monitoring Memory Reasoning Trace ( ) Strategies Episodic Memory Metaknowledge Self Model...it is from incorrect or missing memory associations (i.e., indices). Similarly, correct information may exist in the input stream, but may not be

Event-Based Prospective Memory Is Independently Associated with Self-Report of Medication Management in Older Adults

PubMed Central

Woods, Steven Paul; Weinborn, Michael; Maxwell, Brenton R.; Gummery, Alice; Mo, Kevin; Ng, Amanda R. J.; Bucks, Romola S.

2014-01-01

Background Identifying potentially modifiable risk factors for medication non-adherence in older adults is important in order to enhance screening and intervention efforts designed to improve medication-taking behavior and health outcomes. The current study sought to determine the unique contribution of prospective memory (i.e., “remembering to remember”) to successful self-reported medication management in older adults. Methods Sixty-five older adults with current medication prescriptions completed a comprehensive research evaluation of sociodemographic, psychiatric, and neurocognitive functioning, which included the Memory for Adherence to Medication Scale (MAMS), Prospective and Retrospective Memory Questionnaire (PRMQ), and a performance-based measure of prospective memory that measured both semantically-related and semantically-unrelated cue-intention (i.e., when-what) pairings. Results A series of hierarchical regressions controlling for biopsychosocial, other neurocognitive, and medication-related factors showed that elevated complaints on the PM scale of the PRMQ and worse performance on an objective semantically-unrelated event-based prospective memory task were independent predictors of poorer medication adherence as measured by the MAMS. Conclusions Prospective memory plays an important role in self-report of successful medication management among older adults. Findings may have implications for screening for older individuals “at risk” of non-adherence, as well as the development of prospective memory-based interventions to improve medication adherence and, ultimately, long-term health outcomes in older adults. PMID:24410357

Mobile, Virtual Enhancements for Rehabilitation (MOVER)

DTIC Science & Technology

2013-11-28

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

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

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

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

PubMed

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

2017-02-01

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

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2016-05-01

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

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

NASA Astrophysics Data System (ADS)

Liang, Yuanchang; Taya, Minoru; Kuga, Yasuo

2004-07-01

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

Inflated speedups in parallel simulations via malloc()

NASA Technical Reports Server (NTRS)

Nicol, David M.

1990-01-01

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

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

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

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

2011-05-01

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

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

PubMed Central

Stone, John E.; Kohlmeyer, Axel

2011-01-01

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

Weather prediction using a genetic memory

NASA Technical Reports Server (NTRS)

Rogers, David

1990-01-01

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

Improving Working Memory Efficiency by Reframing Metacognitive Interpretation of Task Difficulty

ERIC Educational Resources Information Center

Autin, Frederique; Croizet, Jean-Claude

2012-01-01

Working memory capacity, our ability to manage incoming information for processing purposes, predicts achievement on a wide range of intellectual abilities. Three randomized experiments (N = 310) tested the effectiveness of a brief psychological intervention designed to boost working memory efficiency (i.e., state working memory capacity) by…

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

NASA Technical Reports Server (NTRS)

Turner, Travis L.

2001-01-01

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

Investigation and design of a Project Management Decision Support System for the 4950th Test Wing.

DTIC Science & Technology

1986-03-01

all decision makers is the need for memory aids (reports, hand written notes, mental memory joggers, etc.). 4. Even in similar decision making ... memories to synthesize a decision- making process based on their individual styles, skills, and knowledge (Sprague, 1982: 106). Control mechanisms...representations shown in Figures 4.9 and 4.10 provide a means to this objective. By enabling a manager to make and record reasonable changes to

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

NASA Astrophysics Data System (ADS)

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

1990-08-01

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

Rutger's CAM2000 chip architecture

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

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

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

Shen, Xipeng

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

Configurable memory system and method for providing atomic counting operations in a memory device

DOEpatents

Bellofatto, Ralph E.; Gara, Alan G.; Giampapa, Mark E.; Ohmacht, Martin

2010-09-14

A memory system and method for providing atomic memory-based counter operations to operating systems and applications that make most efficient use of counter-backing memory and virtual and physical address space, while simplifying operating system memory management, and enabling the counter-backing memory to be used for purposes other than counter-backing storage when desired. The encoding and address decoding enabled by the invention provides all this functionality through a combination of software and hardware.

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

PubMed Central

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

2011-01-01

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

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

PubMed

Osman, Magda

2010-01-01

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

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

NASA Astrophysics Data System (ADS)

Izvekov, Sergei

2017-01-01

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

Enhancement of fear memory by retrieval through reconsolidation

PubMed Central

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

2014-01-01

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

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

PubMed Central

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

2008-01-01

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

Feedback coupling in dynamical systems

NASA Astrophysics Data System (ADS)

Trimper, Steffen; Zabrocki, Knud

2003-05-01

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

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

PubMed

Kemps, Eva; Andrade, Jackie

2012-05-01

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

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

PubMed

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

2016-06-16

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

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

PubMed

Boreland, B; Clement, G; Kunze, H

2015-08-01

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

Controlled Shape Memory Behavior of a Smectic Main-Chain Liquid Crystalline Elastomer

DOE PAGES

Li, Yuzhan; Pruitt, Cole; Rios, Orlando; ...

2015-04-10

Here, we describe how a smectic main-chain liquid crystalline elastomer (LCE), with controlled shape memory behavior, is synthesized by polymerizing a biphenyl-based epoxy monomer with an aliphatic carboxylic acid curing agent. Microstructures of the LCEs, including their liquid crystallinity and cross-linking density, are modified by adjusting the stoichiometric ratio of the reactants to tailor the thermomechanical properties and shape memory behavior of the material. Thermal and liquid crystalline properties of the LCEs, characterized using differential scanning calorimetry and dynamic mechanical analysis, and structural analysis, performed using small-angle and wide-angle X-ray scattering, show that liquid crystallinity, cross-linking density, and network rigiditymore » are strongly affected by the stoichiometry of the curing reaction. With appropriate structural modifications it is possible to tune the thermal, dynamic mechanical, and thermomechanical properties as well as the shape memory and thermal degradation behavior of LCEs.« less

Controlled Shape Memory Behavior of a Smectic Main-Chain Liquid Crystalline Elastomer

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

Li, Yuzhan; Pruitt, Cole; Rios, Orlando

Here, we describe how a smectic main-chain liquid crystalline elastomer (LCE), with controlled shape memory behavior, is synthesized by polymerizing a biphenyl-based epoxy monomer with an aliphatic carboxylic acid curing agent. Microstructures of the LCEs, including their liquid crystallinity and cross-linking density, are modified by adjusting the stoichiometric ratio of the reactants to tailor the thermomechanical properties and shape memory behavior of the material. Thermal and liquid crystalline properties of the LCEs, characterized using differential scanning calorimetry and dynamic mechanical analysis, and structural analysis, performed using small-angle and wide-angle X-ray scattering, show that liquid crystallinity, cross-linking density, and network rigiditymore » are strongly affected by the stoichiometry of the curing reaction. With appropriate structural modifications it is possible to tune the thermal, dynamic mechanical, and thermomechanical properties as well as the shape memory and thermal degradation behavior of LCEs.« less

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

PubMed Central

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Mother-caregiver expectations for function among survivors of childhood brain tumors

PubMed Central

Barakat, Lamia P.; Ulrich, Connie M.; Jones, Nora L.; Deatrick, Janet A.

2015-01-01

Purpose Children diagnosed with brain tumors increasingly survive to adulthood, although they do so with needs often requiring continued parental caregiving. We sought to describe the nature of caregivers’ expectations about survivors’ function and how expectations connect to ongoing management and decision-making. Methods Forty-five qualitative interviews with mother-caregivers were conducted and coded for themes related to expectations for their adolescent/young adult children living post-childhood brain tumors. Results Five main themes emerged as integral to mother-caregiver expectations: realizing a difference in the survivor, noticing limitations to independence in the survivor, memories of learning about clinical prognoses as understood from consent meetings and education, managing these realizations, and acknowledging unresolved challenges. Conclusions Caregiver expectations are influenced by both initial clinical interactions and contemporary family dynamics and require individual- and family-specific survivorship planning. As caregiver expectations can influence management behaviors that impact outcomes and possibly independence, implications for clinician-caregiver shared decision-making are substantial. PMID:26556212

Dynamic Load Balancing for Adaptive Computations on Distributed-Memory Machines

NASA Technical Reports Server (NTRS)

1999-01-01

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

Josephson-CMOS Hybrid Memories

DTIC Science & Technology

2007-04-25

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

A Time-Aware Routing Map for Indoor Evacuation †

PubMed Central

Zhao, Haifeng; Winter, Stephan

2016-01-01

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

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

PubMed

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

Navlakha, Nupur; Kranti, Abhinav

2017-11-01

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

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

ERIC Educational Resources Information Center

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

2006-01-01

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

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

ERIC Educational Resources Information Center

Petrov, Alexander A.; Anderson, John R.

2005-01-01

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

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

PubMed

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

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

Sasano, Koji; Okajima, Hiroshi; Matsunaga, Nobutomo

Recently, the fractional order PID (FO-PID) control, which is the extension of the PID control, has been focused on. Even though the FO-PID requires the high-order filter, it is difficult to realize the high-order filter due to the memory limitation of digital computer. For implementation of FO-PID, approximation of the fractional integrator and differentiator are required. Short memory principle (SMP) is one of the effective approximation methods. However, there is a disadvantage that the approximated filter with SMP cannot eliminate the steady-state error. For this problem, we introduce the distributed implementation of the integrator and the dynamic quantizer to make the efficient use of permissible memory. The objective of this study is to clarify how to implement the accurate FO-PID with limited memories. In this paper, we propose the implementation method of FO-PID with memory constraint using dynamic quantizer. And the trade off between approximation of fractional elements and quantized data size are examined so as to close to the ideal FO-PID responses. The effectiveness of proposed method is evaluated by numerical example and experiment in the temperature control of heat plate.

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

PubMed Central

D’Esposito, Mark

2017-01-01

Recent work has established that visual working memory is subject to serial dependence: current information in memory blends with that from the recent past as a function of their similarity. This tuned temporal smoothing likely promotes the stability of memory in the face of noise and occlusion. Serial dependence accumulates over several seconds in memory and deteriorates with increased separation between trials. While this phenomenon has been extensively characterized in behavior, its neural mechanism is unknown. In the present study, we investigate the circuit-level origins of serial dependence in a biophysical model of cortex. We explore two distinct kinds of mechanisms: stable persistent activity during the memory delay period and dynamic “activity-silent” synaptic plasticity. We find that networks endowed with both strong reverberation to support persistent activity and dynamic synapses can closely reproduce behavioral serial dependence. Specifically, elevated activity drives synaptic augmentation, which biases activity on the subsequent trial, giving rise to a spatiotemporally tuned shift in the population response. Our hybrid neural model is a theoretical advance beyond abstract mathematical characterizations, offers testable hypotheses for physiological research, and demonstrates the power of biological insights to provide a quantitative explanation of human behavior. PMID:29244810

Rapid learning dynamics in individual honeybees during classical conditioning.

PubMed

Pamir, Evren; Szyszka, Paul; Scheiner, Ricarda; Nawrot, Martin P

2014-01-01

Associative learning in insects has been studied extensively by a multitude of classical conditioning protocols. However, so far little emphasis has been put on the dynamics of learning in individuals. The honeybee is a well-established animal model for learning and memory. We here studied associative learning as expressed in individual behavior based on a large collection of data on olfactory classical conditioning (25 datasets, 3298 animals). We show that the group-averaged learning curve and memory retention score confound three attributes of individual learning: the ability or inability to learn a given task, the generally fast acquisition of a conditioned response (CR) in learners, and the high stability of the CR during consecutive training and memory retention trials. We reassessed the prevailing view that more training results in better memory performance and found that 24 h memory retention can be indistinguishable after single-trial and multiple-trial conditioning in individuals. We explain how inter-individual differences in learning can be accommodated within the Rescorla-Wagner theory of associative learning. In both data-analysis and modeling we demonstrate how the conflict between population-level and single-animal perspectives on learning and memory can be disentangled.

Rapid learning dynamics in individual honeybees during classical conditioning

PubMed Central

Pamir, Evren; Szyszka, Paul; Scheiner, Ricarda; Nawrot, Martin P.

2014-01-01

Associative learning in insects has been studied extensively by a multitude of classical conditioning protocols. However, so far little emphasis has been put on the dynamics of learning in individuals. The honeybee is a well-established animal model for learning and memory. We here studied associative learning as expressed in individual behavior based on a large collection of data on olfactory classical conditioning (25 datasets, 3298 animals). We show that the group-averaged learning curve and memory retention score confound three attributes of individual learning: the ability or inability to learn a given task, the generally fast acquisition of a conditioned response (CR) in learners, and the high stability of the CR during consecutive training and memory retention trials. We reassessed the prevailing view that more training results in better memory performance and found that 24 h memory retention can be indistinguishable after single-trial and multiple-trial conditioning in individuals. We explain how inter-individual differences in learning can be accommodated within the Rescorla–Wagner theory of associative learning. In both data-analysis and modeling we demonstrate how the conflict between population-level and single-animal perspectives on learning and memory can be disentangled. PMID:25309366

Spectral decomposition of nonlinear systems with memory

NASA Astrophysics Data System (ADS)

Svenkeson, Adam; Glaz, Bryan; Stanton, Samuel; West, Bruce J.

2016-02-01

We present an alternative approach to the analysis of nonlinear systems with long-term memory that is based on the Koopman operator and a Lévy transformation in time. Memory effects are considered to be the result of interactions between a system and its surrounding environment. The analysis leads to the decomposition of a nonlinear system with memory into modes whose temporal behavior is anomalous and lacks a characteristic scale. On average, the time evolution of a mode follows a Mittag-Leffler function, and the system can be described using the fractional calculus. The general theory is demonstrated on the fractional linear harmonic oscillator and the fractional nonlinear logistic equation. When analyzing data from an ill-defined (black-box) system, the spectral decomposition in terms of Mittag-Leffler functions that we propose may uncover inherent memory effects through identification of a small set of dynamically relevant structures that would otherwise be obscured by conventional spectral methods. Consequently, the theoretical concepts we present may be useful for developing more general methods for numerical modeling that are able to determine whether observables of a dynamical system are better represented by memoryless operators, or operators with long-term memory in time, when model details are unknown.

Dynamics of Hippocampal Protein Expression During Long-term Spatial Memory Formation*

PubMed Central

Borovok, Natalia; Nesher, Elimelech; Levin, Yishai; Reichenstein, Michal; Pinhasov, Albert

2016-01-01

Spatial memory depends on the hippocampus, which is particularly vulnerable to aging. This vulnerability has implications for the impairment of navigation capacities in older people, who may show a marked drop in performance of spatial tasks with advancing age. Contemporary understanding of long-term memory formation relies on molecular mechanisms underlying long-term synaptic plasticity. With memory acquisition, activity-dependent changes occurring in synapses initiate multiple signal transduction pathways enhancing protein turnover. This enhancement facilitates de novo synthesis of plasticity related proteins, crucial factors for establishing persistent long-term synaptic plasticity and forming memory engrams. Extensive studies have been performed to elucidate molecular mechanisms of memory traces formation; however, the identity of plasticity related proteins is still evasive. In this study, we investigated protein turnover in mouse hippocampus during long-term spatial memory formation using the reference memory version of radial arm maze (RAM) paradigm. We identified 1592 proteins, which exhibited a complex picture of expression changes during spatial memory formation. Variable linear decomposition reduced significantly data dimensionality and enriched three principal factors responsible for variance of memory-related protein levels at (1) the initial phase of memory acquisition (165 proteins), (2) during the steep learning improvement (148 proteins), and (3) the final phase of the learning curve (123 proteins). Gene ontology and signaling pathways analysis revealed a clear correlation between memory improvement and learning phase-curbed expression profiles of proteins belonging to specific functional categories. We found differential enrichment of (1) neurotrophic factors signaling pathways, proteins regulating synaptic transmission, and actin microfilament during the first day of the learning curve; (2) transcription and translation machinery, protein trafficking, enhancement of metabolic activity, and Wnt signaling pathway during the steep phase of memory formation; and (3) cytoskeleton organization proteins. Taken together, this study clearly demonstrates dynamic assembly and disassembly of protein-protein interaction networks depending on the stage of memory formation engrams. PMID:26598641

Strategies for Energy Efficient Resource Management of Hybrid Programming Models

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

Li, Dong; Supinski, Bronis de; Schulz, Martin

2013-01-01

Many scientific applications are programmed using hybrid programming models that use both message-passing and shared-memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes. Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared-memory or message-passing, in isolation. The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoptionmore » of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems. In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations. We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74% on average and up to 13.8%) with some performance gain (up to 7.5%) or negligible performance loss.« less

Past makes future: role of pFC in prediction.

PubMed

Fuster, Joaquín M; Bressler, Steven L

2015-04-01

The pFC enables the essential human capacities for predicting future events and preadapting to them. These capacities rest on both the structure and dynamics of the human pFC. Structurally, pFC, together with posterior association cortex, is at the highest hierarchical level of cortical organization, harboring neural networks that represent complex goal-directed actions. Dynamically, pFC is at the highest level of the perception-action cycle, the circular processing loop through the cortex that interfaces the organism with the environment in the pursuit of goals. In its predictive and preadaptive roles, pFC supports cognitive functions that are critical for the temporal organization of future behavior, including planning, attentional set, working memory, decision-making, and error monitoring. These functions have a common future perspective and are dynamically intertwined in goal-directed action. They all utilize the same neural infrastructure: a vast array of widely distributed, overlapping, and interactive cortical networks of personal memory and semantic knowledge, named cognits, which are formed by synaptic reinforcement in learning and memory acquisition. From this cortex-wide reservoir of memory and knowledge, pFC generates purposeful, goal-directed actions that are preadapted to predicted future events.

Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision.

PubMed

Shi, Junxing; Wen, Haiguang; Zhang, Yizhen; Han, Kuan; Liu, Zhongming

2018-05-01

The human visual cortex extracts both spatial and temporal visual features to support perception and guide behavior. Deep convolutional neural networks (CNNs) provide a computational framework to model cortical representation and organization for spatial visual processing, but unable to explain how the brain processes temporal information. To overcome this limitation, we extended a CNN by adding recurrent connections to different layers of the CNN to allow spatial representations to be remembered and accumulated over time. The extended model, or the recurrent neural network (RNN), embodied a hierarchical and distributed model of process memory as an integral part of visual processing. Unlike the CNN, the RNN learned spatiotemporal features from videos to enable action recognition. The RNN better predicted cortical responses to natural movie stimuli than the CNN, at all visual areas, especially those along the dorsal stream. As a fully observable model of visual processing, the RNN also revealed a cortical hierarchy of temporal receptive window, dynamics of process memory, and spatiotemporal representations. These results support the hypothesis of process memory, and demonstrate the potential of using the RNN for in-depth computational understanding of dynamic natural vision. © 2018 Wiley Periodicals, Inc.

Multifractal analysis of information processing in hippocampal neural ensembles during working memory under Δ9-tetrahydrocannabinol administration

PubMed Central

Fetterhoff, Dustin; Opris, Ioan; Simpson, Sean L.; Deadwyler, Sam A.; Hampson, Robert E.; Kraft, Robert A.

2014-01-01

Background Multifractal analysis quantifies the time-scale-invariant properties in data by describing the structure of variability over time. By applying this analysis to hippocampal interspike interval sequences recorded during performance of a working memory task, a measure of long-range temporal correlations and multifractal dynamics can reveal single neuron correlates of information processing. New method Wavelet leaders-based multifractal analysis (WLMA) was applied to hippocampal interspike intervals recorded during a working memory task. WLMA can be used to identify neurons likely to exhibit information processing relevant to operation of brain–computer interfaces and nonlinear neuronal models. Results Neurons involved in memory processing (“Functional Cell Types” or FCTs) showed a greater degree of multifractal firing properties than neurons without task-relevant firing characteristics. In addition, previously unidentified FCTs were revealed because multifractal analysis suggested further functional classification. The cannabinoid-type 1 receptor partial agonist, tetrahydrocannabinol (THC), selectively reduced multifractal dynamics in FCT neurons compared to non-FCT neurons. Comparison with existing methods WLMA is an objective tool for quantifying the memory-correlated complexity represented by FCTs that reveals additional information compared to classification of FCTs using traditional z-scores to identify neuronal correlates of behavioral events. Conclusion z-Score-based FCT classification provides limited information about the dynamical range of neuronal activity characterized by WLMA. Increased complexity, as measured with multifractal analysis, may be a marker of functional involvement in memory processing. The level of multifractal attributes can be used to differentially emphasize neural signals to improve computational models and algorithms underlying brain–computer interfaces. PMID:25086297

78 FR 23866 - Airworthiness Directives; the Boeing Company

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-23

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

Hemiboreal forest: natural disturbances and the importance of ecosystem legacies to management

Treesearch

Kalev Jogiste; Henn Korjus; John Stanturf; Lee E. Frelich; Endijs Baders; Janis Donis; Aris Jansons; Ahto Kangur; Kajar Koster; Diana Laarmann; Tiit Maaten; Vitas Marozas; Marek Metslaid; Kristi Nigul; Olga Polyachenko; Tiit Randveer; Floortje Vodde

2017-01-01

The condition of forest ecosystems depends on the temporal and spatial pattern of management interventions and natural disturbances. Remnants of previous conditions persisting after disturbances, or ecosystem legacies, collectively comprise ecosystem memory. Ecosystem memory in turn contributes to resilience and possibilities of ecosystem reorganization...

Cue-independent memory impairment by reactivation-coupled interference in human declarative memory.

PubMed

Zhu, Zijian; Wang, Yingying; Cao, Zhijun; Chen, Biqing; Cai, Huaqian; Wu, Yanhong; Rao, Yi

2016-10-01

Memory is a dynamic process. While memory becomes increasingly resistant to interference after consolidation, a brief reactivation renders it unstable again. Previous studies have shown that interference, when applied upon reactivation, impairs the consolidated memory, presumably by disrupting the reconsolidation of the memory. However, attempts have failed in disrupting human declarative memory, raising a question about whether declarative memory becomes unstable upon reactivation. Here, we used a double-cue/one-target paradigm, which associated the same target with two different cues in initial memory formation. Only one cue/target association was later reactivated and treated with behavioral interference. Our results showed, for the first time, that reactivation-coupled interference caused cue-independent memory impairment that generalized to other cues associated with the memory. Critically, such memory impairment appeared immediately after interference, before the reconsolidation process was completed, suggesting that common manipulations of reactivation-coupled interference procedures might disrupt other processes in addition to the reconsolidation process in human declarative memory. Copyright © 2016. Published by Elsevier B.V.

Double dynamic scaling in human communication dynamics

NASA Astrophysics Data System (ADS)

Wang, Shengfeng; Feng, Xin; Wu, Ye; Xiao, Jinhua

2017-05-01

In the last decades, human behavior has been deeply understanding owing to the huge quantities data of human behavior available for study. The main finding in human dynamics shows that temporal processes consist of high-activity bursty intervals alternating with long low-activity periods. A model, assuming the initiator of bursty follow a Poisson process, is widely used in the modeling of human behavior. Here, we provide further evidence for the hypothesis that different bursty intervals are independent. Furthermore, we introduce a special threshold to quantitatively distinguish the time scales of complex dynamics based on the hypothesis. Our results suggest that human communication behavior is a composite process of double dynamics with midrange memory length. The method for calculating memory length would enhance the performance of many sequence-dependent systems, such as server operation and topic identification.

Method and device for maximizing memory system bandwidth by accessing data in a dynamically determined order

NASA Technical Reports Server (NTRS)

Schwab, Andrew J. (Inventor); Aylor, James (Inventor); Hitchcock, Charles Young (Inventor); Wulf, William A. (Inventor); McKee, Sally A. (Inventor); Moyer, Stephen A. (Inventor); Klenke, Robert (Inventor)

2000-01-01

A data processing system is disclosed which comprises a data processor and memory control device for controlling the access of information from the memory. The memory control device includes temporary storage and decision ability for determining what order to execute the memory accesses. The compiler detects the requirements of the data processor and selects the data to stream to the memory control device which determines a memory access order. The order in which to access said information is selected based on the location of information stored in the memory. The information is repeatedly accessed from memory and stored in the temporary storage until all streamed information is accessed. The information is stored until required by the data processor. The selection of the order in which to access information maximizes bandwidth and decreases the retrieval time.

Remembrance of Things Past

ERIC Educational Resources Information Center

Heckel, Robert V.; Heckel, Nancy W.

1976-01-01

An attempt was undertaken to demonstrate a relationship between earliest memories and a perception of significant future events. Relevance here was in the role that early memories play in the theoretical bases and treatment processes of all dynamically oriented therapies. (Author/RK)

Synchronization of heteroclinic circuits through learning in coupled neural networks

NASA Astrophysics Data System (ADS)

Selskii, Anton; Makarov, Valeri A.

2016-01-01

The synchronization of oscillatory activity in neural networks is usually implemented by coupling the state variables describing neuronal dynamics. Here we study another, but complementary mechanism based on a learning process with memory. A driver network, acting as a teacher, exhibits winner-less competition (WLC) dynamics, while a driven network, a learner, tunes its internal couplings according to the oscillations observed in the teacher. We show that under appropriate training the learner can "copy" the coupling structure and thus synchronize oscillations with the teacher. The replication of the WLC dynamics occurs for intermediate memory lengths only, consequently, the learner network exhibits a phenomenon of learning resonance.

Does reactivation trigger episodic memory change? A meta-analysis.

PubMed

Scully, Iiona D; Napper, Lucy E; Hupbach, Almut

2017-07-01

According to the reconsolidation hypothesis, long-term memories return to a plastic state upon their reactivation, leaving them vulnerable to interference effects and requiring re-storage processes or else these memories might be permanently lost. The present study used a meta-analytic approach to critically evaluate the evidence for reactivation-induced changes in human episodic memory. Results indicated that reactivation makes episodic memories susceptible to physiological and behavioral interference. When applied shortly after reactivation, interference manipulations altered the amount of information that could be retrieved from the original learning event. This effect was more pronounced for remote memories and memories of narrative structure. Additionally, new learning following reactivation reliably increased the number of intrusions from new information into the original memory. These findings support a dynamic view of long-term memory by showing that memories can be changed long after they were acquired. Copyright © 2016 Elsevier Inc. All rights reserved.

Identification of a novel protein for memory regulation in the hippocampus.

PubMed

Zhang, Xue-Han; Zhang, Hui; Tu, Yanyang; Gao, Xiang; Zhou, Changfu; Jin, Meilei; Zhao, Guoping; Jing, Naihe; Li, Bao-Ming; Yu, Lei

2005-08-26

Memory formation, maintenance, and retrieval are a dynamic process, reflecting a combined outcome of new memory formation on one hand, and older memory suppression/clearance on the other. Although much knowledge has been gained regarding new memory formation, less is known about the molecular components and processes that serve the function of memory suppression/clearance. Here, we report the identification of a novel protein, termed hippyragranin (HGN), that is expressed in the rat hippocampus and its expression is reduced by hippocampal denervation. Inhibition of HGN by antisense oligonucleotide in area CA1 results in enhanced performance in Morris water maze, as well as elevated long-term potentiation. These results suggest that HGN is involved in negative memory regulation.

Human TSCM cell dynamics in vivo are compatible with long-lived immunological memory and stemness.

PubMed

Del Amo, Pedro Costa; Beneytez, Julio Lahoz; Boelen, Lies; Ahmed, Raya; Miners, Kelly L; Zhang, Yan; Roger, Laureline; Jones, Rhiannon E; Marraco, Silvia A Fuertes; Speiser, Daniel E; Baird, Duncan M; Price, David A; Ladell, Kristin; Macallan, Derek; Asquith, Becca

2018-06-22

Adaptive immunity relies on the generation and maintenance of memory T cells to provide protection against repeated antigen exposure. It has been hypothesised that a self-renewing population of T cells, named stem cell-like memory T (TSCM) cells, are responsible for maintaining memory. However, it is not clear if the dynamics of TSCM cells in vivo are compatible with this hypothesis. To address this issue, we investigated the dynamics of TSCM cells under physiological conditions in humans in vivo using a multidisciplinary approach that combines mathematical modelling, stable isotope labelling, telomere length analysis, and cross-sectional data from vaccine recipients. We show that, unexpectedly, the average longevity of a TSCM clone is very short (half-life < 1 year, degree of self-renewal = 430 days): far too short to constitute a stem cell population. However, we also find that the TSCM population is comprised of at least 2 kinetically distinct subpopulations that turn over at different rates. Whilst one subpopulation is rapidly replaced (half-life = 5 months) and explains the rapid average turnover of the bulk TSCM population, the half-life of the other TSCM subpopulation is approximately 9 years, consistent with the longevity of the recall response. We also show that this latter population exhibited a high degree of self-renewal, with a cell residing without dying or differentiating for 15% of our lifetime. Finally, although small, the population was not subject to excessive stochasticity. We conclude that the majority of TSCM cells are not stem cell-like but that there is a subpopulation of TSCM cells whose dynamics are compatible with their putative role in the maintenance of T cell memory.

Effective connectivity within the frontoparietal control network differentiates cognitive control and working memory.

PubMed

Harding, Ian H; Yücel, Murat; Harrison, Ben J; Pantelis, Christos; Breakspear, Michael

2015-02-01

Cognitive control and working memory rely upon a common fronto-parietal network that includes the inferior frontal junction (IFJ), dorsolateral prefrontal cortex (dlPFC), pre-supplementary motor area/dorsal anterior cingulate cortex (pSMA/dACC), and intraparietal sulcus (IPS). This network is able to flexibly adapt its function in response to changing behavioral goals, mediating a wide range of cognitive demands. Here we apply dynamic causal modeling to functional magnetic resonance imaging data to characterize task-related alterations in the strength of network interactions across distinct cognitive processes. Evidence in favor of task-related connectivity dynamics was accrued across a very large space of possible network structures. Cognitive control and working memory demands were manipulated using a factorial combination of the multi-source interference task and a verbal 2-back working memory task, respectively. Both were found to alter the sensitivity of the IFJ to perceptual information, and to increase IFJ-to-pSMA/dACC connectivity. In contrast, increased connectivity from the pSMA/dACC to the IPS, as well as from the dlPFC to the IFJ, was uniquely driven by cognitive control demands; a task-induced negative influence of the dlPFC on the pSMA/dACC was specific to working memory demands. These results reflect a system of both shared and unique context-dependent dynamics within the fronto-parietal network. Mechanisms supporting cognitive engagement, response selection, and action evaluation may be shared across cognitive domains, while dynamic updating of task and context representations within this network are potentially specific to changing demands on cognitive control. Copyright © 2014 Elsevier Inc. All rights reserved.

Human Stem Cell-like Memory T Cells Are Maintained in a State of Dynamic Flux.

PubMed

Ahmed, Raya; Roger, Laureline; Costa Del Amo, Pedro; Miners, Kelly L; Jones, Rhiannon E; Boelen, Lies; Fali, Tinhinane; Elemans, Marjet; Zhang, Yan; Appay, Victor; Baird, Duncan M; Asquith, Becca; Price, David A; Macallan, Derek C; Ladell, Kristin

2016-12-13

Adaptive immunity requires the generation of memory T cells from naive precursors selected in the thymus. The key intermediaries in this process are stem cell-like memory T (T SCM ) cells, multipotent progenitors that can both self-renew and replenish more differentiated subsets of memory T cells. In theory, antigen specificity within the T SCM pool may be imprinted statically as a function of largely dormant cells and/or retained dynamically by more transitory subpopulations. To explore the origins of immunological memory, we measured the turnover of T SCM cells in vivo using stable isotope labeling with heavy water. The data indicate that T SCM cells in both young and elderly subjects are maintained by ongoing proliferation. In line with this finding, T SCM cells displayed limited telomere length erosion coupled with high expression levels of active telomerase and Ki67. Collectively, these observations show that T SCM cells exist in a state of perpetual flux throughout the human lifespan. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Zero-dynamics principle for perfect quantum memory in linear networks

NASA Astrophysics Data System (ADS)

Yamamoto, Naoki; James, Matthew R.

2014-07-01

In this paper, we study a general linear networked system that contains a tunable memory subsystem; that is, it is decoupled from an optical field for state transportation during the storage process, while it couples to the field during the writing or reading process. The input is given by a single photon state or a coherent state in a pulsed light field. We then completely and explicitly characterize the condition required on the pulse shape achieving the perfect state transfer from the light field to the memory subsystem. The key idea to obtain this result is the use of zero-dynamics principle, which in our case means that, for perfect state transfer, the output field during the writing process must be a vacuum. A useful interpretation of the result in terms of the transfer function is also given. Moreover, a four-node network composed of atomic ensembles is studied as an example, demonstrating how the input field state is transferred to the memory subsystem and what the input pulse shape to be engineered for perfect memory looks like.

Dynamic Load-Balancing for Distributed Heterogeneous Computing of Parallel CFD Problems

NASA Technical Reports Server (NTRS)

Ecer, A.; Chien, Y. P.; Boenisch, T.; Akay, H. U.

2000-01-01

The developed methodology is aimed at improving the efficiency of executing block-structured algorithms on parallel, distributed, heterogeneous computers. The basic approach of these algorithms is to divide the flow domain into many sub- domains called blocks, and solve the governing equations over these blocks. Dynamic load balancing problem is defined as the efficient distribution of the blocks among the available processors over a period of several hours of computations. In environments with computers of different architecture, operating systems, CPU speed, memory size, load, and network speed, balancing the loads and managing the communication between processors becomes crucial. Load balancing software tools for mutually dependent parallel processes have been created to efficiently utilize an advanced computation environment and algorithms. These tools are dynamic in nature because of the chances in the computer environment during execution time. More recently, these tools were extended to a second operating system: NT. In this paper, the problems associated with this application will be discussed. Also, the developed algorithms were combined with the load sharing capability of LSF to efficiently utilize workstation clusters for parallel computing. Finally, results will be presented on running a NASA based code ADPAC to demonstrate the developed tools for dynamic load balancing.

On the effect of memory in a quantum prisoner's dilemma cellular automaton

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón; Revuelta, Fabio

2018-03-01

The disrupting effect of quantum memory on the dynamics of a spatial quantum formulation of the iterated prisoner's dilemma game with variable entangling is studied. The game is played within a cellular automata framework, i.e., with local and synchronous interactions. The main findings of this work refer to the shrinking effect of memory on the disruption induced by noise.

Design of Unstructured Adaptive (UA) NAS Parallel Benchmark Featuring Irregular, Dynamic Memory Accesses

NASA Technical Reports Server (NTRS)

Feng, Hui-Yu; VanderWijngaart, Rob; Biswas, Rupak; Biegel, Bryan (Technical Monitor)

2001-01-01

We describe the design of a new method for the measurement of the performance of modern computer systems when solving scientific problems featuring irregular, dynamic memory accesses. The method involves the solution of a stylized heat transfer problem on an unstructured, adaptive grid. A Spectral Element Method (SEM) with an adaptive, nonconforming mesh is selected to discretize the transport equation. The relatively high order of the SEM lowers the fraction of wall clock time spent on inter-processor communication, which eases the load balancing task and allows us to concentrate on the memory accesses. The benchmark is designed to be three-dimensional. Parallelization and load balance issues of a reference implementation will be described in detail in future reports.

Dynamic interactions between visual working memory and saccade target selection

PubMed Central

Schneegans, Sebastian; Spencer, John P.; Schöner, Gregor; Hwang, Seongmin; Hollingworth, Andrew

2014-01-01

Recent psychophysical experiments have shown that working memory for visual surface features interacts with saccadic motor planning, even in tasks where the saccade target is unambiguously specified by spatial cues. Specifically, a match between a memorized color and the color of either the designated target or a distractor stimulus influences saccade target selection, saccade amplitudes, and latencies in a systematic fashion. To elucidate these effects, we present a dynamic neural field model in combination with new experimental data. The model captures the neural processes underlying visual perception, working memory, and saccade planning relevant to the psychophysical experiment. It consists of a low-level visual sensory representation that interacts with two separate pathways: a spatial pathway implementing spatial attention and saccade generation, and a surface feature pathway implementing color working memory and feature attention. Due to bidirectional coupling between visual working memory and feature attention in the model, the working memory content can indirectly exert an effect on perceptual processing in the low-level sensory representation. This in turn biases saccadic movement planning in the spatial pathway, allowing the model to quantitatively reproduce the observed interaction effects. The continuous coupling between representations in the model also implies that modulation should be bidirectional, and model simulations provide specific predictions for complementary effects of saccade target selection on visual working memory. These predictions were empirically confirmed in a new experiment: Memory for a sample color was biased toward the color of a task-irrelevant saccade target object, demonstrating the bidirectional coupling between visual working memory and perceptual processing. PMID:25228628

The mysteries of remote memory.

PubMed

Albo, Zimbul; Gräff, Johannes

2018-03-19

Long-lasting memories form the basis of our identity as individuals and lie central in shaping future behaviours that guide survival. Surprisingly, however, our current knowledge of how such memories are stored in the brain and retrieved, as well as the dynamics of the circuits involved, remains scarce despite seminal technical and experimental breakthroughs in recent years. Traditionally, it has been proposed that, over time, information initially learnt in the hippocampus is stored in distributed cortical networks. This process-the standard theory of memory consolidation-would stabilize the newly encoded information into a lasting memory, become independent of the hippocampus, and remain essentially unmodifiable throughout the lifetime of the individual. In recent years, several pieces of evidence have started to challenge this view and indicate that long-lasting memories might already ab ovo be encoded, and subsequently stored in distributed cortical networks, akin to the multiple trace theory of memory consolidation. In this review, we summarize these recent findings and attempt to identify the biologically plausible mechanisms based on which a contextual memory becomes remote by integrating different levels of analysis: from neural circuits to cell ensembles across synaptic remodelling and epigenetic modifications. From these studies, remote memory formation and maintenance appear to occur through a multi-trace, dynamic and integrative cellular process ranging from the synapse to the nucleus, and represent an exciting field of research primed to change quickly as new experimental evidence emerges.This article is part of a discussion meeting issue 'Of mice and mental health: facilitating dialogue between basic and clinical neuroscientists'. © 2018 The Authors.

Memory and Energy Optimization Strategies for Multithreaded Operating System on the Resource-Constrained Wireless Sensor Node

PubMed Central

Liu, Xing; Hou, Kun Mean; de Vaulx, Christophe; Xu, Jun; Yang, Jianfeng; Zhou, Haiying; Shi, Hongling; Zhou, Peng

2015-01-01

Memory and energy optimization strategies are essential for the resource-constrained wireless sensor network (WSN) nodes. In this article, a new memory-optimized and energy-optimized multithreaded WSN operating system (OS) LiveOS is designed and implemented. Memory cost of LiveOS is optimized by using the stack-shifting hybrid scheduling approach. Different from the traditional multithreaded OS in which thread stacks are allocated statically by the pre-reservation, thread stacks in LiveOS are allocated dynamically by using the stack-shifting technique. As a result, memory waste problems caused by the static pre-reservation can be avoided. In addition to the stack-shifting dynamic allocation approach, the hybrid scheduling mechanism which can decrease both the thread scheduling overhead and the thread stack number is also implemented in LiveOS. With these mechanisms, the stack memory cost of LiveOS can be reduced more than 50% if compared to that of a traditional multithreaded OS. Not is memory cost optimized, but also the energy cost is optimized in LiveOS, and this is achieved by using the multi-core “context aware” and multi-core “power-off/wakeup” energy conservation approaches. By using these approaches, energy cost of LiveOS can be reduced more than 30% when compared to the single-core WSN system. Memory and energy optimization strategies in LiveOS not only prolong the lifetime of WSN nodes, but also make the multithreaded OS feasible to run on the memory-constrained WSN nodes. PMID:25545264

The mysteries of remote memory

PubMed Central

2018-01-01

Long-lasting memories form the basis of our identity as individuals and lie central in shaping future behaviours that guide survival. Surprisingly, however, our current knowledge of how such memories are stored in the brain and retrieved, as well as the dynamics of the circuits involved, remains scarce despite seminal technical and experimental breakthroughs in recent years. Traditionally, it has been proposed that, over time, information initially learnt in the hippocampus is stored in distributed cortical networks. This process—the standard theory of memory consolidation—would stabilize the newly encoded information into a lasting memory, become independent of the hippocampus, and remain essentially unmodifiable throughout the lifetime of the individual. In recent years, several pieces of evidence have started to challenge this view and indicate that long-lasting memories might already ab ovo be encoded, and subsequently stored in distributed cortical networks, akin to the multiple trace theory of memory consolidation. In this review, we summarize these recent findings and attempt to identify the biologically plausible mechanisms based on which a contextual memory becomes remote by integrating different levels of analysis: from neural circuits to cell ensembles across synaptic remodelling and epigenetic modifications. From these studies, remote memory formation and maintenance appear to occur through a multi-trace, dynamic and integrative cellular process ranging from the synapse to the nucleus, and represent an exciting field of research primed to change quickly as new experimental evidence emerges. This article is part of a discussion meeting issue ‘Of mice and mental health: facilitating dialogue between basic and clinical neuroscientists’. PMID:29352028

Fast but fleeting: adaptive motor learning processes associated with aging and cognitive decline.

PubMed

Trewartha, Kevin M; Garcia, Angeles; Wolpert, Daniel M; Flanagan, J Randall

2014-10-01

Motor learning has been shown to depend on multiple interacting learning processes. For example, learning to adapt when moving grasped objects with novel dynamics involves a fast process that adapts and decays quickly-and that has been linked to explicit memory-and a slower process that adapts and decays more gradually. Each process is characterized by a learning rate that controls how strongly motor memory is updated based on experienced errors and a retention factor determining the movement-to-movement decay in motor memory. Here we examined whether fast and slow motor learning processes involved in learning novel dynamics differ between younger and older adults. In addition, we investigated how age-related decline in explicit memory performance influences learning and retention parameters. Although the groups adapted equally well, they did so with markedly different underlying processes. Whereas the groups had similar fast processes, they had different slow processes. Specifically, the older adults exhibited decreased retention in their slow process compared with younger adults. Within the older group, who exhibited considerable variation in explicit memory performance, we found that poor explicit memory was associated with reduced retention in the fast process, as well as the slow process. These findings suggest that explicit memory resources are a determining factor in impairments in the both the fast and slow processes for motor learning but that aging effects on the slow process are independent of explicit memory declines. Copyright © 2014 the authors 0270-6474/14/3413411-11$15.00/0.

Improving family medicine resident training in dementia care: an experiential learning opportunity in Primary Care Collaborative Memory Clinics.

PubMed

Lee, Linda; Weston, W Wayne; Hillier, Loretta; Archibald, Douglas; Lee, Joseph

2018-06-21

Family physicians often find themselves inadequately prepared to manage dementia. This article describes the curriculum for a resident training intervention in Primary Care Collaborative Memory Clinics (PCCMC), outlines its underlying educational principles, and examines its impact on residents' ability to provide dementia care. PCCMCs are family physician-led interprofessional clinic teams that provide evidence-informed comprehensive assessment and management of memory concerns. Within PCCMCs residents learn to apply a structured approach to assessment, diagnosis, and management; training consists of a tutorial covering various topics related to dementia followed by work-based learning within the clinic. Significantly more residents who trained in PCCMCs (sample = 98), as compared to those in usual training programs (sample = 35), reported positive changes in knowledge, ability, and confidence in ability to assess and manage memory problems. The PCCMC training intervention for family medicine residents provides a significant opportunity for residents to learn about best clinical practices and interprofessional care needed for optimal dementia care integrated within primary care practice.

An Investigation of Unified Memory Access Performance in CUDA

PubMed Central

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

2015-01-01

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

Application-Controlled Demand Paging for Out-of-Core Visualization

NASA Technical Reports Server (NTRS)

Cox, Michael; Ellsworth, David; Kutler, Paul (Technical Monitor)

1997-01-01

In the area of scientific visualization, input data sets are often very large. In visualization of Computational Fluid Dynamics (CFD) in particular, input data sets today can surpass 100 Gbytes, and are expected to scale with the ability of supercomputers to generate them. Some visualization tools already partition large data sets into segments, and load appropriate segments as they are needed. However, this does not remove the problem for two reasons: 1) there are data sets for which even the individual segments are too large for the largest graphics workstations, 2) many practitioners do not have access to workstations with the memory capacity required to load even a segment, especially since the state-of-the-art visualization tools tend to be developed by researchers with much more powerful machines. When the size of the data that must be accessed is larger than the size of memory, some form of virtual memory is simply required. This may be by segmentation, paging, or by paged segments. In this paper we demonstrate that complete reliance on operating system virtual memory for out-of-core visualization leads to poor performance. We then describe a paged segment system that we have implemented, and explore the principles of memory management that can be employed by the application for out-of-core visualization. We show that application control over some of these can significantly improve performance. We show that sparse traversal can be exploited by loading only those data actually required. We show also that application control over data loading can be exploited by 1) loading data from alternative storage format (in particular 3-dimensional data stored in sub-cubes), 2) controlling the page size. Both of these techniques effectively reduce the total memory required by visualization at run-time. We also describe experiments we have done on remote out-of-core visualization (when pages are read by demand from remote disk) whose results are promising.

Efficient Parallelization of a Dynamic Unstructured Application on the Tera MTA

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Biswas, Rupak

1999-01-01

The success of parallel computing in solving real-life computationally-intensive problems relies on their efficient mapping and execution on large-scale multiprocessor architectures. Many important applications are both unstructured and dynamic in nature, making their efficient parallel implementation a daunting task. This paper presents the parallelization of a dynamic unstructured mesh adaptation algorithm using three popular programming paradigms on three leading supercomputers. We examine an MPI message-passing implementation on the Cray T3E and the SGI Origin2OOO, a shared-memory implementation using cache coherent nonuniform memory access (CC-NUMA) of the Origin2OOO, and a multi-threaded version on the newly-released Tera Multi-threaded Architecture (MTA). We compare several critical factors of this parallel code development, including runtime, scalability, programmability, and memory overhead. Our overall results demonstrate that multi-threaded systems offer tremendous potential for quickly and efficiently solving some of the most challenging real-life problems on parallel computers.

Memory effects in stock price dynamics: evidences of technical trading

PubMed Central

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

2014-01-01

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

Memory effects in stock price dynamics: evidences of technical trading

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

Combining Distributed and Shared Memory Models: Approach and Evolution of the Global Arrays Toolkit

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

Nieplocha, Jarek; Harrison, Robert J.; Kumar, Mukul

2002-07-29

Both shared memory and distributed memory models have advantages and shortcomings. Shared memory model is much easier to use but it ignores data locality/placement. Given the hierarchical nature of the memory subsystems in the modern computers this characteristic might have a negative impact on performance and scalability. Various techniques, such as code restructuring to increase data reuse and introducing blocking in data accesses, can address the problem and yield performance competitive with message passing[Singh], however at the cost of compromising the ease of use feature. Distributed memory models such as message passing or one-sided communication offer performance and scalability butmore » they compromise the ease-of-use. In this context, the message-passing model is sometimes referred to as?assembly programming for the scientific computing?. The Global Arrays toolkit[GA1, GA2] attempts to offer the best features of both models. It implements a shared-memory programming model in which data locality is managed explicitly by the programmer. This management is achieved by explicit calls to functions that transfer data between a global address space (a distributed array) and local storage. In this respect, the GA model has similarities to the distributed shared-memory models that provide an explicit acquire/release protocol. However, the GA model acknowledges that remote data is slower to access than local data and allows data locality to be explicitly specified and hence managed. The GA model exposes to the programmer the hierarchical memory of modern high-performance computer systems, and by recognizing the communication overhead for remote data transfer, it promotes data reuse and locality of reference. This paper describes the characteristics of the Global Arrays programming model, capabilities of the toolkit, and discusses its evolution.« less

Modifying Memory: Selectively Enhancing and Updating Personal Memories for a Museum Tour by Reactivating Them

PubMed Central

St. Jacques, Peggy L.; Schacter, Daniel L.

2013-01-01

Memory can be modified when reactivated, but little is known about how the properties and extent of reactivation can selectively affect subsequent memory. We developed a novel museum paradigm to directly investigate reactivation-induced plasticity for personal memories. Participants reactivated memories triggered by photos taken from a camera they wore during a museum tour and made relatedness judgments on novel photos taken from a different tour of the same museum. Subsequent recognition memory for events at the museum was better for memories that were highly reactivated (i.e., the retrieval cues during reactivation matched the encoding experience) than for memories that were reactivated at a lower level (i.e., the retrieval cues during reactivation mismatched the encoding experience), but reactivation also increased false recognition of photographs depicting stops that were not experienced during the museum tour. Reactivation thus enables memories to be selectively enhanced and distorted via updating, thereby supporting the dynamic and flexible nature of memory. PMID:23406611

Community-based memorials to September 11, 2001: environmental stewardship as memory work

Treesearch

Erika S. Svendsen; Lindsay K. Campbell

2014-01-01

This chapter investigates how people use trees, parks, gardens, and other natural resources as raw materials in and settings for memorials to September 11, 2001. In particular, we focus on 'found space living memorials', which we define as sites that are community-managed, re-appropriated from their prior use, often carved out of the public right-of-way, and...

Membrane Capacitive Memory Alters Spiking in Neurons Described by the Fractional-Order Hodgkin-Huxley Model

PubMed Central

Weinberg, Seth H.

2015-01-01

Excitable cells and cell membranes are often modeled by the simple yet elegant parallel resistor-capacitor circuit. However, studies have shown that the passive properties of membranes may be more appropriately modeled with a non-ideal capacitor, in which the current-voltage relationship is given by a fractional-order derivative. Fractional-order membrane potential dynamics introduce capacitive memory effects, i.e., dynamics are influenced by a weighted sum of the membrane potential prior history. However, it is not clear to what extent fractional-order dynamics may alter the properties of active excitable cells. In this study, we investigate the spiking properties of the neuronal membrane patch, nerve axon, and neural networks described by the fractional-order Hodgkin-Huxley neuron model. We find that in the membrane patch model, as fractional-order decreases, i.e., a greater influence of membrane potential memory, peak sodium and potassium currents are altered, and spike frequency and amplitude are generally reduced. In the nerve axon, the velocity of spike propagation increases as fractional-order decreases, while in a neural network, electrical activity is more likely to cease for smaller fractional-order. Importantly, we demonstrate that the modulation of the peak ionic currents that occurs for reduced fractional-order alone fails to reproduce many of the key alterations in spiking properties, suggesting that membrane capacitive memory and fractional-order membrane potential dynamics are important and necessary to reproduce neuronal electrical activity. PMID:25970534

Information management in DNA replication modeled by directional, stochastic chains with memory

NASA Astrophysics Data System (ADS)

Arias-Gonzalez, J. Ricardo

2016-11-01

Stochastic chains represent a key variety of phenomena in many branches of science within the context of information theory and thermodynamics. They are typically approached by a sequence of independent events or by a memoryless Markov process. Stochastic chains are of special significance to molecular biology, where genes are conveyed by linear polymers made up of molecular subunits and transferred from DNA to proteins by specialized molecular motors in the presence of errors. Here, we demonstrate that when memory is introduced, the statistics of the chain depends on the mechanism by which objects or symbols are assembled, even in the slow dynamics limit wherein friction can be neglected. To analyze these systems, we introduce a sequence-dependent partition function, investigate its properties, and compare it to the standard normalization defined by the statistical physics of ensembles. We then apply this theory to characterize the enzyme-mediated information transfer involved in DNA replication under the real, non-equilibrium conditions, reproducing measured error rates and explaining the typical 100-fold increase in fidelity that is experimentally found when proofreading and edition take place. Our model further predicts that approximately 1 kT has to be consumed to elevate fidelity in one order of magnitude. We anticipate that our results are necessary to interpret configurational order and information management in many molecular systems within biophysics, materials science, communication, and engineering.

PERK Regulates Working Memory and Protein Synthesis-Dependent Memory Flexibility

PubMed Central

Zhu, Siying; Henninger, Keely; McGrath, Barbara C.; Cavener, Douglas R.

2016-01-01

PERK (EIF2AK3) is an ER-resident eIF2α kinase required for memory flexibility and metabotropic glutamate receptor-dependent long-term depression, processes known to be dependent on new protein synthesis. Here we investigated PERK’s role in working memory, a cognitive ability that is independent of new protein synthesis, but instead is dependent on cellular Ca2+ dynamics. We found that working memory is impaired in forebrain-specific Perk knockout and pharmacologically PERK-inhibited mice. Moreover, inhibition of PERK in wild-type mice mimics the fear extinction impairment observed in forebrain-specific Perk knockout mice. Our findings reveal a novel role of PERK in cognitive functions and suggest that PERK regulates both Ca2+ -dependent working memory and protein synthesis-dependent memory flexibility. PMID:27627766

Brain-Based Devices for Neuromorphic Computer Systems

DTIC Science & Technology

2013-07-01

and Deco, G. (2012). Effective Visual Working Memory Capacity: An Emergent Effect from the Neural Dynamics in an Attractor Network. PLoS ONE 7, e42719...models, apply them to a recognition task, and to demonstrate a working memory . In the course of this work a new analytical method for spiking data was...4 3.4 Spiking Neural Model Simulation of Working Memory ..................................... 5 3.5 A Novel Method for Analysis

Dynamic burstiness of word-occurrence and network modularity in textbook systems

NASA Astrophysics Data System (ADS)

Cui, Xue-Mei; Yoon, Chang No; Youn, Hyejin; Lee, Sang Hoon; Jung, Jean S.; Han, Seung Kee

2017-12-01

We show that the dynamic burstiness of word occurrence in textbook systems is attributed to the modularity of the word association networks. At first, a measure of dynamic burstiness is introduced to quantify burstiness of word occurrence in a textbook. The advantage of this measure is that the dynamic burstiness is decomposable into two contributions: one coming from the inter-event variance and the other from the memory effects. Comparing network structures of physics textbook systems with those of surrogate random textbooks without the memory or variance effects are absent, we show that the network modularity increases systematically with the dynamic burstiness. The intra-connectivity of individual word representing the strength of a tie with which a node is bound to a module accordingly increases with the dynamic burstiness, suggesting individual words with high burstiness are strongly bound to one module. Based on the frequency and dynamic burstiness, physics terminology is classified into four categories: fundamental words, topical words, special words, and common words. In addition, we test the correlation between the dynamic burstiness of word occurrence and network modularity using a two-state model of burst generation.

Fame emerges as a result of small memory

NASA Astrophysics Data System (ADS)

Bingol, Haluk

2008-03-01

A dynamic memory model is proposed in which an agent “learns” a new agent by means of recommendation. The agents can also “remember” and “forget.” The memory size is decreased while the population size is kept constant. “Fame” emerged as a few agents become very well known in expense of the majority being completely forgotten. The minimum and the maximum of fame change linearly with the relative memory size. The network properties of the who-knows-who graph, which represents the state of the system, are investigated.

Architectural design and simulation of a virtual memory

NASA Technical Reports Server (NTRS)

Kwok, G.; Chu, Y.

1971-01-01

Virtual memory is an imaginary main memory with a very large capacity which the programmer has at his disposal. It greatly contributes to the solution of the dynamic storage allocation problem. The architectural design of a virtual memory is presented which implements by hardware the idea of queuing and scheduling the page requests to a paging drum in such a way that the access of the paging drum is increased many times. With the design, an increase of up to 16 times in page transfer rate is achievable when the virtual memory is heavily loaded. This in turn makes feasible a great increase in the system throughput.

Fabry-Perot confocal resonator optical associative memory

NASA Astrophysics Data System (ADS)

Burns, Thomas J.; Rogers, Steven K.; Vogel, George A.

1993-03-01

A unique optical associative memory architecture is presented that combines the optical processing environment of a Fabry-Perot confocal resonator with the dynamic storage and recall properties of volume holograms. The confocal resonator reduces the size and complexity of previous associative memory architectures by folding a large number of discrete optical components into an integrated, compact optical processing environment. Experimental results demonstrate the system is capable of recalling a complete object from memory when presented with partial information about the object. A Fourier optics model of the system's operation shows it implements a spatially continuous version of a discrete, binary Hopfield neural network associative memory.

Emulating short-term synaptic dynamics with memristive devices

NASA Astrophysics Data System (ADS)

Berdan, Radu; Vasilaki, Eleni; Khiat, Ali; Indiveri, Giacomo; Serb, Alexandru; Prodromakis, Themistoklis

2016-01-01

Neuromorphic architectures offer great promise for achieving computation capacities beyond conventional Von Neumann machines. The essential elements for achieving this vision are highly scalable synaptic mimics that do not undermine biological fidelity. Here we demonstrate that single solid-state TiO2 memristors can exhibit non-associative plasticity phenomena observed in biological synapses, supported by their metastable memory state transition properties. We show that, contrary to conventional uses of solid-state memory, the existence of rate-limiting volatility is a key feature for capturing short-term synaptic dynamics. We also show how the temporal dynamics of our prototypes can be exploited to implement spatio-temporal computation, demonstrating the memristors full potential for building biophysically realistic neural processing systems.

Dynamic Neuroplasticity after Human Prefrontal Cortex Damage

PubMed Central

Voytek, Bradley; Davis, Matar; Yago, Elena; Barceló, Francisco; Vogel, Edward K.; Knight, Robert T.

2010-01-01

Summary Memory and attention deficits are common after prefrontal cortex (PFC) damage, yet people generally recover some function over time. Recovery is thought to be dependent upon undamaged brain regions but the temporal dynamics underlying cognitive recovery are poorly understood. Here we provide evidence that the intact PFC compensates for damage in the lesioned PFC on a trial-by-trial basis dependent on cognitive load. The extent of this rapid functional compensation is indexed by transient increases in electrophysiological measures of attention and memory in the intact PFC, detectable within a second after stimulus presentation and only when the lesioned hemisphere is challenged. These observations provide evidence supporting a dynamic and flexible model of compensatory neural plasticity. PMID:21040843

Learning to recognize objects on the fly: a neurally based dynamic field approach.

PubMed

Faubel, Christian; Schöner, Gregor

2008-05-01

Autonomous robots interacting with human users need to build and continuously update scene representations. This entails the problem of rapidly learning to recognize new objects under user guidance. Based on analogies with human visual working memory, we propose a dynamical field architecture, in which localized peaks of activation represent objects over a small number of simple feature dimensions. Learning consists of laying down memory traces of such peaks. We implement the dynamical field model on a service robot and demonstrate how it learns 30 objects from a very small number of views (about 5 per object are sufficient). We also illustrate how properties of feature binding emerge from this framework.

An Efficient Means of Adaptive Refinement Within Systems of Overset Grids

NASA Technical Reports Server (NTRS)

Meakin, Robert L.

1996-01-01

An efficient means of adaptive refinement within systems of overset grids is presented. Problem domains are segregated into near-body and off-body fields. Near-body fields are discretized via overlapping body-fitted grids that extend only a short distance from body surfaces. Off-body fields are discretized via systems of overlapping uniform Cartesian grids of varying levels of refinement. a novel off-body grid generation and management scheme provides the mechanism for carrying out adaptive refinement of off-body flow dynamics and solid body motion. The scheme allows for very efficient use of memory resources, and flow solvers and domain connectivity routines that can exploit the structure inherent to uniform Cartesian grids.

Dynamism in Electronic Performance Support Systems.

ERIC Educational Resources Information Center

Laffey, James

1995-01-01

Describes a model for dynamic electronic performance support systems based on NNAble, a system developed by the training group at Apple Computer. Principles for designing dynamic performance support are discussed, including a systems approach, performer-centered design, awareness of situated cognition, organizational memory, and technology use.…

Interference due to shared features between action plans is influenced by working memory span.

PubMed

Fournier, Lisa R; Behmer, Lawrence P; Stubblefield, Alexandra M

2014-12-01

In this study, we examined the interactions between the action plans that we hold in memory and the actions that we carry out, asking whether the interference due to shared features between action plans is due to selection demands imposed on working memory. Individuals with low and high working memory spans learned arbitrary motor actions in response to two different visual events (A and B), presented in a serial order. They planned a response to the first event (A) and while maintaining this action plan in memory they then executed a speeded response to the second event (B). Afterward, they executed the action plan for the first event (A) maintained in memory. Speeded responses to the second event (B) were delayed when it shared an action feature (feature overlap) with the first event (A), relative to when it did not (no feature overlap). The size of the feature-overlap delay was greater for low-span than for high-span participants. This indicates that interference due to overlapping action plans is greater when fewer working memory resources are available, suggesting that this interference is due to selection demands imposed on working memory. Thus, working memory plays an important role in managing current and upcoming action plans, at least for newly learned tasks. Also, managing multiple action plans is compromised in individuals who have low versus high working memory spans.

Retrieval Demands Adaptively Change Striatal Old/New Signals and Boost Subsequent Long-Term Memory.

PubMed

Herweg, Nora A; Sommer, Tobias; Bunzeck, Nico

2018-01-17

The striatum is a central part of the dopaminergic mesolimbic system and contributes both to the encoding and retrieval of long-term memories. In this regard, the co-occurrence of striatal novelty and retrieval success effects in independent studies underlines the structure's double duty and suggests dynamic contextual adaptation. To test this hypothesis and further investigate the underlying mechanisms of encoding and retrieval dynamics, human subjects viewed pre-familiarized scene images intermixed with new scenes and classified them as indoor versus outdoor (encoding task) or old versus new (retrieval task), while fMRI and eye tracking data were recorded. Subsequently, subjects performed a final recognition task. As hypothesized, striatal activity and pupil size reflected task-conditional salience of old and new stimuli, but, unexpectedly, this effect was not reflected in the substantia nigra and ventral tegmental area (SN/VTA), medial temporal lobe, or subsequent memory performance. Instead, subsequent memory generally benefitted from retrieval, an effect possibly driven by task difficulty and activity in a network including different parts of the striatum and SN/VTA. Our findings extend memory models of encoding and retrieval dynamics by pinpointing a specific contextual factor that differentially modulates the functional properties of the mesolimbic system. SIGNIFICANCE STATEMENT The mesolimbic system is involved in the encoding and retrieval of information but it is unclear how these two processes are achieved within the same network of brain regions. In particular, memory retrieval and novelty encoding were considered in independent studies, implying that novelty (new > old) and retrieval success (old > new) effects may co-occur in the striatum. Here, we used a common framework implicating the striatum, but not other parts of the mesolimbic system, in tracking context-dependent salience of old and new information. The current study, therefore, paves the way for a more comprehensive understanding of the functional properties of the mesolimbic system during memory encoding and retrieval. Copyright © 2018 the authors 0270-6474/18/380745-10$15.00/0.

Field enhanced charge carrier reconfiguration in electronic and ionic coupled dynamic polymer resistive memory.

PubMed

Zhao, Jun Hui; Thomson, Douglas J; Pilapil, Matt; Pillai, Rajesh G; Rahman, G M Aminur; Freund, Michael S

2010-04-02

Dynamic resistive memory devices based on a conjugated polymer composite (PPy(0)DBS(-)Li(+) (PPy: polypyrrole; DBS(-): dodecylbenzenesulfonate)), with field-driven ion migration, have been demonstrated. In this work the dynamics of these systems has been investigated and it has been concluded that increasing the applied field can dramatically increase the rate at which information can be 'written' into these devices. A conductance model using space charge limited current coupled with an electric field induced ion reconfiguration has been successfully utilized to interpret the experimentally observed transient conducting behaviors. The memory devices use the rising and falling transient current states for the storage of digital states. The magnitude of these transient currents is controlled by the magnitude and width of the write/read pulse. For the 500 nm length devices used in this work an increase in 'write' potential from 2.5 to 5.5 V decreased the time required to create a transient conductance state that can be converted into the digital signal by 50 times. This work suggests that the scaling of these devices will be favorable and that 'write' times for the conjugated polymer composite memory devices will decrease rapidly as ion driving fields increase with decreasing device size.

Experiments and Analyses of Data Transfers Over Wide-Area Dedicated Connections

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

Rao, Nageswara S.; Liu, Qiang; Sen, Satyabrata

Dedicated wide-area network connections are increasingly employed in high-performance computing and big data scenarios. One might expect the performance and dynamics of data transfers over such connections to be easy to analyze due to the lack of competing traffic. However, non-linear transport dynamics and end-system complexities (e.g., multi-core hosts and distributed filesystems) can in fact make analysis surprisingly challenging. We present extensive measurements of memory-to-memory and disk-to-disk file transfers over 10 Gbps physical and emulated connections with 0–366 ms round trip times (RTTs). For memory-to-memory transfers, profiles of both TCP and UDT throughput as a function of RTT show concavemore » and convex regions; large buffer sizes and more parallel flows lead to wider concave regions, which are highly desirable. TCP and UDT both also display complex throughput dynamics, as indicated by their Poincare maps and Lyapunov exponents. For disk-to-disk transfers, we determine that high throughput can be achieved via a combination of parallel I/O threads, parallel network threads, and direct I/O mode. Our measurements also show that Lustre filesystems can be mounted over long-haul connections using LNet routers, although challenges remain in jointly optimizing file I/O and transport method parameters to achieve peak throughput.« less

Cannabinoids disrupt memory encoding by functionally isolating hippocampal CA1 from CA3.

PubMed

Sandler, Roman A; Fetterhoff, Dustin; Hampson, Robert E; Deadwyler, Sam A; Marmarelis, Vasilis Z

2017-07-01

Much of the research on cannabinoids (CBs) has focused on their effects at the molecular and synaptic level. However, the effects of CBs on the dynamics of neural circuits remains poorly understood. This study aims to disentangle the effects of CBs on the functional dynamics of the hippocampal Schaffer collateral synapse by using data-driven nonparametric modeling. Multi-unit activity was recorded from rats doing an working memory task in control sessions and under the influence of exogenously administered tetrahydrocannabinol (THC), the primary CB found in marijuana. It was found that THC left firing rate unaltered and only slightly reduced theta oscillations. Multivariate autoregressive models, estimated from spontaneous spiking activity, were then used to describe the dynamical transformation from CA3 to CA1. They revealed that THC served to functionally isolate CA1 from CA3 by reducing feedforward excitation and theta information flow. The functional isolation was compensated by increased feedback excitation within CA1, thus leading to unaltered firing rates. Finally, both of these effects were shown to be correlated with memory impairments in the working memory task. By elucidating the circuit mechanisms of CBs, these results help close the gap in knowledge between the cellular and behavioral effects of CBs.

The dynamics of access to groups in working memory.

PubMed

Farrell, Simon; Lelièvre, Anna

2012-11-01

The finding that participants leave a pause between groups when attempting serial recall of temporally grouped lists has been taken to indicate access to a hierarchical representation of the list in working memory. An alternative explanation is that the dynamics of serial recall solely reflect output (rather than memorial) processes, with the temporal pattern at input merely suggesting a basis for the pattern of output buffering. Three experiments are presented here that disentangle input structure from output buffering in serial recall. In Experiment 1, participants were asked to recall a subset of visually presented digits from a temporally grouped list in their original order, where either within-group position or group position was kept constant. In Experiment 2, participants performed more standard serial recall of spoken digits, and input and output position were dissociated by asking participants to initiate recall from a post-cued position in the list. In Experiment 3, participants were asked to serially recall temporally grouped lists of visually presented digits where the grouping structure was unpredictable, under either articulatory suppression or silent conditions. The 3 experiments point to a tight linkage between implied memorial structures (i.e., the pattern of grouping at encoding) and the output structure implied by retrieval times and call into question a purely motoric account of the dynamics of recall.

Cannabinoids disrupt memory encoding by functionally isolating hippocampal CA1 from CA3

PubMed Central

Fetterhoff, Dustin; Hampson, Robert E.; Deadwyler, Sam A.; Marmarelis, Vasilis Z.

2017-01-01

Much of the research on cannabinoids (CBs) has focused on their effects at the molecular and synaptic level. However, the effects of CBs on the dynamics of neural circuits remains poorly understood. This study aims to disentangle the effects of CBs on the functional dynamics of the hippocampal Schaffer collateral synapse by using data-driven nonparametric modeling. Multi-unit activity was recorded from rats doing an working memory task in control sessions and under the influence of exogenously administered tetrahydrocannabinol (THC), the primary CB found in marijuana. It was found that THC left firing rate unaltered and only slightly reduced theta oscillations. Multivariate autoregressive models, estimated from spontaneous spiking activity, were then used to describe the dynamical transformation from CA3 to CA1. They revealed that THC served to functionally isolate CA1 from CA3 by reducing feedforward excitation and theta information flow. The functional isolation was compensated by increased feedback excitation within CA1, thus leading to unaltered firing rates. Finally, both of these effects were shown to be correlated with memory impairments in the working memory task. By elucidating the circuit mechanisms of CBs, these results help close the gap in knowledge between the cellular and behavioral effects of CBs. PMID:28686594

A Dynamical Systems Explanation of the Hurst Effect and Atmospheric Low-Frequency Variability

PubMed Central

Franzke, Christian L. E.; Osprey, Scott M.; Davini, Paolo; Watkins, Nicholas W.

2015-01-01

The Hurst effect plays an important role in many areas such as physics, climate and finance. It describes the anomalous growth of range and constrains the behavior and predictability of these systems. The Hurst effect is frequently taken to be synonymous with Long-Range Dependence (LRD) and is typically assumed to be produced by a stationary stochastic process which has infinite memory. However, infinite memory appears to be at odds with the Markovian nature of most physical laws while the stationarity assumption lacks robustness. Here we use Lorenz's paradigmatic chaotic model to show that regime behavior can also cause the Hurst effect. By giving an alternative, parsimonious, explanation using nonstationary Markovian dynamics, our results question the common belief that the Hurst effect necessarily implies a stationary infinite memory process. We also demonstrate that our results can explain atmospheric variability without the infinite memory previously thought necessary and are consistent with climate model simulations. PMID:25765880

Multiple-object permanence tracking: limitation in maintenance and transformation of perceptual objects.

PubMed

Saiki, Jun

2002-01-01

Research on change blindness and transsaccadic memory revealed that a limited amount of information is retained across visual disruptions in visual working memory. It has been proposed that visual working memory can hold four to five coherent object representations. To investigate their maintenance and transformation in dynamic situations, I devised an experimental paradigm called multiple-object permanence tracking (MOPT) that measures memory for multiple feature-location bindings in dynamic situations. Observers were asked to detect any color switch in the middle of a regular rotation of a pattern with multiple colored disks behind an occluder. The color-switch detection performance dramatically declined as the pattern rotation velocity increased, and this effect of object motion was independent of the number of targets. The MOPT task with various shapes and colors showed that color-shape conjunctions are not available in the MOPT task. These results suggest that even completely predictable motion severely reduces our capacity of object representations, from four to only one or two.

Working memory capacity and retrieval limitations from long-term memory: an examination of differences in accessibility.

PubMed

Unsworth, Nash; Spillers, Gregory J; Brewer, Gene A

2012-01-01

In two experiments, the locus of individual differences in working memory capacity and long-term memory recall was examined. Participants performed categorical cued and free recall tasks, and individual differences in the dynamics of recall were interpreted in terms of a hierarchical-search framework. The results from this study are in accordance with recent theorizing suggesting a strong relation between working memory capacity and retrieval from long-term memory. Furthermore, the results also indicate that individual differences in categorical recall are partially due to differences in accessibility. In terms of accessibility of target information, two important factors drive the difference between high- and low-working-memory-capacity participants. Low-working-memory-capacity participants fail to utilize appropriate retrieval strategies to access cues, and they also have difficulty resolving cue overload. Thus, when low-working-memory-capacity participants were given specific cues that activated a smaller set of potential targets, their recall performance was the same as that of high-working-memory-capacity participants.

A Putative Biochemical Engram of Long-term Memory

PubMed Central

Li, Liying; Sanchez, Consuelo Perez; Slaughter, Brian D.; Zhao, Yubai; Khan, Mohammed Repon; Unruh, Jay R.; Rubinstein, Boris; Si, Kausik

2016-01-01

Summary How a transient experience creates an enduring yet dynamic memory remains an unresolved issue in studies of memory. Experience-dependent aggregation of the RNA-binding protein CPEB/Orb2 is one of the candidate mechanisms of memory maintenance. Here, using tools that allow rapid and reversible inactivation of Orb2 protein in neurons we find that Orb2 activity is required for encoding and recall of memory. From a screen we have identified a DNA-J family chaperone, JJJ2, which facilitates Orb2 aggregation, and ectopic expression of JJJ2 enhances the animal’s capacity to form long-term memory. Finally, we have developed tools to visualize training-dependent aggregation of Orb2. We find that aggregated Orb2 in a subset of mushroom body neurons can serve as a “molecular signature” of memory and predict memory strength. Our data indicates that self-sustaining aggregates of Orb2 may serve as a physical substrate of memory and provide a molecular basis for the perduring yet malleable nature of memory. PMID:27818176

Memory retrieval and the passage of time: from reconsolidation and strengthening to extinction

PubMed Central

Inda, Maria Carmen; Muravieva, Elizaveta V.; Alberini, Cristina M.

2011-01-01

An established memory can be made transiently labile if retrieved or reactivated. Over time, it becomes again resistant to disruption and this process that renders the memory stable is termed reconsolidation. The reasons why a memory becomes labile after retrieval and reconsolidates still remains debated. Here, using inhibitory avoidance (IA) learning in rats, we provide evidence that retrievals of a young memory, which are accompanied by its reconsolidation, result in memory strengthening and contribute to its overall consolidation. This function associated to reconsolidation is temporally limited. With the passage of time, the stored memory undergoes important changes, as revealed by the behavioral outcomes of its retrieval. Over time, without explicit retrievals, memory first strengthens and becomes refractory to both retrieval-dependent interference and strengthening. At later times, the same retrievals that lead to reconsolidation of a young memory extinguish an older memory. We conclude that the storage of information is very dynamic and that its temporal evolution regulates behavioral outcomes. These results are important for potential clinical applications. PMID:21289172

Teuchos C++ memory management classes, idioms, and related topics, the complete reference : a comprehensive strategy for safe and efficient memory management in C++ for high performance computing.

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

Bartlett, Roscoe Ainsworth

2010-05-01

The ubiquitous use of raw pointers in higher-level code is the primary cause of all memory usage problems and memory leaks in C++ programs. This paper describes what might be considered a radical approach to the problem which is to encapsulate the use of all raw pointers and all raw calls to new and delete in higher-level C++ code. Instead, a set of cooperating template classes developed in the Trilinos package Teuchos are used to encapsulate every use of raw C++ pointers in every use case where it appears in high-level code. Included in the set of memory management classesmore » is the typical reference-counted smart pointer class similar to boost::shared ptr (and therefore C++0x std::shared ptr). However, what is missing in boost and the new standard library are non-reference counted classes for remaining use cases where raw C++ pointers would need to be used. These classes have a debug build mode where nearly all programmer errors are caught and gracefully reported at runtime. The default optimized build mode strips all runtime checks and allows the code to perform as efficiently as raw C++ pointers with reasonable usage. Also included is a novel approach for dealing with the circular references problem that imparts little extra overhead and is almost completely invisible to most of the code (unlike the boost and therefore C++0x approach). Rather than being a radical approach, encapsulating all raw C++ pointers is simply the logical progression of a trend in the C++ development and standards community that started with std::auto ptr and is continued (but not finished) with std::shared ptr in C++0x. Using the Teuchos reference-counted memory management classes allows one to remove unnecessary constraints in the use of objects by removing arbitrary lifetime ordering constraints which are a type of unnecessary coupling [23]. The code one writes with these classes will be more likely to be correct on first writing, will be less likely to contain silent (but deadly) memory usage errors, and will be much more robust to later refactoring and maintenance. The level of debug-mode runtime checking provided by the Teuchos memory management classes is stronger in many respects than what is provided by memory checking tools like Valgrind and Purify while being much less expensive. However, tools like Valgrind and Purify perform a number of types of checks (like usage of uninitialized memory) that makes these tools very valuable and therefore complement the Teuchos memory management debug-mode runtime checking. The Teuchos memory management classes and idioms largely address the technical issues in resolving the fragile built-in C++ memory management model (with the exception of circular references which has no easy solution but can be managed as discussed). All that remains is to teach these classes and idioms and expand their usage in C++ codes. The long-term viability of C++ as a usable and productive language depends on it. Otherwise, if C++ is no safer than C, then is the greater complexity of C++ worth what one gets as extra features? Given that C is smaller and easier to learn than C++ and since most programmers don't know object-orientation (or templates or X, Y, and Z features of C++) all that well anyway, then what really are most programmers getting extra out of C++ that would outweigh the extra complexity of C++ over C? C++ zealots will argue this point but the reality is that C++ popularity has peaked and is becoming less popular while the popularity of C has remained fairly stable over the last decade22. Idioms like are advocated in this paper can help to avert this trend but it will require wide community buy-in and a change in the way C++ is taught in order to have the greatest impact. To make these programs more secure, compiler vendors or static analysis tools (e.g. klocwork23) could implement a preprocessor-like language similar to OpenMP24 that would allow the programmer to declare (in comments) that certain blocks of code should be ''pointer-free'' or allow smaller blocks to be 'pointers allowed'. This would significantly improve the robustness of code that uses the memory management classes described here.« less

Real-Time Rocket/Vehicle System Integrated Health Management Laboratory For Development and Testing of Health Monitoring/Management Systems

NASA Technical Reports Server (NTRS)

Aguilar, R.

2006-01-01

Pratt & Whitney Rocketdyne has developed a real-time engine/vehicle system integrated health management laboratory, or testbed, for developing and testing health management system concepts. This laboratory simulates components of an integrated system such as the rocket engine, rocket engine controller, vehicle or test controller, as well as a health management computer on separate general purpose computers. These general purpose computers can be replaced with more realistic components such as actual electronic controllers and valve actuators for hardware-in-the-loop simulation. Various engine configurations and propellant combinations are available. Fault or failure insertion capability on-the-fly using direct memory insertion from a user console is used to test system detection and response. The laboratory is currently capable of simulating the flow-path of a single rocket engine but work is underway to include structural and multiengine simulation capability as well as a dedicated data acquisition system. The ultimate goal is to simulate as accurately and realistically as possible the environment in which the health management system will operate including noise, dynamic response of the engine/engine controller, sensor time delays, and asynchronous operation of the various components. The rationale for the laboratory is also discussed including limited alternatives for demonstrating the effectiveness and safety of a flight system.

Robust dynamical decoupling for quantum computing and quantum memory.

PubMed

Souza, Alexandre M; Alvarez, Gonzalo A; Suter, Dieter

2011-06-17

Dynamical decoupling (DD) is a popular technique for protecting qubits from the environment. However, unless special care is taken, experimental errors in the control pulses used in this technique can destroy the quantum information instead of preserving it. Here, we investigate techniques for making DD sequences robust against different types of experimental errors while retaining good decoupling efficiency in a fluctuating environment. We present experimental data from solid-state nuclear spin qubits and introduce a new DD sequence that is suitable for quantum computing and quantum memory.

Cholinergic manipulations bidirectionally regulate object memory destabilization

PubMed Central

Stiver, Mikaela L.; Jacklin, Derek L.; Mitchnick, Krista A.; Vicic, Nevena; Carlin, Justine; O'Hara, Matthew

2015-01-01

Consolidated memories can become destabilized and open to modification upon retrieval. Destabilization is most reliably prompted when novel information is present during memory reactivation. We hypothesized that the neurotransmitter acetylcholine (ACh) plays an important role in novelty-induced memory destabilization because of its established involvement in new learning. Accordingly, we investigated the effects of cholinergic manipulations in rats using an object recognition paradigm that requires reactivation novelty to destabilize object memories. The muscarinic receptor antagonist scopolamine, systemically or infused directly into the perirhinal cortex, blocked this novelty-induced memory destabilization. Conversely, systemic oxotremorine or carbachol, muscarinic receptor agonists, administered systemically or intraperirhinally, respectively, mimicked the destabilizing effect of novel information during reactivation. These bidirectional effects suggest a crucial influence of ACh on memory destabilization and the updating functions of reconsolidation. This is a hitherto unappreciated mnemonic role for ACh with implications for its potential involvement in cognitive flexibility and the dynamic process of long-term memory storage. PMID:25776038

A semi-floating gate memory based on van der Waals heterostructures for quasi-non-volatile applications

NASA Astrophysics Data System (ADS)

Liu, Chunsen; Yan, Xiao; Song, Xiongfei; Ding, Shijin; Zhang, David Wei; Zhou, Peng

2018-05-01

As conventional circuits based on field-effect transistors are approaching their physical limits due to quantum phenomena, semi-floating gate transistors have emerged as an alternative ultrafast and silicon-compatible technology. Here, we show a quasi-non-volatile memory featuring a semi-floating gate architecture with band-engineered van der Waals heterostructures. This two-dimensional semi-floating gate memory demonstrates 156 times longer refresh time with respect to that of dynamic random access memory and ultrahigh-speed writing operations on nanosecond timescales. The semi-floating gate architecture greatly enhances the writing operation performance and is approximately 106 times faster than other memories based on two-dimensional materials. The demonstrated characteristics suggest that the quasi-non-volatile memory has the potential to bridge the gap between volatile and non-volatile memory technologies and decrease the power consumption required for frequent refresh operations, enabling a high-speed and low-power random access memory.

Influence of personality and neuropsychological ability on social functioning and self-management in bipolar disorder.

PubMed

Vierck, Esther; Joyce, Peter R

2015-10-30

A majority of bipolar patients (BD) show functional difficulties even in remission. In recent years cognitive functions and personality characteristics have been associated with occupational and psychosocial outcomes, but findings are not consistent. We assessed personality and cognitive functioning through a range of tests in BD and control participants. Three cognitive domains-verbal memory, facial-executive, and spatial memory-were extracted by principal component analysis. These factors and selected personality dimensions were included in hierarchical regression analysis to predict psychosocial functioning and the use of self-management strategies while controlling for mood status. The best determinants of good psychosocial functioning were good verbal memory and high self-directedness. The use of self-management techniques was associated with a low level of harm-avoidance. Our findings indicate that strategies to improve memory and self-directedness may be useful for increasing functioning in individuals with bipolar disorder. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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

Edwards, Harold C.; Ibanez, Daniel Alejandro

This report documents the ASC/ATDM Kokkos deliverable "Production Portable Dy- namic Task DAG Capability." This capability enables applications to create and execute a dynamic task DAG ; a collection of heterogeneous computational tasks with a directed acyclic graph (DAG) of "execute after" dependencies where tasks and their dependencies are dynamically created and destroyed as tasks execute. The Kokkos task scheduler executes the dynamic task DAG on the target execution resource; e.g. a multicore CPU, a manycore CPU such as Intel's Knights Landing (KNL), or an NVIDIA GPU. Several major technical challenges had to be addressed during development of Kokkos' Taskmore » DAG capability: (1) portability to a GPU with it's simplified hardware and micro- runtime, (2) thread-scalable memory allocation and deallocation from a bounded pool of memory, (3) thread-scalable scheduler for dynamic task DAG, (4) usability by applications.« less

Enhanced oscillatory activity in the hippocampal-prefrontal network is related to short-term memory function after early-life seizures

PubMed Central

Kleen, Jonathan K.; Wu, Edie X.; Holmes, Gregory L.; Scott, Rod C.; Lenck-Santini, Pierre-Pascal

2011-01-01

Neurological insults during development are associated with later impairments in learning and memory. Although remedial training can help restore cognitive function, the neural mechanisms of this recovery in memory systems are largely unknown. To examine this issue we measured electrophysiological oscillatory activity in the hippocampus (both CA3 and CA1) and prefrontal cortex of adult rats that had experienced repeated seizures in the first weeks of life, while they were remedially trained on a delayed-nonmatch-to-sample memory task. Seizure-exposed rats showed initial difficulties learning the task but performed similar to control rats after extra training. Whole-session analyses illustrated enhanced theta power in all three structures while seizure rats learned response tasks prior to the memory task. Whilst performing the memory task, dynamic oscillation patterns revealed that prefrontal cortex theta power was increased among seizure-exposed rats. This enhancement appeared after the first memory training steps using short delays and plateaued at the most difficult steps which included both short and long delays. Further, seizure rats showed enhanced CA1-prefrontal theta coherence in correct trials compared to incorrect trials when long delays were imposed, suggesting increased hippocampal-prefrontal synchrony for the task in this group when memory demand was high. Seizure-exposed rats also showed heightened gamma power and coherence among all three structures during the trials. Our results demonstrate the first evidence of hippocampal-prefrontal enhancements following seizures in early development. Dynamic compensatory changes in this network and interconnected circuits may underpin cognitive rehabilitation following other neurological insults to higher cognitive systems. PMID:22031886

Dynamic phenotypic restructuring of the CD4 and CD8 T-cell subsets with age in healthy humans: a compartmental model analysis.

PubMed

Jackola, D R; Hallgren, H M

1998-11-16

In healthy humans, phenotypic restructuring occurs with age within the CD3+ T-lymphocyte complement. This is characterized by a non-linear decrease of the percentage of 'naive' (CD45RA+) cells and a corresponding non-linear increase of the percentage of 'memory' (CD45R0+) cells among both the CD4+ and CD8+ T-cell subsets. We devised a simple compartmental model to study the age-dependent kinetics of phenotypic restructuring. We also derived differential equations whose parameters determined yearly gains minus losses of the percentage and absolute numbers of circulating naive cells, yearly gains minus losses of the percentage and absolute numbers of circulating memory cells, and the yearly rate of conversion of naive to memory cells. Solutions of these evaluative differential equations demonstrate the following: (1) the memory cell complement 'resides' within its compartment for a longer time than the naive cell complement within its compartment for both CD4 and CD8 cells; (2) the average, annual 'turnover rate' is the same for CD4 and CD8 naive cells. In contrast, the average, annual 'turnover rate' for memory CD8 cells is 1.5 times that of memory CD4 cells; (3) the average, annual conversion rate of CD4 naive cells to memory cells is twice that of the CD8 conversion rate; (4) a transition in dynamic restructuring occurs during the third decade of life that is due to these differences in turnover and conversion rates, between and from naive to memory cells.

Associative memory in phasing neuron networks

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

Nair, Niketh S; Bochove, Erik J.; Braiman, Yehuda

2014-01-01

We studied pattern formation in a network of coupled Hindmarsh-Rose model neurons and introduced a new model for associative memory retrieval using networks of Kuramoto oscillators. Hindmarsh-Rose Neural Networks can exhibit a rich set of collective dynamics that can be controlled by their connectivity. Specifically, we showed an instance of Hebb's rule where spiking was correlated with network topology. Based on this, we presented a simple model of associative memory in coupled phase oscillators.

76 FR 24409 - Proposed Amendment of Class E Airspace; Ava, MO

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-02

...) at Bill Martin Memorial Airport, Ava, MO, has made this action necessary for the safety and management of Instrument Flight Rules (IFR) operations at Bill Martin Memorial Airport. DATES: Comments must... from 700 feet above the surface for standard instrument approach procedures at Bill Martin Memorial...

A Hardware Platform for Characterizing and Validating 1-Dimensional Optical Systems

DTIC Science & Technology

2014-09-01

principle laboratory experiments, a bread -board sensor and data collection system was created to gather fuze data to postprocess after the event...merely differentiates this bistable memory category from dynamic random access memory [RAM], which must be periodically refreshed to retain data.) A

Kinetic memory based on the enzyme-limited competition.

PubMed

Hatakeyama, Tetsuhiro S; Kaneko, Kunihiko

2014-08-01

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

Examining Event-Related Potential (ERP) Correlates of Decision Bias in Recognition Memory Judgments

PubMed Central

Hill, Holger; Windmann, Sabine

2014-01-01

Memory judgments can be based on accurate memory information or on decision bias (the tendency to report that an event is part of episodic memory when one is in fact unsure). Event related potentials (ERP) correlates are important research tools for elucidating the dynamics underlying memory judgments but so far have been established only for investigations of accurate old/new discrimination. To identify the ERP correlates of bias, and observe how these interact with ERP correlates of memory, we conducted three experiments that manipulated decision bias within participants via instructions during recognition memory tests while their ERPs were recorded. In Experiment 1, the bias manipulation was performed between blocks of trials (automatized bias) and compared to trial-by-trial shifts of bias in accord with an external cue (flexibly controlled bias). In Experiment 2, the bias manipulation was performed at two different levels of accurate old/new discrimination as the memory strength of old (studied) items was varied. In Experiment 3, the bias manipulation was added to another, bottom-up driven manipulation of bias induced via familiarity. In the first two Experiments, and in the low familiarity condition of Experiment 3, we found evidence of an early frontocentral ERP component at 320 ms poststimulus (the FN320) that was sensitive to the manipulation of bias via instruction, with more negative amplitudes indexing more liberal bias. By contrast, later during the trial (500–700 ms poststimulus), bias effects interacted with old/new effects across all three experiments. Results suggest that the decision criterion is typically activated early during recognition memory trials, and is integrated with retrieved memory signals and task-specific processing demands later during the trial. More generally, the findings demonstrate how ERPs can help to specify the dynamics of recognition memory processes under top-down and bottom-up controlled retrieval conditions. PMID:25264982

Examining Event-Related Potential (ERP) correlates of decision bias in recognition memory judgments.

PubMed

Hill, Holger; Windmann, Sabine

2014-01-01

Memory judgments can be based on accurate memory information or on decision bias (the tendency to report that an event is part of episodic memory when one is in fact unsure). Event related potentials (ERP) correlates are important research tools for elucidating the dynamics underlying memory judgments but so far have been established only for investigations of accurate old/new discrimination. To identify the ERP correlates of bias, and observe how these interact with ERP correlates of memory, we conducted three experiments that manipulated decision bias within participants via instructions during recognition memory tests while their ERPs were recorded. In Experiment 1, the bias manipulation was performed between blocks of trials (automatized bias) and compared to trial-by-trial shifts of bias in accord with an external cue (flexibly controlled bias). In Experiment 2, the bias manipulation was performed at two different levels of accurate old/new discrimination as the memory strength of old (studied) items was varied. In Experiment 3, the bias manipulation was added to another, bottom-up driven manipulation of bias induced via familiarity. In the first two Experiments, and in the low familiarity condition of Experiment 3, we found evidence of an early frontocentral ERP component at 320 ms poststimulus (the FN320) that was sensitive to the manipulation of bias via instruction, with more negative amplitudes indexing more liberal bias. By contrast, later during the trial (500-700 ms poststimulus), bias effects interacted with old/new effects across all three experiments. Results suggest that the decision criterion is typically activated early during recognition memory trials, and is integrated with retrieved memory signals and task-specific processing demands later during the trial. More generally, the findings demonstrate how ERPs can help to specify the dynamics of recognition memory processes under top-down and bottom-up controlled retrieval conditions.

Offline memory reprocessing: involvement of the brain's default network in spontaneous thought processes.

PubMed

Wang, Kun; Yu, Chunshui; Xu, Lijuan; Qin, Wen; Li, Kuncheng; Xu, Lin; Jiang, Tianzi

2009-01-01

Spontaneous thought processes (STPs), also called daydreaming or mind-wandering, occur ubiquitously in daily life. However, the functional significance of STPs remains largely unknown. Using functional magnetic resonance imaging (fMRI), we first identified an STPs-network whose activity was positively correlated with the subjects' tendency of having STPs during a task-free state. The STPs-network was then found to be strongly associated with the default network, which has previously been established as being active during the task-free state. Interestingly, we found that offline reprocessing of previously memorized information further increased the activity of the STPs-network regions, although during a state with less STPs. In addition, we found that the STPs-network kept a dynamic balance between functional integration and functional separation among its component regions to execute offline memory reprocessing in STPs. These findings strengthen a view that offline memory reprocessing and STPs share the brain's default network, and thus implicate that offline memory reprocessing may be a predetermined function of STPs. This supports the perspective that memory can be consolidated and modified during STPs, and thus gives rise to a dynamic behavior dependent on both previous external and internal experiences.

Dynamic working memory performance in individuals with single-domain amnestic mild cognitive impairment.

PubMed

Guild, Emma B; Vasquez, Brandon P; Maione, Andrea M; Mah, Linda; Ween, Jon; Anderson, Nicole D

2014-01-01

Previous studies have observed poorer working memory performance in individuals with amnestic mild cognitive impairment than in healthy older adults. It is unclear, however, whether these difficulties are true only of the multiple-domain clinical subtype in whom poorer executive functioning is common. The current study examined working memory, as measured by the self-ordered pointing task (SOPT) and an n-back task, in healthy older adults and adults with single-domain amnestic mild cognitive impairment (aMCI). Individuals with single-domain aMCI committed more errors and required longer to develop an organizational strategy on the SOPT. The single-domain aMCI group did not differ from healthy older adults on the 1-back or 2-back, but had poorer discrimination on the 3-back task. This is, to our knowledge, the first characterization of dynamic working memory performance in a single-domain aMCI group. These results lend support for the idea that clinical amnestic MCI subtypes may reflect different stages on a continuum of progression to dementia and question whether standardized measures of working memory (span tasks) are sensitive enough to capture subtle changes in performance.

Rambrain - a library for virtually extending physical memory

NASA Astrophysics Data System (ADS)

Imgrund, Maximilian; Arth, Alexander

2017-08-01

We introduce Rambrain, a user space library that manages memory consumption of your code. Using Rambrain you can overcommit memory over the size of physical memory present in the system. Rambrain takes care of temporarily swapping out data to disk and can handle multiples of the physical memory size present. Rambrain is thread-safe, OpenMP and MPI compatible and supports Asynchronous IO. The library was designed to require minimal changes to existing programs and to be easy to use.

Colloquium: Non-Markovian dynamics in open quantum systems

NASA Astrophysics Data System (ADS)

Breuer, Heinz-Peter; Laine, Elsi-Mari; Piilo, Jyrki; Vacchini, Bassano

2016-04-01

The dynamical behavior of open quantum systems plays a key role in many applications of quantum mechanics, examples ranging from fundamental problems, such as the environment-induced decay of quantum coherence and relaxation in many-body systems, to applications in condensed matter theory, quantum transport, quantum chemistry, and quantum information. In close analogy to a classical Markovian stochastic process, the interaction of an open quantum system with a noisy environment is often modeled phenomenologically by means of a dynamical semigroup with a corresponding time-independent generator in Lindblad form, which describes a memoryless dynamics of the open system typically leading to an irreversible loss of characteristic quantum features. However, in many applications open systems exhibit pronounced memory effects and a revival of genuine quantum properties such as quantum coherence, correlations, and entanglement. Here recent theoretical results on the rich non-Markovian quantum dynamics of open systems are discussed, paying particular attention to the rigorous mathematical definition, to the physical interpretation and classification, as well as to the quantification of quantum memory effects. The general theory is illustrated by a series of physical examples. The analysis reveals that memory effects of the open system dynamics reflect characteristic features of the environment which opens a new perspective for applications, namely, to exploit a small open system as a quantum probe signifying nontrivial features of the environment it is interacting with. This Colloquium further explores the various physical sources of non-Markovian quantum dynamics, such as structured environmental spectral densities, nonlocal correlations between environmental degrees of freedom, and correlations in the initial system-environment state, in addition to developing schemes for their local detection. Recent experiments addressing the detection, quantification, and control of non-Markovian quantum dynamics are also briefly discussed.

Dynamic testing in schizophrenia: does training change the construct validity of a test?

PubMed

Wiedl, Karl H; Schöttke, Henning; Green, Michael F; Nuechterlein, Keith H

2004-01-01

Dynamic testing typically involves specific interventions for a test to assess the extent to which test performance can be modified, beyond level of baseline (static) performance. This study used a dynamic version of the Wisconsin Card Sorting Test (WCST) that is based on cognitive remediation techniques within a test-training-test procedure. From results of previous studies with schizophrenia patients, we concluded that the dynamic and static versions of the WCST should have different construct validity. This hypothesis was tested by examining the patterns of correlations with measures of executive functioning, secondary verbal memory, and verbal intelligence. Results demonstrated a specific construct validity of WCST dynamic (i.e., posttest) scores as an index of problem solving (Tower of Hanoi) and secondary verbal memory and learning (Auditory Verbal Learning Test), whereas the impact of general verbal capacity and selective attention (Verbal IQ, Stroop Test) was reduced. It is concluded that the construct validity of the test changes with dynamic administration and that this difference helps to explain why the dynamic version of the WCST predicts functional outcome better than the static version.

Memory formation during anaesthesia: plausibility of a neurophysiological basis

PubMed Central

Veselis, R. A.

2015-01-01

As opposed to conscious, personally relevant (explicit) memories that we can recall at will, implicit (unconscious) memories are prototypical of ‘hidden’ memory; memories that exist, but that we do not know we possess. Nevertheless, our behaviour can be affected by these memories; in fact, these memories allow us to function in an ever-changing world. It is still unclear from behavioural studies whether similar memories can be formed during anaesthesia. Thus, a relevant question is whether implicit memory formation is a realistic possibility during anaesthesia, considering the underlying neurophysiology. A different conceptualization of memory taxonomy is presented, the serial parallel independent model of Tulving, which focuses on dynamic information processing with interactions among different memory systems rather than static classification of different types of memories. The neurophysiological basis for subliminal information processing is considered in the context of brain function as embodied in network interactions. Function of sensory cortices and thalamic activity during anaesthesia are reviewed. The role of sensory and perisensory cortices, in particular the auditory cortex, in support of memory function is discussed. Although improbable, with the current knowledge of neurophysiology one cannot rule out the possibility of memory formation during anaesthesia. PMID:25735711

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

PubMed

Marcotti, Petra; St Jacques, Peggy L

2018-03-01

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

Formal verification of a set of memory management units

NASA Technical Reports Server (NTRS)

Schubert, E. Thomas; Levitt, K.; Cohen, Gerald C.

1992-01-01

This document describes the verification of a set of memory management units (MMU). The verification effort demonstrates the use of hierarchical decomposition and abstract theories. The MMUs can be organized into a complexity hierarchy. Each new level in the hierarchy adds a few significant features or modifications to the lower level MMU. The units described include: (1) a page check translation look-aside module (TLM); (2) a page check TLM with supervisor line; (3) a base bounds MMU; (4) a virtual address translation MMU; and (5) a virtual address translation MMU with memory resident segment table.

Angular Gyrus Involvement at Encoding and Retrieval Is Associated with Durable But Less Specific Memories.

PubMed

van der Linden, Marieke; Berkers, Ruud M W J; Morris, Richard G M; Fernández, Guillén

2017-09-27

After consolidation, information belonging to a mental schema is better remembered, but such memory can be less specific when it comes to details. A neuronal mechanism consistent with this behavioral pattern could result from a dynamic interaction that entails mediation by a specific cortical network with associated hippocampal disengagement. We now report that, in male and female adult human subjects, encoding and later consolidation of a series of objects embedded in a semantic schema was associated with a buildup of activity in the angular gyrus (AG) that predicted memory 24 h later. In parallel, the posterior hippocampus became less involved as schema objects were encoded successively. Hippocampal disengagement was related to an increase in falsely remembering objects that were not presented at encoding. During both encoding and retrieval, the AG and lateral occipital complex (LOC) became functionally connected and this interaction was beneficial for successful retrieval. Therefore, a network including the AG and LOC enhances the overnight retention of schema-related memories and their simultaneous detachment from the hippocampus reduces the specificity of the memory. SIGNIFICANCE STATEMENT This study provides the first empirical evidence on how the hippocampus and the neocortex interact dynamically when acquiring and then effectively retaining durable knowledge that is associated to preexisting knowledge, but they do so at the cost of memory specificity. This interaction is a fundamental mnemonic operation that has thus far been largely overlooked in memory research. Copyright © 2017 the authors 0270-6474/17/379474-12$15.00/0.

Optical mass memory system (AMM-13). AMM/DBMS interface control document

NASA Technical Reports Server (NTRS)

Bailey, G. A.

1980-01-01

The baseline for external interfaces of a 10 to the 13th power bit, optical archival mass memory system (AMM-13) is established. The types of interfaces addressed include data transfer; AMM-13, Data Base Management System, NASA End-to-End Data System computer interconnect; data/control input and output interfaces; test input data source; file management; and facilities interface.

Memory management and compiler support for rapid recovery from failures in computer systems

NASA Technical Reports Server (NTRS)

Fuchs, W. K.

1991-01-01

This paper describes recent developments in the use of memory management and compiler technology to support rapid recovery from failures in computer systems. The techniques described include cache coherence protocols for user transparent checkpointing in multiprocessor systems, compiler-based checkpoint placement, compiler-based code modification for multiple instruction retry, and forward recovery in distributed systems utilizing optimistic execution.

Architecture of security management unit for safe hosting of multiple agents

NASA Astrophysics Data System (ADS)

Gilmont, Tanguy; Legat, Jean-Didier; Quisquater, Jean-Jacques

1999-04-01

In such growing areas as remote applications in large public networks, electronic commerce, digital signature, intellectual property and copyright protection, and even operating system extensibility, the hardware security level offered by existing processors is insufficient. They lack protection mechanisms that prevent the user from tampering critical data owned by those applications. Some devices make exception, but have not enough processing power nor enough memory to stand up to such applications (e.g. smart cards). This paper proposes an architecture of secure processor, in which the classical memory management unit is extended into a new security management unit. It allows ciphered code execution and ciphered data processing. An internal permanent memory can store cipher keys and critical data for several client agents simultaneously. The ordinary supervisor privilege scheme is replaced by a privilege inheritance mechanism that is more suited to operating system extensibility. The result is a secure processor that has hardware support for extensible multitask operating systems, and can be used for both general applications and critical applications needing strong protection. The security management unit and the internal permanent memory can be added to an existing CPU core without loss of performance, and do not require it to be modified.

Method and system for training dynamic nonlinear adaptive filters which have embedded memory

NASA Technical Reports Server (NTRS)

Rabinowitz, Matthew (Inventor)

2002-01-01

Described herein is a method and system for training nonlinear adaptive filters (or neural networks) which have embedded memory. Such memory can arise in a multi-layer finite impulse response (FIR) architecture, or an infinite impulse response (IIR) architecture. We focus on filter architectures with separate linear dynamic components and static nonlinear components. Such filters can be structured so as to restrict their degrees of computational freedom based on a priori knowledge about the dynamic operation to be emulated. The method is detailed for an FIR architecture which consists of linear FIR filters together with nonlinear generalized single layer subnets. For the IIR case, we extend the methodology to a general nonlinear architecture which uses feedback. For these dynamic architectures, we describe how one can apply optimization techniques which make updates closer to the Newton direction than those of a steepest descent method, such as backpropagation. We detail a novel adaptive modified Gauss-Newton optimization technique, which uses an adaptive learning rate to determine both the magnitude and direction of update steps. For a wide range of adaptive filtering applications, the new training algorithm converges faster and to a smaller value of cost than both steepest-descent methods such as backpropagation-through-time, and standard quasi-Newton methods. We apply the algorithm to modeling the inverse of a nonlinear dynamic tracking system 5, as well as a nonlinear amplifier 6.

Microscopic derivation of particle-based coarse-grained dynamics: Exact expression for memory function

NASA Astrophysics Data System (ADS)

Izvekov, Sergei

2017-03-01

We consider the generalized Langevin equations of motion describing exactly the particle-based coarse-grained dynamics in the classical microscopic ensemble that were derived recently within the Mori-Zwanzig formalism based on new projection operators [S. Izvekov, J. Chem. Phys. 138(13), 134106 (2013)]. The fundamental difference between the new family of projection operators and the standard Zwanzig projection operator used in the past to derive the coarse-grained equations of motion is that the new operators average out the explicit irrelevant trajectories leading to the possibility of solving the projected dynamics exactly. We clarify the definition of the projection operators and revisit the formalism to compute the projected dynamics exactly for the microscopic system in equilibrium. The resulting expression for the projected force is in the form of a "generalized additive fluctuating force" describing the departure of the generalized microscopic force associated with the coarse-grained coordinate from its projection. Starting with this key expression, we formulate a new exact formula for the memory function in terms of microscopic and coarse-grained conservative forces. We conclude by studying two independent limiting cases of practical importance: the Markov limit (vanishing correlations of projected force) and the limit of weak dependence of the memory function on the particle momenta. We present computationally affordable expressions which can be efficiently evaluated from standard molecular dynamics simulations.

Complex dynamics of memristive circuits: Analytical results and universal slow relaxation

NASA Astrophysics Data System (ADS)

Caravelli, F.; Traversa, F. L.; Di Ventra, M.

2017-02-01

Networks with memristive elements (resistors with memory) are being explored for a variety of applications ranging from unconventional computing to models of the brain. However, analytical results that highlight the role of the graph connectivity on the memory dynamics are still few, thus limiting our understanding of these important dynamical systems. In this paper, we derive an exact matrix equation of motion that takes into account all the network constraints of a purely memristive circuit, and we employ it to derive analytical results regarding its relaxation properties. We are able to describe the memory evolution in terms of orthogonal projection operators onto the subspace of fundamental loop space of the underlying circuit. This orthogonal projection explicitly reveals the coupling between the spatial and temporal sectors of the memristive circuits and compactly describes the circuit topology. For the case of disordered graphs, we are able to explain the emergence of a power-law relaxation as a superposition of exponential relaxation times with a broad range of scales using random matrices. This power law is also universal, namely independent of the topology of the underlying graph but dependent only on the density of loops. In the case of circuits subject to alternating voltage instead, we are able to obtain an approximate solution of the dynamics, which is tested against a specific network topology. These results suggest a much richer dynamics of memristive networks than previously considered.

The hippocampus and related neocortical structures in memory transformation.

PubMed

Sekeres, Melanie J; Winocur, Gordon; Moscovitch, Morris

2018-05-04

Episodic memories are multifaceted and malleable, capable of being transformed with time and experience at both the neural level and psychological level. At the neural level, episodic memories are transformed from being dependent on the hippocampus to becoming represented in neocortical structures, such as the medial prefrontal cortex (mPFC), and back again, while at the psychological level, detailed, perceptually rich memories, are transformed to ones retaining only the gist of an experience or a schema related to it. Trace Transformation Theory (TTT) initially proposed that neural and psychological transformations are linked and proceed in tandem. Building on recent studies on the neurobiology of memory transformation in rodents and on the organization of the hippocampus and its functional cortical connectivity in humans, we present an updated version of TTT that is more precise and detailed with respect to the dynamic processes and structures implicated in memory transformation. At the heart of the updated TTT lies the long axis of the hippocampus whose functional differentiation and connectivity to neocortex make it a hub for memory formation and transformation. The posterior hippocampus, connected to perceptual and spatial representational systems in posterior neocortex, supports fine, perceptually rich, local details of memories; the anterior hippocampus, connected to conceptual systems in anterior neocortex, supports coarse, global representations that constitute the gist of a memory. Notable among the anterior structures is the medial prefrontal cortex which supports representation of schemas that code for common aspects of memories across different episodes. Linking the aHPC with mPFC is the entorhinal cortex (EC) which conveys information needed for the interaction/translation between gist and schemas. Thus, the long axis of the hippocampus, mPFC and EC provide the representational gradient, from fine to coarse and from perceptual to conceptual, that can implement processes implicated in memory transformation. Each of these representations of an episodic memory can co-exist with one another and be in dynamic flux as they interact with one another throughout the memory's lifetime, going from detailed to schematic and possibly back again, all mediated by corresponding changes in neural representation. Copyright © 2018 Elsevier B.V. All rights reserved.

Fault tolerant function of dynamic refreshing holographic memory with shutter-less optical feedback circuit

NASA Astrophysics Data System (ADS)

Okamoto, Atsushi; Ito, Terumasa; Bunsen, Masatoshi; Takayama, Yoshihisa

2005-11-01

The optical system, consisting of two photorefractive memories and a shutter-less optical feedback circuit, will be demonstrated to function as data mirroring. This function is known to automatically detect the data dropout and restore data, using unimpaired data in another memory, in the event that part or all of the data in either of them were lost for some reason. This memory system also can cope with a damaged hologram, a result of reading beams, which is a disadvantage of rewritable photorefractive memory, to ensure non-destructive holographic reading. It can be achieved by using no electronic circuits or mechanical structures; our optical experimental method in particular obtains this basic action.

Memory Circuit Fault Simulator

NASA Technical Reports Server (NTRS)

Sheldon, Douglas J.; McClure, Tucker

2013-01-01

Spacecraft are known to experience significant memory part-related failures and problems, both pre- and postlaunch. These memory parts include both static and dynamic memories (SRAM and DRAM). These failures manifest themselves in a variety of ways, such as pattern-sensitive failures, timingsensitive failures, etc. Because of the mission critical nature memory devices play in spacecraft architecture and operation, understanding their failure modes is vital to successful mission operation. To support this need, a generic simulation tool that can model different data patterns in conjunction with variable write and read conditions was developed. This tool is a mathematical and graphical way to embed pattern, electrical, and physical information to perform what-if analysis as part of a root cause failure analysis effort.

Sparse distributed memory prototype: Principles of operation

NASA Technical Reports Server (NTRS)

Flynn, Michael J.; Kanerva, Pentti; Ahanin, Bahram; Bhadkamkar, Neal; Flaherty, Paul; Hickey, Philip

1988-01-01

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

Selective memory retrieval can impair and improve retrieval of other memories.

PubMed

Bäuml, Karl-Heinz T; Samenieh, Anuscheh

2012-03-01

Research from the past decades has shown that retrieval of a specific memory (e.g., retrieving part of a previous vacation) typically attenuates retrieval of other memories (e.g., memories for other details of the event), causing retrieval-induced forgetting. More recently, however, it has been shown that retrieval can both attenuate and aid recall of other memories (K.-H. T. Bäuml & A. Samenieh, 2010). To identify the circumstances under which retrieval aids recall, the authors examined retrieval dynamics in listwise directed forgetting, context-dependent forgetting, proactive interference, and in the absence of any induced memory impairment. They found beneficial effects of selective retrieval in listwise directed forgetting and context-dependent forgetting but detrimental effects in all the other conditions. Because context-dependent forgetting and listwise directed forgetting arguably reflect impaired context access, the results suggest that memory retrieval aids recall of memories that are subject to impaired context access but attenuates recall in the absence of such circumstances. The findings are consistent with a 2-factor account of memory retrieval and suggest the existence of 2 faces of memory retrieval. 2012 APA, all rights reserved

Reconsolidation of drug memories

PubMed Central

Sorg, Barbara A.

2012-01-01

Persistent, unwanted memories are believed to be key contributors to drug addiction and the chronic relapse problem over the lifetime of the addict. Contrary to the long-held idea that memories are static and fixed, new studies in the last decade have shown that memories are dynamic and changeable. However, they are changeable only under specific conditions. When a memory is retrieved (reactivated), it becomes labile for a period of minutes to hours and then is reconsolidated to maintain long-term memory. Recent findings indicate that even well-established long-term memories may be susceptible to disruption by interfering with reconsolidation through delivery of certain amnestic agents during memory retrieval. Here I review the growing literature on memory reconsolidation in animal models of addiction, including sensitization, conditioned place preference and self-administration. I also discuss (a) several issues that need to be considered in interpreting the findings from reconsolidation studies and (b) future challenges and directions for memory reconsolidation studies in the field of addiction. The findings indicate promise for using this approach as a therapy for disrupting the long-lasting memories that can trigger relapse. PMID:22342780

Working memory capacity and controlled serial memory search.

PubMed

Mızrak, Eda; Öztekin, Ilke

2016-08-01

The speed-accuracy trade-off (SAT) procedure was used to investigate the relationship between working memory capacity (WMC) and the dynamics of temporal order memory retrieval. High- and low-span participants (HSs, LSs) studied sequentially presented five-item lists, followed by two probes from the study list. Participants indicated the more recent probe. Overall, accuracy was higher for HSs compared to LSs. Crucially, in contrast to previous investigations that observed no impact of WMC on speed of access to item information in memory (e.g., Öztekin & McElree, 2010), recovery of temporal order memory was slower for LSs. While accessing an item's representation in memory can be direct, recovery of relational information such as temporal order information requires a more controlled serial memory search. Collectively, these data indicate that WMC effects are particularly prominent during high demands of cognitive control, such as serial search operations necessary to access temporal order information from memory. Copyright © 2016 Elsevier B.V. All rights reserved.

Linear Optics Simulation of Quantum Non-Markovian Dynamics

PubMed Central

Chiuri, Andrea; Greganti, Chiara; Mazzola, Laura; Paternostro, Mauro; Mataloni, Paolo

2012-01-01

The simulation of open quantum dynamics has recently allowed the direct investigation of the features of system-environment interaction and of their consequences on the evolution of a quantum system. Such interaction threatens the quantum properties of the system, spoiling them and causing the phenomenon of decoherence. Sometimes however a coherent exchange of information takes place between system and environment, memory effects arise and the dynamics of the system becomes non-Markovian. Here we report the experimental realisation of a non-Markovian process where system and environment are coupled through a simulated transverse Ising model. By engineering the evolution in a photonic quantum simulator, we demonstrate the role played by system-environment correlations in the emergence of memory effects. PMID:23236588

Adaptive synchronization and anticipatory dynamical systems

NASA Astrophysics Data System (ADS)

Yang, Ying-Jen; Chen, Chun-Chung; Lai, Pik-Yin; Chan, C. K.

2015-09-01

Many biological systems can sense periodical variations in a stimulus input and produce well-timed, anticipatory responses after the input is removed. Such systems show memory effects for retaining timing information in the stimulus and cannot be understood from traditional synchronization consideration of passive oscillatory systems. To understand this anticipatory phenomena, we consider oscillators built from excitable systems with the addition of an adaptive dynamics. With such systems, well-timed post-stimulus responses similar to those from experiments can be obtained. Furthermore, a well-known model of working memory is shown to possess similar anticipatory dynamics when the adaptive mechanism is identified with synaptic facilitation. The last finding suggests that this type of oscillator can be common in neuronal systems with plasticity.

Adaptive synchronization and anticipatory dynamical systems.

PubMed

Yang, Ying-Jen; Chen, Chun-Chung; Lai, Pik-Yin; Chan, C K

2015-09-01

Many biological systems can sense periodical variations in a stimulus input and produce well-timed, anticipatory responses after the input is removed. Such systems show memory effects for retaining timing information in the stimulus and cannot be understood from traditional synchronization consideration of passive oscillatory systems. To understand this anticipatory phenomena, we consider oscillators built from excitable systems with the addition of an adaptive dynamics. With such systems, well-timed post-stimulus responses similar to those from experiments can be obtained. Furthermore, a well-known model of working memory is shown to possess similar anticipatory dynamics when the adaptive mechanism is identified with synaptic facilitation. The last finding suggests that this type of oscillator can be common in neuronal systems with plasticity.

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

PubMed

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

2014-03-01

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

Radiation Test Challenges for Scaled Commerical Memories

NASA Technical Reports Server (NTRS)

LaBel, Kenneth A.; Ladbury, Ray L.; Cohn, Lewis M.; Oldham, Timothy

2007-01-01

As sub-100nm CMOS technologies gather interest, the radiation effects performance of these technologies provide a significant challenge. In this talk, we shall discuss the radiation testing challenges as related to commercial memory devices. The focus will be on complex test and failure modes emerging in state-of-the-art Flash non-volatile memories (NVMs) and synchronous dynamic random access memories (SDRAMs), which are volatile. Due to their very high bit density, these device types are highly desirable for use in the natural space environment. In this presentation, we shall discuss these devices with emphasis on considerations for test and qualification methods required.

Noise stabilization of self-organized memories.

PubMed

Povinelli, M L; Coppersmith, S N; Kadanoff, L P; Nagel, S R; Venkataramani, S C

1999-05-01

We investigate a nonlinear dynamical system which "remembers" preselected values of a system parameter. The deterministic version of the system can encode many parameter values during a transient period, but in the limit of long times, almost all of them are forgotten. Here we show that a certain type of stochastic noise can stabilize multiple memories, enabling many parameter values to be encoded permanently. We present analytic results that provide insight both into the memory formation and into the noise-induced memory stabilization. The relevance of our results to experiments on the charge-density wave material NbSe3 is discussed.

Generalized hydrodynamic correlations and fractional memory functions

NASA Astrophysics Data System (ADS)

Rodríguez, Rosalio F.; Fujioka, Jorge

2015-12-01

A fractional generalized hydrodynamic (GH) model of the longitudinal velocity fluctuations correlation, and its associated memory function, for a complex fluid is analyzed. The adiabatic elimination of fast variables introduces memory effects in the transport equations, and the dynamic of the fluctuations is described by a generalized Langevin equation with long-range noise correlations. These features motivate the introduction of Caputo time fractional derivatives and allows us to calculate analytic expressions for the fractional longitudinal velocity correlation function and its associated memory function. Our analysis eliminates a spurious constant term in the non-fractional memory function found in the non-fractional description. It also produces a significantly slower power-law decay of the memory function in the GH regime that reduces to the well-known exponential decay in the non-fractional Navier-Stokes limit.

The dynamic nature of systems consolidation: Stress during learning as a switch guiding the rate of the hippocampal dependency and memory quality.

PubMed

Pedraza, Lizeth K; Sierra, Rodrigo O; Boos, Flávia Z; Haubrich, Josué; Quillfeldt, Jorge A; Alvares, Lucas de Oliveira

2016-03-01

Memory fades over time, becoming more schematic or abstract. The loss of contextual detail in memory may reflect a time-dependent change in the brain structures supporting memory. It has been well established that contextual fear memory relies on the hippocampus for expression shortly after learning, but it becomes hippocampus-independent at a later time point, a process called systems consolidation. This time-dependent process correlates with the loss of memory precision. Here, we investigated whether training intensity predicts the gradual decay of hippocampal dependency to retrieve memory, and the quality of the contextual memory representation over time. We have found that training intensity modulates the progressive decay of hippocampal dependency and memory precision. Strong training intensity accelerates systems consolidation and memory generalization in a remarkable timeframe match. The mechanisms underpinning such process are triggered by glucocorticoid and noradrenaline released during training. These results suggest that the stress levels during emotional learning act as a switch, determining the fate of memory quality. Moderate stress will create a detailed memory, whereas a highly stressful training will develop a generic gist-like memory. © 2015 Wiley Periodicals, Inc.

ERPs and oscillations during encoding predict retrieval of digit memory in superior mnemonists.

PubMed

Pan, Yafeng; Li, Xianchun; Chen, Xi; Ku, Yixuan; Dong, Yujie; Dou, Zheng; He, Lin; Hu, Yi; Li, Weidong; Zhou, Xiaolin

2017-10-01

Previous studies have consistently demonstrated that superior mnemonists (SMs) outperform normal individuals in domain-specific memory tasks. However, the neural correlates of memory-related processes remain unclear. In the current EEG study, SMs and control participants performed a digit memory task during which their brain activity was recorded. Chinese SMs used a digit-image mnemonic for encoding digits, in which they associated 2-digit groups with images immediately after the presentation of each even-position digit in sequences. Behaviorally, SMs' memory of digit sequences was better than the controls'. During encoding in the study phase, SMs showed an increased right central P2 (150-250ms post onset) and a larger right posterior high-alpha (10-14Hz, 500-1720ms) oscillation on digits at even-positions compared with digits at odd-positions. Both P2 and high-alpha oscillations in the study phase co-varied with performance in the recall phase, but only in SMs, indicating that neural dynamics during encoding could predict successful retrieval of digit memory in SMs. Our findings suggest that representation of a digit sequence in SMs using mnemonics may recruit both the early-stage attention allocation process and the sustained information preservation process. This study provides evidence for the role of dynamic and efficient neural encoding processes in mnemonists. Copyright © 2017. Published by Elsevier Inc.

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

PubMed

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

2013-09-27

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.

Automatic Generation of OpenMP Directives and Its Application to Computational Fluid Dynamics Codes

NASA Technical Reports Server (NTRS)

Yan, Jerry; Jin, Haoqiang; Frumkin, Michael; Yan, Jerry (Technical Monitor)

2000-01-01

The shared-memory programming model is a very effective way to achieve parallelism on shared memory parallel computers. As great progress was made in hardware and software technologies, performance of parallel programs with compiler directives has demonstrated large improvement. The introduction of OpenMP directives, the industrial standard for shared-memory programming, has minimized the issue of portability. In this study, we have extended CAPTools, a computer-aided parallelization toolkit, to automatically generate OpenMP-based parallel programs with nominal user assistance. We outline techniques used in the implementation of the tool and discuss the application of this tool on the NAS Parallel Benchmarks and several computational fluid dynamics codes. This work demonstrates the great potential of using the tool to quickly port parallel programs and also achieve good performance that exceeds some of the commercial tools.

A controlled ac Stark echo for quantum memories.

PubMed

Ham, Byoung S

2017-08-09

A quantum memory protocol of controlled ac Stark echoes (CASE) based on a double rephasing photon echo scheme via controlled Rabi flopping is proposed. The double rephasing scheme of photon echoes inherently satisfies the no-population inversion requirement for quantum memories, but the resultant absorptive echo remains a fundamental problem. Herein, it is reported that the first echo in the double rephasing scheme can be dynamically controlled so that it does not affect the second echo, which is accomplished by using unbalanced ac Stark shifts. Then, the second echo is coherently controlled to be emissive via controlled coherence conversion. Finally a near perfect ultralong CASE is presented using a backward echo scheme. Compared with other methods such as dc Stark echoes, the present protocol is all-optical with advantages of wavelength-selective dynamic control of quantum processing for erasing, buffering, and channel multiplexing.

Four-electron model for singlet and triplet excitation energy transfers with inclusion of coherence memory, inelastic tunneling and nuclear quantum effects

NASA Astrophysics Data System (ADS)

Suzuki, Yosuke; Ebina, Kuniyoshi; Tanaka, Shigenori

2016-08-01

A computational scheme to describe the coherent dynamics of excitation energy transfer (EET) in molecular systems is proposed on the basis of generalized master equations with memory kernels. This formalism takes into account those physical effects in electron-bath coupling system such as the spin symmetry of excitons, the inelastic electron tunneling and the quantum features of nuclear motions, thus providing a theoretical framework to perform an ab initio description of EET through molecular simulations for evaluating the spectral density and the temporal correlation function of electronic coupling. Some test calculations have then been carried out to investigate the dependence of exciton population dynamics on coherence memory, inelastic tunneling correlation time, magnitude of electronic coupling, quantum correction to temporal correlation function, reorganization energy and energy gap.

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

NASA Astrophysics Data System (ADS)

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

2008-06-01

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

Sequential memory: Binding dynamics.

PubMed

Afraimovich, Valentin; Gong, Xue; Rabinovich, Mikhail

2015-10-01

Temporal order memories are critical for everyday animal and human functioning. Experiments and our own experience show that the binding or association of various features of an event together and the maintaining of multimodality events in sequential order are the key components of any sequential memories-episodic, semantic, working, etc. We study a robustness of binding sequential dynamics based on our previously introduced model in the form of generalized Lotka-Volterra equations. In the phase space of the model, there exists a multi-dimensional binding heteroclinic network consisting of saddle equilibrium points and heteroclinic trajectories joining them. We prove here the robustness of the binding sequential dynamics, i.e., the feasibility phenomenon for coupled heteroclinic networks: for each collection of successive heteroclinic trajectories inside the unified networks, there is an open set of initial points such that the trajectory going through each of them follows the prescribed collection staying in a small neighborhood of it. We show also that the symbolic complexity function of the system restricted to this neighborhood is a polynomial of degree L - 1, where L is the number of modalities.

Rotordynamics on the PC: Transient Analysis With ARDS

NASA Technical Reports Server (NTRS)

Fleming, David P.

1997-01-01

Personal computers can now do many jobs that formerly required a large mainframe computer. An example is NASA Lewis Research Center's program Analysis of RotorDynamic Systems (ARDS), which uses the component mode synthesis method to analyze the dynamic motion of up to five rotating shafts. As originally written in the early 1980's, this program was considered large for the mainframe computers of the time. ARDS, which was written in Fortran 77, has been successfully ported to a 486 personal computer. Plots appear on the computer monitor via calls programmed for the original CALCOMP plotter; plots can also be output on a standard laser printer. The executable code, which uses the full array sizes of the mainframe version, easily fits on a high-density floppy disk. The program runs under DOS with an extended memory manager. In addition to transient analysis of blade loss, step turns, and base acceleration, with simulation of squeeze-film dampers and rubs, ARDS calculates natural frequencies and unbalance response.

Implications of the Turing machine model of computation for processor and programming language design

NASA Astrophysics Data System (ADS)

Hunter, Geoffrey

2004-01-01

A computational process is classified according to the theoretical model that is capable of executing it; computational processes that require a non-predeterminable amount of intermediate storage for their execution are Turing-machine (TM) processes, while those whose storage are predeterminable are Finite Automation (FA) processes. Simple processes (such as traffic light controller) are executable by Finite Automation, whereas the most general kind of computation requires a Turing Machine for its execution. This implies that a TM process must have a non-predeterminable amount of memory allocated to it at intermediate instants of its execution; i.e. dynamic memory allocation. Many processes encountered in practice are TM processes. The implication for computational practice is that the hardware (CPU) architecture and its operating system must facilitate dynamic memory allocation, and that the programming language used to specify TM processes must have statements with the semantic attribute of dynamic memory allocation, for in Alan Turing"s thesis on computation (1936) the "standard description" of a process is invariant over the most general data that the process is designed to process; i.e. the program describing the process should never have to be modified to allow for differences in the data that is to be processed in different instantiations; i.e. data-invariant programming. Any non-trivial program is partitioned into sub-programs (procedures, subroutines, functions, modules, etc). Examination of the calls/returns between the subprograms reveals that they are nodes in a tree-structure; this tree-structure is independent of the programming language used to encode (define) the process. Each sub-program typically needs some memory for its own use (to store values intermediate between its received data and its computed results); this locally required memory is not needed before the subprogram commences execution, and it is not needed after its execution terminates; it may be allocated as its execution commences, and deallocated as its execution terminates, and if the amount of this local memory is not known until just before execution commencement, then it is essential that it be allocated dynamically as the first action of its execution. This dynamically allocated/deallocated storage of each subprogram"s intermediate values, conforms with the stack discipline; i.e. last allocated = first to be deallocated, an incidental benefit of which is automatic overlaying of variables. This stack-based dynamic memory allocation was a semantic implication of the nested block structure that originated in the ALGOL-60 programming language. AGLOL-60 was a TM language, because the amount of memory allocated on subprogram (block/procedure) entry (for arrays, etc) was computable at execution time. A more general requirement of a Turing machine process is for code generation at run-time; this mandates access to the source language processor (compiler/interpretor) during execution of the process. This fundamental aspect of computer science is important to the future of system design, because it has been overlooked throughout the 55 years since modern computing began in 1048. The popular computer systems of this first half-century of computing were constrained by compile-time (or even operating system boot-time) memory allocation, and were thus limited to executing FA processes. The practical effect was that the distinction between the data-invariant program and its variable data was blurred; programmers had to make trial and error executions, modifying the program"s compile-time constants (array dimensions) to iterate towards the values required at run-time by the data being processed. This era of trial and error computing still persists; it pervades the culture of current (2003) computing practice.

A bi-population based scheme for an explicit exploration/exploitation trade-off in dynamic environments

NASA Astrophysics Data System (ADS)

Ben-Romdhane, Hajer; Krichen, Saoussen; Alba, Enrique

2017-05-01

Optimisation in changing environments is a challenging research topic since many real-world problems are inherently dynamic. Inspired by the natural evolution process, evolutionary algorithms (EAs) are among the most successful and promising approaches that have addressed dynamic optimisation problems. However, managing the exploration/exploitation trade-off in EAs is still a prevalent issue, and this is due to the difficulties associated with the control and measurement of such a behaviour. The proposal of this paper is to achieve a balance between exploration and exploitation in an explicit manner. The idea is to use two equally sized populations: the first one performs exploration while the second one is responsible for exploitation. These tasks are alternated from one generation to the next one in a regular pattern, so as to obtain a balanced search engine. Besides, we reinforce the ability of our algorithm to quickly adapt after cnhanges by means of a memory of past solutions. Such a combination aims to restrain the premature convergence, to broaden the search area, and to speed up the optimisation. We show through computational experiments, and based on a series of dynamic problems and many performance measures, that our approach improves the performance of EAs and outperforms competing algorithms.

Construction of non-Markovian coarse-grained models employing the Mori-Zwanzig formalism and iterative Boltzmann inversion

NASA Astrophysics Data System (ADS)

Yoshimoto, Yuta; Li, Zhen; Kinefuchi, Ikuya; Karniadakis, George Em

2017-12-01

We propose a new coarse-grained (CG) molecular simulation technique based on the Mori-Zwanzig (MZ) formalism along with the iterative Boltzmann inversion (IBI). Non-Markovian dissipative particle dynamics (NMDPD) taking into account memory effects is derived in a pairwise interaction form from the MZ-guided generalized Langevin equation. It is based on the introduction of auxiliary variables that allow for the replacement of a non-Markovian equation with a Markovian one in a higher dimensional space. We demonstrate that the NMDPD model exploiting MZ-guided memory kernels can successfully reproduce the dynamic properties such as the mean square displacement and velocity autocorrelation function of a Lennard-Jones system, as long as the memory kernels are appropriately evaluated based on the Volterra integral equation using the force-velocity and velocity-velocity correlations. Furthermore, we find that the IBI correction of a pair CG potential significantly improves the representation of static properties characterized by a radial distribution function and pressure, while it has little influence on the dynamic processes. Our findings suggest that combining the advantages of both the MZ formalism and IBI leads to an accurate representation of both the static and dynamic properties of microscopic systems that exhibit non-Markovian behavior.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

How Managers' everyday decisions create or destroy your company's strategy.

PubMed

Bower, Joseph L; Gilbert, Clark G

2007-02-01

Senior executives have long been frustrated by the disconnection between the plans and strategies they devise and the actual behavior of the managers throughout the company. This article approaches the problem from the ground up, recognizing that every time a manager allocates resources, that decision moves the company either into or out of alignment with its announced strategy. A well-known story--Intel's exit from the memory business--illustrates this point. When discussing what businesses Intel should be in, Andy Grove asked Gordon Moore what they would do if Intel were a company that they had just acquired. When Moore answered, "Get out of memory," they decided to do just that. It turned out, though, that Intel's revenues from memory were by this time only 4% of total sales. Intel's lower-level managers had already exited the business. What Intel hadn't done was to shut down the flow of research funding into memory (which was still eating up one-third of all research expenditures); nor had the company announced its exit to the outside world. Because divisional and operating managers-as well as customers and capital markets-have such a powerful impact on the realized strategy of the firm, senior management might consider focusing less on the company's formal strategy and more on the processes by which the company allocates resources. Top managers must know the track record of the people who are making resource allocation proposals; recognize the strategic issues at stake; reach down to operational managers to work across division lines; frame resource questions to reflect the corporate perspective, especially when large sums of money are involved and conditions are highly uncertain; and create a new context that allows top executives to circumvent the regular resource allocation process when necessary.

Information Processing Capacity of Dynamical Systems

NASA Astrophysics Data System (ADS)

Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Massar, Serge

2012-07-01

Many dynamical systems, both natural and artificial, are stimulated by time dependent external signals, somehow processing the information contained therein. We demonstrate how to quantify the different modes in which information can be processed by such systems and combine them to define the computational capacity of a dynamical system. This is bounded by the number of linearly independent state variables of the dynamical system, equaling it if the system obeys the fading memory condition. It can be interpreted as the total number of linearly independent functions of its stimuli the system can compute. Our theory combines concepts from machine learning (reservoir computing), system modeling, stochastic processes, and functional analysis. We illustrate our theory by numerical simulations for the logistic map, a recurrent neural network, and a two-dimensional reaction diffusion system, uncovering universal trade-offs between the non-linearity of the computation and the system's short-term memory.

Information Processing Capacity of Dynamical Systems

PubMed Central

Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Massar, Serge

2012-01-01

Many dynamical systems, both natural and artificial, are stimulated by time dependent external signals, somehow processing the information contained therein. We demonstrate how to quantify the different modes in which information can be processed by such systems and combine them to define the computational capacity of a dynamical system. This is bounded by the number of linearly independent state variables of the dynamical system, equaling it if the system obeys the fading memory condition. It can be interpreted as the total number of linearly independent functions of its stimuli the system can compute. Our theory combines concepts from machine learning (reservoir computing), system modeling, stochastic processes, and functional analysis. We illustrate our theory by numerical simulations for the logistic map, a recurrent neural network, and a two-dimensional reaction diffusion system, uncovering universal trade-offs between the non-linearity of the computation and the system's short-term memory. PMID:22816038

Audiovisual integration supports face-name associative memory formation.

PubMed

Lee, Hweeling; Stirnberg, Rüdiger; Stöcker, Tony; Axmacher, Nikolai

2017-10-01

Prior multisensory experience influences how we perceive our environment, and hence how memories are encoded for subsequent retrieval. This study investigated if audiovisual (AV) integration and associative memory formation rely on overlapping or distinct processes. Our functional magnetic resonance imaging results demonstrate that the neural mechanisms underlying AV integration and associative memory overlap substantially. In particular, activity in anterior superior temporal sulcus (STS) is increased during AV integration and also determines the success of novel AV face-name association formation. Dynamic causal modeling results further demonstrate how the anterior STS interacts with the associative memory system to facilitate successful memory formation for AV face-name associations. Specifically, the connection of fusiform gyrus to anterior STS is enhanced while the reverse connection is reduced when participants subsequently remembered both face and name. Collectively, our results demonstrate how multisensory associative memories can be formed for subsequent retrieval.

A Putative Biochemical Engram of Long-Term Memory.

PubMed

Li, Liying; Sanchez, Consuelo Perez; Slaughter, Brian D; Zhao, Yubai; Khan, Mohammed Repon; Unruh, Jay R; Rubinstein, Boris; Si, Kausik

2016-12-05

How a transient experience creates an enduring yet dynamic memory remains an unresolved issue in studies of memory. Experience-dependent aggregation of the RNA-binding protein CPEB/Orb2 is one of the candidate mechanisms of memory maintenance. Here, using tools that allow rapid and reversible inactivation of Orb2 protein in neurons, we find that Orb2 activity is required for encoding and recall of memory. From a screen, we have identified a DNA-J family chaperone, JJJ2, which facilitates Orb2 aggregation, and ectopic expression of JJJ2 enhances the animal's capacity to form long-term memory. Finally, we have developed tools to visualize training-dependent aggregation of Orb2. We find that aggregated Orb2 in a subset of mushroom body neurons can serve as a "molecular signature" of memory and predict memory strength. Our data indicate that self-sustaining aggregates of Orb2 may serve as a physical substrate of memory and provide a molecular basis for the perduring yet malleable nature of memory. Copyright © 2016 Elsevier Ltd. All rights reserved.

Neural circuit mechanisms of short-term memory

NASA Astrophysics Data System (ADS)

Goldman, Mark

Memory over time scales of seconds to tens of seconds is thought to be maintained by neural activity that is triggered by a memorized stimulus and persists long after the stimulus is turned off. This presents a challenge to current models of memory-storing mechanisms, because the typical time scales associated with cellular and synaptic dynamics are two orders of magnitude smaller than this. While such long time scales can easily be achieved by bistable processes that toggle like a flip-flop between a baseline and elevated-activity state, many neuronal systems have been observed experimentally to be capable of maintaining a continuum of stable states. For example, in neural integrator networks involved in the accumulation of evidence for decision making and in motor control, individual neurons have been recorded whose activity reflects the mathematical integral of their inputs; in the absence of input, these neurons sustain activity at a level proportional to the running total of their inputs. This represents an analog form of memory whose dynamics can be conceptualized through an energy landscape with a continuum of lowest-energy states. Such continuous attractor landscapes are structurally non-robust, in seeming violation of the relative robustness of biological memory systems. In this talk, I will present and compare different biologically motivated circuit motifs for the accumulation and storage of signals in short-term memory. Challenges to generating robust memory maintenance will be highlighted and potential mechanisms for ameliorating the sensitivity of memory networks to perturbations will be discussed. Funding for this work was provided by NIH R01 MH065034, NSF IIS-1208218, Simons Foundation 324260, and a UC Davis Ophthalmology Research to Prevent Blindness Grant.

Scaling Irregular Applications through Data Aggregation and Software Multithreading

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

Morari, Alessandro; Tumeo, Antonino; Chavarría-Miranda, Daniel

Bioinformatics, data analytics, semantic databases, knowledge discovery are emerging high performance application areas that exploit dynamic, linked data structures such as graphs, unbalanced trees or unstructured grids. These data structures usually are very large, requiring significantly more memory than available on single shared memory systems. Additionally, these data structures are difficult to partition on distributed memory systems. They also present poor spatial and temporal locality, thus generating unpredictable memory and network accesses. The Partitioned Global Address Space (PGAS) programming model seems suitable for these applications, because it allows using a shared memory abstraction across distributed-memory clusters. However, current PGAS languagesmore » and libraries are built to target regular remote data accesses and block transfers. Furthermore, they usually rely on the Single Program Multiple Data (SPMD) parallel control model, which is not well suited to the fine grained, dynamic and unbalanced parallelism of irregular applications. In this paper we present {\\bf GMT} (Global Memory and Threading library), a custom runtime library that enables efficient execution of irregular applications on commodity clusters. GMT integrates a PGAS data substrate with simple fork/join parallelism and provides automatic load balancing on a per node basis. It implements multi-level aggregation and lightweight multithreading to maximize memory and network bandwidth with fine-grained data accesses and tolerate long data access latencies. A key innovation in the GMT runtime is its thread specialization (workers, helpers and communication threads) that realize the overall functionality. We compare our approach with other PGAS models, such as UPC running using GASNet, and hand-optimized MPI code on a set of typical large-scale irregular applications, demonstrating speedups of an order of magnitude.« less

Memory is Not Enough: The Neurobiological Substrates of Dynamic Cognitive Reserve.

PubMed

Serra, Laura; Bruschini, Michela; Di Domenico, Carlotta; Gabrielli, Giulia Bechi; Marra, Camillo; Caltagirone, Carlo; Cercignani, Mara; Bozzali, Marco

2017-01-01

Changes in the residual memory variance are considered as a dynamic aspect of cognitive reserve (d-CR). We aimed to investigate for the first time the neural substrate associated with changes in the residual memory variance overtime in patients with amnestic mild cognitive impairment (aMCI). Thirty-four aMCI patients followed-up for 36 months and 48 healthy elderly individuals (HE) were recruited. All participants underwent 3T MRI, collecting T1-weighted images for voxel-based morphometry (VBM). They underwent an extensive neuropsychological battery, including six episodic memory tests. In patients and controls, factor analyses were used on the episodic memory scores to obtain a composite memory score (C-MS). Partial Least Square analyses were used to decompose the variance of C-MS in latent variables (LT scores), accounting for demographic variables and for the general cognitive efficiency level; linear regressions were applied on LT scores, striping off any contribution of general cognitive abilities, to obtain the residual value of memory variance, considered as an index of d-CR. LT scores and d-CR were used in discriminant analysis, in patients only. Finally, LT scores and d-CR were used as variable of interest in VBM analysis. The d-CR score was not able to correctly classify patients. In both aMCI patients and HE, LT1st and d-CR scores showed correlations with grey matter volumes in common and in specific brain areas. Using CR measures limited to assess memory function is likely less sensitive to detect the cognitive decline and predict the evolution of Alzheimer's disease. In conclusion, d-CR needs a measure of general cognition to identify conversion to Alzheimer's disease efficiently.

Fabrication and characterization of shape memory polymers at small-scales

NASA Astrophysics Data System (ADS)

Wornyo, Edem

The objective of this research is to thoroughly investigate the shape memory effect in polymers, characterize, and optimize these polymers for applications in information storage systems. Previous research effort in this field concentrated on shape memory metals for biomedical applications such as stents. Minimal work has been done on shape memory polymers; and the available work on shape memory polymers has not characterized the behaviors of this category of polymers fully. Copolymer shape memory materials based on diethylene glycol dimethacrylate (DEGDMA) crosslinker, and tert butyl acrylate (tBA) monomer are designed. The design encompasses a careful control of the backbone chemistry of the materials. Characterization methods such as dynamic mechanical analysis (DMA), differential scanning calorimetry (DSC); and novel nanoscale techniques such as atomic force microscopy (AFM), and nanoindentation are applied to this system of materials. Designed experiments are conducted on the materials to optimize spin coating conditions for thin films. Furthermore, the recovery, a key for the use of these polymeric materials for information storage, is examined in detail with respect to temperature. In sum, the overarching objectives of the proposed research are to: (i) Design shape memory polymers based on polyethylene glycol dimethacrylate (PEGDMA) and diethylene glycol dimethacrylate (DEGDMA) crosslinkers, 2-hydroxyethyl methacrylate (HEMA) and tert-butyl acrylate monomer (tBA). (ii) Utilize dynamic mechanical analysis (DMA) to comprehend the thermomechanical properties of shape memory polymers based on DEGDMA and tBA. (iii) Utilize nanoindentation and atomic force microscopy (AFM) to understand the nanoscale behavior of these SMPs, and explore the strain storage and recovery of the polymers from a deformed state. (iv) Study spin coating conditions on thin film quality with designed experiments. (iv) Apply neural networks and genetic algorithms to optimize these systems.

Strange and scary memories of the intensive care unit: a qualitative, longitudinal study inspired by Ricoeur's interpretation theory.

PubMed

Svenningsen, Helle; Egerod, Ingrid; Dreyer, Pia

2016-10-01

To describe the content of former intensive care unit patients' memories of delusions. Intensive care unit patients often have strange and frightening experiences during the critical stage of illness. Earlier studies have provided small-sample in-depth descriptions of patient experiences in intensive care unit, but large-scale studies are also needed to inform intensive care unit follow-up. The study had a qualitative design using phenomenological hermeneutic analysis inspired by Ricoeur's interpretive theory. Patients were assessed with Confusion Assessment Method of the Intensive Care Unit for delirium in intensive care unit, and after discharge, memories of delusions were described by 114 of 325 patients in face-to-face (after two weeks) and telephone interviews (after two and six months) using the Intensive Care Unit Memory Tool. Four themes emerged: the ever-present family, dynamic spaces, surviving challenges and constant motion. Memories of delusions were a vivid mix of fact and fiction, demonstrating dynamic shifts in time, place and motion, but not dependent on the presence of delirium assessed by Confusion Assessment Method of the Intensive Care Unit. Analysis based on Ricoeurian phenomenological hermeneutics provided insights into themes in intensive care unit patients' memories of delusions. More studies are needed to understand the meaning of memories of delusions, the commonality of themes and the association between delusions and delirium after an intensive care unit stay. Understanding patients' memories of delusions is beneficial to nurses caring for patients that are anxious, upset or agitated. It opens a window to the world of the patient who is unable to communicate due to intubation and general weakness. We recommend the provision of nurse-led intensive care unit follow-up enabling patients to describe and discuss their intensive care unit experiences. © 2016 John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

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

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

Memory Effect Manifested by a Boson Peak in Metallic Glass.

PubMed

Luo, P; Li, Y Z; Bai, H Y; Wen, P; Wang, W H

2016-04-29

We explore the correlation between a boson peak and structural relaxation in a typical metallic glass. Consistent with enthalpy recovery, a boson peak shows a memory effect in an aging-and-scan procedure. Single-step isothermal aging produces a monotonic decrease of enthalpy and boson peak intensity; for double-step isothermal aging, both enthalpy and boson peak intensity experience, coincidently, an incipient increase to a maximum and a subsequent decrease toward the equilibrium state. Our results indicate a direct link between slow structural relaxation and fast boson peak dynamics, which presents a profound understanding of the two dynamic behaviors in glass.

Predicting the Development of Analytical and Creative Abilities in Upper Elementary Grades

ERIC Educational Resources Information Center

Gubbels, Joyce; Segers, Eliane; Verhoeven, Ludo

2017-01-01

In some models, intelligence has been described as a multidimensional construct comprising both analytical and creative abilities. In addition, intelligence is considered to be dynamic rather than static. A structural equation model was used to examine the predictive role of cognitive (visual short-term memory, verbal short-term memory, selective…

Models Provide Specificity: Testing a Proposed Mechanism of Visual Working Memory Capacity Development

ERIC Educational Resources Information Center

Simmering, Vanessa R.; Patterson, Rebecca

2012-01-01

Numerous studies have established that visual working memory has a limited capacity that increases during childhood. However, debate continues over the source of capacity limits and its developmental increase. Simmering (2008) adapted a computational model of spatial cognitive development, the Dynamic Field Theory, to explain not only the source…

The Perceptual Root of Object-Based Storage: An Interactive Model of Perception and Visual Working Memory

ERIC Educational Resources Information Center

Gao, Tao; Gao, Zaifeng; Li, Jie; Sun, Zhongqiang; Shen, Mowei

2011-01-01

Mainstream theories of visual perception assume that visual working memory (VWM) is critical for integrating online perceptual information and constructing coherent visual experiences in changing environments. Given the dynamic interaction between online perception and VWM, we propose that how visual information is processed during visual…

Thinking Can Cause Forgetting: Memory Dynamics in Creative Problem Solving

ERIC Educational Resources Information Center

Storm, Benjamin C.; Angello, Genna; Bjork, Elizabeth Ligon

2011-01-01

Research on retrieval-induced forgetting has shown that retrieval can cause the forgetting of related or competing items in memory (Anderson, Bjork, & Bjork, 1994). In the present research, we examined whether an analogous phenomenon occurs in the context of creative problem solving. Using the Remote Associates Test (RAT; Mednick, 1962), we…

Proactive Control Processes in Event-Based Prospective Memory: Evidence from Intraindividual Variability and Ex-Gaussian Analyses

ERIC Educational Resources Information Center

Ball, B. Hunter; Brewer, Gene A.

2018-01-01

The present study implemented an individual differences approach in conjunction with response time (RT) variability and distribution modeling techniques to better characterize the cognitive control dynamics underlying ongoing task cost (i.e., slowing) and cue detection in event-based prospective memory (PM). Three experiments assessed the relation…

Memory formation during anaesthesia: plausibility of a neurophysiological basis.

PubMed

Veselis, R A

2015-07-01

As opposed to conscious, personally relevant (explicit) memories that we can recall at will, implicit (unconscious) memories are prototypical of 'hidden' memory; memories that exist, but that we do not know we possess. Nevertheless, our behaviour can be affected by these memories; in fact, these memories allow us to function in an ever-changing world. It is still unclear from behavioural studies whether similar memories can be formed during anaesthesia. Thus, a relevant question is whether implicit memory formation is a realistic possibility during anaesthesia, considering the underlying neurophysiology. A different conceptualization of memory taxonomy is presented, the serial parallel independent model of Tulving, which focuses on dynamic information processing with interactions among different memory systems rather than static classification of different types of memories. The neurophysiological basis for subliminal information processing is considered in the context of brain function as embodied in network interactions. Function of sensory cortices and thalamic activity during anaesthesia are reviewed. The role of sensory and perisensory cortices, in particular the auditory cortex, in support of memory function is discussed. Although improbable, with the current knowledge of neurophysiology one cannot rule out the possibility of memory formation during anaesthesia. © The Author 2015. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

NASA Astrophysics Data System (ADS)

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

2005-05-01

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

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

PubMed Central

Schutte, Anne R.; Spencer, John P.

2009-01-01

This study tested a dynamic field theory (DFT) of spatial working memory and an associated spatial precision hypothesis (SPH). Between three and six years of age there is a qualitative shift in how children use reference axes to remember locations: 3-year-olds’ spatial recall responses are biased toward reference axes after short memory delays, whereas 6-year-olds’ responses are biased away from reference axes. According to the DFT and the SPH, quantitative improvements over development in the precision of excitatory and inhibitory working memory processes lead to this qualitative shift. Simulations of the DFT in Experiment 1 predict that improvements in precision should cause the spatial range of targets attracted toward a reference axis to narrow gradually over development with repulsion emerging and gradually increasing until responses to most targets show biases away from the axis. Results from Experiment 2 with 3- to 5-year-olds support these predictions. Simulations of the DFT in Experiment 3 quantitatively fit the empirical results and offer insights into the neural processes underlying this developmental change. PMID:19968430

Feature to prototype transition in neural networks

NASA Astrophysics Data System (ADS)

Krotov, Dmitry; Hopfield, John

Models of associative memory with higher order (higher than quadratic) interactions, and their relationship to neural networks used in deep learning are discussed. Associative memory is conventionally described by recurrent neural networks with dynamical convergence to stable points. Deep learning typically uses feedforward neural nets without dynamics. However, a simple duality relates these two different views when applied to problems of pattern classification. From the perspective of associative memory such models deserve attention because they make it possible to store a much larger number of memories, compared to the quadratic case. In the dual description, these models correspond to feedforward neural networks with one hidden layer and unusual activation functions transmitting the activities of the visible neurons to the hidden layer. These activation functions are rectified polynomials of a higher degree rather than the rectified linear functions used in deep learning. The network learns representations of the data in terms of features for rectified linear functions, but as the power in the activation function is increased there is a gradual shift to a prototype-based representation, the two extreme regimes of pattern recognition known in cognitive psychology. Simons Center for Systems Biology.

Using chaotic artificial neural networks to model memory in the brain

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Practical Verification & Safeguard Tools for C/C++

DTIC Science & Technology

2007-11-01

735; RDDC Valcartier; novembre 2007. Ce document est le rapport final d’un projet de recherche qui a été mené en 2005-2006. Le but de ce projet... 13 2.8 On Defects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.9 Memory Management Problems... 13 2.9.1 Use of Freed Memory . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.9.2 Underallocated Memory for a

Dopaminergic neurons write and update memories with cell-type-specific rules

PubMed Central

Aso, Yoshinori; Rubin, Gerald M

2016-01-01

Associative learning is thought to involve parallel and distributed mechanisms of memory formation and storage. In Drosophila, the mushroom body (MB) is the major site of associative odor memory formation. Previously we described the anatomy of the adult MB and defined 20 types of dopaminergic neurons (DANs) that each innervate distinct MB compartments (Aso et al., 2014a, 2014b). Here we compare the properties of memories formed by optogenetic activation of individual DAN cell types. We found extensive differences in training requirements for memory formation, decay dynamics, storage capacity and flexibility to learn new associations. Even a single DAN cell type can either write or reduce an aversive memory, or write an appetitive memory, depending on when it is activated relative to odor delivery. Our results show that different learning rules are executed in seemingly parallel memory systems, providing multiple distinct circuit-based strategies to predict future events from past experiences. DOI: http://dx.doi.org/10.7554/eLife.16135.001 PMID:27441388

Calpain modulates fear memory consolidation, retrieval and reconsolidation in the hippocampus.

PubMed

Popik, Bruno; Crestani, Ana Paula; Silva, Mateus Oliveira; Quillfeldt, Jorge Alberto; de Oliveira Alvares, Lucas

2018-05-01

It has been proposed that long-lasting changes in dendritic spines provide a physical correlate for memory formation and maintenance. Spine size and shape are highly plastic, controlled by actin polymerization/depolymerization cycles. This actin dynamics are regulated by proteins such as calpain, a calcium-dependent cysteine protease that cleaves the structural cytoskeleton proteins and other targets involved in synaptic plasticity. Here, we tested whether the pharmacological inhibition of calpain in the dorsal hippocampus affects memory consolidation, retrieval and reconsolidation in rats trained in contextual fear conditioning. We first found that post-training infusion of the calpain inhibitor PD150606 impaired long-term memory consolidation, but not short-term memory. Next, we showed that pre-test infusion of the calpain inhibitor hindered memory retrieval. Finally, blocking calpain activity after memory reactivation disrupted reconsolidation. Taken together, our results show that calpain play an essential role in the hippocampus by enabling memory formation, expression and reconsolidation. Copyright © 2018 Elsevier Inc. All rights reserved.

Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance.

PubMed

Keerativittayayut, Ruedeerat; Aoki, Ryuta; Sarabi, Mitra Taghizadeh; Jimura, Koji; Nakahara, Kiyoshi

2018-06-18

Although activation/deactivation of specific brain regions have been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here we investigated time-varying functional connectivity patterns across the human brain in periods of 30-40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding. © 2018, Keerativittayayut et al.

The Need for Psychoanalysis is Alive and Well in Community Psychiatry

PubMed Central

Bell, Carl C.

1979-01-01

While the author recognizes the positive impact community psychiatry has had on postpsychotic patients by the uses of medical management and environmental manipulation, he demonstrates that there is a deficiency in the treatment of lower socioeconomic patients with neurotic illnesses. Specifically, neurotic patients tend to be given supportive therapy and psychopharmacotherapy when a form of psychoanalytic psychotherapy would be more appropriate. The author supports these contentions by presenting three cases which have a diagnosis of hysterical neurosis and which clearly demonstrate the economic, topographical, structural, dynamic, and genetic components of the psychoanalytic theory. Finally, as psychoanalytic psychotherapy is too time-consuming, the author suggests that Freud's early psychoanalytic technique of symptom removal by memory recovery be used when appropriate. PMID:439170

Preventing messaging queue deadlocks in a DMA environment

DOEpatents

Blocksome, Michael A; Chen, Dong; Gooding, Thomas; Heidelberger, Philip; Parker, Jeff

2014-01-14

Embodiments of the invention may be used to manage message queues in a parallel computing environment to prevent message queue deadlock. A direct memory access controller of a compute node may determine when a messaging queue is full. In response, the DMA may generate and interrupt. An interrupt handler may stop the DMA and swap all descriptors from the full messaging queue into a larger queue (or enlarge the original queue). The interrupt handler then restarts the DMA. Alternatively, the interrupt handler stops the DMA, allocates a memory block to hold queue data, and then moves descriptors from the full messaging queue into the allocated memory block. The interrupt handler then restarts the DMA. During a normal messaging advance cycle, a messaging manager attempts to inject the descriptors in the memory block into other messaging queues until the descriptors have all been processed.

Telomere length dynamics in human memory T cells specific for viruses causing acute or latent infections

PubMed Central

2013-01-01

Background Declining telomere length (TL) is associated with T cell senescence. While TL in naïve and memory T cells declines with increasing age, there is limited data on TL dynamics in virus-specific memory CD4+ T cells in healthy adults. We combined BrdU-labeling of virus-stimulated T cells followed with flow cytometry-fluorescent in situ hybridization for TL determination. We analyzed TL in T cells specific for several virus infections: non-recurring acute (vaccinia virus, VACV), recurring-acute (influenza A virus, IAV), and reactivating viruses (varicella-zoster virus, VZV, and cytomegalovirus, CMV) in 10 healthy subjects. Additionally, five subjects provided multiple blood samples separated by up to 10 years. Results VACV- and CMV-specific T cells had longer average TL than IAV-specific CD4+ T cells. Although most virus-specific cells were CD45RA-, we observed a minor population of BrdU+ CD45RA+ T cells characterized by long telomeres. Longitudinal analysis demonstrated a slow decline in average TL in virus-specific T cells. However, in one subject, VZV reactivation led to an increase in average TL in VZV-specific memory T cells, suggesting a conversion of longer TL cells from the naïve T cell repertoire. Conclusions TLs in memory CD4+ T cells in otherwise healthy adults are heterogeneous and follow distinct virus-specific kinetics. These findings suggests that the distribution of TL and the creation and maintenance of long TL memory T cells could be important for the persistence of long-lived T cell memory. PMID:23971624

Telomere length dynamics in human memory T cells specific for viruses causing acute or latent infections.

PubMed

O'Bryan, Joel M; Woda, Marcia; Co, Mary; Mathew, Anuja; Rothman, Alan L

2013-08-26

Declining telomere length (TL) is associated with T cell senescence. While TL in naïve and memory T cells declines with increasing age, there is limited data on TL dynamics in virus-specific memory CD4+ T cells in healthy adults. We combined BrdU-labeling of virus-stimulated T cells followed with flow cytometry-fluorescent in situ hybridization for TL determination. We analyzed TL in T cells specific for several virus infections: non-recurring acute (vaccinia virus, VACV), recurring-acute (influenza A virus, IAV), and reactivating viruses (varicella-zoster virus, VZV, and cytomegalovirus, CMV) in 10 healthy subjects. Additionally, five subjects provided multiple blood samples separated by up to 10 years. VACV- and CMV-specific T cells had longer average TL than IAV-specific CD4+ T cells. Although most virus-specific cells were CD45RA-, we observed a minor population of BrdU+ CD45RA+ T cells characterized by long telomeres. Longitudinal analysis demonstrated a slow decline in average TL in virus-specific T cells. However, in one subject, VZV reactivation led to an increase in average TL in VZV-specific memory T cells, suggesting a conversion of longer TL cells from the naïve T cell repertoire. TLs in memory CD4+ T cells in otherwise healthy adults are heterogeneous and follow distinct virus-specific kinetics. These findings suggests that the distribution of TL and the creation and maintenance of long TL memory T cells could be important for the persistence of long-lived T cell memory.

Characterization of mechanical properties of pseudoelastic shape memory alloys under harmonic excitation

NASA Astrophysics Data System (ADS)

Böttcher, J.; Jahn, M.; Tatzko, S.

2017-12-01

Pseudoelastic shape memory alloys exhibit a stress-induced phase transformation which leads to high strains during deformation of the material. The stress-strain characteristic during this thermomechanical process is hysteretic and results in the conversion of mechanical energy into thermal energy. This energy conversion allows for the use of shape memory alloys in vibration reduction. For the application of shape memory alloys as vibration damping devices a dynamic modeling of the material behavior is necessary. In this context experimentally determined material parameters which accurately represent the material behavior are essential for a reliable material model. Subject of this publication is the declaration of suitable material parameters for pseudoelastic shape memory alloys and the methodology of their identification from experimental investigations. The used test rig was specifically designed for the characterization of pseudoelastic shape memory alloys.

Temperature and electrical memory of polymer fibers

NASA Astrophysics Data System (ADS)

Yuan, Jinkai; Zakri, Cécile; Grillard, Fabienne; Neri, Wilfrid; Poulin, Philippe

2014-05-01

We report in this work studies of the shape memory behavior of polymer fibers loaded with carbon nanotubes or graphene flakes. These materials exhibit enhanced shape memory properties with the generation of a giant stress upon shape recovery. In addition, they exhibit a surprising temperature memory with a peak of generated stress at a temperature nearly equal to the temperature of programming. This temperature memory is ascribed to the presence of dynamical heterogeneities and to the intrinsic broadness of the glass transition. We present recent experiments related to observables other than mechanical properties. In particular nanocomposite fibers exhibit variations of electrical conductivity with an accurate memory. Indeed, the rate of conductivity variations during temperature changes reaches a well defined maximum at a temperature equal to the temperature of programming. Such materials are promising for future actuators that couple dimensional changes with sensing electronic functionalities.