Optimal mapping of neural-network learning on message-passing multicomputers

NASA Technical Reports Server (NTRS)

Chu, Lon-Chan; Wah, Benjamin W.

1992-01-01

A minimization of learning-algorithm completion time is sought in the present optimal-mapping study of the learning process in multilayer feed-forward artificial neural networks (ANNs) for message-passing multicomputers. A novel approximation algorithm for mappings of this kind is derived from observations of the dominance of a parallel ANN algorithm over its communication time. Attention is given to both static and dynamic mapping schemes for systems with static and dynamic background workloads, as well as to experimental results obtained for simulated mappings on multicomputers with dynamic background workloads.

Algorithm To Architecture Mapping Model (ATAMM) multicomputer operating system functional specification

NASA Technical Reports Server (NTRS)

Mielke, R.; Stoughton, J.; Som, S.; Obando, R.; Malekpour, M.; Mandala, B.

1990-01-01

A functional description of the ATAMM Multicomputer Operating System is presented. ATAMM (Algorithm to Architecture Mapping Model) is a marked graph model which describes the implementation of large grained, decomposed algorithms on data flow architectures. AMOS, the ATAMM Multicomputer Operating System, is an operating system which implements the ATAMM rules. A first generation version of AMOS which was developed for the Advanced Development Module (ADM) is described. A second generation version of AMOS being developed for the Generic VHSIC Spaceborne Computer (GVSC) is also presented.

A Simple Simulator for Multicomputer Routing Networks

DTIC Science & Technology

1992-03-05

Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that...SUBTITLE Submicron Systems Architecture Project. A Smple Simulator for Multicomputer Routing Networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c

Prevention of design flaws in multicomputer systems

NASA Technical Reports Server (NTRS)

1975-01-01

Multicomputer configurations and redundancy management techniques used in various airborne systems were investigated to determine methods to prevent and/or treat generic design flaws. The findings are intended for use in the design of a computer system for use in the space shuttle orbiter.

Automatic data partitioning on distributed memory multicomputers. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Gupta, Manish

1992-01-01

Distributed-memory parallel computers are increasingly being used to provide high levels of performance for scientific applications. Unfortunately, such machines are not very easy to program. A number of research efforts seek to alleviate this problem by developing compilers that take over the task of generating communication. The communication overheads and the extent of parallelism exploited in the resulting target program are determined largely by the manner in which data is partitioned across different processors of the machine. Most of the compilers provide no assistance to the programmer in the crucial task of determining a good data partitioning scheme. A novel approach is presented, the constraints-based approach, to the problem of automatic data partitioning for numeric programs. In this approach, the compiler identifies some desirable requirements on the distribution of various arrays being referenced in each statement, based on performance considerations. These desirable requirements are referred to as constraints. For each constraint, the compiler determines a quality measure that captures its importance with respect to the performance of the program. The quality measure is obtained through static performance estimation, without actually generating the target data-parallel program with explicit communication. Each data distribution decision is taken by combining all the relevant constraints. The compiler attempts to resolve any conflicts between constraints such that the overall execution time of the parallel program is minimized. This approach has been implemented as part of a compiler called Paradigm, that accepts Fortran 77 programs, and specifies the partitioning scheme to be used for each array in the program. We have obtained results on some programs taken from the Linpack and Eispack libraries, and the Perfect Benchmarks. These results are quite promising, and demonstrate the feasibility of automatic data partitioning for a significant class of scientific application programs with regular computations.

Empirical comparison of heuristic load distribution in point-to-point multicomputer networks

NASA Technical Reports Server (NTRS)

Grunwald, Dirk C.; Nazief, Bobby A. A.; Reed, Daniel A.

1990-01-01

The study compared several load placement algorithms using instrumented programs and synthetic program models. Salient characteristics of these program traces (total computation time, total number of messages sent, and average message time) span two orders of magnitude. Load distribution algorithms determine the initial placement for processes, a precursor to the more general problem of load redistribution. It is found that desirable workload distribution strategies will place new processes globally, rather than locally, to spread processes rapidly, but that local information should be used to refine global placement.

An Adaptive Flow Solver for Air-Borne Vehicles Undergoing Time-Dependent Motions/Deformations

NASA Technical Reports Server (NTRS)

Singh, Jatinder; Taylor, Stephen

1997-01-01

This report describes a concurrent Euler flow solver for flows around complex 3-D bodies. The solver is based on a cell-centered finite volume methodology on 3-D unstructured tetrahedral grids. In this algorithm, spatial discretization for the inviscid convective term is accomplished using an upwind scheme. A localized reconstruction is done for flow variables which is second order accurate. Evolution in time is accomplished using an explicit three-stage Runge-Kutta method which has second order temporal accuracy. This is adapted for concurrent execution using another proven methodology based on concurrent graph abstraction. This solver operates on heterogeneous network architectures. These architectures may include a broad variety of UNIX workstations and PCs running Windows NT, symmetric multiprocessors and distributed-memory multi-computers. The unstructured grid is generated using commercial grid generation tools. The grid is automatically partitioned using a concurrent algorithm based on heat diffusion. This results in memory requirements that are inversely proportional to the number of processors. The solver uses automatic granularity control and resource management techniques both to balance load and communication requirements, and deal with differing memory constraints. These ideas are again based on heat diffusion. Results are subsequently combined for visualization and analysis using commercial CFD tools. Flow simulation results are demonstrated for a constant section wing at subsonic, transonic, and a supersonic case. These results are compared with experimental data and numerical results of other researchers. Performance results are under way for a variety of network topologies.

Global synchronization algorithms for the Intel iPSC/860

NASA Technical Reports Server (NTRS)

Seidel, Steven R.; Davis, Mark A.

1992-01-01

In a distributed memory multicomputer that has no global clock, global processor synchronization can only be achieved through software. Global synchronization algorithms are used in tridiagonal systems solvers, CFD codes, sequence comparison algorithms, and sorting algorithms. They are also useful for event simulation, debugging, and for solving mutual exclusion problems. For the Intel iPSC/860 in particular, global synchronization can be used to ensure the most effective use of the communication network for operations such as the shift, where each processor in a one-dimensional array or ring concurrently sends a message to its right (or left) neighbor. Three global synchronization algorithms are considered for the iPSC/860: the gysnc() primitive provided by Intel, the PICL primitive sync0(), and a new recursive doubling synchronization (RDS) algorithm. The performance of these algorithms is compared to the performance predicted by communication models of both the long and forced message protocols. Measurements of the cost of shift operations preceded by global synchronization show that the RDS algorithm always synchronizes the nodes more precisely and costs only slightly more than the other two algorithms.

Execution of parallel algorithms on a heterogeneous multicomputer

NASA Astrophysics Data System (ADS)

Isenstein, Barry S.; Greene, Jonathon

1995-04-01

Many aerospace/defense sensing and dual-use applications require high-performance computing, extensive high-bandwidth interconnect and realtime deterministic operation. This paper will describe the architecture of a scalable multicomputer that includes DSP and RISC processors. A single chassis implementation is capable of delivering in excess of 10 GFLOPS of DSP processing power with 2 Gbytes/s of realtime sensor I/O. A software approach to implementing parallel algorithms called the Parallel Application System (PAS) is also presented. An example of applying PAS to a DSP application is shown.

k-RP*{sub s}: A scalable distributed data structure for high-performance multi-attribute access

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

Litwin, W.; Neimat, M.A.

k-RP*{sub s} is a new data structure for scalable multicomputer files with multi-attribute (k-d) keys. We discuss the k-RP*{sub s} file evolution and search algorithms. Performance analysis shows that a k-RP*{sub s} file can be much larger and orders of magnitude faster than a traditional k-d file. The speed-up is especially important for range and partial match searches that are often impractical with traditional k-d files. This opens up a new perspective for many applications.

Common spaceborne multicomputer operating system and development environment

NASA Technical Reports Server (NTRS)

Craymer, L. G.; Lewis, B. F.; Hayes, P. J.; Jones, R. L.

1994-01-01

A preliminary technical specification for a multicomputer operating system is developed. The operating system is targeted for spaceborne flight missions and provides a broad range of real-time functionality, dynamic remote code-patching capability, and system fault tolerance and long-term survivability features. Dataflow concepts are used for representing application algorithms. Functional features are included to ensure real-time predictability for a class of algorithms which require data-driven execution on an iterative steady state basis. The development environment supports the development of algorithm code, design of control parameters, performance analysis, simulation of real-time dataflow applications, and compiling and downloading of the resulting application.

Performance of a Heterogeneous Grid Partitioner for N-body Applications

NASA Technical Reports Server (NTRS)

Harvey, Daniel J.; Das, Sajal K.; Biswas, Rupak

2003-01-01

An important characteristic of distributed grids is that they allow geographically separated multicomputers to be tied together in a transparent virtual environment to solve large-scale computational problems. However, many of these applications require effective runtime load balancing for the resulting solutions to be viable. Recently, we developed a latency tolerant partitioner, called MinEX, specifically for use in distributed grid environments. This paper compares the performance of MinEX to that of METIS, a popular multilevel family of partitioners, using simulated heterogeneous grid configurations. A solver for the classical N-body problem is implemented to provide a framework for the comparisons. Experimental results show that MinEX provides superior quality partitions while being competitive to METIS in speed of execution.

Measurement and analysis of operating system fault tolerance

NASA Technical Reports Server (NTRS)

Lee, I.; Tang, D.; Iyer, R. K.

1992-01-01

This paper demonstrates a methodology to model and evaluate the fault tolerance characteristics of operational software. The methodology is illustrated through case studies on three different operating systems: the Tandem GUARDIAN fault-tolerant system, the VAX/VMS distributed system, and the IBM/MVS system. Measurements are made on these systems for substantial periods to collect software error and recovery data. In addition to investigating basic dependability characteristics such as major software problems and error distributions, we develop two levels of models to describe error and recovery processes inside an operating system and on multiple instances of an operating system running in a distributed environment. Based on the models, reward analysis is conducted to evaluate the loss of service due to software errors and the effect of the fault-tolerance techniques implemented in the systems. Software error correlation in multicomputer systems is also investigated.

Efficient Memory Access with NumPy Global Arrays using Local Memory Access

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

Daily, Jeffrey A.; Berghofer, Dan C.

This paper discusses the work completed working with Global Arrays of data on distributed multi-computer systems and improving their performance. The tasks completed were done at Pacific Northwest National Laboratory in the Science Undergrad Laboratory Internship program in the summer of 2013 for the Data Intensive Computing Group in the Fundamental and Computational Sciences DIrectorate. This work was done on the Global Arrays Toolkit developed by this group. This toolkit is an interface for programmers to more easily create arrays of data on networks of computers. This is useful because scientific computation is often done on large amounts of datamore » sometimes so large that individual computers cannot hold all of it. This data is held in array form and can best be processed on supercomputers which often consist of a network of individual computers doing their computation in parallel. One major challenge for this sort of programming is that operations on arrays on multiple computers is very complex and an interface is needed so that these arrays seem like they are on a single computer. This is what global arrays does. The work done here is to use more efficient operations on that data that requires less copying of data to be completed. This saves a lot of time because copying data on many different computers is time intensive. The way this challenge was solved is when data to be operated on with binary operations are on the same computer, they are not copied when they are accessed. When they are on separate computers, only one set is copied when accessed. This saves time because of less copying done although more data access operations were done.« less

Communication overhead on the Intel Paragon, IBM SP2 and Meiko CS-2

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.

1995-01-01

Interprocessor communication overhead is a crucial measure of the power of parallel computing systems-its impact can severely limit the performance of parallel programs. This report presents measurements of communication overhead on three contemporary commercial multicomputer systems: the Intel Paragon, the IBM SP2 and the Meiko CS-2. In each case the time to communicate between processors is presented as a function of message length. The time for global synchronization and memory access is discussed. The performance of these machines in emulating hypercubes and executing random pairwise exchanges is also investigated. It is shown that the interprocessor communication time depends heavily on the specific communication pattern required. These observations contradict the commonly held belief that communication overhead on contemporary machines is independent of the placement of tasks on processors. The information presented in this report permits the evaluation of the efficiency of parallel algorithm implementations against standard baselines.

Advanced information processing system: Local system services

NASA Technical Reports Server (NTRS)

Burkhardt, Laura; Alger, Linda; Whittredge, Roy; Stasiowski, Peter

1989-01-01

The Advanced Information Processing System (AIPS) is a multi-computer architecture composed of hardware and software building blocks that can be configured to meet a broad range of application requirements. The hardware building blocks are fault-tolerant, general-purpose computers, fault-and damage-tolerant networks (both computer and input/output), and interfaces between the networks and the computers. The software building blocks are the major software functions: local system services, input/output, system services, inter-computer system services, and the system manager. The foundation of the local system services is an operating system with the functions required for a traditional real-time multi-tasking computer, such as task scheduling, inter-task communication, memory management, interrupt handling, and time maintenance. Resting on this foundation are the redundancy management functions necessary in a redundant computer and the status reporting functions required for an operator interface. The functional requirements, functional design and detailed specifications for all the local system services are documented.

Performance and evaluation of real-time multicomputer control systems

NASA Technical Reports Server (NTRS)

Shin, K. G.

1983-01-01

New performance measures, detailed examples, modeling of error detection process, performance evaluation of rollback recovery methods, experiments on FTMP, and optimal size of an NMR cluster are discussed.

Performance and evaluation of real-time multicomputer control systems

NASA Technical Reports Server (NTRS)

Shin, K. G.

1985-01-01

Three experiments on fault tolerant multiprocessors (FTMP) were begun. They are: (1) measurement of fault latency in FTMP; (2) validation and analysis of FTMP synchronization protocols; and investigation of error propagation in FTMP.

A Performance Prediction Model for a Fault-Tolerant Computer During Recovery and Restoration. Ph.D. Thesis Report, 1 Jan. - 31 Dec. 1992

NASA Technical Reports Server (NTRS)

Stoughton, John W.; Obando, Rodrigo A.

1993-01-01

The modeling and design of a fault-tolerant multiprocessor system is addressed. In particular, the behavior of the system during recovery and restoration after a fault has occurred is investigated. Given that a multicomputer system is designed using the Algorithm to Architecture to Mapping Model (ATAMM), and that a fault (death of a computing resource) occurs during its normal steady-state operation, a model is presented as a viable research tool for predicting the performance bounds of the system during its recovery and restoration phases. Furthermore, the bounds of the performance behavior of the system during this transient mode can be assessed. These bounds include: time to recover from the fault (t(sub rec)), time to restore the system (t(sub rec)) and whether there is a permanent delay in the system's Time Between Input and Output (TBIO) after the system has reached a steady state. An implementation of an ATAMM based computer was developed with the Generic VHSIC Spaceborne Computer (GVSC) as the target system. A simulation of the GVSC was also written based on the code used in ATAMM Multicomputer Operating System (AMOS). The simulation is in turn used to validate the new model in the usefulness and accuracy in tracking the propagation of the delay through the system and predicting the behavior in the transient state of recovery and restoration. The model is validated as an accurate method to predict the transient behavior of an ATAMM based multicomputer during recovery and restoration.

Interactive shape metamorphosis

NASA Technical Reports Server (NTRS)

Chen, David T.; State, Andrei; Banks, David

1994-01-01

A technique for controlled metamorphosis between surfaces in 3-space is described. Well-understood techniques to produce shape metamorphosis between models in a 2D parametric space is applied. The user selects morphable features interactively, and the morphing process executes in real time on a high-performance graphics multicomputer.

A Model for Speedup of Parallel Programs

DTIC Science & Technology

1997-01-01

Sanjeev. K Setia . The interaction between mem- ory allocation and adaptive partitioning in message- passing multicomputers. In IPPS 󈨣 Workshop on Job...Scheduling Strategies for Parallel Processing, pages 89{99, 1995. [15] Sanjeev K. Setia and Satish K. Tripathi. A compar- ative analysis of static

Dust Dynamics in Protoplanetary Disks: Parallel Computing with PVM

NASA Astrophysics Data System (ADS)

de La Fuente Marcos, Carlos; Barge, Pierre; de La Fuente Marcos, Raúl

2002-03-01

We describe a parallel version of our high-order-accuracy particle-mesh code for the simulation of collisionless protoplanetary disks. We use this code to carry out a massively parallel, two-dimensional, time-dependent, numerical simulation, which includes dust particles, to study the potential role of large-scale, gaseous vortices in protoplanetary disks. This noncollisional problem is easy to parallelize on message-passing multicomputer architectures. We performed the simulations on a cache-coherent nonuniform memory access Origin 2000 machine, using both the parallel virtual machine (PVM) and message-passing interface (MPI) message-passing libraries. Our performance analysis suggests that, for our problem, PVM is about 25% faster than MPI. Using PVM and MPI made it possible to reduce CPU time and increase code performance. This allows for simulations with a large number of particles (N ~ 105-106) in reasonable CPU times. The performances of our implementation of the pa! rallel code on an Origin 2000 supercomputer are presented and discussed. They exhibit very good speedup behavior and low load unbalancing. Our results confirm that giant gaseous vortices can play a dominant role in giant planet formation.

Quick realization of a ship steering training simulation system by virtual reality

NASA Astrophysics Data System (ADS)

Sun, Jifeng; Zhi, Pinghua; Nie, Weiguo

2003-09-01

This paper addresses two problems of a ship handling simulator. Firstly, 360 scene generation, especially 3D dynamic sea wave modeling, is described. Secondly, a multi-computer complementation of ship handling simulator. This paper also gives the experimental results of the proposed ship handling simulator.

CSM parallel structural methods research

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.

1989-01-01

Parallel structural methods, research team activities, advanced architecture computers for parallel computational structural mechanics (CSM) research, the FLEX/32 multicomputer, a parallel structural analyses testbed, blade-stiffened aluminum panel with a circular cutout and the dynamic characteristics of a 60 meter, 54-bay, 3-longeron deployable truss beam are among the topics discussed.

Design of a modular digital computer system

NASA Technical Reports Server (NTRS)

1980-01-01

A Central Control Element (CCE) module which controls the Automatically Reconfigurable Modular System (ARMS) and allows both redundant processing and multi-computing in the same computer with real time mode switching, is discussed. The same hardware is used for either reliability enhancement, speed enhancement, or for a combination of both.

An assessment of the connection machine

NASA Technical Reports Server (NTRS)

Schreiber, Robert

1990-01-01

The CM-2 is an example of a connection machine. The strengths and problems of this implementation are considered as well as important issues in the architecture and programming environment of connection machines in general. These are contrasted to the same issues in Multiple Instruction/Multiple Data (MIMD) microprocessors and multicomputers.

A High Performance Computer Architecture for Embedded And/Or Multi-Computer Applications

DTIC Science & Technology

1990-09-01

commercially available, real - time operating system . CHOICES and ARTS are real-time operating systems developed at the University of Illinois and CMU...respectively. Selection of a real - time operating system will be made in the next phase of the project. U BIBLIOGRAPHY U Wulf, Wm. A. The WM Computer

Parallel computer vision

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

Uhr, L.

1987-01-01

This book is written by research scientists involved in the development of massively parallel, but hierarchically structured, algorithms, architectures, and programs for image processing, pattern recognition, and computer vision. The book gives an integrated picture of the programs and algorithms that are being developed, and also of the multi-computer hardware architectures for which these systems are designed.

A network flow model for load balancing in circuit-switched multicomputers

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.

1990-01-01

In multicomputers that utilize circuit switching or wormhole routing, communication overhead depends largely on link contention - the variation due to distance between nodes is negligible. This has a major impact on the load balancing problem. In this case, there are some nodes with excess load (sources) and others with deficit load (sinks) and it is required to find a matching of sources to sinks that avoids contention. The problem is made complex by the hardwired routing on currently available machines: the user can control only which nodes communicate but not how the messages are routed. Network flow models of message flow in the mesh and the hypercube were developed to solve this problem. The crucial property of these models is the correspondence between minimum cost flows and correctly routed messages. To solve a given load balancing problem, a minimum cost flow algorithm is applied to the network. This permits one to determine efficiently a maximum contention free matching of sources to sinks which, in turn, tells one how much of the given imbalance can be eliminated without contention.

Implementation of a cone-beam backprojection algorithm on the cell broadband engine processor

NASA Astrophysics Data System (ADS)

Bockenbach, Olivier; Knaup, Michael; Kachelrieß, Marc

2007-03-01

Tomographic image reconstruction is computationally very demanding. In all cases the backprojection represents the performance bottleneck due to the high operational count and due to the high demand put on the memory subsystem. In the past, solving this problem has lead to the implementation of specific architectures, connecting Application Specific Integrated Circuits (ASICs) or Field Programmable Gate Arrays (FPGAs) to memory through dedicated high speed busses. More recently, there have also been attempt to use Graphic Processing Units (GPUs) to perform the backprojection step. Originally aimed at the gaming market, IBM, Toshiba and Sony have introduced the Cell Broadband Engine (CBE) processor, often considered as a multicomputer on a chip. Clocked at 3 GHz, the Cell allows for a theoretical performance of 192 GFlops and a peak data transfer rate over the internal bus of 200 GB/s. This performance indeed makes the Cell a very attractive architecture for implementing tomographic image reconstruction algorithms. In this study, we investigate the relative performance of a perspective backprojection algorithm when implemented on a standard PC and on the Cell processor. We compare these results to the performance achievable with FPGAs based boards and high end GPUs. The cone-beam backprojection performance was assessed by backprojecting a full circle scan of 512 projections of 1024x1024 pixels into a volume of size 512x512x512 voxels. It took 3.2 minutes on the PC (single CPU) and is as fast as 13.6 seconds on the Cell.

A real-time diagnostic and performance monitor for UNIX. M.S. Thesis

NASA Technical Reports Server (NTRS)

Dong, Hongchao

1992-01-01

There are now over one million UNIX sites and the pace at which new installations are added is steadily increasing. Along with this increase, comes a need to develop simple efficient, effective and adaptable ways of simultaneously collecting real-time diagnostic and performance data. This need exists because distributed systems can give rise to complex failure situations that are often un-identifiable with single-machine diagnostic software. The simultaneous collection of error and performance data is also important for research in failure prediction and error/performance studies. This paper introduces a portable method to concurrently collect real-time diagnostic and performance data on a distributed UNIX system. The combined diagnostic/performance data collection is implemented on a distributed multi-computer system using SUN4's as servers. The approach uses existing UNIX system facilities to gather system dependability information such as error and crash reports. In addition, performance data such as CPU utilization, disk usage, I/O transfer rate and network contention is also collected. In the future, the collected data will be used to identify dependability bottlenecks and to analyze the impact of failures on system performance.

Fault Tolerance for VLSI Multicomputers

DTIC Science & Technology

1985-08-01

that consists of hundreds or thousands of VLSI computation nodes interconnected by dedicated links. Some important applications of high-end computers...technology, and intended applications . A proposed fault tolerance scheme combines hardware that performs error detection and system-level protocols for...order to recover from the error and resume correct operation, a valid system state must be restored. A low-overhead, application -transparent error

A Performance Prediction Model for a Fault-Tolerant Computer During Recovery and Restoration

NASA Technical Reports Server (NTRS)

Obando, Rodrigo A.; Stoughton, John W.

1995-01-01

The modeling and design of a fault-tolerant multiprocessor system is addressed. Of interest is the behavior of the system during recovery and restoration after a fault has occurred. The multiprocessor systems are based on the Algorithm to Architecture Mapping Model (ATAMM) and the fault considered is the death of a processor. The developed model is useful in the determination of performance bounds of the system during recovery and restoration. The performance bounds include time to recover from the fault, time to restore the system, and determination of any permanent delay in the input to output latency after the system has regained steady state. Implementation of an ATAMM based computer was developed for a four-processor generic VHSIC spaceborne computer (GVSC) as the target system. A simulation of the GVSC was also written on the code used in the ATAMM Multicomputer Operating System (AMOS). The simulation is used to verify the new model for tracking the propagation of the delay through the system and predicting the behavior of the transient state of recovery and restoration. The model is shown to accurately predict the transient behavior of an ATAMM based multicomputer during recovery and restoration.

MAX - An advanced parallel computer for space applications

NASA Technical Reports Server (NTRS)

Lewis, Blair F.; Bunker, Robert L.

1991-01-01

MAX is a fault-tolerant multicomputer hardware and software architecture designed to meet the needs of NASA spacecraft systems. It consists of conventional computing modules (computers) connected via a dual network topology. One network is used to transfer data among the computers and between computers and I/O devices. This network's topology is arbitrary. The second network operates as a broadcast medium for operating system synchronization messages and supports the operating system's Byzantine resilience. A fully distributed operating system supports multitasking in an asynchronous event and data driven environment. A large grain dataflow paradigm is used to coordinate the multitasking and provide easy control of concurrency. It is the basis of the system's fault tolerance and allows both static and dynamical location of tasks. Redundant execution of tasks with software voting of results may be specified for critical tasks. The dataflow paradigm also supports simplified software design, test and maintenance. A unique feature is a method for reliably patching code in an executing dataflow application.

A Prototype Two-Level Multicomputer Study

DTIC Science & Technology

1999-01-01

Wakeup : When this input is asserted, the wakeJnt bit in the special register ISR (Interrupt Status Register) is set. 43 MYRINET SAN INTERFACE Pin...including the double-word pointed to by RMC, the headJnt bit of ISR is set (page 10). RMW Receive-Message Header Wakeup : This is the same physical register...Register) are both equal to 1. WAKE synch. I Wakeup : When this input is asserted, the wakeJnt bit in the special register ISR (Interrupt Status

Failure analysis and modeling of a multicomputer system. M.S. Thesis

NASA Technical Reports Server (NTRS)

Subramani, Sujatha Srinivasan

1990-01-01

This thesis describes the results of an extensive measurement-based analysis of real error data collected from a 7-machine DEC VaxCluster multicomputer system. In addition to evaluating basic system error and failure characteristics, we develop reward models to analyze the impact of failures and errors on the system. The results show that, although 98 percent of errors in the shared resources recover, they result in 48 percent of all system failures. The analysis of rewards shows that the expected reward rate for the VaxCluster decreases to 0.5 in 100 days for a 3 out of 7 model, which is well over a 100 times that for a 7-out-of-7 model. A comparison of the reward rates for a range of k-out-of-n models indicates that the maximum increase in reward rate (0.25) occurs in going from the 6-out-of-7 model to the 5-out-of-7 model. The analysis also shows that software errors have the lowest reward (0.2 vs. 0.91 for network errors). The large loss in reward rate for software errors is due to the fact that a large proportion (94 percent) of software errors lead to failure. In comparison, the high reward rate for network errors is due to fast recovery from a majority of these errors (median recovery duration is 0 seconds).

Hyperswitch Network For Hypercube Computer

NASA Technical Reports Server (NTRS)

Chow, Edward; Madan, Herbert; Peterson, John

1989-01-01

Data-driven dynamic switching enables high speed data transfer. Proposed hyperswitch network based on mixed static and dynamic topologies. Routing header modified in response to congestion or faults encountered as path established. Static topology meets requirement if nodes have switching elements that perform necessary routing header revisions dynamically. Hypercube topology now being implemented with switching element in each computer node aimed at designing very-richly-interconnected multicomputer system. Interconnection network connects great number of small computer nodes, using fixed hypercube topology, characterized by point-to-point links between nodes.

Kanerva's sparse distributed memory: An associative memory algorithm well-suited to the Connection Machine

NASA Technical Reports Server (NTRS)

Rogers, David

1988-01-01

The advent of the Connection Machine profoundly changes the world of supercomputers. The highly nontraditional architecture makes possible the exploration of algorithms that were impractical for standard Von Neumann architectures. Sparse distributed memory (SDM) is an example of such an algorithm. Sparse distributed memory is a particularly simple and elegant formulation for an associative memory. The foundations for sparse distributed memory are described, and some simple examples of using the memory are presented. The relationship of sparse distributed memory to three important computational systems is shown: random-access memory, neural networks, and the cerebellum of the brain. Finally, the implementation of the algorithm for sparse distributed memory on the Connection Machine is discussed.

Implementation of Ada protocols on Mil-STD-1553 B data bus

NASA Technical Reports Server (NTRS)

Ruhman, Smil; Rosemberg, Flavia

1986-01-01

Standardization activity of data communication in avionic systems started in 1968 for the purpose of total system integration and the elimination of heavy wire bundles carrying signals between various subassemblies. The growing complexity of avionic systems is straining the capabilities of MIL-STD-1553 B (first issued in 1973), but a much greater challenge to it is posed by Ada, the standard language adopted for real-time, computer embedded-systems. Hardware implementation of Ada communication protocols in a contention/token bus or token ring network is proposed. However, during the transition period when the current command/response multiplex data bus is still flourishing and the development environment for distributed multi-computer Ada systems is as yet lacking, a temporary accomodation of the standard language with the standard bus could be very useful and even highly desirable. By concentrating all status informtion and decisions at the bus controller, it was found to be possible to construct an elegant and efficient harware impelementation of the Ada protocols at the bus interface. This solution is discussed.

Failure analysis and modeling of a VAXcluster system

NASA Technical Reports Server (NTRS)

Tang, Dong; Iyer, Ravishankar K.; Subramani, Sujatha S.

1990-01-01

This paper discusses the results of a measurement-based analysis of real error data collected from a DEC VAXcluster multicomputer system. In addition to evaluating basic system dependability characteristics such as error and failure distributions and hazard rates for both individual machines and for the VAXcluster, reward models were developed to analyze the impact of failures on the system as a whole. The results show that more than 46 percent of all failures were due to errors in shared resources. This is despite the fact that these errors have a recovery probability greater than 0.99. The hazard rate calculations show that not only errors, but also failures occur in bursts. Approximately 40 percent of all failures occur in bursts and involved multiple machines. This result indicates that correlated failures are significant. Analysis of rewards shows that software errors have the lowest reward (0.05 vs 0.74 for disk errors). The expected reward rate (reliability measure) of the VAXcluster drops to 0.5 in 18 hours for the 7-out-of-7 model and in 80 days for the 3-out-of-7 model.

Over-Distribution in Source Memory

PubMed Central

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

2012-01-01

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

An assessment of the real-time application capabilities of the SIFT computer system

NASA Technical Reports Server (NTRS)

Butler, R. W.

1982-01-01

The real-time capabilities of the SIFT computer system, a highly reliable multicomputer architecture developed to support the flight controls of a relaxed static stability aircraft, are discussed. The SIFT computer system was designed to meet extremely high reliability requirements and to facilitate a formal proof of its correctness. Although SIFT represents a significant achievement in fault-tolerant system research it presents an unusual and restrictive interface to its users. The characteristics of the user interface and its impact on application system design are assessed.

Multiscale Methods, Parallel Computation, and Neural Networks for Real-Time Computer Vision.

NASA Astrophysics Data System (ADS)

Battiti, Roberto

1990-01-01

This thesis presents new algorithms for low and intermediate level computer vision. The guiding ideas in the presented approach are those of hierarchical and adaptive processing, concurrent computation, and supervised learning. Processing of the visual data at different resolutions is used not only to reduce the amount of computation necessary to reach the fixed point, but also to produce a more accurate estimation of the desired parameters. The presented adaptive multiple scale technique is applied to the problem of motion field estimation. Different parts of the image are analyzed at a resolution that is chosen in order to minimize the error in the coefficients of the differential equations to be solved. Tests with video-acquired images show that velocity estimation is more accurate over a wide range of motion with respect to the homogeneous scheme. In some cases introduction of explicit discontinuities coupled to the continuous variables can be used to avoid propagation of visual information from areas corresponding to objects with different physical and/or kinematic properties. The human visual system uses concurrent computation in order to process the vast amount of visual data in "real -time." Although with different technological constraints, parallel computation can be used efficiently for computer vision. All the presented algorithms have been implemented on medium grain distributed memory multicomputers with a speed-up approximately proportional to the number of processors used. A simple two-dimensional domain decomposition assigns regions of the multiresolution pyramid to the different processors. The inter-processor communication needed during the solution process is proportional to the linear dimension of the assigned domain, so that efficiency is close to 100% if a large region is assigned to each processor. Finally, learning algorithms are shown to be a viable technique to engineer computer vision systems for different applications starting from multiple-purpose modules. In the last part of the thesis a well known optimization method (the Broyden-Fletcher-Goldfarb-Shanno memoryless quasi -Newton method) is applied to simple classification problems and shown to be superior to the "error back-propagation" algorithm for numerical stability, automatic selection of parameters, and convergence properties.

A general purpose subroutine for fast fourier transform on a distributed memory parallel machine

NASA Technical Reports Server (NTRS)

Dubey, A.; Zubair, M.; Grosch, C. E.

1992-01-01

One issue which is central in developing a general purpose Fast Fourier Transform (FFT) subroutine on a distributed memory parallel machine is the data distribution. It is possible that different users would like to use the FFT routine with different data distributions. Thus, there is a need to design FFT schemes on distributed memory parallel machines which can support a variety of data distributions. An FFT implementation on a distributed memory parallel machine which works for a number of data distributions commonly encountered in scientific applications is presented. The problem of rearranging the data after computing the FFT is also addressed. The performance of the implementation on a distributed memory parallel machine Intel iPSC/860 is evaluated.

The application of a sparse, distributed memory to the detection, identification and manipulation of physical objects

NASA Technical Reports Server (NTRS)

Kanerva, P.

1986-01-01

To determine the relation of the sparse, distributed memory to other architectures, a broad review of the literature was made. The memory is called a pattern memory because they work with large patterns of features (high-dimensional vectors). A pattern is stored in a pattern memory by distributing it over a large number of storage elements and by superimposing it over other stored patterns. A pattern is retrieved by mathematical or statistical reconstruction from the distributed elements. Three pattern memories are discussed.

Sparse distributed memory overview

NASA Technical Reports Server (NTRS)

Raugh, Mike

1990-01-01

The Sparse Distributed Memory (SDM) project is investigating the theory and applications of massively parallel computing architecture, called sparse distributed memory, that will support the storage and retrieval of sensory and motor patterns characteristic of autonomous systems. The immediate objectives of the project are centered in studies of the memory itself and in the use of the memory to solve problems in speech, vision, and robotics. Investigation of methods for encoding sensory data is an important part of the research. Examples of NASA missions that may benefit from this work are Space Station, planetary rovers, and solar exploration. Sparse distributed memory offers promising technology for systems that must learn through experience and be capable of adapting to new circumstances, and for operating any large complex system requiring automatic monitoring and control. Sparse distributed memory is a massively parallel architecture motivated by efforts to understand how the human brain works. Sparse distributed memory is an associative memory, able to retrieve information from cues that only partially match patterns stored in the memory. It is able to store long temporal sequences derived from the behavior of a complex system, such as progressive records of the system's sensory data and correlated records of the system's motor controls.

Very fast motion planning for highly dexterous-articulated robots

NASA Technical Reports Server (NTRS)

Challou, Daniel J.; Gini, Maria; Kumar, Vipin

1994-01-01

Due to the inherent danger of space exploration, the need for greater use of teleoperated and autonomous robotic systems in space-based applications has long been apparent. Autonomous and semi-autonomous robotic devices have been proposed for carrying out routine functions associated with scientific experiments aboard the shuttle and space station. Finally, research into the use of such devices for planetary exploration continues. To accomplish their assigned tasks, all such autonomous and semi-autonomous devices will require the ability to move themselves through space without hitting themselves or the objects which surround them. In space it is important to execute the necessary motions correctly when they are first attempted because repositioning is expensive in terms of both time and resources (e.g., fuel). Finally, such devices will have to function in a variety of different environments. Given these constraints, a means for fast motion planning to insure the correct movement of robotic devices would be ideal. Unfortunately, motion planning algorithms are rarely used in practice because of their computational complexity. Fast methods have been developed for detecting imminent collisions, but the more general problem of motion planning remains computationally intractable. However, in this paper we show how the use of multicomputers and appropriate parallel algorithms can substantially reduce the time required to synthesize paths for dexterous articulated robots with a large number of joints. We have developed a parallel formulation of the Randomized Path Planner proposed by Barraquand and Latombe. We have shown that our parallel formulation is capable of formulating plans in a few seconds or less on various parallel architectures including: the nCUBE2 multicomputer with up to 1024 processors (nCUBE2 is a registered trademark of the nCUBE corporation), and a network of workstations.

Neural networks and logical reasoning systems: a translation table.

PubMed

Martins, J; Mendes, R V

2001-04-01

A correspondence is established between the basic elements of logic reasoning systems (knowledge bases, rules, inference and queries) and the structure and dynamical evolution laws of neural networks. The correspondence is pictured as a translation dictionary which might allow to go back and forth between symbolic and network formulations, a desirable step in learning-oriented systems and multicomputer networks. In the framework of Horn clause logics, it is found that atomic propositions with n arguments correspond to nodes with nth order synapses, rules to synaptic intensity constraints, forward chaining to synaptic dynamics and queries either to simple node activation or to a query tensor dynamics.

Immunological memory is associative

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

Smith, D.J.; Forrest, S.; Perelson, A.S.

1996-12-31

The purpose of this paper is to show that immunological memory is an associative and robust memory that belongs to the class of sparse distributed memories. This class of memories derives its associative and robust nature by sparsely sampling the input space and distributing the data among many independent agents. Other members of this class include a model of the cerebellar cortex and Sparse Distributed Memory (SDM). First we present a simplified account of the immune response and immunological memory. Next we present SDM, and then we show the correlations between immunological memory and SDM. Finally, we show how associativemore » recall in the immune response can be both beneficial and detrimental to the fitness of an individual.« less

Distributed representations in memory: Insights from functional brain imaging

PubMed Central

Rissman, Jesse; Wagner, Anthony D.

2015-01-01

Forging new memories for facts and events, holding critical details in mind on a moment-to-moment basis, and retrieving knowledge in the service of current goals all depend on a complex interplay between neural ensembles throughout the brain. Over the past decade, researchers have increasingly leveraged powerful analytical tools (e.g., multi-voxel pattern analysis) to decode the information represented within distributed fMRI activity patterns. In this review, we discuss how these methods can sensitively index neural representations of perceptual and semantic content, and how leverage on the engagement of distributed representations provides unique insights into distinct aspects of memory-guided behavior. We emphasize that, in addition to characterizing the contents of memories, analyses of distributed patterns shed light on the processes that influence how information is encoded, maintained, or retrieved, and thus inform memory theory. We conclude by highlighting open questions about memory that can be addressed through distributed pattern analyses. PMID:21943171

Mnemonic transmission, social contagion, and emergence of collective memory: Influence of emotional valence, group structure, and information distribution.

PubMed

Choi, Hae-Yoon; Kensinger, Elizabeth A; Rajaram, Suparna

2017-09-01

Social transmission of memory and its consequence on collective memory have generated enduring interdisciplinary interest because of their widespread significance in interpersonal, sociocultural, and political arenas. We tested the influence of 3 key factors-emotional salience of information, group structure, and information distribution-on mnemonic transmission, social contagion, and collective memory. Participants individually studied emotionally salient (negative or positive) and nonemotional (neutral) picture-word pairs that were completely shared, partially shared, or unshared within participant triads, and then completed 3 consecutive recalls in 1 of 3 conditions: individual-individual-individual (control), collaborative-collaborative (identical group; insular structure)-individual, and collaborative-collaborative (reconfigured group; diverse structure)-individual. Collaboration enhanced negative memories especially in insular group structure and especially for shared information, and promoted collective forgetting of positive memories. Diverse group structure reduced this negativity effect. Unequally distributed information led to social contagion that creates false memories; diverse structure propagated a greater variety of false memories whereas insular structure promoted confidence in false recognition and false collective memory. A simultaneous assessment of network structure, information distribution, and emotional valence breaks new ground to specify how network structure shapes the spread of negative memories and false memories, and the emergence of collective memory. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Three Types of Memory in Emergency Medical Services Communication

ERIC Educational Resources Information Center

Angeli, Elizabeth L.

2015-01-01

This article examines memory and distributed cognition involved in the writing practices of emergency medical services (EMS) professionals. Results from a 16-month study indicate that EMS professionals rely on distributed cognition and three kinds of memory: individual, collaborative, and professional. Distributed cognition and the three types of…

Distributed-Memory Fast Maximal Independent Set

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

Kanewala Appuhamilage, Thejaka Amila J.; Zalewski, Marcin J.; Lumsdaine, Andrew

The Maximal Independent Set (MIS) graph problem arises in many applications such as computer vision, information theory, molecular biology, and process scheduling. The growing scale of MIS problems suggests the use of distributed-memory hardware as a cost-effective approach to providing necessary compute and memory resources. Luby proposed four randomized algorithms to solve the MIS problem. All those algorithms are designed focusing on shared-memory machines and are analyzed using the PRAM model. These algorithms do not have direct efficient distributed-memory implementations. In this paper, we extend two of Luby’s seminal MIS algorithms, “Luby(A)” and “Luby(B),” to distributed-memory execution, and we evaluatemore » their performance. We compare our results with the “Filtered MIS” implementation in the Combinatorial BLAS library for two types of synthetic graph inputs.« less

Continuous Time Random Walks with memory and financial distributions

NASA Astrophysics Data System (ADS)

Montero, Miquel; Masoliver, Jaume

2017-11-01

We study financial distributions from the perspective of Continuous Time Random Walks with memory. We review some of our previous developments and apply them to financial problems. We also present some new models with memory that can be useful in characterizing tendency effects which are inherent in most markets. We also briefly study the effect on return distributions of fractional behaviors in the distribution of pausing times between successive transactions.

Total recall in distributive associative memories

NASA Technical Reports Server (NTRS)

Danforth, Douglas G.

1991-01-01

Iterative error correction of asymptotically large associative memories is equivalent to a one-step learning rule. This rule is the inverse of the activation function of the memory. Spectral representations of nonlinear activation functions are used to obtain the inverse in closed form for Sparse Distributed Memory, Selected-Coordinate Design, and Radial Basis Functions.

How can individual differences in autobiographical memory distributions of older adults be explained?

PubMed

Wolf, Tabea; Zimprich, Daniel

2016-10-01

The reminiscence bump phenomenon has frequently been reported for the recall of autobiographical memories. The present study complements previous research by examining individual differences in the distribution of word-cued autobiographical memories. More importantly, we introduce predictor variables that might account for individual differences in the mean (location) and the standard deviation (scale) of individual memory distributions. All variables were derived from different theoretical accounts for the reminiscence bump phenomenon. We used a mixed location-scale logitnormal model, to analyse the 4602 autobiographical memories reported by 118 older participants. Results show reliable individual differences in the location and the scale. After controlling for age and gender, individual proportions of first-time experiences and individual proportions of positive memories, as well as the ratings on Openness to new Experiences and Self-Concept Clarity accounted for 29% of individual differences in location and 42% of individual differences in scale of autobiographical memory distributions. Results dovetail with a life-story account for the reminiscence bump which integrates central components of previous accounts.

The Generalized Quantum Episodic Memory Model.

PubMed

Trueblood, Jennifer S; Hemmer, Pernille

2017-11-01

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

Differentiation and Response Bias in Episodic Memory: Evidence from Reaction Time Distributions

ERIC Educational Resources Information Center

Criss, Amy H.

2010-01-01

In differentiation models, the processes of encoding and retrieval produce an increase in the distribution of memory strength for targets and a decrease in the distribution of memory strength for foils as the amount of encoding increases. This produces an increase in the hit rate and decrease in the false-alarm rate for a strongly encoded compared…

Shared versus distributed memory multiprocessors

NASA Technical Reports Server (NTRS)

Jordan, Harry F.

1991-01-01

The question of whether multiprocessors should have shared or distributed memory has attracted a great deal of attention. Some researchers argue strongly for building distributed memory machines, while others argue just as strongly for programming shared memory multiprocessors. A great deal of research is underway on both types of parallel systems. Special emphasis is placed on systems with a very large number of processors for computation intensive tasks and considers research and implementation trends. It appears that the two types of systems will likely converge to a common form for large scale multiprocessors.

Statistical prediction with Kanerva's sparse distributed memory

NASA Technical Reports Server (NTRS)

Rogers, David

1989-01-01

A new viewpoint of the processing performed by Kanerva's sparse distributed memory (SDM) is presented. In conditions of near- or over-capacity, where the associative-memory behavior of the model breaks down, the processing performed by the model can be interpreted as that of a statistical predictor. Mathematical results are presented which serve as the framework for a new statistical viewpoint of sparse distributed memory and for which the standard formulation of SDM is a special case. This viewpoint suggests possible enhancements to the SDM model, including a procedure for improving the predictiveness of the system based on Holland's work with genetic algorithms, and a method for improving the capacity of SDM even when used as an associative memory.

Supporting shared data structures on distributed memory architectures

NASA Technical Reports Server (NTRS)

Koelbel, Charles; Mehrotra, Piyush; Vanrosendale, John

1990-01-01

Programming nonshared memory systems is more difficult than programming shared memory systems, since there is no support for shared data structures. Current programming languages for distributed memory architectures force the user to decompose all data structures into separate pieces, with each piece owned by one of the processors in the machine, and with all communication explicitly specified by low-level message-passing primitives. A new programming environment is presented for distributed memory architectures, providing a global name space and allowing direct access to remote parts of data values. The analysis and program transformations required to implement this environment are described, and the efficiency of the resulting code on the NCUBE/7 and IPSC/2 hypercubes are described.

Differential memory in the earth's magnetotail

NASA Technical Reports Server (NTRS)

Burkhart, G. R.; Chen, J.

1991-01-01

The process of 'differential memory' in the earth's magnetotail is studied in the framework of the modified Harris magnetotail geometry. It is verified that differential memory can generate non-Maxwellian features in the modified Harris field model. The time scales and the potentially observable distribution functions associated with the process of differential memory are investigated, and it is shown that non-Maxwelllian distributions can evolve as a test particle response to distribution function boundary conditions in a Harris field magnetotail model. The non-Maxwellian features which arise from distribution function mapping have definite time scales associated with them, which are generally shorter than the earthward convection time scale but longer than the typical Alfven crossing time.

Low Latency Messages on Distributed Memory Multiprocessors

DOE PAGES

Rosing, Matt; Saltz, Joel

1995-01-01

This article describes many of the issues in developing an efficient interface for communication on distributed memory machines. Although the hardware component of message latency is less than 1 ws on many distributed memory machines, the software latency associated with sending and receiving typed messages is on the order of 50 μs. The reason for this imbalance is that the software interface does not match the hardware. By changing the interface to match the hardware more closely, applications with fine grained communication can be put on these machines. This article describes several tests performed and many of the issues involvedmore » in supporting low latency messages on distributed memory machines.« less

Limits of the memory coefficient in measuring correlated bursts

NASA Astrophysics Data System (ADS)

Jo, Hang-Hyun; Hiraoka, Takayuki

2018-03-01

Temporal inhomogeneities in event sequences of natural and social phenomena have been characterized in terms of interevent times and correlations between interevent times. The inhomogeneities of interevent times have been extensively studied, while the correlations between interevent times, often called correlated bursts, are far from being fully understood. For measuring the correlated bursts, two relevant approaches were suggested, i.e., memory coefficient and burst size distribution. Here a burst size denotes the number of events in a bursty train detected for a given time window. Empirical analyses have revealed that the larger memory coefficient tends to be associated with the heavier tail of the burst size distribution. In particular, empirical findings in human activities appear inconsistent, such that the memory coefficient is close to 0, while burst size distributions follow a power law. In order to comprehend these observations, by assuming the conditional independence between consecutive interevent times, we derive the analytical form of the memory coefficient as a function of parameters describing interevent time and burst size distributions. Our analytical result can explain the general tendency of the larger memory coefficient being associated with the heavier tail of burst size distribution. We also find that the apparently inconsistent observations in human activities are compatible with each other, indicating that the memory coefficient has limits to measure the correlated bursts.

Applications and development of communication models for the touchstone GAMMA and DELTA prototypes

NASA Technical Reports Server (NTRS)

Seidel, Steven R.

1993-01-01

The goal of this project was to develop models of the interconnection networks of the Intel iPSC/860 and DELTA multicomputers to guide the design of efficient algorithms for interprocessor communication in problems that commonly occur in CFD codes and other applications. Interprocessor communication costs of codes for message-passing architectures such as the iPSC/860 and DELTA significantly affect the level of performance that can be obtained from those machines. This project addressed several specific problems in the achievement of efficient communication on the Intel iPSC/860 hypercube and DELTA mesh. In particular, an efficient global processor synchronization algorithm was developed for the iPSC/860 and numerous broadcast algorithms were designed for the DELTA.

Traffic routing for multicomputer networks with virtual cut-through capability

NASA Technical Reports Server (NTRS)

Kandlur, Dilip D.; Shin, Kang G.

1992-01-01

Consideration is given to the problem of selecting routes for interprocess communication in a network with virtual cut-through capability, while balancing the network load and minimizing the number of times that a message gets buffered. An approach is proposed that formulates the route selection problem as a minimization problem with a link cost function that depends upon the traffic through the link. The form of this cost function is derived using the probability of establishing a virtual cut-through route. The route selection problem is shown to be NP-hard, and an algorithm is developed to incrementally reduce the cost by rerouting the traffic. The performance of this algorithm is exemplified by two network topologies: the hypercube and the C-wrapped hexagonal mesh.

Notes on implementation of sparsely distributed memory

NASA Technical Reports Server (NTRS)

Keeler, J. D.; Denning, P. J.

1986-01-01

The Sparsely Distributed Memory (SDM) developed by Kanerva is an unconventional memory design with very interesting and desirable properties. The memory works in a manner that is closely related to modern theories of human memory. The SDM model is discussed in terms of its implementation in hardware. Two appendices discuss the unconventional approaches of the SDM: Appendix A treats a resistive circuit for fast, parallel address decoding; and Appendix B treats a systolic array for high throughput read and write operations.

Distributed memory compiler methods for irregular problems: Data copy reuse and runtime partitioning

NASA Technical Reports Server (NTRS)

Das, Raja; Ponnusamy, Ravi; Saltz, Joel; Mavriplis, Dimitri

1991-01-01

Outlined here are two methods which we believe will play an important role in any distributed memory compiler able to handle sparse and unstructured problems. We describe how to link runtime partitioners to distributed memory compilers. In our scheme, programmers can implicitly specify how data and loop iterations are to be distributed between processors. This insulates users from having to deal explicitly with potentially complex algorithms that carry out work and data partitioning. We also describe a viable mechanism for tracking and reusing copies of off-processor data. In many programs, several loops access the same off-processor memory locations. As long as it can be verified that the values assigned to off-processor memory locations remain unmodified, we show that we can effectively reuse stored off-processor data. We present experimental data from a 3-D unstructured Euler solver run on iPSC/860 to demonstrate the usefulness of our methods.

Implementation of a Fully-Balanced Periodic Tridiagonal Solver on a Parallel Distributed Memory Architecture

DTIC Science & Technology

1994-05-01

PARALLEL DISTRIBUTED MEMORY ARCHITECTURE LTJh T. M. Eidson 0 - 8 l 9 5 " G. Erlebacher _ _ _. _ DTIe QUALITY INSPECTED a Contract NAS I - 19480 May 1994...DISTRIBUTED MEMORY ARCHITECTURE T.M. Eidson * High Technology Corporation Hampton, VA 23665 G. Erlebachert Institute for Computer Applications in Science and...developed and evaluated. Simple model calculations as well as timing results are pres.nted to evaluate the various strategies. The particular

Examining procedural working memory processing in obsessive-compulsive disorder.

PubMed

Shahar, Nitzan; Teodorescu, Andrei R; Anholt, Gideon E; Karmon-Presser, Anat; Meiran, Nachshon

2017-07-01

Previous research has suggested that a deficit in working memory might underlie the difficulty of obsessive-compulsive disorder (OCD) patients to control their thoughts and actions. However, a recent meta-analyses found only small effect sizes for working memory deficits in OCD. Recently, a distinction has been made between declarative and procedural working memory. Working memory in OCD was tested mostly using declarative measurements. However, OCD symptoms typically concerns actions, making procedural working-memory more relevant. Here, we tested the operation of procedural working memory in OCD. Participants with OCD and healthy controls performed a battery of choice reaction tasks under high and low procedural working memory demands. Reaction-times (RT) were estimated using ex-Gaussian distribution fitting, revealing no group differences in the size of the RT distribution tail (i.e., τ parameter), known to be sensitive to procedural working memory manipulations. Group differences, unrelated to working memory manipulations, were found in the leading-edge of the RT distribution and analyzed using a two-stage evidence accumulation model. Modeling results suggested that perceptual difficulties might underlie the current group differences. In conclusion, our results suggest that procedural working-memory processing is most likely intact in OCD, and raise a novel, yet untested assumption regarding perceptual deficits in OCD. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Episodic memory in aspects of large-scale brain networks

PubMed Central

Jeong, Woorim; Chung, Chun Kee; Kim, June Sic

2015-01-01

Understanding human episodic memory in aspects of large-scale brain networks has become one of the central themes in neuroscience over the last decade. Traditionally, episodic memory was regarded as mostly relying on medial temporal lobe (MTL) structures. However, recent studies have suggested involvement of more widely distributed cortical network and the importance of its interactive roles in the memory process. Both direct and indirect neuro-modulations of the memory network have been tried in experimental treatments of memory disorders. In this review, we focus on the functional organization of the MTL and other neocortical areas in episodic memory. Task-related neuroimaging studies together with lesion studies suggested that specific sub-regions of the MTL are responsible for specific components of memory. However, recent studies have emphasized that connectivity within MTL structures and even their network dynamics with other cortical areas are essential in the memory process. Resting-state functional network studies also have revealed that memory function is subserved by not only the MTL system but also a distributed network, particularly the default-mode network (DMN). Furthermore, researchers have begun to investigate memory networks throughout the entire brain not restricted to the specific resting-state network (RSN). Altered patterns of functional connectivity (FC) among distributed brain regions were observed in patients with memory impairments. Recently, studies have shown that brain stimulation may impact memory through modulating functional networks, carrying future implications of a novel interventional therapy for memory impairment. PMID:26321939

Modeling Confidence and Response Time in Recognition Memory

ERIC Educational Resources Information Center

Ratcliff, Roger; Starns, Jeffrey J.

2009-01-01

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

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

Programming distributed memory architectures using Kali

NASA Technical Reports Server (NTRS)

Mehrotra, Piyush; Vanrosendale, John

1990-01-01

Programming nonshared memory systems is more difficult than programming shared memory systems, in part because of the relatively low level of current programming environments for such machines. A new programming environment is presented, Kali, which provides a global name space and allows direct access to remote data values. In order to retain efficiency, Kali provides a system on annotations, allowing the user to control those aspects of the program critical to performance, such as data distribution and load balancing. The primitives and constructs provided by the language is described, and some of the issues raised in translating a Kali program for execution on distributed memory systems are also discussed.

Distributed simulation using a real-time shared memory network

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Mattern, Duane L.; Wong, Edmond; Musgrave, Jeffrey L.

1993-01-01

The Advanced Control Technology Branch of the NASA Lewis Research Center performs research in the area of advanced digital controls for aeronautic and space propulsion systems. This work requires the real-time implementation of both control software and complex dynamical models of the propulsion system. We are implementing these systems in a distributed, multi-vendor computer environment. Therefore, a need exists for real-time communication and synchronization between the distributed multi-vendor computers. A shared memory network is a potential solution which offers several advantages over other real-time communication approaches. A candidate shared memory network was tested for basic performance. The shared memory network was then used to implement a distributed simulation of a ramjet engine. The accuracy and execution time of the distributed simulation was measured and compared to the performance of the non-partitioned simulation. The ease of partitioning the simulation, the minimal time required to develop for communication between the processors and the resulting execution time all indicate that the shared memory network is a real-time communication technique worthy of serious consideration.

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

PubMed Central

El-Zawawy, Mohamed A.

2014-01-01

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

An empirical investigation of sparse distributed memory using discrete speech recognition

NASA Technical Reports Server (NTRS)

Danforth, Douglas G.

1990-01-01

Presented here is a step by step analysis of how the basic Sparse Distributed Memory (SDM) model can be modified to enhance its generalization capabilities for classification tasks. Data is taken from speech generated by a single talker. Experiments are used to investigate the theory of associative memories and the question of generalization from specific instances.

Implementation of a parallel unstructured Euler solver on shared and distributed memory architectures

NASA Technical Reports Server (NTRS)

Mavriplis, D. J.; Das, Raja; Saltz, Joel; Vermeland, R. E.

1992-01-01

An efficient three dimensional unstructured Euler solver is parallelized on a Cray Y-MP C90 shared memory computer and on an Intel Touchstone Delta distributed memory computer. This paper relates the experiences gained and describes the software tools and hardware used in this study. Performance comparisons between two differing architectures are made.

Switching behavior of resistive change memory using oxide nanowires

NASA Astrophysics Data System (ADS)

Aono, Takashige; Sugawa, Kosuke; Shimizu, Tomohiro; Shingubara, Shoso; Takase, Kouichi

2018-06-01

Resistive change random access memory (ReRAM), which is expected to be the next-generation nonvolatile memory, often has wide switching voltage distributions due to many kinds of conductive filaments. In this study, we have tried to suppress the distribution through the structural restriction of the filament-forming area using NiO nanowires. The capacitor with Ni metal nanowires whose surface is oxidized showed good switching behaviors with narrow distributions. The knowledge gained from our study will be very helpful in producing practical ReRAM devices.

Cultural scripts guide recall of intensely positive life events.

PubMed

Collins, Katherine A; Pillemer, David B; Ivcevic, Zorana; Gooze, Rachel A

2007-06-01

In four studies, we examined the temporal distribution of positive and negative memories of momentous life events. College students and middle-aged adults reported events occurring from the ages of 8 to 18 years in which they had felt especially good or especially bad about themselves. Distributions of positive memories showed a marked peak at ages 17 and 18. In contrast, distributions of negative memories were relatively flat. These patterns were consistent for males and females and for younger and older adults. Content analyses indicated that a substantial proportion of positive memories from late adolescence described culturally prescribed landmark events surrounding the major life transition from high school to college. When the participants were asked for recollections from life periods that lack obvious age-linked milestone events, age distributions of positive and negative memories were similar. The results support and extend Berntsen and Rubin's (2004) conclusion that cultural expectations, or life scripts, organize recall of positive, but not negative, events.

Distributed learning enhances relational memory consolidation.

PubMed

Litman, Leib; Davachi, Lila

2008-09-01

It has long been known that distributed learning (DL) provides a mnemonic advantage over massed learning (ML). However, the underlying mechanisms that drive this robust mnemonic effect remain largely unknown. In two experiments, we show that DL across a 24 hr interval does not enhance immediate memory performance but instead slows the rate of forgetting relative to ML. Furthermore, we demonstrate that this savings in forgetting is specific to relational, but not item, memory. In the context of extant theories and knowledge of memory consolidation, these results suggest that an important mechanism underlying the mnemonic benefit of DL is enhanced memory consolidation. We speculate that synaptic strengthening mechanisms supporting long-term memory consolidation may be differentially mediated by the spacing of memory reactivation. These findings have broad implications for the scientific study of episodic memory consolidation and, more generally, for educational curriculum development and policy.

Vienna FORTRAN: A FORTRAN language extension for distributed memory multiprocessors

NASA Technical Reports Server (NTRS)

Chapman, Barbara; Mehrotra, Piyush; Zima, Hans

1991-01-01

Exploiting the performance potential of distributed memory machines requires a careful distribution of data across the processors. Vienna FORTRAN is a language extension of FORTRAN which provides the user with a wide range of facilities for such mapping of data structures. However, programs in Vienna FORTRAN are written using global data references. Thus, the user has the advantage of a shared memory programming paradigm while explicitly controlling the placement of data. The basic features of Vienna FORTRAN are presented along with a set of examples illustrating the use of these features.

The Effect of the Underlying Distribution in Hurst Exponent Estimation

PubMed Central

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

2015-01-01

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

Modeling Distributions of Immediate Memory Effects: No Strategies Needed?

ERIC Educational Resources Information Center

Beaman, C. Philip; Neath, Ian; Surprenant, Aimee M.

2008-01-01

Many models of immediate memory predict the presence or absence of various effects, but none have been tested to see whether they predict an appropriate distribution of effect sizes. The authors show that the feature model (J. S. Nairne, 1990) produces appropriate distributions of effect sizes for both the phonological confusion effect and the…

Address tracing for parallel machines

NASA Technical Reports Server (NTRS)

Stunkel, Craig B.; Janssens, Bob; Fuchs, W. Kent

1991-01-01

Recently implemented parallel system address-tracing methods based on several metrics are surveyed. The issues specific to collection of traces for both shared and distributed memory parallel computers are highlighted. Five general categories of address-trace collection methods are examined: hardware-captured, interrupt-based, simulation-based, altered microcode-based, and instrumented program-based traces. The problems unique to shared memory and distributed memory multiprocessors are examined separately.

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.

Memory-assisted quantum key distribution resilient against multiple-excitation effects

NASA Astrophysics Data System (ADS)

Lo Piparo, Nicolò; Sinclair, Neil; Razavi, Mohsen

2018-01-01

Memory-assisted measurement-device-independent quantum key distribution (MA-MDI-QKD) has recently been proposed as a technique to improve the rate-versus-distance behavior of QKD systems by using existing, or nearly-achievable, quantum technologies. The promise is that MA-MDI-QKD would require less demanding quantum memories than the ones needed for probabilistic quantum repeaters. Nevertheless, early investigations suggest that, in order to beat the conventional memory-less QKD schemes, the quantum memories used in the MA-MDI-QKD protocols must have high bandwidth-storage products and short interaction times. Among different types of quantum memories, ensemble-based memories offer some of the required specifications, but they typically suffer from multiple excitation effects. To avoid the latter issue, in this paper, we propose two new variants of MA-MDI-QKD both relying on single-photon sources for entangling purposes. One is based on known techniques for entanglement distribution in quantum repeaters. This scheme turns out to offer no advantage even if one uses ideal single-photon sources. By finding the root cause of the problem, we then propose another setup, which can outperform single memory-less setups even if we allow for some imperfections in our single-photon sources. For such a scheme, we compare the key rate for different types of ensemble-based memories and show that certain classes of atomic ensembles can improve the rate-versus-distance behavior.

Execution time supports for adaptive scientific algorithms on distributed memory machines

NASA Technical Reports Server (NTRS)

Berryman, Harry; Saltz, Joel; Scroggs, Jeffrey

1990-01-01

Optimizations are considered that are required for efficient execution of code segments that consists of loops over distributed data structures. The PARTI (Parallel Automated Runtime Toolkit at ICASE) execution time primitives are designed to carry out these optimizations and can be used to implement a wide range of scientific algorithms on distributed memory machines. These primitives allow the user to control array mappings in a way that gives an appearance of shared memory. Computations can be based on a global index set. Primitives are used to carry out gather and scatter operations on distributed arrays. Communications patterns are derived at runtime, and the appropriate send and receive messages are automatically generated.

Execution time support for scientific programs on distributed memory machines

NASA Technical Reports Server (NTRS)

Berryman, Harry; Saltz, Joel; Scroggs, Jeffrey

1990-01-01

Optimizations are considered that are required for efficient execution of code segments that consists of loops over distributed data structures. The PARTI (Parallel Automated Runtime Toolkit at ICASE) execution time primitives are designed to carry out these optimizations and can be used to implement a wide range of scientific algorithms on distributed memory machines. These primitives allow the user to control array mappings in a way that gives an appearance of shared memory. Computations can be based on a global index set. Primitives are used to carry out gather and scatter operations on distributed arrays. Communications patterns are derived at runtime, and the appropriate send and receive messages are automatically generated.

Two-Dimensional Sequential and Concurrent Finite Element Analysis of Unstiffened and Stiffened Aluminum and Composite Panels with Hole

NASA Technical Reports Server (NTRS)

Razzaq, Zia; Prasad, Venkatesh

1988-01-01

The results of a detailed investigation of the distribution of stresses in aluminum and composite panels subjected to uniform end shortening are presented. The focus problem is a rectangular panel with two longitudinal stiffeners, and an inner stiffener discontinuous at a central hole in the panel. The influence of the stiffeners on the stresses is evaluated through a two-dimensional global finite element analysis in the absence or presence of the hole. Contrary to the physical feel, it is found that the maximum stresses from the glocal analysis for both stiffened aluminum and composite panels are greater than the corresponding stresses for the unstiffened panels. The inner discontinuous stiffener causes a greater increase in stresses than the reduction provided by the two outer stiffeners. A detailed layer-by-layer study of stresses around the hole is also presented for both unstiffened and stiffened composite panels. A parallel equation solver is used for the global system of equations since the computational time is far less than that using a sequential scheme. A parallel Choleski method with up to 16 processors is used on Flex/32 Multicomputer at NASA Langley Research Center. The parallel computing results are summarized and include the computational times, speedups, bandwidths, and their inter-relationships for the panel problems. It is found that the computational time for the Choleski method decreases with a decrease in bandwidth, and better speedups result as the bandwidth increases.

Two alternate proofs of Wang's lune formula for sparse distributed memory and an integral approximation

NASA Technical Reports Server (NTRS)

Jaeckel, Louis A.

1988-01-01

In Kanerva's Sparse Distributed Memory, writing to and reading from the memory are done in relation to spheres in an n-dimensional binary vector space. Thus it is important to know how many points are in the intersection of two spheres in this space. Two proofs are given of Wang's formula for spheres of unequal radii, and an integral approximation for the intersection in this case.

Sparse distributed memory: Principles and operation

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

Are memory traces localized or distributed?

PubMed

Thompson, R F

1991-01-01

Evidence supports the view that "memory traces" are formed in the hippocampus and in the cerebellum in classical conditioning of discrete behavioral responses (e.g. eyeblink conditioning). In the hippocampus, learning results in long-lasting increases in excitability of pyramidal neurons that appear to be localized to these neurons (i.e. changes in membrane properties and receptor function). However, these learning-altered pyramidal neurons are distributed widely throughout CA3 and CA1. Although it plays a key role in certain aspects of classical conditioning, the hippocampus is not necessary for learning and memory of the basic conditioned responses. The cerebellum and its associated brain stem circuitry, on the other hand, does appear to be essential (necessary and sufficient) for learning and memory of the conditioned response. Evidence to date is most consistent with a localized trace in the interpositus nucleus and multiple localized traces in cerebellar cortex, each involving relatively large ensembles of neurons. Perhaps "procedural" memory traces are relatively localized and "declarative" traces more widely distributed.

Distributed Saturation

NASA Technical Reports Server (NTRS)

Chung, Ming-Ying; Ciardo, Gianfranco; Siminiceanu, Radu I.

2007-01-01

The Saturation algorithm for symbolic state-space generation, has been a recent break-through in the exhaustive veri cation of complex systems, in particular globally-asyn- chronous/locally-synchronous systems. The algorithm uses a very compact Multiway Decision Diagram (MDD) encoding for states and the fastest symbolic exploration algo- rithm to date. The distributed version of Saturation uses the overall memory available on a network of workstations (NOW) to efficiently spread the memory load during the highly irregular exploration. A crucial factor in limiting the memory consumption during the symbolic state-space generation is the ability to perform garbage collection to free up the memory occupied by dead nodes. However, garbage collection over a NOW requires a nontrivial communication overhead. In addition, operation cache policies become critical while analyzing large-scale systems using the symbolic approach. In this technical report, we develop a garbage collection scheme and several operation cache policies to help on solving extremely complex systems. Experiments show that our schemes improve the performance of the original distributed implementation, SmArTNow, in terms of time and memory efficiency.

Sparse distributed memory: understanding the speed and robustness of expert memory

PubMed Central

Brogliato, Marcelo S.; Chada, Daniel M.; Linhares, Alexandre

2014-01-01

How can experts, sometimes in exacting detail, almost immediately and very precisely recall memory items from a vast repertoire? The problem in which we will be interested concerns models of theoretical neuroscience that could explain the speed and robustness of an expert's recollection. The approach is based on Sparse Distributed Memory, which has been shown to be plausible, both in a neuroscientific and in a psychological manner, in a number of ways. A crucial characteristic concerns the limits of human recollection, the “tip-of-tongue” memory event—which is found at a non-linearity in the model. We expand the theoretical framework, deriving an optimization formula to solve this non-linearity. Numerical results demonstrate how the higher frequency of rehearsal, through work or study, immediately increases the robustness and speed associated with expert memory. PMID:24808842

Thermodynamic Model of Spatial Memory

NASA Astrophysics Data System (ADS)

Kaufman, Miron; Allen, P.

1998-03-01

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

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

Distributed practice can boost evaluative conditioning by increasing memory for the stimulus pairs.

PubMed

Richter, Jasmin; Gast, Anne

2017-09-01

When presenting a neutral stimulus (CS) in close temporal and spatial proximity to a positive or negative stimulus (US) the former is often observed to adopt the valence of the latter, a phenomenon named evaluative conditioning (EC). It is already well established that under most conditions, contingency awareness is important for an EC effect to occur. In addition to that, some findings suggest that awareness of the stimulus pairs is not only relevant during the learning phase, but that it is also relevant whether memory for the pairings is still available during the measurement phase. As previous research has shown that memory is better after temporally distributed than after contiguous (massed) repetitions, it seems plausible that also EC effects are moderated by distributed practice manipulations. This was tested in the current studies. In two experiments with successful distributed practice manipulations on memory, we show that also the magnitude of the EC effect was larger for pairs learned under spaced compared to massed conditions. Both effects, on memory and on EC, are found after a within-participant and after a between-participant manipulation. However, we did not find significant differences in the EC effect for different conditions of spaced practice. These findings are in line with the assumption that EC is based on similar processes as memory for the pairings. Copyright © 2017 Elsevier B.V. All rights reserved.

BIRD: A general interface for sparse distributed memory simulators

NASA Technical Reports Server (NTRS)

Rogers, David

1990-01-01

Kanerva's sparse distributed memory (SDM) has now been implemented for at least six different computers, including SUN3 workstations, the Apple Macintosh, and the Connection Machine. A common interface for input of commands would both aid testing of programs on a broad range of computer architectures and assist users in transferring results from research environments to applications. A common interface also allows secondary programs to generate command sequences for a sparse distributed memory, which may then be executed on the appropriate hardware. The BIRD program is an attempt to create such an interface. Simplifying access to different simulators should assist developers in finding appropriate uses for SDM.

Autobiographical Memory in Semantic Dementia: A Longitudinal fMRI Study

ERIC Educational Resources Information Center

Maguire, Eleanor A.; Kumaran, Dharshan; Hassabis, Demis; Kopelman, Michael D.

2010-01-01

Whilst patients with semantic dementia (SD) are known to suffer from semantic memory and language impairments, there is less agreement about whether memory for personal everyday experiences, autobiographical memory, is compromised. In healthy individuals, functional MRI (fMRI) has helped to delineate a consistent and distributed brain network…

Efficient High Performance Collective Communication for Distributed Memory Environments

ERIC Educational Resources Information Center

Ali, Qasim

2009-01-01

Collective communication allows efficient communication and synchronization among a collection of processes, unlike point-to-point communication that only involves a pair of communicating processes. Achieving high performance for both kernels and full-scale applications running on a distributed memory system requires an efficient implementation of…

Efficient packing of patterns in sparse distributed memory by selective weighting of input bits

NASA Technical Reports Server (NTRS)

Kanerva, Pentti

1991-01-01

When a set of patterns is stored in a distributed memory, any given storage location participates in the storage of many patterns. From the perspective of any one stored pattern, the other patterns act as noise, and such noise limits the memory's storage capacity. The more similar the retrieval cues for two patterns are, the more the patterns interfere with each other in memory, and the harder it is to separate them on retrieval. A method is described of weighting the retrieval cues to reduce such interference and thus to improve the separability of patterns that have similar cues.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

An alternative design for a sparse distributed memory

NASA Technical Reports Server (NTRS)

Jaeckel, Louis A.

1989-01-01

A new design for a Sparse Distributed Memory, called the selected-coordinate design, is described. As in the original design, there are a large number of memory locations, each of which may be activated by many different addresses (binary vectors) in a very large address space. Each memory location is defined by specifying ten selected coordinates (bit positions in the address vectors) and a set of corresponding assigned values, consisting of one bit for each selected coordinate. A memory location is activated by an address if, for all ten of the locations's selected coordinates, the corresponding bits in the address vector match the respective assigned value bits, regardless of the other bits in the address vector. Some comparative memory capacity and signal-to-noise ratio estimates for the both the new and original designs are given. A few possible hardware embodiments of the new design are described.

Autobiographical memory distributions for negative self-images: memories are organised around negative as well as positive aspects of identity.

PubMed

Rathbone, Clare J; Steel, Craig

2015-01-01

The relationship between developmental experiences, and an individual's emerging beliefs about themselves and the world, is central to many forms of psychotherapy. People suffering from a variety of mental health problems have been shown to use negative memories when defining the self; however, little is known about how these negative memories might be organised and relate to negative self-images. In two online studies with middle-aged (N = 18; study 1) and young (N = 56; study 2) adults, we found that participants' negative self-images (e.g., I am a failure) were associated with sets of autobiographical memories that formed clustered distributions around times of self-formation, in much the same pattern as for positive self-images (e.g., I am talented). This novel result shows that highly organised sets of salient memories may be responsible for perpetuating negative beliefs about the self. Implications for therapy are discussed.

Parallel computing for probabilistic fatigue analysis

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Lua, Yuan J.; Smith, Mark D.

1993-01-01

This paper presents the results of Phase I research to investigate the most effective parallel processing software strategies and hardware configurations for probabilistic structural analysis. We investigate the efficiency of both shared and distributed-memory architectures via a probabilistic fatigue life analysis problem. We also present a parallel programming approach, the virtual shared-memory paradigm, that is applicable across both types of hardware. Using this approach, problems can be solved on a variety of parallel configurations, including networks of single or multiprocessor workstations. We conclude that it is possible to effectively parallelize probabilistic fatigue analysis codes; however, special strategies will be needed to achieve large-scale parallelism to keep large number of processors busy and to treat problems with the large memory requirements encountered in practice. We also conclude that distributed-memory architecture is preferable to shared-memory for achieving large scale parallelism; however, in the future, the currently emerging hybrid-memory architectures will likely be optimal.

Sparse distributed memory and related models

NASA Technical Reports Server (NTRS)

Kanerva, Pentti

1992-01-01

Described here is sparse distributed memory (SDM) as a neural-net associative memory. It is characterized by two weight matrices and by a large internal dimension - the number of hidden units is much larger than the number of input or output units. The first matrix, A, is fixed and possibly random, and the second matrix, C, is modifiable. The SDM is compared and contrasted to (1) computer memory, (2) correlation-matrix memory, (3) feet-forward artificial neural network, (4) cortex of the cerebellum, (5) Marr and Albus models of the cerebellum, and (6) Albus' cerebellar model arithmetic computer (CMAC). Several variations of the basic SDM design are discussed: the selected-coordinate and hyperplane designs of Jaeckel, the pseudorandom associative neural memory of Hassoun, and SDM with real-valued input variables by Prager and Fallside. SDM research conducted mainly at the Research Institute for Advanced Computer Science (RIACS) in 1986-1991 is highlighted.

Persistently active neurons in human medial frontal and medial temporal lobe support working memory

PubMed Central

Kamiński, J; Sullivan, S; Chung, JM; Ross, IB; Mamelak, AN; Rutishauser, U

2017-01-01

Persistent neural activity is a putative mechanism for the maintenance of working memories. Persistent activity relies on the activity of a distributed network of areas, but the differential contribution of each area remains unclear. We recorded single neurons in the human medial frontal cortex and the medial temporal lobe while subjects held up to three items in memory. We found persistently active neurons in both areas. Persistent activity of hippocampal and amygdala neurons was stimulus-specific, formed stable attractors, and was predictive of memory content. Medial frontal cortex persistent activity, on the other hand, was modulated by memory load and task set but was not stimulus-specific. Trial-by-trial variability in persistent activity in both areas was related to memory strength, because it predicted the speed and accuracy by which stimuli were remembered. This work reveals, in humans, direct evidence for a distributed network of persistently active neurons supporting working memory maintenance. PMID:28218914

Feature-Based Visual Short-Term Memory Is Widely Distributed and Hierarchically Organized.

PubMed

Dotson, Nicholas M; Hoffman, Steven J; Goodell, Baldwin; Gray, Charles M

2018-06-15

Feature-based visual short-term memory is known to engage both sensory and association cortices. However, the extent of the participating circuit and the neural mechanisms underlying memory maintenance is still a matter of vigorous debate. To address these questions, we recorded neuronal activity from 42 cortical areas in monkeys performing a feature-based visual short-term memory task and an interleaved fixation task. We find that task-dependent differences in firing rates are widely distributed throughout the cortex, while stimulus-specific changes in firing rates are more restricted and hierarchically organized. We also show that microsaccades during the memory delay encode the stimuli held in memory and that units modulated by microsaccades are more likely to exhibit stimulus specificity, suggesting that eye movements contribute to visual short-term memory processes. These results support a framework in which most cortical areas, within a modality, contribute to mnemonic representations at timescales that increase along the cortical hierarchy. Copyright © 2018 Elsevier Inc. All rights reserved.

Learning to read aloud: A neural network approach using sparse distributed memory

NASA Technical Reports Server (NTRS)

Joglekar, Umesh Dwarkanath

1989-01-01

An attempt to solve a problem of text-to-phoneme mapping is described which does not appear amenable to solution by use of standard algorithmic procedures. Experiments based on a model of distributed processing are also described. This model (sparse distributed memory (SDM)) can be used in an iterative supervised learning mode to solve the problem. Additional improvements aimed at obtaining better performance are suggested.

Sequential associative memory with nonuniformity of the layer sizes.

PubMed

Teramae, Jun-Nosuke; Fukai, Tomoki

2007-01-01

Sequence retrieval has a fundamental importance in information processing by the brain, and has extensively been studied in neural network models. Most of the previous sequential associative memory embedded sequences of memory patterns have nearly equal sizes. It was recently shown that local cortical networks display many diverse yet repeatable precise temporal sequences of neuronal activities, termed "neuronal avalanches." Interestingly, these avalanches displayed size and lifetime distributions that obey power laws. Inspired by these experimental findings, here we consider an associative memory model of binary neurons that stores sequences of memory patterns with highly variable sizes. Our analysis includes the case where the statistics of these size variations obey the above-mentioned power laws. We study the retrieval dynamics of such memory systems by analytically deriving the equations that govern the time evolution of macroscopic order parameters. We calculate the critical sequence length beyond which the network cannot retrieve memory sequences correctly. As an application of the analysis, we show how the present variability in sequential memory patterns degrades the power-law lifetime distribution of retrieved neural activities.

Patterns of particle distribution in multiparticle systems by random walks with memory enhancement and decay

NASA Astrophysics Data System (ADS)

Tan, Zhi-Jie; Zou, Xian-Wu; Huang, Sheng-You; Zhang, Wei; Jin, Zhun-Zhi

2002-07-01

We investigate the pattern of particle distribution and its evolution with time in multiparticle systems using the model of random walks with memory enhancement and decay. This model describes some biological intelligent walks. With decrease in the memory decay exponent α, the distribution of particles changes from a random dispersive pattern to a locally dense one, and then returns to the random one. Correspondingly, the fractal dimension Df,p characterizing the distribution of particle positions increases from a low value to a maximum and then decreases to the low one again. This is determined by the degree of overlap of regions consisting of sites with remanent information. The second moment of the density ρ(2) was introduced to investigate the inhomogeneity of the particle distribution. The dependence of ρ(2) on α is similar to that of Df,p on α. ρ(2) increases with time as a power law in the process of adjusting the particle distribution, and then ρ(2) tends to a stable equilibrium value.

Vascular system modeling in parallel environment - distributed and shared memory approaches

PubMed Central

Jurczuk, Krzysztof; Kretowski, Marek; Bezy-Wendling, Johanne

2011-01-01

The paper presents two approaches in parallel modeling of vascular system development in internal organs. In the first approach, new parts of tissue are distributed among processors and each processor is responsible for perfusing its assigned parts of tissue to all vascular trees. Communication between processors is accomplished by passing messages and therefore this algorithm is perfectly suited for distributed memory architectures. The second approach is designed for shared memory machines. It parallelizes the perfusion process during which individual processing units perform calculations concerning different vascular trees. The experimental results, performed on a computing cluster and multi-core machines, show that both algorithms provide a significant speedup. PMID:21550891

Optimizing NEURON Simulation Environment Using Remote Memory Access with Recursive Doubling on Distributed Memory Systems.

PubMed

Shehzad, Danish; Bozkuş, Zeki

2016-01-01

Increase in complexity of neuronal network models escalated the efforts to make NEURON simulation environment efficient. The computational neuroscientists divided the equations into subnets amongst multiple processors for achieving better hardware performance. On parallel machines for neuronal networks, interprocessor spikes exchange consumes large section of overall simulation time. In NEURON for communication between processors Message Passing Interface (MPI) is used. MPI_Allgather collective is exercised for spikes exchange after each interval across distributed memory systems. The increase in number of processors though results in achieving concurrency and better performance but it inversely affects MPI_Allgather which increases communication time between processors. This necessitates improving communication methodology to decrease the spikes exchange time over distributed memory systems. This work has improved MPI_Allgather method using Remote Memory Access (RMA) by moving two-sided communication to one-sided communication, and use of recursive doubling mechanism facilitates achieving efficient communication between the processors in precise steps. This approach enhanced communication concurrency and has improved overall runtime making NEURON more efficient for simulation of large neuronal network models.

Optimizing NEURON Simulation Environment Using Remote Memory Access with Recursive Doubling on Distributed Memory Systems

PubMed Central

Bozkuş, Zeki

2016-01-01

Increase in complexity of neuronal network models escalated the efforts to make NEURON simulation environment efficient. The computational neuroscientists divided the equations into subnets amongst multiple processors for achieving better hardware performance. On parallel machines for neuronal networks, interprocessor spikes exchange consumes large section of overall simulation time. In NEURON for communication between processors Message Passing Interface (MPI) is used. MPI_Allgather collective is exercised for spikes exchange after each interval across distributed memory systems. The increase in number of processors though results in achieving concurrency and better performance but it inversely affects MPI_Allgather which increases communication time between processors. This necessitates improving communication methodology to decrease the spikes exchange time over distributed memory systems. This work has improved MPI_Allgather method using Remote Memory Access (RMA) by moving two-sided communication to one-sided communication, and use of recursive doubling mechanism facilitates achieving efficient communication between the processors in precise steps. This approach enhanced communication concurrency and has improved overall runtime making NEURON more efficient for simulation of large neuronal network models. PMID:27413363

Storage of multiple single-photon pulses emitted from a quantum dot in a solid-state quantum memory.

PubMed

Tang, Jian-Shun; Zhou, Zong-Quan; Wang, Yi-Tao; Li, Yu-Long; Liu, Xiao; Hua, Yi-Lin; Zou, Yang; Wang, Shuang; He, De-Yong; Chen, Geng; Sun, Yong-Nan; Yu, Ying; Li, Mi-Feng; Zha, Guo-Wei; Ni, Hai-Qiao; Niu, Zhi-Chuan; Li, Chuan-Feng; Guo, Guang-Can

2015-10-15

Quantum repeaters are critical components for distributing entanglement over long distances in presence of unavoidable optical losses during transmission. Stimulated by the Duan-Lukin-Cirac-Zoller protocol, many improved quantum repeater protocols based on quantum memories have been proposed, which commonly focus on the entanglement-distribution rate. Among these protocols, the elimination of multiple photons (or multiple photon-pairs) and the use of multimode quantum memory are demonstrated to have the ability to greatly improve the entanglement-distribution rate. Here, we demonstrate the storage of deterministic single photons emitted from a quantum dot in a polarization-maintaining solid-state quantum memory; in addition, multi-temporal-mode memory with 1, 20 and 100 narrow single-photon pulses is also demonstrated. Multi-photons are eliminated, and only one photon at most is contained in each pulse. Moreover, the solid-state properties of both sub-systems make this configuration more stable and easier to be scalable. Our work will be helpful in the construction of efficient quantum repeaters based on all-solid-state devices.

Storage of multiple single-photon pulses emitted from a quantum dot in a solid-state quantum memory

PubMed Central

Tang, Jian-Shun; Zhou, Zong-Quan; Wang, Yi-Tao; Li, Yu-Long; Liu, Xiao; Hua, Yi-Lin; Zou, Yang; Wang, Shuang; He, De-Yong; Chen, Geng; Sun, Yong-Nan; Yu, Ying; Li, Mi-Feng; Zha, Guo-Wei; Ni, Hai-Qiao; Niu, Zhi-Chuan; Li, Chuan-Feng; Guo, Guang-Can

2015-01-01

Quantum repeaters are critical components for distributing entanglement over long distances in presence of unavoidable optical losses during transmission. Stimulated by the Duan–Lukin–Cirac–Zoller protocol, many improved quantum repeater protocols based on quantum memories have been proposed, which commonly focus on the entanglement-distribution rate. Among these protocols, the elimination of multiple photons (or multiple photon-pairs) and the use of multimode quantum memory are demonstrated to have the ability to greatly improve the entanglement-distribution rate. Here, we demonstrate the storage of deterministic single photons emitted from a quantum dot in a polarization-maintaining solid-state quantum memory; in addition, multi-temporal-mode memory with 1, 20 and 100 narrow single-photon pulses is also demonstrated. Multi-photons are eliminated, and only one photon at most is contained in each pulse. Moreover, the solid-state properties of both sub-systems make this configuration more stable and easier to be scalable. Our work will be helpful in the construction of efficient quantum repeaters based on all-solid-state devices. PMID:26468996

Modeling node bandwidth limits and their effects on vector combining algorithms

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

Littlefield, R.J.

Each node in a message-passing multicomputer typically has several communication links. However, the maximum aggregate communication speed of a node is often less than the sum of its individual link speeds. Such computers are called node bandwidth limited (NBL). The NBL constraint is important when choosing algorithms because it can change the relative performance of different algorithms that accomplish the same task. This paper introduces a model of communication performance for NBL computers and uses the model to analyze the overall performance of three algorithms for vector combining (global sum) on the Intel Touchstone DELTA computer. Each of the threemore » algorithms is found to be at least 33% faster than the other two for some combinations of machine size and vector length. The NBL constraint is shown to significantly affect the conditions under which each algorithm is fastest.« less

Distributed Learning Enhances Relational Memory Consolidation

ERIC Educational Resources Information Center

Litman, Leib; Davachi, Lila

2008-01-01

It has long been known that distributed learning (DL) provides a mnemonic advantage over massed learning (ML). However, the underlying mechanisms that drive this robust mnemonic effect remain largely unknown. In two experiments, we show that DL across a 24 hr interval does not enhance immediate memory performance but instead slows the rate of…

Distributed memory compiler design for sparse problems

NASA Technical Reports Server (NTRS)

Wu, Janet; Saltz, Joel; Berryman, Harry; Hiranandani, Seema

1991-01-01

A compiler and runtime support mechanism is described and demonstrated. The methods presented are capable of solving a wide range of sparse and unstructured problems in scientific computing. The compiler takes as input a FORTRAN 77 program enhanced with specifications for distributing data, and the compiler outputs a message passing program that runs on a distributed memory computer. The runtime support for this compiler is a library of primitives designed to efficiently support irregular patterns of distributed array accesses and irregular distributed array partitions. A variety of Intel iPSC/860 performance results obtained through the use of this compiler are presented.

Enhancement of Immune Memory Responses to Respiratory Infection

DTIC Science & Technology

2017-08-01

Unlimited Distribution 13. SUPPLEMENTARY NOTES 14. ABSTRACT Maintenance of long - term immunological memory against pathogens is crucial for the rapid...highly expressed in memory B cells in mice, and Atg7 is required for maintenance of long - term memory B cells needed to protect against influenza...AWARD NUMBER: W81XWH-16-1-0360 TITLE: Enhancement of Immune Memory Responses to Respiratory Infection PRINCIPAL INVESTIGATORs: Dr Min Chen PhD

Autobiographical Memory and Depression in the Later Age: The Bump Is a Turning Point

ERIC Educational Resources Information Center

Gidron, Yori; Alon, Shirly

2007-01-01

This preliminary study integrated previous findings of the distribution of autobiographical memories in the later age according to their age of occurrence, with the overgeneral memory bias predictive of depression. Twenty-five non-demented, Israeli participants between 65-89 years of age provided autobiographical memories to 4 groups of word cues…

Cortex and Memory: Emergence of a New Paradigm

ERIC Educational Resources Information Center

Fuster, Joaquin M.

2009-01-01

Converging evidence from humans and nonhuman primates is obliging us to abandon conventional models in favor of a radically different, distributed-network paradigm of cortical memory. Central to the new paradigm is the concept of memory network or cognit--that is, a memory or an item of knowledge defined by a pattern of connections between neuron…

Memories of Physical Education

ERIC Educational Resources Information Center

Sidwell, Amy M.; Walls, Richard T.

2014-01-01

The purpose of this investigation was to explore college students' autobiographical memories of physical education (PE). Questionnaires were distributed to students enrolled in undergraduate Introduction to PE and Introduction to Communications courses. The 261 participants wrote about memories of PE. These students recalled events from Grades…

Immigration, Language Proficiency, and Autobiographical Memories: Lifespan Distribution and Second-Language Access

PubMed Central

Esposito, Alena G.; Baker-Ward, Lynne

2015-01-01

This investigation examined two controversies in the autobiographical literature: how cross-language immigration affects the distribution of autobiographical memories across the lifespan and under what circumstances language-dependent recall is observed. Both Spanish/English bilingual immigrants and English monolingual non-immigrants participated in a cue word study, with the bilingual sample taking part in a within-subject language manipulation. The expected bump in the number of memories from early life was observed for non-immigrants but not immigrants, who reported more memories for events surrounding immigration. Aspects of the methodology addressed possible reasons for past discrepant findings. Language-dependent recall was influenced by second-language proficiency. Results were interpreted as evidence that bilinguals with high second-language proficiency, in contrast to those with lower second-language proficiency, access a single conceptual store through either language. The final multi-level model predicting language-dependent recall, including second-language proficiency, age of immigration, internal language, and cue word language, explained ¾ of the between-person variance and ⅕ of the within-person variance. We arrive at two conclusions. First, major life transitions influence the distribution of memories. Second, concept representation across multiple languages follows a developmental model. In addition, the results underscore the importance of considering language experience in research involving memory reports. PMID:26274061

Immigration, language proficiency, and autobiographical memories: Lifespan distribution and second-language access.

PubMed

Esposito, Alena G; Baker-Ward, Lynne

2016-08-01

This investigation examined two controversies in the autobiographical literature: how cross-language immigration affects the distribution of autobiographical memories across the lifespan and under what circumstances language-dependent recall is observed. Both Spanish/English bilingual immigrants and English monolingual non-immigrants participated in a cue word study, with the bilingual sample taking part in a within-subject language manipulation. The expected bump in the number of memories from early life was observed for non-immigrants but not immigrants, who reported more memories for events surrounding immigration. Aspects of the methodology addressed possible reasons for past discrepant findings. Language-dependent recall was influenced by second-language proficiency. Results were interpreted as evidence that bilinguals with high second-language proficiency, in contrast to those with lower second-language proficiency, access a single conceptual store through either language. The final multi-level model predicting language-dependent recall, including second-language proficiency, age of immigration, internal language, and cue word language, explained ¾ of the between-person variance and (1)/5 of the within-person variance. We arrive at two conclusions. First, major life transitions influence the distribution of memories. Second, concept representation across multiple languages follows a developmental model. In addition, the results underscore the importance of considering language experience in research involving memory reports.

A ten-year follow-up of a study of memory for the attack of September 11, 2001: Flashbulb memories and memories for flashbulb events.

PubMed

Hirst, William; Phelps, Elizabeth A; Meksin, Robert; Vaidya, Chandan J; Johnson, Marcia K; Mitchell, Karen J; Buckner, Randy L; Budson, Andrew E; Gabrieli, John D E; Lustig, Cindy; Mather, Mara; Ochsner, Kevin N; Schacter, Daniel; Simons, Jon S; Lyle, Keith B; Cuc, Alexandru F; Olsson, Andreas

2015-06-01

Within a week of the attack of September 11, 2001, a consortium of researchers from across the United States distributed a survey asking about the circumstances in which respondents learned of the attack (their flashbulb memories) and the facts about the attack itself (their event memories). Follow-up surveys were distributed 11, 25, and 119 months after the attack. The study, therefore, examines retention of flashbulb memories and event memories at a substantially longer retention interval than any previous study using a test-retest methodology, allowing for the study of such memories over the long term. There was rapid forgetting of both flashbulb and event memories within the first year, but the forgetting curves leveled off after that, not significantly changing even after a 10-year delay. Despite the initial rapid forgetting, confidence remained high throughout the 10-year period. Five putative factors affecting flashbulb memory consistency and event memory accuracy were examined: (a) attention to media, (b) the amount of discussion, (c) residency, (d) personal loss and/or inconvenience, and (e) emotional intensity. After 10 years, none of these factors predicted flashbulb memory consistency; media attention and ensuing conversation predicted event memory accuracy. Inconsistent flashbulb memories were more likely to be repeated rather than corrected over the 10-year period; inaccurate event memories, however, were more likely to be corrected. The findings suggest that even traumatic memories and those implicated in a community's collective identity may be inconsistent over time and these inconsistencies can persist without the corrective force of external influences. (c) 2015 APA, all rights reserved).

Two demonstrators and a simulator for a sparse, distributed memory

NASA Technical Reports Server (NTRS)

Brown, Robert L.

1987-01-01

Described are two programs demonstrating different aspects of Kanerva's Sparse, Distributed Memory (SDM). These programs run on Sun 3 workstations, one using color, and have straightforward graphically oriented user interfaces and graphical output. Presented are descriptions of the programs, how to use them, and what they show. Additionally, this paper describes the software simulator behind each program.

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.

A manual for PARTI runtime primitives

NASA Technical Reports Server (NTRS)

Berryman, Harry; Saltz, Joel

1990-01-01

Primitives are presented that are designed to help users efficiently program irregular problems (e.g., unstructured mesh sweeps, sparse matrix codes, adaptive mesh partial differential equations solvers) on distributed memory machines. These primitives are also designed for use in compilers for distributed memory multiprocessors. Communications patterns are captured at runtime, and the appropriate send and receive messages are automatically generated.

pyCTQW: A continuous-time quantum walk simulator on distributed memory computers

NASA Astrophysics Data System (ADS)

Izaac, Josh A.; Wang, Jingbo B.

2015-01-01

In the general field of quantum information and computation, quantum walks are playing an increasingly important role in constructing physical models and quantum algorithms. We have recently developed a distributed memory software package pyCTQW, with an object-oriented Python interface, that allows efficient simulation of large multi-particle CTQW (continuous-time quantum walk)-based systems. In this paper, we present an introduction to the Python and Fortran interfaces of pyCTQW, discuss various numerical methods of calculating the matrix exponential, and demonstrate the performance behavior of pyCTQW on a distributed memory cluster. In particular, the Chebyshev and Krylov-subspace methods for calculating the quantum walk propagation are provided, as well as methods for visualization and data analysis.

Biaxial Fatigue Behavior of Niti Shape Memory Alloy

DTIC Science & Technology

2005-03-01

BIAXIAL FATIGUE BEHAVIOR OF NiTi SHAPE MEMORY ALLOY THESIS Daniel M. Jensen, 1st Lieutenant...BIAXIAL FATIGUE BEHAVIOR OF NiTi SHAPE MEMORY ALLOY THESIS Presented to the Faculty Department of Aeronautics and Astronautics Graduate School of...FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED AFIT/GA/ENY/05-M06 BIAXIAL FATIGUE BEHAVIOR OF NiTi SHAPE MEMORY ALLOY Daniel M. Jensen

The Measurement of Visuo-Spatial and Verbal-Numerical Working Memory: Development of IRT-Based Scales

ERIC Educational Resources Information Center

Vock, Miriam; Holling, Heinz

2008-01-01

The objective of this study is to explore the potential for developing IRT-based working memory scales for assessing specific working memory components in children (8-13 years). These working memory scales should measure cognitive abilities reliably in the upper range of ability distribution as well as in the normal range, and provide a…

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.

Diffusion theory of decision making in continuous report.

PubMed

Smith, Philip L

2016-07-01

I present a diffusion model for decision making in continuous report tasks, in which a continuous, circularly distributed, stimulus attribute in working memory is matched to a representation of the attribute in the stimulus display. Memory retrieval is modeled as a 2-dimensional diffusion process with vector-valued drift on a disk, whose bounding circle represents the decision criterion. The direction and magnitude of the drift vector describe the identity of the stimulus and the quality of its representation in memory, respectively. The point at which the diffusion exits the disk determines the reported value of the attribute and the time to exit the disk determines the decision time. Expressions for the joint distribution of decision times and report outcomes are obtained by means of the Girsanov change-of-measure theorem, which allows the properties of the nonzero-drift diffusion process to be characterized as a function of a Euclidian-distance Bessel process. Predicted report precision is equal to the product of the decision criterion and the drift magnitude and follows a von Mises distribution, in agreement with the treatment of precision in the working memory literature. Trial-to-trial variability in criterion and drift rate leads, respectively, to direct and inverse relationships between report accuracy and decision times, in agreement with, and generalizing, the standard diffusion model of 2-choice decisions. The 2-dimensional model provides a process account of working memory precision and its relationship with the diffusion model, and a new way to investigate the properties of working memory, via the distributions of decision times. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

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

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

Secchi, Simone; Tumeo, Antonino; Villa, Oreste

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

Kmerind: A Flexible Parallel Library for K-mer Indexing of Biological Sequences on Distributed Memory Systems.

PubMed

Pan, Tony; Flick, Patrick; Jain, Chirag; Liu, Yongchao; Aluru, Srinivas

2017-10-09

Counting and indexing fixed length substrings, or k-mers, in biological sequences is a key step in many bioinformatics tasks including genome alignment and mapping, genome assembly, and error correction. While advances in next generation sequencing technologies have dramatically reduced the cost and improved latency and throughput, few bioinformatics tools can efficiently process the datasets at the current generation rate of 1.8 terabases every 3 days. We present Kmerind, a high performance parallel k-mer indexing library for distributed memory environments. The Kmerind library provides a set of simple and consistent APIs with sequential semantics and parallel implementations that are designed to be flexible and extensible. Kmerind's k-mer counter performs similarly or better than the best existing k-mer counting tools even on shared memory systems. In a distributed memory environment, Kmerind counts k-mers in a 120 GB sequence read dataset in less than 13 seconds on 1024 Xeon CPU cores, and fully indexes their positions in approximately 17 seconds. Querying for 1% of the k-mers in these indices can be completed in 0.23 seconds and 28 seconds, respectively. Kmerind is the first k-mer indexing library for distributed memory environments, and the first extensible library for general k-mer indexing and counting. Kmerind is available at https://github.com/ParBLiSS/kmerind.

The Shark Random Swim - (Lévy Flight with Memory)

NASA Astrophysics Data System (ADS)

Businger, Silvia

2018-05-01

The Elephant Random Walk (ERW), first introduced by Schütz and Trimper (Phys Rev E 70:045101, 2004), is a one-dimensional simple random walk on Z having a memory about the whole past. We study the Shark Random Swim, a random walk with memory about the whole past, whose steps are α -stable distributed with α \\in (0,2] . Our aim in this work is to study the impact of the heavy tailed step distributions on the asymptotic behavior of the random walk. We shall see that, as for the ERW, the asymptotic behavior of the Shark Random Swim depends on its memory parameter p, and that a phase transition can be observed at the critical value p=1/α.

Rapid solution of large-scale systems of equations

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.

1994-01-01

The analysis and design of complex aerospace structures requires the rapid solution of large systems of linear and nonlinear equations, eigenvalue extraction for buckling, vibration and flutter modes, structural optimization and design sensitivity calculation. Computers with multiple processors and vector capabilities can offer substantial computational advantages over traditional scalar computer for these analyses. These computers fall into two categories: shared memory computers and distributed memory computers. This presentation covers general-purpose, highly efficient algorithms for generation/assembly or element matrices, solution of systems of linear and nonlinear equations, eigenvalue and design sensitivity analysis and optimization. All algorithms are coded in FORTRAN for shared memory computers and many are adapted to distributed memory computers. The capability and numerical performance of these algorithms will be addressed.

Efficient entanglement distillation without quantum memory.

PubMed

Abdelkhalek, Daniela; Syllwasschy, Mareike; Cerf, Nicolas J; Fiurášek, Jaromír; Schnabel, Roman

2016-05-31

Entanglement distribution between distant parties is an essential component to most quantum communication protocols. Unfortunately, decoherence effects such as phase noise in optical fibres are known to demolish entanglement. Iterative (multistep) entanglement distillation protocols have long been proposed to overcome decoherence, but their probabilistic nature makes them inefficient since the success probability decays exponentially with the number of steps. Quantum memories have been contemplated to make entanglement distillation practical, but suitable quantum memories are not realised to date. Here, we present the theory for an efficient iterative entanglement distillation protocol without quantum memories and provide a proof-of-principle experimental demonstration. The scheme is applied to phase-diffused two-mode-squeezed states and proven to distil entanglement for up to three iteration steps. The data are indistinguishable from those that an efficient scheme using quantum memories would produce. Since our protocol includes the final measurement it is particularly promising for enhancing continuous-variable quantum key distribution.

Efficient entanglement distillation without quantum memory

PubMed Central

Abdelkhalek, Daniela; Syllwasschy, Mareike; Cerf, Nicolas J.; Fiurášek, Jaromír; Schnabel, Roman

2016-01-01

Entanglement distribution between distant parties is an essential component to most quantum communication protocols. Unfortunately, decoherence effects such as phase noise in optical fibres are known to demolish entanglement. Iterative (multistep) entanglement distillation protocols have long been proposed to overcome decoherence, but their probabilistic nature makes them inefficient since the success probability decays exponentially with the number of steps. Quantum memories have been contemplated to make entanglement distillation practical, but suitable quantum memories are not realised to date. Here, we present the theory for an efficient iterative entanglement distillation protocol without quantum memories and provide a proof-of-principle experimental demonstration. The scheme is applied to phase-diffused two-mode-squeezed states and proven to distil entanglement for up to three iteration steps. The data are indistinguishable from those that an efficient scheme using quantum memories would produce. Since our protocol includes the final measurement it is particularly promising for enhancing continuous-variable quantum key distribution. PMID:27241946

UPC++ Programmer’s Guide (v1.0 2017.9)

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

Bachan, J.; Baden, S.; Bonachea, D.

UPC++ is a C++11 library that provides Asynchronous Partitioned Global Address Space (APGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The APGAS model is single program, multiple-data (SPMD), with each separate thread of execution (referred to as a rank, a term borrowed from MPI) having access to local memory as it would in C++. However, APGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the ranks. UPC++ provides numerous methods for accessing and using global memory. In UPC++, allmore » operations that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.« less

UPC++ Programmer’s Guide, v1.0-2018.3.0

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

Bachan, J.; Baden, S.; Bonachea, Dan

UPC++ is a C++11 library that provides Partitioned Global Address Space (PGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The PGAS model is single program, multiple-data (SPMD), with each separate thread of execution (referred to as a rank, a term borrowed from MPI) having access to local memory as it would in C++. However, PGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the ranks. UPC++ provides numerous methods for accessing and using global memory. In UPC++, all operationsmore » that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.« less

Retrieval of high-fidelity memory arises from distributed cortical networks.

PubMed

Wais, Peter E; Jahanikia, Sahar; Steiner, Daniel; Stark, Craig E L; Gazzaley, Adam

2017-04-01

Medial temporal lobe (MTL) function is well established as necessary for memory of facts and events. It is likely that lateral cortical regions critically guide cognitive control processes to tune in high-fidelity details that are most relevant for memory retrieval. Here, convergent results from functional and structural MRI show that retrieval of detailed episodic memory arises from lateral cortical-MTL networks, including regions of inferior frontal and angular gyrii. Results also suggest that recognition of items based on low-fidelity, generalized information, rather than memory arising from retrieval of relevant episodic details, is not associated with functional connectivity between MTL and lateral cortical regions. Additionally, individual differences in microstructural properties in white matter pathways, associated with distributed MTL-cortical networks, are positively correlated with better performance on a mnemonic discrimination task. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Development and Verification of Sputtered Thin-Film Nickel-Titanium (NiTi) Shape Memory Alloy (SMA)

DTIC Science & Technology

2015-08-01

Shape Memory Alloy (SMA) by Cory R Knick and Christopher J Morris Approved for public release; distribution unlimited...Laboratory Development and Verification of Sputtered Thin-Film Nickel-Titanium (NiTi) Shape Memory Alloy (SMA) by Cory R Knick and Christopher

JuxtaView - A tool for interactive visualization of large imagery on scalable tiled displays

USGS Publications Warehouse

Krishnaprasad, N.K.; Vishwanath, V.; Venkataraman, S.; Rao, A.G.; Renambot, L.; Leigh, J.; Johnson, A.E.; Davis, B.

2004-01-01

JuxtaView is a cluster-based application for viewing ultra-high-resolution images on scalable tiled displays. We present in JuxtaView, a new parallel computing and distributed memory approach for out-of-core montage visualization, using LambdaRAM, a software-based network-level cache system. The ultimate goal of JuxtaView is to enable a user to interactively roam through potentially terabytes of distributed, spatially referenced image data such as those from electron microscopes, satellites and aerial photographs. In working towards this goal, we describe our first prototype implemented over a local area network, where the image is distributed using LambdaRAM, on the memory of all nodes of a PC cluster driving a tiled display wall. Aggressive pre-fetching schemes employed by LambdaRAM help to reduce latency involved in remote memory access. We compare LambdaRAM with a more traditional memory-mapped file approach for out-of-core visualization. ?? 2004 IEEE.

Human short-term spatial memory: precision predicts capacity.

PubMed

Banta Lavenex, Pamela; Boujon, Valérie; Ndarugendamwo, Angélique; Lavenex, Pierre

2015-03-01

Here, we aimed to determine the capacity of human short-term memory for allocentric spatial information in a real-world setting. Young adults were tested on their ability to learn, on a trial-unique basis, and remember over a 1-min interval the location(s) of 1, 3, 5, or 7 illuminating pads, among 23 pads distributed in a 4m×4m arena surrounded by curtains on three sides. Participants had to walk to and touch the pads with their foot to illuminate the goal locations. In contrast to the predictions from classical slot models of working memory capacity limited to a fixed number of items, i.e., Miller's magical number 7 or Cowan's magical number 4, we found that the number of visited locations to find the goals was consistently about 1.6 times the number of goals, whereas the number of correct choices before erring and the number of errorless trials varied with memory load even when memory load was below the hypothetical memory capacity. In contrast to resource models of visual working memory, we found no evidence that memory resources were evenly distributed among unlimited numbers of items to be remembered. Instead, we found that memory for even one individual location was imprecise, and that memory performance for one location could be used to predict memory performance for multiple locations. Our findings are consistent with a theoretical model suggesting that the precision of the memory for individual locations might determine the capacity of human short-term memory for spatial information. Copyright © 2015 Elsevier Inc. All rights reserved.

Parallel and distributed computation for fault-tolerant object recognition

NASA Technical Reports Server (NTRS)

Wechsler, Harry

1988-01-01

The distributed associative memory (DAM) model is suggested for distributed and fault-tolerant computation as it relates to object recognition tasks. The fault-tolerance is with respect to geometrical distortions (scale and rotation), noisy inputs, occulsion/overlap, and memory faults. An experimental system was developed for fault-tolerant structure recognition which shows the feasibility of such an approach. The approach is futher extended to the problem of multisensory data integration and applied successfully to the recognition of colored polyhedral objects.

Kanerva's sparse distributed memory with multiple hamming thresholds

NASA Technical Reports Server (NTRS)

Pohja, Seppo; Kaski, Kimmo

1992-01-01

If the stored input patterns of Kanerva's Sparse Distributed Memory (SDM) are highly correlated, utilization of the storage capacity is very low compared to the case of uniformly distributed random input patterns. We consider a variation of SDM that has a better storage capacity utilization for correlated input patterns. This approach uses a separate selection threshold for each physical storage address or hard location. The selection of the hard locations for reading or writing can be done in parallel of which SDM implementations can benefit.

A manual for PARTI runtime primitives, revision 1

NASA Technical Reports Server (NTRS)

Das, Raja; Saltz, Joel; Berryman, Harry

1991-01-01

Primitives are presented that are designed to help users efficiently program irregular problems (e.g., unstructured mesh sweeps, sparse matrix codes, adaptive mesh partial differential equations solvers) on distributed memory machines. These primitives are also designed for use in compilers for distributed memory multiprocessors. Communications patterns are captured at runtime, and the appropriate send and receive messages are automatically generated.

Distributed memory parallel Markov random fields using graph partitioning

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

Heinemann, C.; Perciano, T.; Ushizima, D.

Markov random fields (MRF) based algorithms have attracted a large amount of interest in image analysis due to their ability to exploit contextual information about data. Image data generated by experimental facilities, though, continues to grow larger and more complex, making it more difficult to analyze in a reasonable amount of time. Applying image processing algorithms to large datasets requires alternative approaches to circumvent performance problems. Aiming to provide scientists with a new tool to recover valuable information from such datasets, we developed a general purpose distributed memory parallel MRF-based image analysis framework (MPI-PMRF). MPI-PMRF overcomes performance and memory limitationsmore » by distributing data and computations across processors. The proposed approach was successfully tested with synthetic and experimental datasets. Additionally, the performance of the MPI-PMRF framework is analyzed through a detailed scalability study. We show that a performance increase is obtained while maintaining an accuracy of the segmentation results higher than 98%. The contributions of this paper are: (a) development of a distributed memory MRF framework; (b) measurement of the performance increase of the proposed approach; (c) verification of segmentation accuracy in both synthetic and experimental, real-world datasets« less

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

PubMed Central

Purcell, Jeremy; Hillis, Argye E.; Capasso, Rita; Miceli, Gabriele

2016-01-01

Spelling a word involves the retrieval of information about the word’s letters and their order from long-term memory as well as the maintenance and processing of this information by working memory in preparation for serial production by the motor system. While it is known that brain lesions may selectively affect orthographic long-term memory and working memory processes, relatively little is known about the neurotopographic distribution of the substrates that support these cognitive processes, or the lesions that give rise to the distinct forms of dysgraphia that affect these cognitive processes. To examine these issues, this study uses a voxel-based mapping approach to analyse the lesion distribution of 27 individuals with dysgraphia subsequent to stroke, who were identified on the basis of their behavioural profiles alone, as suffering from deficits only affecting either orthographic long-term or working memory, as well as six other individuals with deficits affecting both sets of processes. The findings provide, for the first time, clear evidence of substrates that selectively support orthographic long-term and working memory processes, with orthographic long-term memory deficits centred in either the left posterior inferior frontal region or left ventral temporal cortex, and orthographic working memory deficits primarily arising from lesions of the left parietal cortex centred on the intraparietal sulcus. These findings also contribute to our understanding of the relationship between the neural instantiation of written language processes and spoken language, working memory and other cognitive skills. PMID:26685156

Memory for Context becomes Less Specific with Time

ERIC Educational Resources Information Center

Wiltgen, Brian J.; Silva, Alcino J.

2007-01-01

Context memories initially require the hippocampus, but over time become independent of this structure. This shift reflects a consolidation process whereby memories are gradually stored in distributed regions of the cortex. The function of this process is thought to be the extraction of statistical regularities and general knowledge from specific…

A Memory-Based Theory of Verbal Cognition

ERIC Educational Resources Information Center

Dennis, Simon

2005-01-01

The syntagmatic paradigmatic model is a distributed, memory-based account of verbal processing. Built on a Bayesian interpretation of string edit theory, it characterizes the control of verbal cognition as the retrieval of sets of syntagmatic and paradigmatic constraints from sequential and relational long-term memory and the resolution of these…

Autobiographical Memory from a Life Span Perspective

ERIC Educational Resources Information Center

Schroots, Johannes J. F.; van Dijkum, Cor; Assink, Marian H. J.

2004-01-01

This comparative study (i.e., three age groups, three measures) explores the distribution of retrospective and prospective autobiographical memory data across the lifespan, in particular the bump pattern of disproportionally higher recall of memories from the ages 10 to 30, as generally observed in older age groups, in conjunction with the…

Changing concepts of working memory

PubMed Central

Ma, Wei Ji; Husain, Masud; Bays, Paul M

2014-01-01

Working memory is widely considered to be limited in capacity, holding a fixed, small number of items, such as Miller's ‘magical number’ seven or Cowan's four. It has recently been proposed that working memory might better be conceptualized as a limited resource that is distributed flexibly among all items to be maintained in memory. According to this view, the quality rather than the quantity of working memory representations determines performance. Here we consider behavioral and emerging neural evidence for this proposal. PMID:24569831

Memory access in shared virtual memory

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

Berrendorf, R.

1992-01-01

Shared virtual memory (SVM) is a virtual memory layer with a single address space on top of a distributed real memory on parallel computers. We examine the behavior and performance of SVM running a parallel program with medium-grained, loop-level parallelism on top of it. A simulator for the underlying parallel architecture can be used to examine the behavior of SVM more deeply. The influence of several parameters, such as the number of processors, page size, cold or warm start, and restricted page replication, is studied.

Memory access in shared virtual memory

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

Berrendorf, R.

1992-09-01

Shared virtual memory (SVM) is a virtual memory layer with a single address space on top of a distributed real memory on parallel computers. We examine the behavior and performance of SVM running a parallel program with medium-grained, loop-level parallelism on top of it. A simulator for the underlying parallel architecture can be used to examine the behavior of SVM more deeply. The influence of several parameters, such as the number of processors, page size, cold or warm start, and restricted page replication, is studied.

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.

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.

The Basolateral Amygdala and Nucleus Accumbens Core Mediate Dissociable Aspects of Drug Memory Reconsolidation

ERIC Educational Resources Information Center

Theberge, Florence R. M.; Milton, Amy L.; Belin, David; Lee, Jonathan L. C.; Everitt, Barry J.

2010-01-01

A distributed limbic-corticostriatal circuitry is implicated in cue-induced drug craving and relapse. Exposure to drug-paired cues not only precipitates relapse, but also triggers the reactivation and reconsolidation of the cue-drug memory. However, the limbic cortical-striatal circuitry underlying drug memory reconsolidation is unclear. The aim…

NAS Applications and Advanced Algorithms

NASA Technical Reports Server (NTRS)

Bailey, David H.; Biswas, Rupak; VanDerWijngaart, Rob; Kutler, Paul (Technical Monitor)

1997-01-01

This paper examines the applications most commonly run on the supercomputers at the Numerical Aerospace Simulation (NAS) facility. It analyzes the extent to which such applications are fundamentally oriented to vector computers, and whether or not they can be efficiently implemented on hierarchical memory machines, such as systems with cache memories and highly parallel, distributed memory systems.

Programming in Vienna Fortran

NASA Technical Reports Server (NTRS)

Chapman, Barbara; Mehrotra, Piyush; Zima, Hans

1992-01-01

Exploiting the full performance potential of distributed memory machines requires a careful distribution of data across the processors. Vienna Fortran is a language extension of Fortran which provides the user with a wide range of facilities for such mapping of data structures. In contrast to current programming practice, programs in Vienna Fortran are written using global data references. Thus, the user has the advantages of a shared memory programming paradigm while explicitly controlling the data distribution. In this paper, we present the language features of Vienna Fortran for FORTRAN 77, together with examples illustrating the use of these features.

Detection of weak signals in memory thermal baths.

PubMed

Jiménez-Aquino, J I; Velasco, R M; Romero-Bastida, M

2014-11-01

The nonlinear relaxation time and the statistics of the first passage time distribution in connection with the quasideterministic approach are used to detect weak signals in the decay process of the unstable state of a Brownian particle embedded in memory thermal baths. The study is performed in the overdamped approximation of a generalized Langevin equation characterized by an exponential decay in the friction memory kernel. A detection criterion for each time scale is studied: The first one is referred to as the receiver output, which is given as a function of the nonlinear relaxation time, and the second one is related to the statistics of the first passage time distribution.

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.

Quantitative autoradiographic analysis of muscarinic receptor subtypes and their role in representational memory

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

Messer, W.S.

1986-01-01

Autoradiographic techniques were used to examine the distribution of muscarinic receptors in rat brain slices. Agonist and selective antagonist binding were examined by measuring the ability for unlabeled ligands to inhibit (/sup 3/H)-1-QNB labeling of muscarinic receptors. The distribution of high affinity pirenzepine binding sites (M/sub 1/ subtype) was distinct from the distribution of high affinity carbamylcholine sites, which corresponded to the M/sub 2/ subtype. In a separate assay, the binding profile for pirenzepine was shown to differ from the profile for scopolamine, a classical muscarinic antagonist. Muscarinic antagonists, when injected into the Hippocampus, impaired performance of a representational memorymore » task. Pirenzepine, the M/sub 1/ selective antagonist, produced representational memory deficits. Scopolamine, a less selective muscarinic antagonist, caused increases in running times in some animals which prevented a definitive interpretation of the nature of the impairment. Pirenzepine displayed a higher affinity for the hippocampus and was more effective in producing a selective impairment of representational memory than scopolamine. The data indicated that cholinergic activity in the hippocampus was necessary for representation memory function.« less

A class of designs for a sparse distributed memory

NASA Technical Reports Server (NTRS)

Jaeckel, Louis A.

1989-01-01

A general class of designs for a space distributed memory (SDM) is described. The author shows that Kanerva's original design and the selected-coordinate design are related, and that there is a series of possible intermediate designs between those two designs. In each such design, the set of addresses that activate a memory location is a sphere in the address space. We can also have hybrid designs, in which the memory locations may be a mixture of those found in the other designs. In some applications, the bits of the read and write addresses that will actually be used might be mostly zeros; that is, the addresses might lie on or near z hyperplane in the address space. The author describes a hyperplane design which is adapted to this situation and compares it to an adaptation of Kanerva's design. To study the performance of these designs, he computes the expected number of memory locations activated by both of two addresses.

Quantum cryptography: individual eavesdropping with the knowledge of the error-correcting protocol

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

Horoshko, D B

2007-12-31

The quantum key distribution protocol BB84 combined with the repetition protocol for error correction is analysed from the point of view of its security against individual eavesdropping relying on quantum memory. It is shown that the mere knowledge of the error-correcting protocol changes the optimal attack and provides the eavesdropper with additional information on the distributed key. (fifth seminar in memory of d.n. klyshko)

Parallel Programming Paradigms

DTIC Science & Technology

1987-07-01

Unclassified IS.. DECLASSIFICATIONIOOWNGRADIN G 16. DISTRIBUTION STATEMENT (of this Report) Distribution of this report is unlimited. 17...8416878 and by the Office of Naval Research Contracts No. N00014-86-K-0264 and No. N00014-85- K-0328. 8 ?~~ O . G 1 49 II Parallel Programming Paradigms...processors -. "to fetch from the same memory cell (list head) and thus seems to favor a shared memory - g implementation [37). In this dissertation, we

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.

Low latency messages on distributed memory multiprocessors

NASA Technical Reports Server (NTRS)

Rosing, Matthew; Saltz, Joel

1993-01-01

Many of the issues in developing an efficient interface for communication on distributed memory machines are described and a portable interface is proposed. Although the hardware component of message latency is less than one microsecond on many distributed memory machines, the software latency associated with sending and receiving typed messages is on the order of 50 microseconds. The reason for this imbalance is that the software interface does not match the hardware. By changing the interface to match the hardware more closely, applications with fine grained communication can be put on these machines. Based on several tests that were run on the iPSC/860, an interface that will better match current distributed memory machines is proposed. The model used in the proposed interface consists of a computation processor and a communication processor on each node. Communication between these processors and other nodes in the system is done through a buffered network. Information that is transmitted is either data or procedures to be executed on the remote processor. The dual processor system is better suited for efficiently handling asynchronous communications compared to a single processor system. The ability to send data or procedure is very flexible for minimizing message latency, based on the type of communication being performed. The test performed and the proposed interface are described.

Distributed shared memory for roaming large volumes.

PubMed

Castanié, Laurent; Mion, Christophe; Cavin, Xavier; Lévy, Bruno

2006-01-01

We present a cluster-based volume rendering system for roaming very large volumes. This system allows to move a gigabyte-sized probe inside a total volume of several tens or hundreds of gigabytes in real-time. While the size of the probe is limited by the total amount of texture memory on the cluster, the size of the total data set has no theoretical limit. The cluster is used as a distributed graphics processing unit that both aggregates graphics power and graphics memory. A hardware-accelerated volume renderer runs in parallel on the cluster nodes and the final image compositing is implemented using a pipelined sort-last rendering algorithm. Meanwhile, volume bricking and volume paging allow efficient data caching. On each rendering node, a distributed hierarchical cache system implements a global software-based distributed shared memory on the cluster. In case of a cache miss, this system first checks page residency on the other cluster nodes instead of directly accessing local disks. Using two Gigabit Ethernet network interfaces per node, we accelerate data fetching by a factor of 4 compared to directly accessing local disks. The system also implements asynchronous disk access and texture loading, which makes it possible to overlap data loading, volume slicing and rendering for optimal volume roaming.

A compositional reservoir simulator on distributed memory parallel computers

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

Rame, M.; Delshad, M.

1995-12-31

This paper presents the application of distributed memory parallel computes to field scale reservoir simulations using a parallel version of UTCHEM, The University of Texas Chemical Flooding Simulator. The model is a general purpose highly vectorized chemical compositional simulator that can simulate a wide range of displacement processes at both field and laboratory scales. The original simulator was modified to run on both distributed memory parallel machines (Intel iPSC/960 and Delta, Connection Machine 5, Kendall Square 1 and 2, and CRAY T3D) and a cluster of workstations. A domain decomposition approach has been taken towards parallelization of the code. Amore » portion of the discrete reservoir model is assigned to each processor by a set-up routine that attempts a data layout as even as possible from the load-balance standpoint. Each of these subdomains is extended so that data can be shared between adjacent processors for stencil computation. The added routines that make parallel execution possible are written in a modular fashion that makes the porting to new parallel platforms straight forward. Results of the distributed memory computing performance of Parallel simulator are presented for field scale applications such as tracer flood and polymer flood. A comparison of the wall-clock times for same problems on a vector supercomputer is also presented.« less

Multimodal retrieval of autobiographical memories: sensory information contributes differently to the recollection of events.

PubMed

Willander, Johan; Sikström, Sverker; Karlsson, Kristina

2015-01-01

Previous studies on autobiographical memory have focused on unimodal retrieval cues (i.e., cues pertaining to one modality). However, from an ecological perspective multimodal cues (i.e., cues pertaining to several modalities) are highly important to investigate. In the present study we investigated age distributions and experiential ratings of autobiographical memories retrieved with unimodal and multimodal cues. Sixty-two participants were randomized to one of four cue-conditions: visual, olfactory, auditory, or multimodal. The results showed that the peak of the distributions depends on the modality of the retrieval cue. The results indicated that multimodal retrieval seemed to be driven by visual and auditory information to a larger extent and to a lesser extent by olfactory information. Finally, no differences were observed in the number of retrieved memories or experiential ratings across the four cue-conditions.

Discrete-Slots Models of Visual Working-Memory Response Times

PubMed Central

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

2014-01-01

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

Design of multiple sequence alignment algorithms on parallel, distributed memory supercomputers.

PubMed

Church, Philip C; Goscinski, Andrzej; Holt, Kathryn; Inouye, Michael; Ghoting, Amol; Makarychev, Konstantin; Reumann, Matthias

2011-01-01

The challenge of comparing two or more genomes that have undergone recombination and substantial amounts of segmental loss and gain has recently been addressed for small numbers of genomes. However, datasets of hundreds of genomes are now common and their sizes will only increase in the future. Multiple sequence alignment of hundreds of genomes remains an intractable problem due to quadratic increases in compute time and memory footprint. To date, most alignment algorithms are designed for commodity clusters without parallelism. Hence, we propose the design of a multiple sequence alignment algorithm on massively parallel, distributed memory supercomputers to enable research into comparative genomics on large data sets. Following the methodology of the sequential progressiveMauve algorithm, we design data structures including sequences and sorted k-mer lists on the IBM Blue Gene/P supercomputer (BG/P). Preliminary results show that we can reduce the memory footprint so that we can potentially align over 250 bacterial genomes on a single BG/P compute node. We verify our results on a dataset of E.coli, Shigella and S.pneumoniae genomes. Our implementation returns results matching those of the original algorithm but in 1/2 the time and with 1/4 the memory footprint for scaffold building. In this study, we have laid the basis for multiple sequence alignment of large-scale datasets on a massively parallel, distributed memory supercomputer, thus enabling comparison of hundreds instead of a few genome sequences within reasonable time.

Effects of cacheing on multitasking efficiency and programming strategy on an ELXSI 6400

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

Montry, G.R.; Benner, R.E.

1985-12-01

The impact of a cache/shared memory architecture, and, in particular, the cache coherency problem, upon concurrent algorithm and program development is discussed. In this context, a simple set of programming strategies are proposed which streamline code development and improve code performance when multitasking in a cache/shared memory or distributed memory environment.

Phonotactic Probability Effect in Nonword Recall and Its Relationship with Vocabulary in Monolingual and Bilingual Preschoolers

ERIC Educational Resources Information Center

Messer, Marielle H.; Leseman, Paul P. M.; Boom, Jan; Mayo, Aziza Y.

2010-01-01

The current study examined to what extent information in long-term memory concerning the distribution of phoneme clusters in a language, so-called long-term phonotactic knowledge, increased the capacity of verbal short-term memory in young language learners and, through increased verbal short-term memory capacity, supported these children's first…

Contrasting single and multi-component working-memory systems in dual tasking.

PubMed

Nijboer, Menno; Borst, Jelmer; van Rijn, Hedderik; Taatgen, Niels

2016-05-01

Working memory can be a major source of interference in dual tasking. However, there is no consensus on whether this interference is the result of a single working memory bottleneck, or of interactions between different working memory components that together form a complete working-memory system. We report a behavioral and an fMRI dataset in which working memory requirements are manipulated during multitasking. We show that a computational cognitive model that assumes a distributed version of working memory accounts for both behavioral and neuroimaging data better than a model that takes a more centralized approach. The model's working memory consists of an attentional focus, declarative memory, and a subvocalized rehearsal mechanism. Thus, the data and model favor an account where working memory interference in dual tasking is the result of interactions between different resources that together form a working-memory system. Copyright © 2016 Elsevier Inc. All rights reserved.

System and method for programmable bank selection for banked memory subsystems

DOEpatents

Blumrich, Matthias A.; Chen, Dong; Gara, Alan G.; Giampapa, Mark E.; Hoenicke, Dirk; Ohmacht, Martin; Salapura, Valentina; Sugavanam, Krishnan

2010-09-07

A programmable memory system and method for enabling one or more processor devices access to shared memory in a computing environment, the shared memory including one or more memory storage structures having addressable locations for storing data. The system comprises: one or more first logic devices associated with a respective one or more processor devices, each first logic device for receiving physical memory address signals and programmable for generating a respective memory storage structure select signal upon receipt of pre-determined address bit values at selected physical memory address bit locations; and, a second logic device responsive to each of the respective select signal for generating an address signal used for selecting a memory storage structure for processor access. The system thus enables each processor device of a computing environment memory storage access distributed across the one or more memory storage structures.

Memory consolidation reconfigures neural pathways involved in the suppression of emotional memories

PubMed Central

Liu, Yunzhe; Lin, Wanjun; Liu, Chao; Luo, Yuejia; Wu, Jianhui; Bayley, Peter J.; Qin, Shaozheng

2016-01-01

The ability to suppress unwanted emotional memories is crucial for human mental health. Through consolidation over time, emotional memories often become resistant to change. However, how consolidation impacts the effectiveness of emotional memory suppression is still unknown. Using event-related fMRI while concurrently recording skin conductance, we investigated the neurobiological processes underlying the suppression of aversive memories before and after overnight consolidation. Here we report that consolidated aversive memories retain their emotional reactivity and become more resistant to suppression. Suppression of consolidated memories involves higher prefrontal engagement, and less concomitant hippocampal and amygdala disengagement. In parallel, we show a shift away from hippocampal-dependent representational patterns to distributed neocortical representational patterns in the suppression of aversive memories after consolidation. These findings demonstrate rapid changes in emotional memory organization with overnight consolidation, and suggest possible neurobiological bases underlying the resistance to suppression of emotional memories in affective disorders. PMID:27898050

CDL description of the CDC 6600 stunt box

NASA Technical Reports Server (NTRS)

Hertzog, J. B.

1971-01-01

The CDC 6600 central memory control (stunt box) is described utilizing CDL (Computer Design Language), block diagrams, and text. The stunt box is a clearing house for all central memory references from the 6600 central and peripheral processors. Since memory requests can be issued simultaneously, the stunt box must be capable of assigning priorities to requests, of labeling requests so that the data will be distributed correctly, and of remembering rejected addresses due to memory conflicts.

Recognition of simple visual images using a sparse distributed memory: Some implementations and experiments

NASA Technical Reports Server (NTRS)

Jaeckel, Louis A.

1990-01-01

Previously, a method was described of representing a class of simple visual images so that they could be used with a Sparse Distributed Memory (SDM). Herein, two possible implementations are described of a SDM, for which these images, suitably encoded, will serve both as addresses to the memory and as data to be stored in the memory. A key feature of both implementations is that a pattern that is represented as an unordered set with a variable number of members can be used as an address to the memory. In the 1st model, an image is encoded as a 9072 bit string to be used as a read or write address; the bit string may also be used as data to be stored in the memory. Another representation, in which an image is encoded as a 256 bit string, may be used with either model as data to be stored in the memory, but not as an address. In the 2nd model, an image is not represented as a vector of fixed length to be used as an address. Instead, a rule is given for determining which memory locations are to be activated in response to an encoded image. This activation rule treats the pieces of an image as an unordered set. With this model, the memory can be simulated, based on a method of computing the approximate result of a read operation.

Parallel processing for scientific computations

NASA Technical Reports Server (NTRS)

Alkhatib, Hasan S.

1995-01-01

The scope of this project dealt with the investigation of the requirements to support distributed computing of scientific computations over a cluster of cooperative workstations. Various experiments on computations for the solution of simultaneous linear equations were performed in the early phase of the project to gain experience in the general nature and requirements of scientific applications. A specification of a distributed integrated computing environment, DICE, based on a distributed shared memory communication paradigm has been developed and evaluated. The distributed shared memory model facilitates porting existing parallel algorithms that have been designed for shared memory multiprocessor systems to the new environment. The potential of this new environment is to provide supercomputing capability through the utilization of the aggregate power of workstations cooperating in a cluster interconnected via a local area network. Workstations, generally, do not have the computing power to tackle complex scientific applications, making them primarily useful for visualization, data reduction, and filtering as far as complex scientific applications are concerned. There is a tremendous amount of computing power that is left unused in a network of workstations. Very often a workstation is simply sitting idle on a desk. A set of tools can be developed to take advantage of this potential computing power to create a platform suitable for large scientific computations. The integration of several workstations into a logical cluster of distributed, cooperative, computing stations presents an alternative to shared memory multiprocessor systems. In this project we designed and evaluated such a system.

Modelling parallel programs and multiprocessor architectures with AXE

NASA Technical Reports Server (NTRS)

Yan, Jerry C.; Fineman, Charles E.

1991-01-01

AXE, An Experimental Environment for Parallel Systems, was designed to model and simulate for parallel systems at the process level. It provides an integrated environment for specifying computation models, multiprocessor architectures, data collection, and performance visualization. AXE is being used at NASA-Ames for developing resource management strategies, parallel problem formulation, multiprocessor architectures, and operating system issues related to the High Performance Computing and Communications Program. AXE's simple, structured user-interface enables the user to model parallel programs and machines precisely and efficiently. Its quick turn-around time keeps the user interested and productive. AXE models multicomputers. The user may easily modify various architectural parameters including the number of sites, connection topologies, and overhead for operating system activities. Parallel computations in AXE are represented as collections of autonomous computing objects known as players. Their use and behavior is described. Performance data of the multiprocessor model can be observed on a color screen. These include CPU and message routing bottlenecks, and the dynamic status of the software.

The application of artificial intelligent techniques to accelerator operations at McMaster University

NASA Astrophysics Data System (ADS)

Poehlman, W. F. S.; Garland, Wm. J.; Stark, J. W.

1993-06-01

In an era of downsizing and a limited pool of skilled accelerator personnel from which to draw replacements for an aging workforce, the impetus to integrate intelligent computer automation into the accelerator operator's repertoire is strong. However, successful deployment of an "Operator's Companion" is not trivial. Both graphical and human factors need to be recognized as critical areas that require extra care when formulating the Companion. They include interactive graphical user's interface that mimics, for the operator, familiar accelerator controls; knowledge of acquisition phases during development must acknowledge the expert's mental model of machine operation; and automated operations must be seen as improvements to the operator's environment rather than threats of ultimate replacement. Experiences with the PACES Accelerator Operator Companion developed at two sites over the past three years are related and graphical examples are given. The scale of the work involves multi-computer control of various start-up/shutdown and tuning procedures for Model FN and KN Van de Graaff accelerators. The response from licensing agencies has been encouraging.

Distributed-Memory Breadth-First Search on Massive Graphs

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

Buluc, Aydin; Beamer, Scott; Madduri, Kamesh

This chapter studies the problem of traversing large graphs using the breadth-first search order on distributed-memory supercomputers. We consider both the traditional level-synchronous top-down algorithm as well as the recently discovered direction optimizing algorithm. We analyze the performance and scalability trade-offs in using different local data structures such as CSR and DCSC, enabling in-node multithreading, and graph decompositions such as 1D and 2D decomposition.

Support for Debugging Automatically Parallelized Programs

NASA Technical Reports Server (NTRS)

Hood, Robert; Jost, Gabriele; Biegel, Bryan (Technical Monitor)

2001-01-01

This viewgraph presentation provides information on the technical aspects of debugging computer code that has been automatically converted for use in a parallel computing system. Shared memory parallelization and distributed memory parallelization entail separate and distinct challenges for a debugging program. A prototype system has been developed which integrates various tools for the debugging of automatically parallelized programs including the CAPTools Database which provides variable definition information across subroutines as well as array distribution information.

High Band Technology Program (HiTeP)

DTIC Science & Technology

2005-03-01

clock distribution circuit. One Receiver Memory module receives 60MHz reference sine wave and distributes 60MHz clock signals to all Receiver Memory...Diagram UNCLASSIFIED 23 in N00014-99-C-0314 Integrated Defense Systems Final Report 1 March 2005 .. 4.ran FibreXpress Fibre-Channel PMC "Motrl Medea FCR...the Electrically Short Crossed-Notch (ESCN). It is shorter than traditional traveling wave notch antennas. The 2X ECSN fin length is approximately 1.2

Correlated resistive/capacitive state variability in solid TiO2 based memory devices

NASA Astrophysics Data System (ADS)

Li, Qingjiang; Salaoru, Iulia; Khiat, Ali; Xu, Hui; Prodromakis, Themistoklis

2017-05-01

In this work, we experimentally demonstrated the correlated resistive/capacitive switching and state variability in practical TiO2 based memory devices. Based on filamentary functional mechanism, we argue that the impedance state variability stems from the randomly distributed defects inside the oxide bulk. Finally, our assumption was verified via a current percolation circuit model, by taking into account of random defects distribution and coexistence of memristor and memcapacitor.

Timing in a Variable Interval Procedure: Evidence for a Memory Singularity

PubMed Central

Matell, Matthew S.; Kim, Jung S.; Hartshorne, Loryn

2013-01-01

Rats were trained in either a 30s peak-interval procedure, or a 15–45s variable interval peak procedure with a uniform distribution (Exp 1) or a ramping probability distribution (Exp 2). Rats in all groups showed peak shaped response functions centered around 30s, with the uniform group having an earlier and broader peak response function and rats in the ramping group having a later peak function as compared to the single duration group. The changes in these mean functions, as well as the statistics from single trial analyses, can be better captured by a model of timing in which memory is represented by a single, average, delay to reinforcement compared to one in which all durations are stored as a distribution, such as the complete memory model of Scalar Expectancy Theory or a simple associative model. PMID:24012783

Modeling of long-range memory processes with inverse cubic distributions by the nonlinear stochastic differential equations

NASA Astrophysics Data System (ADS)

Kaulakys, B.; Alaburda, M.; Ruseckas, J.

2016-05-01

A well-known fact in the financial markets is the so-called ‘inverse cubic law’ of the cumulative distributions of the long-range memory fluctuations of market indicators such as a number of events of trades, trading volume and the logarithmic price change. We propose the nonlinear stochastic differential equation (SDE) giving both the power-law behavior of the power spectral density and the long-range dependent inverse cubic law of the cumulative distribution. This is achieved using the suggestion that when the market evolves from calm to violent behavior there is a decrease of the delay time of multiplicative feedback of the system in comparison to the driving noise correlation time. This results in a transition from the Itô to the Stratonovich sense of the SDE and yields a long-range memory process.

Quantifying data retention of perpendicular spin-transfer-torque magnetic random access memory chips using an effective thermal stability factor method

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

Thomas, Luc, E-mail: luc.thomas@headway.com; Jan, Guenole; Le, Son

The thermal stability of perpendicular Spin-Transfer-Torque Magnetic Random Access Memory (STT-MRAM) devices is investigated at chip level. Experimental data are analyzed in the framework of the Néel-Brown model including distributions of the thermal stability factor Δ. We show that in the low error rate regime important for applications, the effect of distributions of Δ can be described by a single quantity, the effective thermal stability factor Δ{sub eff}, which encompasses both the median and the standard deviation of the distributions. Data retention of memory chips can be assessed accurately by measuring Δ{sub eff} as a function of device diameter andmore » temperature. We apply this method to show that 54 nm devices based on our perpendicular STT-MRAM design meet our 10 year data retention target up to 120 °C.« less

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

PubMed

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

2016-02-01

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

A Distributed Platform for Global-Scale Agent-Based Models of Disease Transmission

PubMed Central

Parker, Jon; Epstein, Joshua M.

2013-01-01

The Global-Scale Agent Model (GSAM) is presented. The GSAM is a high-performance distributed platform for agent-based epidemic modeling capable of simulating a disease outbreak in a population of several billion agents. It is unprecedented in its scale, its speed, and its use of Java. Solutions to multiple challenges inherent in distributing massive agent-based models are presented. Communication, synchronization, and memory usage are among the topics covered in detail. The memory usage discussion is Java specific. However, the communication and synchronization discussions apply broadly. We provide benchmarks illustrating the GSAM’s speed and scalability. PMID:24465120

Figuring fact from fiction: unbiased polling of memory T cells.

PubMed

Gerlach, Carmen; Loughhead, Scott M; von Andrian, Ulrich H

2015-05-07

Immunization generates several memory T cell subsets that differ in their migratory properties, anatomic distribution, and, hence, accessibility to investigation. In this issue, Steinert et al. demonstrate that what was believed to be a minor memory cell subset in peripheral tissues has been dramatically underestimated. Thus, current models of protective immunity require revision. Copyright © 2015 Elsevier Inc. All rights reserved.

Working memory retrieval as a decision process

PubMed Central

Pearson, Benjamin; Raškevičius, Julius; Bays, Paul M.; Pertzov, Yoni; Husain, Masud

2014-01-01

Working memory (WM) is a core cognitive process fundamental to human behavior, yet the mechanisms underlying it remain highly controversial. Here we provide a new framework for understanding retrieval of information from WM, conceptualizing it as a decision based on the quality of internal evidence. Recent findings have demonstrated that precision of WM decreases with memory load. If WM retrieval uses a decision process that depends on memory quality, systematic changes in response time distribution should occur as a function of WM precision. We asked participants to view sample arrays and, after a delay, report the direction of change in location or orientation of a probe. As WM precision deteriorated with increasing memory load, retrieval time increased systematically. Crucially, the shape of reaction time distributions was consistent with a linear accumulator decision process. Varying either task relevance of items or maintenance duration influenced memory precision, with corresponding shifts in retrieval time. These results provide strong support for a decision-making account of WM retrieval based on noisy storage of items. Furthermore, they show that encoding, maintenance, and retrieval in WM need not be considered as separate processes, but may instead be conceptually unified as operations on the same noise-limited, neural representation. PMID:24492597

The Molecular Basis of Memory

PubMed Central

2012-01-01

We propose a tripartite biochemical mechanism for memory. Three physiologic components are involved, namely, the neuron (individual and circuit), the surrounding neural extracellular matrix, and the various trace metals distributed within the matrix. The binding of a metal cation affects a corresponding nanostructure (shrinking, twisting, expansion) and dielectric sensibility of the chelating node (address) within the matrix lattice, sensed by the neuron. The neural extracellular matrix serves as an electro-elastic lattice, wherein neurons manipulate multiple trace metals (n > 10) to encode, store, and decode coginive information. The proposed mechanism explains brains low energy requirements and high rates of storage capacity described in multiples of Avogadro number (NA = 6 × 1023). Supportive evidence correlates memory loss to trace metal toxicity or deficiency, or breakdown in the delivery/transport of metals to the matrix, or its degradation. Inherited diseases revolving around dysfunctional trace metal metabolism and memory dysfunction, include Alzheimer's disease (Al, Zn, Fe), Wilson’s disease (Cu), thalassemia (Fe), and autism (metallothionein). The tripartite mechanism points to the electro-elastic interactions of neurons with trace metals distributed within the neural extracellular matrix, as the molecular underpinning of “synaptic plasticity” affecting short-term memory, long-term memory, and forgetting. PMID:23050060

Working memory retrieval as a decision process.

PubMed

Pearson, Benjamin; Raskevicius, Julius; Bays, Paul M; Pertzov, Yoni; Husain, Masud

2014-02-03

Working memory (WM) is a core cognitive process fundamental to human behavior, yet the mechanisms underlying it remain highly controversial. Here we provide a new framework for understanding retrieval of information from WM, conceptualizing it as a decision based on the quality of internal evidence. Recent findings have demonstrated that precision of WM decreases with memory load. If WM retrieval uses a decision process that depends on memory quality, systematic changes in response time distribution should occur as a function of WM precision. We asked participants to view sample arrays and, after a delay, report the direction of change in location or orientation of a probe. As WM precision deteriorated with increasing memory load, retrieval time increased systematically. Crucially, the shape of reaction time distributions was consistent with a linear accumulator decision process. Varying either task relevance of items or maintenance duration influenced memory precision, with corresponding shifts in retrieval time. These results provide strong support for a decision-making account of WM retrieval based on noisy storage of items. Furthermore, they show that encoding, maintenance, and retrieval in WM need not be considered as separate processes, but may instead be conceptually unified as operations on the same noise-limited, neural representation.

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

NASA Astrophysics Data System (ADS)

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

1995-12-01

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

Efficient computation of aerodynamic influence coefficients for aeroelastic analysis on a transputer network

NASA Technical Reports Server (NTRS)

Janetzke, David C.; Murthy, Durbha V.

1991-01-01

Aeroelastic analysis is multi-disciplinary and computationally expensive. Hence, it can greatly benefit from parallel processing. As part of an effort to develop an aeroelastic capability on a distributed memory transputer network, a parallel algorithm for the computation of aerodynamic influence coefficients is implemented on a network of 32 transputers. The aerodynamic influence coefficients are calculated using a 3-D unsteady aerodynamic model and a parallel discretization. Efficiencies up to 85 percent were demonstrated using 32 processors. The effect of subtask ordering, problem size, and network topology are presented. A comparison to results on a shared memory computer indicates that higher speedup is achieved on the distributed memory system.

Stochastic switching of TiO2-based memristive devices with identical initial memory states

PubMed Central

2014-01-01

In this work, we show that identical TiO2-based memristive devices that possess the same initial resistive states are only phenomenologically similar as their internal structures may vary significantly, which could render quite dissimilar switching dynamics. We experimentally demonstrated that the resistive switching of practical devices with similar initial states could occur at different programming stimuli cycles. We argue that similar memory states can be transcribed via numerous distinct active core states through the dissimilar reduced TiO2-x filamentary distributions. Our hypothesis was finally verified via simulated results of the memory state evolution, by taking into account dissimilar initial filamentary distribution. PMID:24994953

Memory operation mechanism of fullerene-containing polymer memory

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

Nakajima, Anri, E-mail: anakajima@hiroshima-u.ac.jp; Fujii, Daiki

2015-03-09

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

Single Event Upset Analysis: On-orbit performance of the Alpha Magnetic Spectrometer Digital Signal Processor Memory aboard the International Space Station

NASA Astrophysics Data System (ADS)

Li, Jiaqiang; Choutko, Vitaly; Xiao, Liyi

2018-03-01

Based on the collection of error data from the Alpha Magnetic Spectrometer (AMS) Digital Signal Processors (DSP), on-orbit Single Event Upsets (SEUs) of the DSP program memory are analyzed. The daily error distribution and time intervals between errors are calculated to evaluate the reliability of the system. The particle density distribution of International Space Station (ISS) orbit is presented and the effects from the South Atlantic Anomaly (SAA) and the geomagnetic poles are analyzed. The impact of solar events on the DSP program memory is carried out combining data analysis and Monte Carlo simulation (MC). From the analysis and simulation results, it is concluded that the area corresponding to the SAA is the main source of errors on the ISS orbit. Solar events can also cause errors on DSP program memory, but the effect depends on the on-orbit particle density.

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

CD4 T-Cell Memory Generation and Maintenance

PubMed Central

Gasper, David J.; Tejera, Melba Marie; Suresh, M.

2014-01-01

Immunologic memory is the adaptive immune system's powerful ability to remember a previous antigen encounter and react with accelerated vigor upon antigen re-exposure. It provides durable protection against reinfection with pathogens and is the foundation for vaccine-induced immunity. Unlike the relatively restricted immunologic purview of memory B cells and CD8 T cells, the field of CD4 T-cell memory must account for multiple distinct lineages with diverse effector functions, the issue of lineage commitment and plasticity, and the variable distribution of memory cells within each lineage. Here, we discuss the evidence for lineage-specific CD4 T-cell memory and summarize the known factors contributing to memory-cell generation, plasticity, and long-term maintenance. PMID:24940912

Mixed memory, (non) Hurst effect, and maximum entropy of rainfall in the tropical Andes

NASA Astrophysics Data System (ADS)

Poveda, Germán

2011-02-01

Diverse linear and nonlinear statistical parameters of rainfall under aggregation in time and the kind of temporal memory are investigated. Data sets from the Andes of Colombia at different resolutions (15 min and 1-h), and record lengths (21 months and 8-40 years) are used. A mixture of two timescales is found in the autocorrelation and autoinformation functions, with short-term memory holding for time lags less than 15-30 min, and long-term memory onwards. Consistently, rainfall variance exhibits different temporal scaling regimes separated at 15-30 min and 24 h. Tests for the Hurst effect evidence the frailty of the R/ S approach in discerning the kind of memory in high resolution rainfall, whereas rigorous statistical tests for short-memory processes do reject the existence of the Hurst effect. Rainfall information entropy grows as a power law of aggregation time, S( T) ˜ Tβ with < β> = 0.51, up to a timescale, TMaxEnt (70-202 h), at which entropy saturates, with β = 0 onwards. Maximum entropy is reached through a dynamic Generalized Pareto distribution, consistently with the maximum information-entropy principle for heavy-tailed random variables, and with its asymptotically infinitely divisible property. The dynamics towards the limit distribution is quantified. Tsallis q-entropies also exhibit power laws with T, such that Sq( T) ˜ Tβ( q) , with β( q) ⩽ 0 for q ⩽ 0, and β( q) ≃ 0.5 for q ⩾ 1. No clear patterns are found in the geographic distribution within and among the statistical parameters studied, confirming the strong variability of tropical Andean rainfall.

Towards Low-Cost Effective and Homogeneous Thermal Activation of Shape Memory Polymers

PubMed Central

Lantada, Andrés Díaz; Rebollo, María Ángeles Santamaría

2013-01-01

A typical limitation of intelligent devices based on the use of shape-memory polymers as actuators is linked to the widespread use of distributed heating resistors, via Joule effect, as activation method, which involves several relevant issues needing attention, such as: (a) Final device size is importantly increased due to the additional space required for the resistances; (b) the use of resistances limits materials’ strength and the obtained devices are normally weaker; (c) the activation process through heating resistances is not homogeneous, thus leading to important temperature differences among the polymeric structure and to undesirable thermal gradients and stresses, also limiting the application fields of shape-memory polymers. In our present work we describe interesting activation alternatives, based on coating shape-memory polymers with different kinds of conductive materials, including textiles, conductive threads and conductive paint, which stand out for their easy, rapid and very cheap implementation. Distributed heating and homogeneous activation can be achieved in several of the alternatives studied and the technical results are comparable to those obtained by using advanced shape-memory nanocomposites, which have to deal with complex synthesis, processing and security aspects. Different combinations of shape memory epoxy resin with several coating electrotextiles, conductive films and paints are prepared, simulated with the help of thermal finite element method based resources and characterized using infrared thermography for validating the simulations and overall design process. A final application linked to an active catheter pincer is detailed and the advantages of using distributed heating instead of conventional resistors are discussed. PMID:28788401

Global Arrays

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

Krishnamoorthy, Sriram; Daily, Jeffrey A.; Vishnu, Abhinav

2015-11-01

Global Arrays (GA) is a distributed-memory programming model that allows for shared-memory-style programming combined with one-sided communication, to create a set of tools that combine high performance with ease-of-use. GA exposes a relatively straightforward programming abstraction, while supporting fully-distributed data structures, locality of reference, and high-performance communication. GA was originally formulated in the early 1990’s to provide a communication layer for the Northwest Chemistry (NWChem) suite of chemistry modeling codes that was being developed concurrently.

Variable Order and Distributed Order Fractional Operators

NASA Technical Reports Server (NTRS)

Lorenzo, Carl F.; Hartley, Tom T.

2002-01-01

Many physical processes appear to exhibit fractional order behavior that may vary with time or space. The continuum of order in the fractional calculus allows the order of the fractional operator to be considered as a variable. This paper develops the concept of variable and distributed order fractional operators. Definitions based on the Riemann-Liouville definitions are introduced and behavior of the operators is studied. Several time domain definitions that assign different arguments to the order q in the Riemann-Liouville definition are introduced. For each of these definitions various characteristics are determined. These include: time invariance of the operator, operator initialization, physical realization, linearity, operational transforms. and memory characteristics of the defining kernels. A measure (m2) for memory retentiveness of the order history is introduced. A generalized linear argument for the order q allows the concept of "tailored" variable order fractional operators whose a, memory may be chosen for a particular application. Memory retentiveness (m2) and order dynamic behavior are investigated and applications are shown. The concept of distributed order operators where the order of the time based operator depends on an additional independent (spatial) variable is also forwarded. Several definitions and their Laplace transforms are developed, analysis methods with these operators are demonstrated, and examples shown. Finally operators of multivariable and distributed order are defined in their various applications are outlined.

Still searching for the engram.

PubMed

Eichenbaum, Howard

2016-09-01

For nearly a century, neurobiologists have searched for the engram-the neural representation of a memory. Early studies showed that the engram is widely distributed both within and across brain areas and is supported by interactions among large networks of neurons. Subsequent research has identified engrams that support memory within dedicated functional systems for habit learning and emotional memory, but the engram for declarative memories has been elusive. Nevertheless, recent years have brought progress from molecular biological approaches that identify neurons and networks that are necessary and sufficient to support memory, and from recording approaches and population analyses that characterize the information coded by large neural networks. These new directions offer the promise of revealing the engrams for episodic and semantic memories.

Emotion-attention interactions in recognition memory for distractor faces.

PubMed

Srinivasan, Narayanan; Gupta, Rashmi

2010-04-01

Effective filtering of distractor information has been shown to be dependent on perceptual load. Given the salience of emotional information and the presence of emotion-attention interactions, we wanted to explore the recognition memory for emotional distractors especially as a function of focused attention and distributed attention by manipulating load and the spatial spread of attention. We performed two experiments to study emotion-attention interactions by measuring recognition memory performance for distractor neutral and emotional faces. Participants performed a color discrimination task (low-load) or letter identification task (high-load) with a letter string display in Experiment 1 and a high-load letter identification task with letters presented in a circular array in Experiment 2. The stimuli were presented against a distractor face background. The recognition memory results show that happy faces were recognized better than sad faces under conditions of less focused or distributed attention. When attention is more spatially focused, sad faces were recognized better than happy faces. The study provides evidence for emotion-attention interactions in which specific emotional information like sad or happy is associated with focused or distributed attention respectively. Distractor processing with emotional information also has implications for theories of attention. Copyright 2010 APA, all rights reserved.

A trade-off between local and distributed information processing associated with remote episodic versus semantic memory.

PubMed

Heisz, Jennifer J; Vakorin, Vasily; Ross, Bernhard; Levine, Brian; McIntosh, Anthony R

2014-01-01

Episodic memory and semantic memory produce very different subjective experiences yet rely on overlapping networks of brain regions for processing. Traditional approaches for characterizing functional brain networks emphasize static states of function and thus are blind to the dynamic information processing within and across brain regions. This study used information theoretic measures of entropy to quantify changes in the complexity of the brain's response as measured by magnetoencephalography while participants listened to audio recordings describing past personal episodic and general semantic events. Personal episodic recordings evoked richer subjective mnemonic experiences and more complex brain responses than general semantic recordings. Critically, we observed a trade-off between the relative contribution of local versus distributed entropy, such that personal episodic recordings produced relatively more local entropy whereas general semantic recordings produced relatively more distributed entropy. Changes in the relative contributions of local and distributed entropy to the total complexity of the system provides a potential mechanism that allows the same network of brain regions to represent cognitive information as either specific episodes or more general semantic knowledge.

Work stealing for GPU-accelerated parallel programs in a global address space framework: WORK STEALING ON GPU-ACCELERATED SYSTEMS

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

Arafat, Humayun; Dinan, James; Krishnamoorthy, Sriram

Task parallelism is an attractive approach to automatically load balance the computation in a parallel system and adapt to dynamism exhibited by parallel systems. Exploiting task parallelism through work stealing has been extensively studied in shared and distributed-memory contexts. In this paper, we study the design of a system that uses work stealing for dynamic load balancing of task-parallel programs executed on hybrid distributed-memory CPU-graphics processing unit (GPU) systems in a global-address space framework. We take into account the unique nature of the accelerator model employed by GPUs, the significant performance difference between GPU and CPU execution as a functionmore » of problem size, and the distinct CPU and GPU memory domains. We consider various alternatives in designing a distributed work stealing algorithm for CPU-GPU systems, while taking into account the impact of task distribution and data movement overheads. These strategies are evaluated using microbenchmarks that capture various execution configurations as well as the state-of-the-art CCSD(T) application module from the computational chemistry domain.« less

Work stealing for GPU-accelerated parallel programs in a global address space framework

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

Arafat, Humayun; Dinan, James; Krishnamoorthy, Sriram

Task parallelism is an attractive approach to automatically load balance the computation in a parallel system and adapt to dynamism exhibited by parallel systems. Exploiting task parallelism through work stealing has been extensively studied in shared and distributed-memory contexts. In this paper, we study the design of a system that uses work stealing for dynamic load balancing of task-parallel programs executed on hybrid distributed-memory CPU-graphics processing unit (GPU) systems in a global-address space framework. We take into account the unique nature of the accelerator model employed by GPUs, the significant performance difference between GPU and CPU execution as a functionmore » of problem size, and the distinct CPU and GPU memory domains. We consider various alternatives in designing a distributed work stealing algorithm for CPU-GPU systems, while taking into account the impact of task distribution and data movement overheads. These strategies are evaluated using microbenchmarks that capture various execution configurations as well as the state-of-the-art CCSD(T) application module from the computational chemistry domain« less

Emotional organization of autobiographical memory.

PubMed

Schulkind, Matthew D; Woldorf, Gillian M

2005-09-01

The emotional organization of autobiographical memory was examined by determining whether emotional cues would influence autobiographical retrieval in younger and older adults. Unfamiliar musical cues that represented orthogonal combinations of positive and negative valence and high and low arousal were used. Whereas cue valence influenced the valence of the retrieved memories, cue arousal did not affect arousal ratings. However, high-arousal cues were associated with reduced response latencies. A significant bias to report positive memories was observed, especially for the older adults, but neither the distribution of memories across the life span nor response latencies varied across memories differing in valence or arousal. These data indicate that emotional information can serve as effective cues for autobiographical memories and that autobiographical memories are organized in terms of emotional valence but not emotional arousal. Thus, current theories of autobiographical memory must be expanded to include emotional valence as a primary dimension of organization.

A Cerebellar-model Associative Memory as a Generalized Random-access Memory

NASA Technical Reports Server (NTRS)

Kanerva, Pentti

1989-01-01

A versatile neural-net model is explained in terms familiar to computer scientists and engineers. It is called the sparse distributed memory, and it is a random-access memory for very long words (for patterns with thousands of bits). Its potential utility is the result of several factors: (1) a large pattern representing an object or a scene or a moment can encode a large amount of information about what it represents; (2) this information can serve as an address to the memory, and it can also serve as data; (3) the memory is noise tolerant--the information need not be exact; (4) the memory can be made arbitrarily large and hence an arbitrary amount of information can be stored in it; and (5) the architecture is inherently parallel, allowing large memories to be fast. Such memories can become important components of future computers.

Performance Modeling and Measurement of Parallelized Code for Distributed Shared Memory Multiprocessors

NASA Technical Reports Server (NTRS)

Waheed, Abdul; Yan, Jerry

1998-01-01

This paper presents a model to evaluate the performance and overhead of parallelizing sequential code using compiler directives for multiprocessing on distributed shared memory (DSM) systems. With increasing popularity of shared address space architectures, it is essential to understand their performance impact on programs that benefit from shared memory multiprocessing. We present a simple model to characterize the performance of programs that are parallelized using compiler directives for shared memory multiprocessing. We parallelized the sequential implementation of NAS benchmarks using native Fortran77 compiler directives for an Origin2000, which is a DSM system based on a cache-coherent Non Uniform Memory Access (ccNUMA) architecture. We report measurement based performance of these parallelized benchmarks from four perspectives: efficacy of parallelization process; scalability; parallelization overhead; and comparison with hand-parallelized and -optimized version of the same benchmarks. Our results indicate that sequential programs can conveniently be parallelized for DSM systems using compiler directives but realizing performance gains as predicted by the performance model depends primarily on minimizing architecture-specific data locality overhead.

Two-dimensional shape recognition using sparse distributed memory

NASA Technical Reports Server (NTRS)

Kanerva, Pentti; Olshausen, Bruno

1990-01-01

Researchers propose a method for recognizing two-dimensional shapes (hand-drawn characters, for example) with an associative memory. The method consists of two stages: first, the image is preprocessed to extract tangents to the contour of the shape; second, the set of tangents is converted to a long bit string for recognition with sparse distributed memory (SDM). SDM provides a simple, massively parallel architecture for an associative memory. Long bit vectors (256 to 1000 bits, for example) serve as both data and addresses to the memory, and patterns are grouped or classified according to similarity in Hamming distance. At the moment, tangents are extracted in a simple manner by progressively blurring the image and then using a Canny-type edge detector (Canny, 1986) to find edges at each stage of blurring. This results in a grid of tangents. While the technique used for obtaining the tangents is at present rather ad hoc, researchers plan to adopt an existing framework for extracting edge orientation information over a variety of resolutions, such as suggested by Watson (1987, 1983), Marr and Hildreth (1980), or Canny (1986).

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 systems in schizophrenia: Modularity is preserved but deficits are generalized.

PubMed

Haut, Kristen M; Karlsgodt, Katherine H; Bilder, Robert M; Congdon, Eliza; Freimer, Nelson B; London, Edythe D; Sabb, Fred W; Ventura, Joseph; Cannon, Tyrone D

2015-10-01

Schizophrenia patients exhibit impaired working and episodic memory, but this may represent generalized impairment across memory modalities or performance deficits restricted to particular memory systems in subgroups of patients. Furthermore, it is unclear whether deficits are unique from those associated with other disorders. Healthy controls (n=1101) and patients with schizophrenia (n=58), bipolar disorder (n=49) and attention-deficit-hyperactivity-disorder (n=46) performed 18 tasks addressing primarily verbal and spatial episodic and working memory. Effect sizes for group contrasts were compared across tasks and the consistency of subjects' distributional positions across memory domains was measured. Schizophrenia patients performed poorly relative to the other groups on every test. While low to moderate correlation was found between memory domains (r=.320), supporting modularity of these systems, there was limited agreement between measures regarding each individual's task performance (ICC=.292) and in identifying those individuals falling into the lowest quintile (kappa=0.259). A general ability factor accounted for nearly all of the group differences in performance and agreement across measures in classifying low performers. Pathophysiological processes involved in schizophrenia appear to act primarily on general abilities required in all tasks rather than on specific abilities within different memory domains and modalities. These effects represent a general shift in the overall distribution of general ability (i.e., each case functioning at a lower level than they would have if not for the illness), rather than presence of a generally low-performing subgroup of patients. There is little evidence that memory impairments in schizophrenia are shared with bipolar disorder and ADHD. Copyright © 2015 Elsevier B.V. All rights reserved.

Memory systems in schizophrenia: Modularity is preserved but deficits are generalized

PubMed Central

Haut, Kristen M.; Karlsgodt, Katherine H.; Bilder, Robert M.; Congdon, Eliza; Freimer, Nelson; London, Edythe D.; Sabb, Fred W.; Ventura, Joseph; Cannon, Tyrone D.

2015-01-01

Objective Schizophrenia patients exhibit impaired working and episodic memory, but this may represent generalized impairment across memory modalities or performance deficits restricted to particular memory systems in subgroups of patients. Furthermore, it is unclear whether deficits are unique from those associated with other disorders. Method Healthy controls (n=1101) and patients with schizophrenia (n=58), bipolar disorder (n=49) and attention-deficit-hyperactivity-disorder (n=46) performed 18 tasks addressing primarily verbal and spatial episodic and working memory. Effect sizes for group contrasts were compared across tasks and the consistency of subjects’ distributional positions across memory domains was measured. Results Schizophrenia patients performed poorly relative to the other groups on every test. While low to moderate correlation was found between memory domains (r=.320), supporting modularity of these systems, there was limited agreement between measures regarding each individual’s task performance (ICC=.292) and in identifying those individuals falling into the lowest quintile (kappa=0.259). A general ability factor accounted for nearly all of the group differences in performance and agreement across measures in classifying low performers. Conclusions Pathophysiological processes involved in schizophrenia appear to act primarily on general abilities required in all tasks rather than on specific abilities within different memory domains and modalities. These effects represent a general shift in the overall distribution of general ability (i.e., each case functioning at a lower level than they would have if not for the illness), rather than presence of a generally low-performing subgroup of patients. There is little evidence that memory impairments in schizophrenia are shared with bipolar disorder and ADHD. PMID:26299707

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

Limits in decision making arise from limits in memory retrieval.

PubMed

Giguère, Gyslain; Love, Bradley C

2013-05-07

Some decisions, such as predicting the winner of a baseball game, are challenging in part because outcomes are probabilistic. When making such decisions, one view is that humans stochastically and selectively retrieve a small set of relevant memories that provides evidence for competing options. We show that optimal performance at test is impossible when retrieving information in this fashion, no matter how extensive training is, because limited retrieval introduces noise into the decision process that cannot be overcome. One implication is that people should be more accurate in predicting future events when trained on idealized rather than on the actual distributions of items. In other words, we predict the best way to convey information to people is to present it in a distorted, idealized form. Idealization of training distributions is predicted to reduce the harmful noise induced by immutable bottlenecks in people's memory retrieval processes. In contrast, machine learning systems that selectively weight (i.e., retrieve) all training examples at test should not benefit from idealization. These conjectures are strongly supported by several studies and supporting analyses. Unlike machine systems, people's test performance on a target distribution is higher when they are trained on an idealized version of the distribution rather than on the actual target distribution. Optimal machine classifiers modified to selectively and stochastically sample from memory match the pattern of human performance. These results suggest firm limits on human rationality and have broad implications for how to train humans tasked with important classification decisions, such as radiologists, baggage screeners, intelligence analysts, and gamblers.

Limits in decision making arise from limits in memory retrieval

PubMed Central

Giguère, Gyslain; Love, Bradley C.

2013-01-01

Some decisions, such as predicting the winner of a baseball game, are challenging in part because outcomes are probabilistic. When making such decisions, one view is that humans stochastically and selectively retrieve a small set of relevant memories that provides evidence for competing options. We show that optimal performance at test is impossible when retrieving information in this fashion, no matter how extensive training is, because limited retrieval introduces noise into the decision process that cannot be overcome. One implication is that people should be more accurate in predicting future events when trained on idealized rather than on the actual distributions of items. In other words, we predict the best way to convey information to people is to present it in a distorted, idealized form. Idealization of training distributions is predicted to reduce the harmful noise induced by immutable bottlenecks in people’s memory retrieval processes. In contrast, machine learning systems that selectively weight (i.e., retrieve) all training examples at test should not benefit from idealization. These conjectures are strongly supported by several studies and supporting analyses. Unlike machine systems, people’s test performance on a target distribution is higher when they are trained on an idealized version of the distribution rather than on the actual target distribution. Optimal machine classifiers modified to selectively and stochastically sample from memory match the pattern of human performance. These results suggest firm limits on human rationality and have broad implications for how to train humans tasked with important classification decisions, such as radiologists, baggage screeners, intelligence analysts, and gamblers. PMID:23610402

Memory for Serial Order.

ERIC Educational Resources Information Center

Lewandowsky, Stephan; Murdock, Bennet B., Jr.

1989-01-01

An extension to Murdock's Theory of Distributed Associative Memory, based on associative chaining between items, is presented. The extended theory is applied to several serial order phenomena, including serial list learning, delayed recall effects, partial report effects, and buildup and release from proactive interference. (TJH)

Exploring the use of memory colors for image enhancement

NASA Astrophysics Data System (ADS)

Xue, Su; Tan, Minghui; McNamara, Ann; Dorsey, Julie; Rushmeier, Holly

2014-02-01

Memory colors refer to those colors recalled in association with familiar objects. While some previous work introduces this concept to assist digital image enhancement, their basis, i.e., on-screen memory colors, are not appropriately investigated. In addition, the resulting adjustment methods developed are not evaluated from a perceptual view of point. In this paper, we first perform a context-free perceptual experiment to establish the overall distributions of screen memory colors for three pervasive objects. Then, we use a context-based experiment to locate the most representative memory colors; at the same time, we investigate the interactions of memory colors between different objects. Finally, we show a simple yet effective application using representative memory colors to enhance digital images. A user study is performed to evaluate the performance of our technique.

PIPS-SBB: A Parallel Distributed-Memory Branch-and-Bound Algorithm for Stochastic Mixed-Integer Programs

DOE PAGES

Munguia, Lluis-Miquel; Oxberry, Geoffrey; Rajan, Deepak

2016-05-01

Stochastic mixed-integer programs (SMIPs) deal with optimization under uncertainty at many levels of the decision-making process. When solved as extensive formulation mixed- integer programs, problem instances can exceed available memory on a single workstation. In order to overcome this limitation, we present PIPS-SBB: a distributed-memory parallel stochastic MIP solver that takes advantage of parallelism at multiple levels of the optimization process. We also show promising results on the SIPLIB benchmark by combining methods known for accelerating Branch and Bound (B&B) methods with new ideas that leverage the structure of SMIPs. Finally, we expect the performance of PIPS-SBB to improve furthermore » as more functionality is added in the future.« less

Capacity for patterns and sequences in Kanerva's SDM as compared to other associative memory models. [Sparse, Distributed Memory

NASA Technical Reports Server (NTRS)

Keeler, James D.

1988-01-01

The information capacity of Kanerva's Sparse Distributed Memory (SDM) and Hopfield-type neural networks is investigated. Under the approximations used here, it is shown that the total information stored in these systems is proportional to the number connections in the network. The proportionality constant is the same for the SDM and Hopfield-type models independent of the particular model, or the order of the model. The approximations are checked numerically. This same analysis can be used to show that the SDM can store sequences of spatiotemporal patterns, and the addition of time-delayed connections allows the retrieval of context dependent temporal patterns. A minor modification of the SDM can be used to store correlated patterns.

Periodic bidirectional associative memory neural networks with distributed delays

NASA Astrophysics Data System (ADS)

Chen, Anping; Huang, Lihong; Liu, Zhigang; Cao, Jinde

2006-05-01

Some sufficient conditions are obtained for the existence and global exponential stability of a periodic solution to the general bidirectional associative memory (BAM) neural networks with distributed delays by using the continuation theorem of Mawhin's coincidence degree theory and the Lyapunov functional method and the Young's inequality technique. These results are helpful for designing a globally exponentially stable and periodic oscillatory BAM neural network, and the conditions can be easily verified and be applied in practice. An example is also given to illustrate our results.

A view of Kanerva's sparse distributed memory

NASA Technical Reports Server (NTRS)

Denning, P. J.

1986-01-01

Pentti Kanerva is working on a new class of computers, which are called pattern computers. Pattern computers may close the gap between capabilities of biological organisms to recognize and act on patterns (visual, auditory, tactile, or olfactory) and capabilities of modern computers. Combinations of numeric, symbolic, and pattern computers may one day be capable of sustaining robots. The overview of the requirements for a pattern computer, a summary of Kanerva's Sparse Distributed Memory (SDM), and examples of tasks this computer can be expected to perform well are given.

Kinetics of Magnetoelastic Twin-Boundary Motion in Ferromagnetic Shape-Memory Alloys

NASA Astrophysics Data System (ADS)

Pramanick, A.; Wang, X.-L.; Stoica, A. D.; Yu, C.; Ren, Y.; Tang, S.; Gai, Z.

2014-05-01

We report the kinetics of twin-boundary motion in the ferromagnetic shape-memory alloy of Ni-Mn-Ga as measured by in situ high energy synchrotron diffraction. The temporal evolution of twin reorientation during the application of a magnetic field is described by thermally activated creep motion of twin boundaries over a distribution of energy barriers. The dynamical creep exponent μ was found to be ˜0.5, suggesting that the distribution of energy barriers is a result of short-range disorders.

Nanophotonic rare-earth quantum memory with optically controlled retrieval

NASA Astrophysics Data System (ADS)

Zhong, Tian; Kindem, Jonathan M.; Bartholomew, John G.; Rochman, Jake; Craiciu, Ioana; Miyazono, Evan; Bettinelli, Marco; Cavalli, Enrico; Verma, Varun; Nam, Sae Woo; Marsili, Francesco; Shaw, Matthew D.; Beyer, Andrew D.; Faraon, Andrei

2017-09-01

Optical quantum memories are essential elements in quantum networks for long-distance distribution of quantum entanglement. Scalable development of quantum network nodes requires on-chip qubit storage functionality with control of the readout time. We demonstrate a high-fidelity nanophotonic quantum memory based on a mesoscopic neodymium ensemble coupled to a photonic crystal cavity. The nanocavity enables >95% spin polarization for efficient initialization of the atomic frequency comb memory and time bin-selective readout through an enhanced optical Stark shift of the comb frequencies. Our solid-state memory is integrable with other chip-scale photon source and detector devices for multiplexed quantum and classical information processing at the network nodes.

Memory for light as a quantum process.

PubMed

Lobino, M; Kupchak, C; Figueroa, E; Lvovsky, A I

2009-05-22

We report complete characterization of an optical memory based on electromagnetically induced transparency. We recover the superoperator associated with the memory, under two different working conditions, by means of a quantum process tomography technique that involves storage of coherent states and their characterization upon retrieval. In this way, we can predict the quantum state retrieved from the memory for any input, for example, the squeezed vacuum or the Fock state. We employ the acquired superoperator to verify the nonclassicality benchmark for the storage of a Gaussian distributed set of coherent states.

Uncertainty relations with quantum memory for the Wehrl entropy

NASA Astrophysics Data System (ADS)

De Palma, Giacomo

2018-03-01

We prove two new fundamental uncertainty relations with quantum memory for the Wehrl entropy. The first relation applies to the bipartite memory scenario. It determines the minimum conditional Wehrl entropy among all the quantum states with a given conditional von Neumann entropy and proves that this minimum is asymptotically achieved by a suitable sequence of quantum Gaussian states. The second relation applies to the tripartite memory scenario. It determines the minimum of the sum of the Wehrl entropy of a quantum state conditioned on the first memory quantum system with the Wehrl entropy of the same state conditioned on the second memory quantum system and proves that also this minimum is asymptotically achieved by a suitable sequence of quantum Gaussian states. The Wehrl entropy of a quantum state is the Shannon differential entropy of the outcome of a heterodyne measurement performed on the state. The heterodyne measurement is one of the main measurements in quantum optics and lies at the basis of one of the most promising protocols for quantum key distribution. These fundamental entropic uncertainty relations will be a valuable tool in quantum information and will, for example, find application in security proofs of quantum key distribution protocols in the asymptotic regime and in entanglement witnessing in quantum optics.

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.

Still searching for the engram

PubMed Central

Eichenbaum, Howard

2016-01-01

For nearly a century neurobiologists have searched for the engram - the neural representation of a memory. Early studies showed that the engram is widely distributed both within and across brain areas and is supported by interactions among large networks of neurons. Subsequent research has identified engrams that support memory within dedicated functional systems for habit learning and emotional memory, but the engram for declarative memories has been elusive. Nevertheless, recent years have brought progress from molecular biological approaches that identify neurons and networks that are necessary and sufficient to support memory, and from recording approaches and population analyses that characterize the information coded by large neural networks. These new directions offer the promise of revealing the engrams for episodic and semantic memories. PMID:26944423

Becoming a better person: temporal remoteness biases autobiographical memories for moral events

PubMed Central

Escobedo, Jessica R.; Adolphs, Ralph

2010-01-01

Our autobiographical self depends on the differential recollection of our personal past, notably including memories of morally laden events. While both emotion and temporal recency are well known to influence memory, very little is known about how we remember moral events, and in particular about the distribution in time of memories for events that were blameworthy or praiseworthy. To investigate this issue in detail, we collected a novel database of 758 confidential, autobiographical narratives for personal moral events from 100 well-characterized healthy adults. Negatively valenced moral memories were significantly more remote than positively valenced memories, both as measured by the valence of the cue word that evoked the memory as well as by the content of the memory itself. The effect was independent of chronological age, ethnicity, gender, or personality, arguing for a general emotional bias in how we construct our moral autobiography. PMID:20677868

Rapid effects on memory consolidation and spine morphology by estradiol in female and male rodents.

PubMed

Luine, Victoria; Serrano, Peter; Frankfurt, Maya

2018-05-16

Rapid, neurosteroid-like effects of estrogens on memory consolidation during recognition memory tasks in both male and female rodents are described. We discuss how these mnemonic changes are related to rapid estrogenic effects on dendritic spine density, the distribution of spine types and the expression of PSD95 and GluA2 within spines in the hippocampus and medial prefrontal cortex, two areas critical for learning and memory. Overall, these data lead to the conclusion that estrogens are capable of exerting rapid and potent influences on memory and spine morphology in both sexes. The demonstration of estrogenic effects in males, which are used in the majority of memory studies, may provide a model for better understanding how hormone dependent changes in signaling pathways mediating memory and spinogenesis are coordinated to promote memory consolidation. Copyright © 2018 Elsevier Inc. All rights reserved.

Distributed memory approaches for robotic neural controllers

NASA Technical Reports Server (NTRS)

Jorgensen, Charles C.

1990-01-01

The suitability is explored of two varieties of distributed memory neutral networks as trainable controllers for a simulated robotics task. The task requires that two cameras observe an arbitrary target point in space. Coordinates of the target on the camera image planes are passed to a neural controller which must learn to solve the inverse kinematics of a manipulator with one revolute and two prismatic joints. Two new network designs are evaluated. The first, radial basis sparse distributed memory (RBSDM), approximates functional mappings as sums of multivariate gaussians centered around previously learned patterns. The second network types involved variations of Adaptive Vector Quantizers or Self Organizing Maps. In these networks, random N dimensional points are given local connectivities. They are then exposed to training patterns and readjust their locations based on a nearest neighbor rule. Both approaches are tested based on their ability to interpolate manipulator joint coordinates for simulated arm movement while simultaneously performing stereo fusion of the camera data. Comparisons are made with classical k-nearest neighbor pattern recognition techniques.

Channel doping concentration and cell program state dependence on random telegraph noise spatial and statistical distribution in 30 nm NAND flash memory

NASA Astrophysics Data System (ADS)

Tomita, Toshihiro; Miyaji, Kousuke

2015-04-01

The dependence of spatial and statistical distribution of random telegraph noise (RTN) in a 30 nm NAND flash memory on channel doping concentration NA and cell program state Vth is comprehensively investigated using three-dimensional Monte Carlo device simulation considering random dopant fluctuation (RDF). It is found that single trap RTN amplitude ΔVth is larger at the center of the channel region in the NAND flash memory, which is closer to the jellium (uniform) doping results since NA is relatively low to suppress junction leakage current. In addition, ΔVth peak at the center of the channel decreases in the higher Vth state due to the current concentration at the shallow trench isolation (STI) edges induced by the high vertical electrical field through the fringing capacitance between the channel and control gate. In such cases, ΔVth distribution slope λ cannot be determined by only considering RDF and single trap.

The effects of nongenetic memory on population level sensitivity to stress

NASA Astrophysics Data System (ADS)

Adams, Rhys; Nevozhay, Dmitry; van Itallie, Elizabeth; Bennett, Matthew; Balazsi, Gabor

2011-03-01

While gene expression is often thought of as a unidirectional determinant of cellular fitness, recent studies have shown how growth retardation due to protein expression can affect gene expression levels in single cells. We developed two yeast strains carrying a drug resistance protein under the control of different synthetic gene constructs, one of which was monostable, while the other was bistable. The gene expression of these cell populations was tuned using a molecular inducer so that their respective means and noises were identical, while their nongenetic memory properties were different. We tested the sensitivity of these two cell population distributions to the antibiotic zeocin. We found that the gene expression distributions of bistable cell populations were sensitive to stressful environments, while the gene expression distribution of monostable cells were nearly unchanged by stress. We conclude that cell populations with high nongenetic memory are more adaptable to their environment. This work was funded by the National Institutes of Health through the NIH Director's New Innovator Award Program, 1-DP2- OD006481-01.

Is magnetite a universal memory molecule?

PubMed

Størmer, Fredrik C

2014-11-01

Human stem cells possess memory, and consequently all living human cells must have a memory system. How memory is stored in cells and organisms is an open question. Magnetite is perhaps the best candidate to be a universal memory molecule. Magnetite may give us a clue, because it is the Earth's most distributed and important magnetic material. It is found in living organisms with no known functions except for involvement in navigation in some organisms. In humans magnetite is found in the brain, heart, liver and spleen. Humans suffer from memory dysfunctions in many cases when iron is out of balance. Anomalous concentrations of magnetite is known to be associated with a neurodegenerative disorder like Alzheimer's disease. Due to the rapid speed and accuracy of our brain, memory and its functions must be governed by quantum mechanics. Copyright © 2014 Elsevier Ltd. All rights reserved.

Comparison of two paradigms for distributed shared memory

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

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

1990-08-01

The paper compares two paradigms for Distributed Shared Memory on loosely coupled computing systems: the shared data-object model as used in Orca, a programming language specially designed for loosely coupled computing systems and the Shared Virtual Memory model. For both paradigms the authors have implemented two systems, one using only point-to-point messages, the other using broadcasting as well. They briefly describe these two paradigms and their implementations. Then they compare their performance on four applications: the traveling salesman problem, alpha-beta search, matrix multiplication and the all pairs shortest paths problem. The measurements show that both paradigms can be used efficientlymore » for programming large-grain parallel applications. Significant speedups were obtained on all applications. The unstructured Shared Virtual Memory paradigm achieves the best absolute performance, although this is largely due to the preliminary nature of the Orca compiler used. The structured shared data-object model achieves the highest speedups and is much easier to program and to debug.« less

High Performance Data Transfer for Distributed Data Intensive Sciences

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

Fang, Chin; Cottrell, R 'Les' A.; Hanushevsky, Andrew B.

We report on the development of ZX software providing high performance data transfer and encryption. The design scales in: computation power, network interfaces, and IOPS while carefully balancing the available resources. Two U.S. patent-pending algorithms help tackle data sets containing lots of small files and very large files, and provide insensitivity to network latency. It has a cluster-oriented architecture, using peer-to-peer technologies to ease deployment, operation, usage, and resource discovery. Its unique optimizations enable effective use of flash memory. Using a pair of existing data transfer nodes at SLAC and NERSC, we compared its performance to that of bbcp andmore » GridFTP and determined that they were comparable. With a proof of concept created using two four-node clusters with multiple distributed multi-core CPUs, network interfaces and flash memory, we achieved 155Gbps memory-to-memory over a 2x100Gbps link aggregated channel and 70Gbps file-to-file with encryption over a 5000 mile 100Gbps link.« less

Abnormal functional connectivity of hippocampus during episodic memory retrieval processing network in amnestic mild cognitive impairment.

PubMed

Bai, Feng; Zhang, Zhijun; Watson, David R; Yu, Hui; Shi, Yongmei; Yuan, Yonggui; Zang, Yufeng; Zhu, Chaozhe; Qian, Yun

2009-06-01

Functional connectivity magnetic resonance imaging technique has revealed the importance of distributed network structures in higher cognitive processes in the human brain. The hippocampus has a key role in a distributed network supporting memory encoding and retrieval. Hippocampal dysfunction is a recurrent finding in memory disorders of aging such as amnestic mild cognitive impairment (aMCI) in which learning- and memory-related cognitive abilities are the predominant impairment. The functional connectivity method provides a novel approach in our attempts to better understand the changes occurring in this structure in aMCI patients. Functional connectivity analysis was used to examine episodic memory retrieval networks in vivo in twenty 28 aMCI patients and 23 well-matched control subjects, specifically between the hippocampal structures and other brain regions. Compared with control subjects, aMCI patients showed significantly lower hippocampus functional connectivity in a network involving prefrontal lobe, temporal lobe, parietal lobe, and cerebellum, and higher functional connectivity to more diffuse areas of the brain than normal aging control subjects. In addition, those regions associated with increased functional connectivity with the hippocampus demonstrated a significantly negative correlation to episodic memory performance. aMCI patients displayed altered patterns of functional connectivity during memory retrieval. The degree of this disturbance appears to be related to level of impairment of processes involved in memory function. Because aMCI is a putative prodromal syndrome to Alzheimer's disease (AD), these early changes in functional connectivity involving the hippocampus may yield important new data to predict whether a patient will eventually develop AD.

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.

The reminiscence bump in autobiographical memory and for public events: A comparison across different cueing methods.

PubMed

Koppel, Jonathan; Berntsen, Dorthe

2016-01-01

The reminiscence bump has been found for both autobiographical memories and memories of public events. However, there have been few comparisons of the bump across each type of event. In the current study, therefore, we compared the bump for autobiographical memories versus the bump for memories of public events. We did so between-subjects, through two cueing methods administered within-subjects, the cue word method and the important memories method. For word-cued memories, we found a similar bump from ages 5 to 19 for both types of memories. However, the bump was more pronounced for autobiographical memories. For most important memories, we found a bump from ages 20 to 29 in autobiographical memory, but little discernible age pattern for public events. Rather, specific public events (e.g., the Fall of the Berlin Wall) dominated recall, producing a chronological distribution characterised by spikes in citations according to the years these events occurred. Follow-up analyses suggested that the bump in most important autobiographical memories was a function of the cultural life script. Our findings did not yield support for any of the dominant existing accounts of the bump as underlying the bump in word-cued memories.

From sensorimotor learning to memory cells in prefrontal and temporal association cortex: a neurocomputational study of disembodiment.

PubMed

Pulvermüller, Friedemann; Garagnani, Max

2014-08-01

Memory cells, the ultimate neurobiological substrates of working memory, remain active for several seconds and are most commonly found in prefrontal cortex and higher multisensory areas. However, if correlated activity in "embodied" sensorimotor systems underlies the formation of memory traces, why should memory cells emerge in areas distant from their antecedent activations in sensorimotor areas, thus leading to "disembodiment" (movement away from sensorimotor systems) of memory mechanisms? We modelled the formation of memory circuits in six-area neurocomputational architectures, implementing motor and sensory primary, secondary and higher association areas in frontotemporal cortices along with known between-area neuroanatomical connections. Sensorimotor learning driven by Hebbian neuroplasticity led to formation of cell assemblies distributed across the different areas of the network. These action-perception circuits (APCs) ignited fully when stimulated, thus providing a neural basis for long-term memory (LTM) of sensorimotor information linked by learning. Subsequent to ignition, activity vanished rapidly from APC neurons in sensorimotor areas but persisted in those in multimodal prefrontal and temporal areas. Such persistent activity provides a mechanism for working memory for actions, perceptions and symbols, including short-term phonological and semantic storage. Cell assembly ignition and "disembodied" working memory retreat of activity to multimodal areas are documented in the neurocomputational models' activity dynamics, at the level of single cells, circuits, and cortical areas. Memory disembodiment is explained neuromechanistically by APC formation and structural neuroanatomical features of the model networks, especially the central role of multimodal prefrontal and temporal cortices in bridging between sensory and motor areas. These simulations answer the "where" question of cortical working memory in terms of distributed APCs and their inner structure, which is, in part, determined by neuroanatomical structure. As the neurocomputational model provides a mechanistic explanation of how memory-related "disembodied" neuronal activity emerges in "embodied" APCs, it may be key to solving aspects of the embodiment debate and eventually to a better understanding of cognitive brain functions. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

FN400 and LPC memory effects for concrete and abstract words

PubMed Central

Stróżak, Paweł; Bird, Christopher W.; Corby, Krystin; Frishkoff, Gwen; Curran, Tim

2016-01-01

According to dual-process models, recognition memory depends on two neurocognitive mechanisms: familiarity, which has been linked to the "frontal N400" (FN400) effect in studies using event-related potentials (ERPs), and recollection, which is reflected by changes in the late positive complex (LPC). Recently, there has been some debate over the relationship between FN400 familiarity effects and N400 semantic effects. According to one view, these effects are one and the same. Proponents of this view have suggested that the frontal distribution of the FN400 could be due to stimulus concreteness: recognition memory experiments commonly use highly imageable or concrete words (or pictures), which elicit semantic ERPs with a frontal distribution. In the present study we tested this claim using a recognition memory paradigm in which subjects memorized concrete and abstract nouns; half of the words changed font color between study and test. FN400 and LPC old/new effects were observed for abstract, as well as concrete words, and were stronger over right hemisphere electrodes for concrete words. However, there was no difference in anteriority of the FN400 effect for the two word types. These findings challenge the notion that the frontal distribution of the FN400 old/new effect is fully explained by stimulus concreteness. PMID:27463978

Dielectric elastomer memory

NASA Astrophysics Data System (ADS)

O'Brien, Benjamin M.; McKay, Thomas G.; Xie, Sheng Q.; Calius, Emilio P.; Anderson, Iain A.

2011-04-01

Life shows us that the distribution of intelligence throughout flexible muscular networks is a highly successful solution to a wide range of challenges, for example: human hearts, octopi, or even starfish. Recreating this success in engineered systems requires soft actuator technologies with embedded sensing and intelligence. Dielectric Elastomer Actuator(s) (DEA) are promising due to their large stresses and strains, as well as quiet flexible multimodal operation. Recently dielectric elastomer devices were presented with built in sensor, driver, and logic capability enabled by a new concept called the Dielectric Elastomer Switch(es) (DES). DES use electrode piezoresistivity to control the charge on DEA and enable the distribution of intelligence throughout a DEA device. In this paper we advance the capabilities of DES further to form volatile memory elements. A set reset flip-flop with inverted reset line was developed based on DES and DEA. With a 3200V supply the flip-flop behaved appropriately and demonstrated the creation of dielectric elastomer memory capable of changing state in response to 1 second long set and reset pulses. This memory opens up applications such as oscillator, de-bounce, timing, and sequential logic circuits; all of which could be distributed throughout biomimetic actuator arrays. Future work will include miniaturisation to improve response speed, implementation into more complex circuits, and investigation of longer lasting and more sensitive switching materials.

Static analysis of the hull plate using the finite element method

NASA Astrophysics Data System (ADS)

Ion, A.

2015-11-01

This paper aims at presenting the static analysis for two levels of a container ship's construction as follows: the first level is at the girder / hull plate and the second level is conducted at the entire strength hull of the vessel. This article will describe the work for the static analysis of a hull plate. We shall use the software package ANSYS Mechanical 14.5. The program is run on a computer with four Intel Xeon X5260 CPU processors at 3.33 GHz, 32 GB memory installed. In terms of software, the shared memory parallel version of ANSYS refers to running ANSYS across multiple cores on a SMP system. The distributed memory parallel version of ANSYS (Distributed ANSYS) refers to running ANSYS across multiple processors on SMP systems or DMP systems.

Memory and event-related potentials for rapidly presented emotional pictures.

PubMed

Versace, Francesco; Bradley, Margaret M; Lang, Peter J

2010-08-01

Dense array event-related potentials (ERPs) and memory performance were assessed following rapid serial visual presentation (RSVP) of emotional and neutral pictures. Despite the extremely brief presentation, emotionally arousing pictures prompted an enhanced negative voltage over occipital sensors, compared to neutral pictures, replicating previous encoding effects. Emotionally arousing pictures were also remembered better in a subsequent recognition test, with higher hit rates and better discrimination performance. ERPs measured during the recognition test showed both an early (250-350 ms) frontally distributed difference between hits and correct rejections, and a later (400-500 ms), more centrally distributed difference, consistent with effects of recognition on ERPs typically found using slower presentation rates. The data are consistent with the hypothesis that features of affective pictures pop out during rapid serial visual presentation, prompting better memory performance.

Distributed Patterns of Reactivation Predict Vividness of Recollection.

PubMed

St-Laurent, Marie; Abdi, Hervé; Buchsbaum, Bradley R

2015-10-01

According to the principle of reactivation, memory retrieval evokes patterns of brain activity that resemble those instantiated when an event was first experienced. Intuitively, one would expect neural reactivation to contribute to recollection (i.e., the vivid impression of reliving past events), but evidence of a direct relationship between the subjective quality of recollection and multiregional reactivation of item-specific neural patterns is lacking. The current study assessed this relationship using fMRI to measure brain activity as participants viewed and mentally replayed a set of short videos. We used multivoxel pattern analysis to train a classifier to identify individual videos based on brain activity evoked during perception and tested how accurately the classifier could distinguish among videos during mental replay. Classification accuracy correlated positively with memory vividness, indicating that the specificity of multivariate brain patterns observed during memory retrieval was related to the subjective quality of a memory. In addition, we identified a set of brain regions whose univariate activity during retrieval predicted both memory vividness and the strength of the classifier's prediction irrespective of the particular video that was retrieved. Our results establish distributed patterns of neural reactivation as a valid and objective marker of the quality of recollection.

Simple and Efficient Single Photon Filter for a Rb-based Quantum Memory

NASA Astrophysics Data System (ADS)

Stack, Daniel; Li, Xiao; Quraishi, Qudsia

2015-05-01

Distribution of entangled quantum states over significant distances is important to the development of future quantum technologies such as long-distance cryptography, networks of atomic clocks, distributed quantum computing, etc. Long-lived quantum memories and single photons are building blocks for systems capable of realizing such applications. The ability to store and retrieve quantum information while filtering unwanted light signals is critical to the operation of quantum memories based on neutral-atom ensembles. We report on an efficient frequency filter which uses a glass cell filled with 85Rb vapor to attenuate noise photons by an order of magnitude with little loss to the single photons associated with the operation of our cold 87Rb quantum memory. An Ar buffer gas is required to differentiate between signal and noise photons or similar statement. Our simple, passive filter requires no optical pumping or external frequency references and provides an additional 18 dB attenuation of our pump laser for every 1 dB loss of the single photon signal. We observe improved non-classical correlations and our data shows that the addition of a frequency filter increases the non-classical correlations and readout efficiency of our quantum memory by ~ 35%.

Theory for long memory in supply and demand

NASA Astrophysics Data System (ADS)

Lillo, Fabrizio; Mike, Szabolcs; Farmer, J. Doyne

2005-06-01

Recent empirical studies have demonstrated long-memory in the signs of orders to buy or sell in financial markets [J.-P. Bouchaud, Y. Gefen, M. Potters, and M. Wyart, Quant. Finance 4, 176 (2004); F. Lillo and J. D. Farmer Dyn. Syst. Appl. 8, 3 (2004)]. We show how this can be caused by delays in market clearing. Under the common practice of order splitting, large orders are broken up into pieces and executed incrementally. If the size of such large orders is power-law distributed, this gives rise to power-law decaying autocorrelations in the signs of executed orders. More specifically, we show that if the cumulative distribution of large orders of volume v is proportional to v-α and the size of executed orders is constant, the autocorrelation of order signs as a function of the lag τ is asymptotically proportional to τ-(α-1) . This is a long-memory process when α<2 . With a few caveats, this gives a good match to the data. A version of the model also shows long-memory fluctuations in order execution rates, which may be relevant for explaining the long memory of price diffusion rates.

Theory for long memory in supply and demand.

PubMed

Lillo, Fabrizio; Mike, Szabolcs; Farmer, J Doyne

2005-06-01

Recent empirical studies have demonstrated long-memory in the signs of orders to buy or sell in financial markets [J.-P. Bouchaud, Y. Gefen, M. Potters, and M. Wyart, Quant. Finance 4, 176 (2004); F. Lillo and J. D. Farmer Dyn. Syst. Appl. 8, 3 (2004)]. We show how this can be caused by delays in market clearing. Under the common practice of order splitting, large orders are broken up into pieces and executed incrementally. If the size of such large orders is power-law distributed, this gives rise to power-law decaying autocorrelations in the signs of executed orders. More specifically, we show that if the cumulative distribution of large orders of volume v is proportional to v(-alpha) and the size of executed orders is constant, the autocorrelation of order signs as a function of the lag tau is asymptotically proportional to tau(-(alpha-1)). This is a long-memory process when alpha < 2. With a few caveats, this gives a good match to the data. A version of the model also shows long-memory fluctuations in order execution rates, which may be relevant for explaining the long memory of price diffusion rates.

Colored noise and memory effects on formal spiking neuron models

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

Evaluating the Role of Attention in the Context of Unconscious Thought Theory: Differential Impact of Attentional Scope and Load on Preference and Memory

PubMed Central

Srinivasan, Narayanan; Mukherjee, Sumitava; Mishra, Maruti V.; Kesarwani, Smriti

2013-01-01

Attention is a key process used to conceptualize and define modes of thought, but we lack information about the role of specific attentional processes on preferential choice and memory in multi-attribute decision making. In this study, we examine the role of attention based on two dimensions, attentional scope and load on choice preference strength and memory using a paradigm that arguably elicits unconscious thought. Scope of attention was manipulated by using global or local processing during distraction (Experiment 1) and before the information-encoding stage (Experiment 2). Load was manipulated by using the n-back task in Experiment 1. Results from Experiment 1 show that global processing or distributed attention during distraction results in stronger preference irrespective of load but better memory only at low cognitive load. Task difficulty or load did not have any effect on preference or memory. In Experiment 2, distributed attention before attribute encoding facilitated only memory but did not influence preference. Results show that attentional processes at different stages of processing like distraction and information-encoding influence decision making processes. Scope of attention not only influences preference and memory but the manner in which attentional scope influences them depends on both load and stage of information processing. The results indicate the important role of attention in processes critical for decision making and calls for a re-evaluation of the unconscious thought theory (UTT) and the need for reconceptualizing the role of attention. PMID:23382726

Evaluating the role of attention in the context of unconscious thought theory: differential impact of attentional scope and load on preference and memory.

PubMed

Srinivasan, Narayanan; Mukherjee, Sumitava; Mishra, Maruti V; Kesarwani, Smriti

2013-01-01

Attention is a key process used to conceptualize and define modes of thought, but we lack information about the role of specific attentional processes on preferential choice and memory in multi-attribute decision making. In this study, we examine the role of attention based on two dimensions, attentional scope and load on choice preference strength and memory using a paradigm that arguably elicits unconscious thought. Scope of attention was manipulated by using global or local processing during distraction (Experiment 1) and before the information-encoding stage (Experiment 2). Load was manipulated by using the n-back task in Experiment 1. Results from Experiment 1 show that global processing or distributed attention during distraction results in stronger preference irrespective of load but better memory only at low cognitive load. Task difficulty or load did not have any effect on preference or memory. In Experiment 2, distributed attention before attribute encoding facilitated only memory but did not influence preference. Results show that attentional processes at different stages of processing like distraction and information-encoding influence decision making processes. Scope of attention not only influences preference and memory but the manner in which attentional scope influences them depends on both load and stage of information processing. The results indicate the important role of attention in processes critical for decision making and calls for a re-evaluation of the unconscious thought theory (UTT) and the need for reconceptualizing the role of attention.

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

NASA Astrophysics Data System (ADS)

Mankin, Romi; Paekivi, Sander

2018-01-01

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

ERP correlates of source memory: unitized source information increases familiarity-based retrieval.

PubMed

Diana, Rachel A; Van den Boom, Wijnand; Yonelinas, Andrew P; Ranganath, Charan

2011-01-07

Source memory tests typically require subjects to make decisions about the context in which an item was encoded and are thought to depend on recollection of details from the study episode. Although it is generally believed that familiarity does not contribute to source memory, recent behavioral studies have suggested that familiarity may also support source recognition when item and source information are integrated, or "unitized," during study (Diana, Yonelinas, and Ranganath, 2008). However, an alternative explanation of these behavioral findings is that unitization affects the manner in which recollection contributes to performance, rather than increasing familiarity-based source memory. To discriminate between these possibilities, we conducted an event-related potential (ERP) study testing the hypothesis that unitization increases the contribution of familiarity to source recognition. Participants studied associations between words and background colors using tasks that either encouraged or discouraged unitization. ERPs were recorded during a source memory test for background color. The results revealed two distinct neural correlates of source recognition: a frontally distributed positivity that was associated with familiarity-based source memory in the high-unitization condition only and a parietally distributed positivity that was associated with recollection-based source memory in both the high- and low-unitization conditions. The ERP and behavioral findings provide converging evidence for the idea that familiarity can contribute to source recognition, particularly when source information is encoded as an item detail. Copyright © 2010 Elsevier B.V. All rights reserved.

Reduced distribution of threshold voltage shift in double layer NiSi2 nanocrystals for nano-floating gate memory applications.

PubMed

Choi, Sungjin; Lee, Junhyuk; Kim, Donghyoun; Oh, Seulki; Song, Wangyu; Choi, Seonjun; Choi, Eunsuk; Lee, Seung-Beck

2011-12-01

We report on the fabrication and capacitance-voltage characteristics of double layer nickel-silicide nanocrystals with Si3N4 interlayer tunnel barrier for nano-floating gate memory applications. Compared with devices using SiO2 interlayer, the use of Si3N4 interlayer separation reduced the average size (4 nm) and distribution (+/- 2.5 nm) of NiSi2 nanocrystal (NC) charge traps by more than 50% and giving a two fold increase in NC density to 2.3 x 10(12) cm(-2). The increased density and reduced NC size distribution resulted in a significantly decrease in the distribution of the device C-V characteristics. For each program voltage, the distribution of the shift in the threshold voltage was reduced by more than 50% on average to less than 0.7 V demonstrating possible multi-level-cell operation.

History Comes Alive: The American Memory Project.

ERIC Educational Resources Information Center

Rottmann, F. K.

1992-01-01

Describes the Library of Congress American Memory Project (AMP), which uses laser videodisc technology to provide online distribution of collections of historical materials. The collections, software, applications, and future possibilities are addressed; and the experiences of Hickman (Missouri) High School as a participant in the AMP pilot…

75 FR 4423 - Distribution of the 2004 Through 2007 Satellite Royalty Funds

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-27

... Madison Memorial Building, LM-401, 101 Independence Avenue, SE, Washington, DC 20559-6000. If delivered by... Board, Library of Congress, James Madison Memorial Building, LM-403, 101 Independence Avenue, SE... Claimants Group, Music Claimants (American Society of Composers, Authors and Publishers, Broadcast Music...

Synaptic clustering within dendrites: an emerging theory of memory formation

PubMed Central

Kastellakis, George; Cai, Denise J.; Mednick, Sara C.; Silva, Alcino J.; Poirazi, Panayiota

2015-01-01

It is generally accepted that complex memories are stored in distributed representations throughout the brain, however the mechanisms underlying these representations are not understood. Here, we review recent findings regarding the subcellular mechanisms implicated in memory formation, which provide evidence for a dendrite-centered theory of memory. Plasticity-related phenomena which affect synaptic properties, such as synaptic tagging and capture, synaptic clustering, branch strength potentiation and spinogenesis provide the foundation for a model of memory storage that relies heavily on processes operating at the dendrite level. The emerging picture suggests that clusters of functionally related synapses may serve as key computational and memory storage units in the brain. We discuss both experimental evidence and theoretical models that support this hypothesis and explore its advantages for neuronal function. PMID:25576663

Improved memory characteristics by NH3-nitrided GdO as charge storage layer for nonvolatile memory applications

NASA Astrophysics Data System (ADS)

Liu, L.; Xu, J. P.; Ji, F.; Chen, J. X.; Lai, P. T.

2012-07-01

Charge-trapping memory capacitor with nitrided gadolinium oxide (GdO) as charge storage layer (CSL) is fabricated, and the influence of post-deposition annealing in NH3 on its memory characteristics is investigated. Transmission electron microscopy, x-ray photoelectron spectroscopy, and x-ray diffraction are used to analyze the cross-section and interface quality, composition, and crystallinity of the stack gate dielectric, respectively. It is found that nitrogen incorporation can improve the memory window and achieve a good trade-off among the memory properties due to NH3-annealing-induced reasonable distribution profile of a large quantity of deep-level bulk traps created in the nitrided GdO film and reduction of shallow traps near the CSL/SiO2 interface.

Computer Sciences and Data Systems, volume 1

NASA Technical Reports Server (NTRS)

1987-01-01

Topics addressed include: software engineering; university grants; institutes; concurrent processing; sparse distributed memory; distributed operating systems; intelligent data management processes; expert system for image analysis; fault tolerant software; and architecture research.

Effects of pre-experimental knowledge on recognition memory.

PubMed

Bird, Chris M; Davies, Rachel A; Ward, Jamie; Burgess, Neil

2011-01-01

The influence of pre-experimental autobiographical knowledge on recognition memory was investigated using as memoranda faces that were either personally known or unknown to the participant. Under a dual process theory, such knowledge boosted both recollection- and familiarity-based recognition judgements. Under an unequal variance signal detection model, pre-experimental knowledge increased both the variance and the separation of the target and foil memory strength distributions, boosting hits and correct rejections. Thus, pre-experimental knowledge has profound effects on the multiple, interacting processes that subserve recognition memory, and likely in the neural systems that underpin them.

Rotation And Scale Invariant Object Recognition Using A Distributed Associative Memory

NASA Astrophysics Data System (ADS)

Wechsler, Harry; Zimmerman, George Lee

1988-04-01

This paper describes an approach to 2-dimensional object recognition. Complex-log conformal mapping is combined with a distributed associative memory to create a system which recognizes objects regardless of changes in rotation or scale. Recalled information from the memorized database is used to classify an object, reconstruct the memorized version of the object, and estimate the magnitude of changes in scale or rotation. The system response is resistant to moderate amounts of noise and occlusion. Several experiments, using real, gray scale images, are presented to show the feasibility of our approach.

TESS

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

Dmitriy Morozov, Tom Peterka

2014-07-29

Computing a Voronoi or Delaunay tessellation from a set of points is a core part of the analysis of many simulated and measured datasets. As the scale of simulations and observations surpasses billions of particles, a distributed-memory scalable parallel algorithm is the only feasible approach. The primary contribution of this software is a distributed-memory parallel Delaunay and Voronoi tessellation algorithm based on existing serial computational geometry libraries that automatically determines which neighbor points need to be exchanged among the subdomains of a spatial decomposition. Other contributions include the addition of periodic and wall boundary conditions.

A new scheduling algorithm for parallel sparse LU factorization with static pivoting

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

Grigori, Laura; Li, Xiaoye S.

2002-08-20

In this paper we present a static scheduling algorithm for parallel sparse LU factorization with static pivoting. The algorithm is divided into mapping and scheduling phases, using the symmetric pruned graphs of L' and U to represent dependencies. The scheduling algorithm is designed for driving the parallel execution of the factorization on a distributed-memory architecture. Experimental results and comparisons with SuperLU{_}DIST are reported after applying this algorithm on real world application matrices on an IBM SP RS/6000 distributed memory machine.

The role of metacognition in prospective memory: anticipated task demands influence attention allocation strategies.

PubMed

Rummel, Jan; Meiser, Thorsten

2013-09-01

The present study investigates how individuals distribute their attentional resources between a prospective memory task and an ongoing task. Therefore, metacognitive expectations about the attentional demands of the prospective-memory task were manipulated while the factual demands were held constant. In Experiments 1a and 1b, we found attentional costs from a prospective-memory task with low factual demands to be significantly reduced when information about the low to-be-expected demands were provided, while prospective-memory performance remained largely unaffected. In Experiment 2, attentional monitoring in a more demanding prospective-memory task also varied with information about the to-be-expected demands (high vs. low) and again there were no equivalent changes in prospective-memory performance. These findings suggest that attention-allocation strategies of prospective memory rely on metacognitive expectations about prospective-memory task demands. Furthermore, the results suggest that attentional monitoring is only functional for prospective memory to the extent to which anticipated task demands reflect objective task demands. Copyright © 2013 Elsevier Inc. All rights reserved.

Correlated bursts and the role of memory range

NASA Astrophysics Data System (ADS)

Jo, Hang-Hyun; Perotti, Juan I.; Kaski, Kimmo; Kertész, János

2015-08-01

Inhomogeneous temporal processes in natural and social phenomena have been described by bursts that are rapidly occurring events within short time periods alternating with long periods of low activity. In addition to the analysis of heavy-tailed interevent time distributions, higher-order correlations between interevent times, called correlated bursts, have been studied only recently. As the underlying mechanism behind such correlated bursts is far from being fully understood, we devise a simple model for correlated bursts using a self-exciting point process with a variable range of memory. Whether a new event occurs is stochastically determined by a memory function that is the sum of decaying memories of past events. In order to incorporate the noise and/or limited memory capacity of systems, we apply two memory loss mechanisms: a fixed number or a variable number of memories. By analysis and numerical simulations, we find that too much memory effect may lead to a Poissonian process, implying that there exists an intermediate range of memory effect to generate correlated bursts comparable to empirical findings. Our conclusions provide a deeper understanding of how long-range memory affects correlated bursts.

Storage of features, conjunctions and objects in visual working memory.

PubMed

Vogel, E K; Woodman, G F; Luck, S J

2001-02-01

Working memory can be divided into separate subsystems for verbal and visual information. Although the verbal system has been well characterized, the storage capacity of visual working memory has not yet been established for simple features or for conjunctions of features. The authors demonstrate that it is possible to retain information about only 3-4 colors or orientations in visual working memory at one time. Observers are also able to retain both the color and the orientation of 3-4 objects, indicating that visual working memory stores integrated objects rather than individual features. Indeed, objects defined by a conjunction of four features can be retained in working memory just as well as single-feature objects, allowing many individual features to be retained when distributed across a small number of objects. Thus, the capacity of visual working memory must be understood in terms of integrated objects rather than individual features.

Neuroanatomic organization of sound memory in humans.

PubMed

Kraut, Michael A; Pitcock, Jeffery A; Calhoun, Vince; Li, Juan; Freeman, Thomas; Hart, John

2006-11-01

The neural interface between sensory perception and memory is a central issue in neuroscience, particularly initial memory organization following perceptual analyses. We used functional magnetic resonance imaging to identify anatomic regions extracting initial auditory semantic memory information related to environmental sounds. Two distinct anatomic foci were detected in the right superior temporal gyrus when subjects identified sounds representing either animals or threatening items. Threatening animal stimuli elicited signal changes in both foci, suggesting a distributed neural representation. Our results demonstrate both category- and feature-specific responses to nonverbal sounds in early stages of extracting semantic memory information from these sounds. This organization allows for these category-feature detection nodes to extract early, semantic memory information for efficient processing of transient sound stimuli. Neural regions selective for threatening sounds are similar to those of nonhuman primates, demonstrating semantic memory organization for basic biological/survival primitives are present across species.

Network Model of Decreased Context Utilization in Autism Spectrum Disorder

ERIC Educational Resources Information Center

Beversdorf, David Q.; Narayanan, Ananth; Hillier, Ashleigh; Hughes, John D.

2007-01-01

Individuals with autism spectrum disorders (ASD) demonstrate impaired utilization of context, which allows for superior performance on the "false memory" task. We report the application of a simplified parallel distributed processing model of context utilization to the false memory task. For individuals without ASD, experiments support a model…

The Relations between Number Property Strategies, Working Memory, and Multiplication in Elementary Students

ERIC Educational Resources Information Center

Liu, Ru-De; Ding, Yi; Gao, Bing-Cheng; Zhang, Dake

2015-01-01

This study aimed to examine the relations among property strategies, working memory, and multiplication tasks with 101 Chinese fourth-grade students. Two multiplication property strategies (associative and distributive) were compared with no strategy and demonstrated differentiated effects on students' accuracy and reaction time. Associative…

Naïve Point Estimation

ERIC Educational Resources Information Center

Lindskog, Marcus; Winman, Anders; Juslin, Peter

2013-01-01

The capacity of short-term memory is a key constraint when people make online judgments requiring them to rely on samples retrieved from memory (e.g., Dougherty & Hunter, 2003). In this article, the authors compare 2 accounts of how people use knowledge of statistical distributions to make point estimates: either by retrieving precomputed…

Control of Vibration in Mechanical Systems Using Shaped Reference Inputs

DTIC Science & Technology

1988-01-01

damping with several discrete actuators. Burke and Hubbard 34! generated a distributed control law by applying a piezoelectric film to the beam that...setpoints from successive memory locations. DATA-kYOVE (- starts servoing to setpoints from successive memory locations for mnicro scified by MN while taking

Treatment of Memory Disorders in Gulf War Illness with High-Definition Transcranial Direct Cortical Stimulation

DTIC Science & Technology

2017-10-01

AWARD NUMBER: W81XWH-16-1-0521 TITLE: Treatment of Memory Disorders in Gulf War Illness with High - Definition Transcranial Direct Cortical...Approved for Public Release; Distribution Unlimited The views, opinions and/or findings contained in this report are those of the author(s) and should...Sep 2017 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Treatment of Memory Disorders in Gulf War Illness with High -Definition Transcranial Direct

Odor Preference Learning and Memory Modify GluA1 Phosphorylation and GluA1 Distribution in the Neonate Rat Olfactory Bulb: Testing the AMPA Receptor Hypothesis in an Appetitive Learning Model

ERIC Educational Resources Information Center

Cui, Wen; Darby-King, Andrea; Grimes, Matthew T.; Howland, John G.; Wang, Yu Tian; McLean, John H.; Harley, Carolyn W.

2011-01-01

An increase in synaptic AMPA receptors is hypothesized to mediate learning and memory. AMPA receptor increases have been reported in aversive learning models, although it is not clear if they are seen with memory maintenance. Here we examine AMPA receptor changes in a cAMP/PKA/CREB-dependent appetitive learning model: odor preference learning in…

Processing statistics: an examination of focused and distributed attention using event related potentials.

PubMed

Baijal, Shruti; Nakatani, Chie; van Leeuwen, Cees; Srinivasan, Narayanan

2013-06-07

Human observers show remarkable efficiency in statistical estimation; they are able, for instance, to estimate the mean size of visual objects, even if their number exceeds the capacity limits of focused attention. This ability has been understood as the result of a distinct mode of attention, i.e. distributed attention. Compared to the focused attention mode, working memory representations under distributed attention are proposed to be more compressed, leading to reduced working memory loads. An alternate proposal is that distributed attention uses less structured, feature-level representations. These would fill up working memory (WM) more, even when target set size is low. Using event-related potentials, we compared WM loading in a typical distributed attention task (mean size estimation) to that in a corresponding focused attention task (object recognition), using a measure called contralateral delay activity (CDA). Participants performed both tasks on 2, 4, or 8 different-sized target disks. In the recognition task, CDA amplitude increased with set size; notably, however, in the mean estimation task the CDA amplitude was high regardless of set size. In particular for set-size 2, the amplitude was higher in the mean estimation task than in the recognition task. The result showed that the task involves full WM loading even with a low target set size. This suggests that in the distributed attention mode, representations are not compressed, but rather less structured than under focused attention conditions. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

Mnemonic training reshapes brain networks to support superior memory

PubMed Central

Dresler, Martin; Shirer, William R.; Konrad, Boris N.; Müller, Nils C.J.; Wagner, Isabella C.; Fernández, Guillén; Czisch, Michael; Greicius, Michael D.

2017-01-01

Summary Memory skills strongly differ across the general population, however little is known about the brain characteristics supporting superior memory performance. Here, we assess functional brain network organization of 23 of the world’s most successful memory athletes and matched controls by fMRI during both task-free resting state baseline and active memory encoding. We demonstrate that in a group of naïve controls, functional connectivity changes induced by six weeks of mnemonic training were correlated with the network organization that distinguishes athletes from controls. During rest, this effect was mainly driven by connections between rather than within the visual, medial temporal lobe and default mode networks, whereas during task it was driven by connectivity within these networks. Similarity with memory athlete connectivity patterns predicted memory improvements up to 4 months after training. In conclusion, mnemonic training drives distributed rather than regional changes, reorganizing the brain’s functional network organization to enable superior memory performance. PMID:28279356

Working Memory and Decision-Making in a Frontoparietal Circuit Model

PubMed Central

2017-01-01

Working memory (WM) and decision-making (DM) are fundamental cognitive functions involving a distributed interacting network of brain areas, with the posterior parietal cortex (PPC) and prefrontal cortex (PFC) at the core. However, the shared and distinct roles of these areas and the nature of their coordination in cognitive function remain poorly understood. Biophysically based computational models of cortical circuits have provided insights into the mechanisms supporting these functions, yet they have primarily focused on the local microcircuit level, raising questions about the principles for distributed cognitive computation in multiregional networks. To examine these issues, we developed a distributed circuit model of two reciprocally interacting modules representing PPC and PFC circuits. The circuit architecture includes hierarchical differences in local recurrent structure and implements reciprocal long-range projections. This parsimonious model captures a range of behavioral and neuronal features of frontoparietal circuits across multiple WM and DM paradigms. In the context of WM, both areas exhibit persistent activity, but, in response to intervening distractors, PPC transiently encodes distractors while PFC filters distractors and supports WM robustness. With regard to DM, the PPC module generates graded representations of accumulated evidence supporting target selection, while the PFC module generates more categorical responses related to action or choice. These findings suggest computational principles for distributed, hierarchical processing in cortex during cognitive function and provide a framework for extension to multiregional models. SIGNIFICANCE STATEMENT Working memory and decision-making are fundamental “building blocks” of cognition, and deficits in these functions are associated with neuropsychiatric disorders such as schizophrenia. These cognitive functions engage distributed networks with prefrontal cortex (PFC) and posterior parietal cortex (PPC) at the core. It is not clear, however, what the contributions of PPC and PFC are in light of the computations that subserve working memory and decision-making. We constructed a biophysical model of a reciprocally connected frontoparietal circuit that revealed shared and distinct functions for the PFC and PPC across working memory and decision-making tasks. Our parsimonious model connects circuit-level properties to cognitive functions and suggests novel design principles beyond those of local circuits for cognitive processing in multiregional brain networks. PMID:29114071

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

PubMed

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

2017-12-13

Working memory (WM) and decision-making (DM) are fundamental cognitive functions involving a distributed interacting network of brain areas, with the posterior parietal cortex (PPC) and prefrontal cortex (PFC) at the core. However, the shared and distinct roles of these areas and the nature of their coordination in cognitive function remain poorly understood. Biophysically based computational models of cortical circuits have provided insights into the mechanisms supporting these functions, yet they have primarily focused on the local microcircuit level, raising questions about the principles for distributed cognitive computation in multiregional networks. To examine these issues, we developed a distributed circuit model of two reciprocally interacting modules representing PPC and PFC circuits. The circuit architecture includes hierarchical differences in local recurrent structure and implements reciprocal long-range projections. This parsimonious model captures a range of behavioral and neuronal features of frontoparietal circuits across multiple WM and DM paradigms. In the context of WM, both areas exhibit persistent activity, but, in response to intervening distractors, PPC transiently encodes distractors while PFC filters distractors and supports WM robustness. With regard to DM, the PPC module generates graded representations of accumulated evidence supporting target selection, while the PFC module generates more categorical responses related to action or choice. These findings suggest computational principles for distributed, hierarchical processing in cortex during cognitive function and provide a framework for extension to multiregional models. SIGNIFICANCE STATEMENT Working memory and decision-making are fundamental "building blocks" of cognition, and deficits in these functions are associated with neuropsychiatric disorders such as schizophrenia. These cognitive functions engage distributed networks with prefrontal cortex (PFC) and posterior parietal cortex (PPC) at the core. It is not clear, however, what the contributions of PPC and PFC are in light of the computations that subserve working memory and decision-making. We constructed a biophysical model of a reciprocally connected frontoparietal circuit that revealed shared and distinct functions for the PFC and PPC across working memory and decision-making tasks. Our parsimonious model connects circuit-level properties to cognitive functions and suggests novel design principles beyond those of local circuits for cognitive processing in multiregional brain networks. Copyright © 2017 the authors 0270-6474/17/3712167-20$15.00/0.

Effects of healthy aging and early stage dementia of the Alzheimer's type on components of response time distributions in three attention tasks.

PubMed

Tse, Chi-Shing; Balota, David A; Yap, Melvin J; Duchek, Janet M; McCabe, David P

2010-05-01

The characteristics of response time (RT) distributions beyond measures of central tendency were explored in 3 attention tasks across groups of young adults, healthy older adults, and individuals with very mild dementia of the Alzheimer's type (DAT). Participants were administered computerized Stroop, Simon, and switching tasks, along with psychometric tasks that tap various cognitive abilities and a standard personality inventory (NEO-FFI). Ex-Gaussian (and Vincentile) analyses were used to capture the characteristics of the RT distributions for each participant across the 3 tasks, which afforded 3 components: mu and sigma (mean and standard deviation of the modal portion of the distribution) and tau (the positive tail of the distribution). The results indicated that across all 3 attention tasks, healthy aging produced large changes in the central tendency mu parameter of the distribution along with some change in sigma and tau (mean etap(2) = .17, .08, and .04, respectively). In contrast, early stage DAT primarily produced an increase in the tau component (mean etap(2) = .06). tau was also correlated with the psychometric measures of episodic/semantic memory, working memory, and processing speed, and with the personality traits of neuroticism and conscientiousness. Structural equation modeling indicated a unique relation between a latent tau construct (-.90), as opposed to sigma (-.09) and mu constructs (.24), with working memory measures. The results suggest a critical role of attentional control systems in discriminating healthy aging from early stage DAT and the utility of RT distribution analyses to better specify the nature of such change.

A direct comparison of popular models of normal memory loss and Alzheimer's disease in samples of African Americans, Mexican Americans, and refugees and immigrants from the former Soviet Union.

PubMed

Schrauf, Robert W; Iris, Madelyn

2011-04-01

To understand how people differentiate normal memory loss from Alzheimer's disease (AD) by investigating cultural models of these conditions. Ethnographic interviews followed by a survey. Cultural consensus analysis was used to test for the presence of group models, derive the "culturally correct" set of beliefs, and compare models of normal memory loss and AD. Chicago, Illinois. One hundred eight individuals from local neighborhoods: African Americans, Mexican Americans, and refugees and immigrants from the former Soviet Union. Participants responded to yes-or-no questions about the nature and causes of normal memory loss and AD and provided information on ethnicity, age, sex, acculturation, and experience with AD. Groups held a common model of AD as a brain-based disease reflecting irreversible cognitive decline. Higher levels of acculturation predicted greater knowledge of AD. Russian speakers favored biological over psychological models of the disease. Groups also held a common model of normal memory loss, including the important belief that "normal" forgetting involves eventual recall of the forgotten material. Popular models of memory loss and AD confirm that patients and clinicians are speaking the same "language" in their discussions of memory loss and AD. Nevertheless, the presence of coherent models of memory loss and AD, and the unequal distribution of that knowledge across groups, suggests that clinicians should include wider circles of patients' families and friends in their consultations. These results frame knowledge as distributed across social groups rather than simply the possession of individual minds. © 2011, Copyright the Authors. Journal compilation © 2011, The American Geriatrics Society.

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

Characterization of the beta amyloid precursor protein-like gene in the central nervous system of the crab Chasmagnathus. Expression during memory consolidation.

PubMed

Fustiñana, Maria Sol; Ariel, Pablo; Federman, Noel; Freudenthal, Ramiro; Romano, Arturo

2010-09-01

Human β-amyloid, the main component in the neuritic plaques found in patients with Alzheimer's disease, is generated by cleavage of the β-amyloid precursor protein. Beyond the role in pathology, members of this protein family are synaptic proteins and have been associated with synaptogenesis, neuronal plasticity and memory, both in vertebrates and in invertebrates. Consolidation is necessary to convert a short-term labile memory to a long-term and stable form. During consolidation, gene expression and de novo protein synthesis are regulated in order to produce key proteins for the maintenance of plastic changes produced during the acquisition of new information. Here we partially cloned and sequenced the beta-amyloid precursor protein like gene homologue in the crab Chasmagnathus (cappl), showing a 37% of identity with the fruit fly Drosophila melanogaster homologue and 23% with Homo sapiens but with much higher degree of sequence similarity in certain regions. We observed a wide distribution of cappl mRNA in the nervous system as well as in muscle and gills. The protein localized in all tissues analyzed with the exception of muscle. Immunofluorescence revealed localization of cAPPL in associative and sensory brain areas. We studied gene and protein expression during long-term memory consolidation using a well characterized memory model: the context-signal associative memory in this crab species. mRNA levels varied at different time points during long-term memory consolidation and correlated with cAPPL protein levels cAPPL mRNA and protein is widely distributed in the central nervous system of the crab and the time course of expression suggests a role of cAPPL during long-term memory formation.

Working memory and spatial judgments: Cognitive load increases the central tendency bias.

PubMed

Allred, Sarah R; Crawford, L Elizabeth; Duffy, Sean; Smith, John

2016-12-01

Previous work demonstrates that memory for simple stimuli can be biased by information about the distribution of which the stimulus is a member. Specifically, people underestimate values greater than the distribution's average and overestimate values smaller than the average. This is referred to as the central tendency bias. This bias has been explained as an optimal use of both noisy sensory information and category information. In largely separate literature, cognitive load (CL) experiments attempt to manipulate the available working memory of participants in order to observe the effect on choice or judgments. In two experiments, we demonstrate that participants under high cognitive load exhibit a stronger central tendency bias than when under a low cognitive load. Although not anticipated at the outset, we also find that judgments exhibit an anchoring bias not described previously.

Composite Particle Swarm Optimizer With Historical Memory for Function Optimization.

PubMed

Li, Jie; Zhang, JunQi; Jiang, ChangJun; Zhou, MengChu

2015-10-01

Particle swarm optimization (PSO) algorithm is a population-based stochastic optimization technique. It is characterized by the collaborative search in which each particle is attracted toward the global best position (gbest) in the swarm and its own best position (pbest). However, all of particles' historical promising pbests in PSO are lost except their current pbests. In order to solve this problem, this paper proposes a novel composite PSO algorithm, called historical memory-based PSO (HMPSO), which uses an estimation of distribution algorithm to estimate and preserve the distribution information of particles' historical promising pbests. Each particle has three candidate positions, which are generated from the historical memory, particles' current pbests, and the swarm's gbest. Then the best candidate position is adopted. Experiments on 28 CEC2013 benchmark functions demonstrate the superiority of HMPSO over other algorithms.

Sparse distributed memory

NASA Technical Reports Server (NTRS)

Denning, Peter J.

1989-01-01

Sparse distributed memory was proposed be Pentti Kanerva as a realizable architecture that could store large patterns and retrieve them based on partial matches with patterns representing current sensory inputs. This memory exhibits behaviors, both in theory and in experiment, that resemble those previously unapproached by machines - e.g., rapid recognition of faces or odors, discovery of new connections between seemingly unrelated ideas, continuation of a sequence of events when given a cue from the middle, knowing that one doesn't know, or getting stuck with an answer on the tip of one's tongue. These behaviors are now within reach of machines that can be incorporated into the computing systems of robots capable of seeing, talking, and manipulating. Kanerva's theory is a break with the Western rationalistic tradition, allowing a new interpretation of learning and cognition that respects biology and the mysteries of individual human beings.

Effects of long memory in the order submission process on the properties of recurrence intervals of large price fluctuations

NASA Astrophysics Data System (ADS)

Meng, Hao; Ren, Fei; Gu, Gao-Feng; Xiong, Xiong; Zhang, Yong-Jie; Zhou, Wei-Xing; Zhang, Wei

2012-05-01

Understanding the statistical properties of recurrence intervals (also termed return intervals in econophysics literature) of extreme events is crucial to risk assessment and management of complex systems. The probability distributions and correlations of recurrence intervals for many systems have been extensively investigated. However, the impacts of microscopic rules of a complex system on the macroscopic properties of its recurrence intervals are less studied. In this letter, we adopt an order-driven stock model to address this issue for stock returns. We find that the distributions of the scaled recurrence intervals of simulated returns have a power-law scaling with stretched exponential cutoff and the intervals possess multifractal nature, which are consistent with empirical results. We further investigate the effects of long memory in the directions (or signs) and relative prices of the order flow on the characteristic quantities of these properties. It is found that the long memory in the order directions (Hurst index Hs) has a negligible effect on the interval distributions and the multifractal nature. In contrast, the power-law exponent of the interval distribution increases linearly with respect to the Hurst index Hx of the relative prices, and the singularity width of the multifractal nature fluctuates around a constant value when Hx<0.7 and then increases with Hx. No evident effects of Hs and Hx are found on the long memory of the recurrence intervals. Our results indicate that the nontrivial properties of the recurrence intervals of returns are mainly caused by traders' behaviors of persistently placing new orders around the best bid and ask prices.

Hippocampal functional connectivity and episodic memory in early childhood

PubMed Central

Riggins, Tracy; Geng, Fengji; Blankenship, Sarah L.; Redcay, Elizabeth

2016-01-01

Episodic memory relies on a distributed network of brain regions, with the hippocampus playing a critical and irreplaceable role. Few studies have examined how changes in this network contribute to episodic memory development early in life. The present addressed this gap by examining relations between hippocampal functional connectivity and episodic memory in 4-and 6-year-old children (n=40). Results revealed similar hippocampal functional connectivity between age groups, which included lateral temporal regions, precuneus, and multiple parietal and prefrontal regions, and functional specialization along the longitudinal axis. Despite these similarities, developmental differences were also observed. Specifically, 3 (of 4) regions within the hippocampal memory network were positively associated with episodic memory in 6-year-old children, but negatively associated with episodic memory in 4-year-old children. In contrast, all 3 regions outside the hippocampal memory network were negatively associated with episodic memory in older children, but positively associated with episodic memory in younger children. These interactions are interpreted within an interactive specialization framework and suggest the hippocampus becomes functionally integrated with cortical regions that are part of the hippocampal memory network in adults and functionally segregated from regions unrelated to memory in adults, both of which are associated with age-related improvements in episodic memory ability. PMID:26900967

Hippocampal functional connectivity and episodic memory in early childhood.

PubMed

Riggins, Tracy; Geng, Fengji; Blankenship, Sarah L; Redcay, Elizabeth

2016-06-01

Episodic memory relies on a distributed network of brain regions, with the hippocampus playing a critical and irreplaceable role. Few studies have examined how changes in this network contribute to episodic memory development early in life. The present addressed this gap by examining relations between hippocampal functional connectivity and episodic memory in 4- and 6-year-old children (n=40). Results revealed similar hippocampal functional connectivity between age groups, which included lateral temporal regions, precuneus, and multiple parietal and prefrontal regions, and functional specialization along the longitudinal axis. Despite these similarities, developmental differences were also observed. Specifically, 3 (of 4) regions within the hippocampal memory network were positively associated with episodic memory in 6-year-old children, but negatively associated with episodic memory in 4-year-old children. In contrast, all 3 regions outside the hippocampal memory network were negatively associated with episodic memory in older children, but positively associated with episodic memory in younger children. These interactions are interpreted within an interactive specialization framework and suggest the hippocampus becomes functionally integrated with cortical regions that are part of the hippocampal memory network in adults and functionally segregated from regions unrelated to memory in adults, both of which are associated with age-related improvements in episodic memory ability. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Multiphase complete exchange on Paragon, SP2 and CS-2

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.

1995-01-01

The overhead of interprocessor communication is a major factor in limiting the performance of parallel computer systems. The complete exchange is the severest communication pattern in that it requires each processor to send a distinct message to every other processor. This pattern is at the heart of many important parallel applications. On hypercubes, multiphase complete exchange has been developed and shown to provide optimal performance over varying message sizes. Most commercial multicomputer systems do not have a hypercube interconnect. However, they use special purpose hardware and dedicated communication processors to achieve very high performance communication and can be made to emulate the hypercube quite well. Multiphase complete exchange has been implemented on three contemporary parallel architectures: the Intel Paragon, IBM SP2 and Meiko CS-2. The essential features of these machines are described and their basic interprocessor communication overheads are discussed. The performance of multiphase complete exchange is evaluated on each machine. It is shown that the theoretical ideas developed for hypercubes are also applicable in practice to these machines and that multiphase complete exchange can lead to major savings in execution time over traditional solutions.

A method to compute SEU fault probabilities in memory arrays with error correction

NASA Technical Reports Server (NTRS)

Gercek, Gokhan

1994-01-01

With the increasing packing densities in VLSI technology, Single Event Upsets (SEU) due to cosmic radiations are becoming more of a critical issue in the design of space avionics systems. In this paper, a method is introduced to compute the fault (mishap) probability for a computer memory of size M words. It is assumed that a Hamming code is used for each word to provide single error correction. It is also assumed that every time a memory location is read, single errors are corrected. Memory is read randomly whose distribution is assumed to be known. In such a scenario, a mishap is defined as two SEU's corrupting the same memory location prior to a read. The paper introduces a method to compute the overall mishap probability for the entire memory for a mission duration of T hours.

A study of the viability of exploiting memory content similarity to improve resilience to memory errors

DOE PAGES

Levy, Scott; Ferreira, Kurt B.; Bridges, Patrick G.; ...

2014-12-09

Building the next-generation of extreme-scale distributed systems will require overcoming several challenges related to system resilience. As the number of processors in these systems grow, the failure rate increases proportionally. One of the most common sources of failure in large-scale systems is memory. In this paper, we propose a novel runtime for transparently exploiting memory content similarity to improve system resilience by reducing the rate at which memory errors lead to node failure. We evaluate the viability of this approach by examining memory snapshots collected from eight high-performance computing (HPC) applications and two important HPC operating systems. Based on themore » characteristics of the similarity uncovered, we conclude that our proposed approach shows promise for addressing system resilience in large-scale systems.« less

High efficiency coherent optical memory with warm rubidium vapour

PubMed Central

Hosseini, M.; Sparkes, B.M.; Campbell, G.; Lam, P.K.; Buchler, B.C.

2011-01-01

By harnessing aspects of quantum mechanics, communication and information processing could be radically transformed. Promising forms of quantum information technology include optical quantum cryptographic systems and computing using photons for quantum logic operations. As with current information processing systems, some form of memory will be required. Quantum repeaters, which are required for long distance quantum key distribution, require quantum optical memory as do deterministic logic gates for optical quantum computing. Here, we present results from a coherent optical memory based on warm rubidium vapour and show 87% efficient recall of light pulses, the highest efficiency measured to date for any coherent optical memory suitable for quantum information applications. We also show storage and recall of up to 20 pulses from our system. These results show that simple warm atomic vapour systems have clear potential as a platform for quantum memory. PMID:21285952

High efficiency coherent optical memory with warm rubidium vapour.

PubMed

Hosseini, M; Sparkes, B M; Campbell, G; Lam, P K; Buchler, B C

2011-02-01

By harnessing aspects of quantum mechanics, communication and information processing could be radically transformed. Promising forms of quantum information technology include optical quantum cryptographic systems and computing using photons for quantum logic operations. As with current information processing systems, some form of memory will be required. Quantum repeaters, which are required for long distance quantum key distribution, require quantum optical memory as do deterministic logic gates for optical quantum computing. Here, we present results from a coherent optical memory based on warm rubidium vapour and show 87% efficient recall of light pulses, the highest efficiency measured to date for any coherent optical memory suitable for quantum information applications. We also show storage and recall of up to 20 pulses from our system. These results show that simple warm atomic vapour systems have clear potential as a platform for quantum memory.

Dually actuated triple shape memory polymers of cross-linked polycyclooctene-carbon nanotube/polyethylene nanocomposites.

PubMed

Wang, Zhenwen; Zhao, Jun; Chen, Min; Yang, Minhao; Tang, Luyang; Dang, Zhi-Min; Chen, Fenghua; Huang, Miaoming; Dong, Xia

2014-11-26

In this work, electrically and thermally actuated triple shape memory polymers (SMPs) of chemically cross-linked polycyclooctene (PCO)-multiwalled carbon nanotube (MWCNT)/polyethylene (PE) nanocomposites with co-continuous structure and selective distribution of fillers in PCO phase are prepared. We systematically studied not only the microstructure including morphology and fillers' selective distribution in one phase of the PCO/PE blends, but also the macroscopic properties including thermal, mechanical, and electrical properties. The co-continuous window of the immiscible PCO/PE blends is found to be the volume fraction of PCO (vPCO) of ca. 40-70 vol %. The selective distribution of fillers in one phase of co-continuous blends is obtained by a masterbatch technique. The prepared triple SMP materials show pronounced triple shape memory effects (SMEs) on the dynamic mechanical thermal analysis (DMTA) and the visual observation by both thermal and electric actuations. Such polyolefin samples with well-defined microstructure, electrical actuation, and triple SMEs might have potential applications as, for example, multiple autochoke elements for engines, self-adjusting orthodontic wires, and ophthalmic devices.

Multiplexed memory-insensitive quantum repeaters.

PubMed

Collins, O A; Jenkins, S D; Kuzmich, A; Kennedy, T A B

2007-02-09

Long-distance quantum communication via distant pairs of entangled quantum bits (qubits) is the first step towards secure message transmission and distributed quantum computing. To date, the most promising proposals require quantum repeaters to mitigate the exponential decrease in communication rate due to optical fiber losses. However, these are exquisitely sensitive to the lifetimes of their memory elements. We propose a multiplexing of quantum nodes that should enable the construction of quantum networks that are largely insensitive to the coherence times of the quantum memory elements.

Distributed trace using central performance counter memory

DOEpatents

Satterfield, David L; Sexton, James C

2013-10-22

A plurality of processing cores, are central storage unit having at least memory connected in a daisy chain manner, forming a daisy chain ring layout on an integrated chip. At least one of the plurality of processing cores places trace data on the daisy chain connection for transmitting the trace data to the central storage unit, and the central storage unit detects the trace data and stores the trace data in the memory co-located in with the central storage unit.

Distributed trace using central performance counter memory

DOEpatents

Satterfield, David L.; Sexton, James C.

2013-01-22

A plurality of processing cores, are central storage unit having at least memory connected in a daisy chain manner, forming a daisy chain ring layout on an integrated chip. At least one of the plurality of processing cores places trace data on the daisy chain connection for transmitting the trace data to the central storage unit, and the central storage unit detects the trace data and stores the trace data in the memory co-located in with the central storage unit.

Neuropeptide-Y both Improves and Impairs Delayed Matching-to-Sample Performance in Rats

DTIC Science & Technology

1991-01-01

Neuropeptide Y distribution in the 422 THOMAS AND AHLERS rat brain. Science 221:877-879; 1983. of animal learning. In: Roitblat , H. L.; Bever, T. G.; Terrace, H...Sources of proactive interference in memory. Hillsdale, NJ: Erlbaum; 1976. animal memory. J. Exp. Psychol. (Anim. Behav.) 1456-70; 1988. 32. Roitblat , H...memory processing by neuropeptide Y varies with brain 33. Roitblat , H. L., Scopatz, R. A. Sequential effects in pigeons de- injection site. Brain Res

Regional brain activity that determines successful and unsuccessful working memory formation.

PubMed

Teramoto, Shohei; Inaoka, Tsubasa; Ono, Yumie

2016-08-01

Using EEG source reconstruction with Multiple Sparse Priors (MSP), we investigated the regional brain activity that determines successful memory encoding in two participant groups of high and low accuracy rates. Eighteen healthy young adults performed a sequential fashion of visual Sternberg memory task. The 32-channel EEG was continuously measured during participants performed two 70 trials of memory task. The regional brain activity corresponding to the oscillatory EEG activity in the alpha band (8-13 Hz) during encoding period was analyzed by MSP implemented in SPM8. We divided the data of all participants into 2 groups (low- and highperformance group) and analyzed differences in regional brain activity between trials in which participants answered correctly and incorrectly within each of the group. Participants in low-performance group showed significant activity increase in the visual cortices in their successful trials compared to unsuccessful ones. On the other hand, those in high-performance group showed a significant activity increase in widely distributed cortical regions in the frontal, temporal, and parietal areas including those suggested as Baddeley's working memory model. Further comparison of activated cortical volumes and mean current source intensities within the cortical regions of Baddeley's model during memory encoding demonstrated that participants in high-performance group showed enhanced activity in the right premotor cortex, which plays an important role in maintaining visuospatial attention, compared to those in low performance group. Our results suggest that better ability in memory encoding is associated with distributed and stronger regional brain activities including the premotor cortex, possibly indicating efficient allocation of cognitive load and maintenance of attention.

White matter structural connectivity and episodic memory in early childhood.

PubMed

Ngo, Chi T; Alm, Kylie H; Metoki, Athanasia; Hampton, William; Riggins, Tracy; Newcombe, Nora S; Olson, Ingrid R

2017-12-01

Episodic memory undergoes dramatic improvement in early childhood; the reason for this is poorly understood. In adults, episodic memory relies on a distributed neural network. Key brain regions that supporting these processes include the hippocampus, portions of the parietal cortex, and portions of prefrontal cortex, each of which shows different developmental profiles. Here we asked whether developmental differences in the axonal pathways connecting these regions may account for the robust gains in episodic memory in young children. Using diffusion weighted imaging, we examined whether white matter connectivity between brain regions implicated in episodic memory differed with age, and were associated with memory performance differences in 4- and 6-year-old children. Results revealed that white matter connecting the hippocampus to the inferior parietal lobule significantly predicted children's performance on episodic memory tasks. In contrast, variation in the white matter connecting the hippocampus to the medial prefrontal cortex did not relate to memory performance. These findings suggest that structural connectivity between the hippocampus and lateral parietal regions is relevant to the development of episodic memory. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Identification of a Functional Connectome for Long-Term Fear Memory in Mice

PubMed Central

Wheeler, Anne L.; Teixeira, Cátia M.; Wang, Afra H.; Xiong, Xuejian; Kovacevic, Natasa; Lerch, Jason P.; McIntosh, Anthony R.; Parkinson, John; Frankland, Paul W.

2013-01-01

Long-term memories are thought to depend upon the coordinated activation of a broad network of cortical and subcortical brain regions. However, the distributed nature of this representation has made it challenging to define the neural elements of the memory trace, and lesion and electrophysiological approaches provide only a narrow window into what is appreciated a much more global network. Here we used a global mapping approach to identify networks of brain regions activated following recall of long-term fear memories in mice. Analysis of Fos expression across 84 brain regions allowed us to identify regions that were co-active following memory recall. These analyses revealed that the functional organization of long-term fear memories depends on memory age and is altered in mutant mice that exhibit premature forgetting. Most importantly, these analyses indicate that long-term memory recall engages a network that has a distinct thalamic-hippocampal-cortical signature. This network is concurrently integrated and segregated and therefore has small-world properties, and contains hub-like regions in the prefrontal cortex and thalamus that may play privileged roles in memory expression. PMID:23300432

White Matter Structural Connectivity and Episodic Memory in Early Childhood

PubMed Central

Ngo, Chi T.; Alm, Kylie H.; Metoki, Athanasia; Hampton, William; Riggins, Tracy; Newcombe, Nora S.; Olson, Ingrid R.

2018-01-01

Episodic memory undergoes dramatic improvement in early childhood; the reason for this is poorly understood. In adults, episodic memory relies on a distributed neural network. Key brain regions that supporting these processes include the hippocampus, portions of the parietal cortex, and portions of prefrontal cortex, each of which shows different developmental profiles. Here we asked whether developmental differences in the axonal pathways connecting these regions may account for the robust gains in episodic memory in young children. Using diffusion weighted imaging, we examined whether white matter connectivity between brain regions implicated in episodic memory differed with age, and were associated with memory performance differences in 4- and 6-year-old children. Results revealed that white matter connecting the hippocampus to the inferior parietal lobule significantly predicted children’s performance on episodic memory tasks. In contrast, variation in the white matter connecting the hippocampus to the medial prefrontal cortex did not relate to memory performance. These findings suggest that structural connectivity between the hippocampus and lateral parietal regions is relevant to the development of episodic memory PMID:29175538

How memory mechanisms are a key component in the guidance of our eye movements: evidence from the global effect.

PubMed

Silvis, J D; Van der Stigchel, S

2014-04-01

Investigating eye movements has been a promising approach to uncover the role of visual working memory in early attentional processes. Prior research has already demonstrated that eye movements in search tasks are more easily drawn toward stimuli that show similarities to working memory content, as compared with neutral stimuli. Previous saccade tasks, however, have always required a selection process, thereby automatically recruiting working memory. The present study was an attempt to confirm the role of working memory in oculomotor selection in an unbiased saccade task that rendered memory mechanisms irrelevant. Participants executed a saccade in a display with two elements, without any instruction to aim for one particular element. The results show that when two objects appear simultaneously, a working memory match attracts the first saccade more profoundly than do mismatch objects, an effect that was present throughout the saccade latency distribution. These findings demonstrate that memory plays a fundamental biasing role in the earliest competitive processes in the selection of visual objects, even when working memory is not recruited during selection.

Continuing the search for the engram: examining the mechanism of fear memories.

PubMed

Josselyn, Sheena A

2010-07-01

The goal of my research is to gain insight using rodent models into the fundamental molecular, cellular and systems that make up the base of memory formation. My work focuses on fear memories. Aberrant fear and/or anxiety may be at the heart of many psychiatric disorders. In this article, I review the results of my research group; these results show that particular neurons in the lateral amygdala, a brain region important for fear, are specifically involved in particular fear memories. We started by showing that the transcription factor CREB (cAMP/Ca(2+) response element binding protein) plays a key role in the formation of fear memories. Next, we used viral vectors to overexpress CREB in a subset of lateral amygdala neurons. This not only facilitated fear memory formation but also "drove" the memory into the neurons with relatively increased CREB function. Finally, we showed that selective ablation of the neurons overexpressing CREB in the lateral amygdala selectively erased the fear memory. These findings are the first to show disruption of a specific memory by disrupting select neurons within a distributed network.

Efficient implementation of multidimensional fast fourier transform on a distributed-memory parallel multi-node computer

DOEpatents

Bhanot, Gyan V [Princeton, NJ; Chen, Dong [Croton-On-Hudson, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

2012-01-10

The present in invention is directed to a method, system and program storage device for efficiently implementing a multidimensional Fast Fourier Transform (FFT) of a multidimensional array comprising a plurality of elements initially distributed in a multi-node computer system comprising a plurality of nodes in communication over a network, comprising: distributing the plurality of elements of the array in a first dimension across the plurality of nodes of the computer system over the network to facilitate a first one-dimensional FFT; performing the first one-dimensional FFT on the elements of the array distributed at each node in the first dimension; re-distributing the one-dimensional FFT-transformed elements at each node in a second dimension via "all-to-all" distribution in random order across other nodes of the computer system over the network; and performing a second one-dimensional FFT on elements of the array re-distributed at each node in the second dimension, wherein the random order facilitates efficient utilization of the network thereby efficiently implementing the multidimensional FFT. The "all-to-all" re-distribution of array elements is further efficiently implemented in applications other than the multidimensional FFT on the distributed-memory parallel supercomputer.

Efficient implementation of a multidimensional fast fourier transform on a distributed-memory parallel multi-node computer

DOEpatents

Bhanot, Gyan V [Princeton, NJ; Chen, Dong [Croton-On-Hudson, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

2008-01-01

The present in invention is directed to a method, system and program storage device for efficiently implementing a multidimensional Fast Fourier Transform (FFT) of a multidimensional array comprising a plurality of elements initially distributed in a multi-node computer system comprising a plurality of nodes in communication over a network, comprising: distributing the plurality of elements of the array in a first dimension across the plurality of nodes of the computer system over the network to facilitate a first one-dimensional FFT; performing the first one-dimensional FFT on the elements of the array distributed at each node in the first dimension; re-distributing the one-dimensional FFT-transformed elements at each node in a second dimension via "all-to-all" distribution in random order across other nodes of the computer system over the network; and performing a second one-dimensional FFT on elements of the array re-distributed at each node in the second dimension, wherein the random order facilitates efficient utilization of the network thereby efficiently implementing the multidimensional FFT. The "all-to-all" re-distribution of array elements is further efficiently implemented in applications other than the multidimensional FFT on the distributed-memory parallel supercomputer.

Effects of Aging and IQ on Item and Associative Memory

ERIC Educational Resources Information Center

Ratcliff, Roger; Thapar, Anjali; McKoon, Gail

2011-01-01

The effects of aging and IQ on performance were examined in 4 memory tasks: item recognition, associative recognition, cued recall, and free recall. For item and associative recognition, accuracy and the response time (RT) distributions for correct and error responses were explained by Ratcliff's (1978) diffusion model at the level of individual…

Common data buffer

NASA Technical Reports Server (NTRS)

Byrne, F.

1981-01-01

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

Investigating Strength and Frequency Effects in Recognition Memory Using Type-2 Signal Detection Theory

ERIC Educational Resources Information Center

Higham, Philip A.; Perfect, Timothy J.; Bruno, Davide

2009-01-01

Criterion- versus distribution-shift accounts of frequency and strength effects in recognition memory were investigated with Type-2 signal detection receiver operating characteristic (ROC) analysis, which provides a measure of metacognitive monitoring. Experiment 1 demonstrated a frequency-based mirror effect, with a higher hit rate and lower…

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…

Ambipolar organic thin-film transistor-based nano-floating-gate nonvolatile memory

NASA Astrophysics Data System (ADS)

Han, Jinhua; Wang, Wei; Ying, Jun; Xie, Wenfa

2014-01-01

An ambipolar organic thin-film transistor-based nano-floating-gate nonvolatile memory was demonstrated, with discrete distributed gold nanoparticles, tetratetracontane (TTC), pentacene as the floating-gate layer, tunneling layer, and active layer, respectively. The electron traps at the TTC/pentacene interface were significantly suppressed, which resulted in an ambipolar operation in present memory. As both electrons and holes were supplied in the channel and trapped in the floating-gate by programming/erasing operations, respectively, i.e., one type of charge carriers was used to overwrite the other, trapped, one, a large memory window, extending on both sides of the initial threshold voltage, was realized.

Memory beyond memory in heart beating, a sign of a healthy physiological condition.

PubMed

Allegrini, P; Grigolini, P; Hamilton, P; Palatella, L; Raffaelli, G

2002-04-01

We describe two types of memory and illustrate each using artificial and actual heartbeat data sets. The first type of memory, yielding anomalous diffusion, implies the inverse power-law nature of the waiting time distribution and the second the correlation among distinct times, and consequently also the occurrence of many pseudoevents, namely, not genuinely random events. Using the method of diffusion entropy analysis, we establish the scaling that would be determined by the real events alone. We prove that the heart beating of healthy patients reveals the existence of many more pseudoevents than in the patients with congestive heart failure.

Memory Network For Distributed Data Processors

NASA Technical Reports Server (NTRS)

Bolen, David; Jensen, Dean; Millard, ED; Robinson, Dave; Scanlon, George

1992-01-01

Universal Memory Network (UMN) is modular, digital data-communication system enabling computers with differing bus architectures to share 32-bit-wide data between locations up to 3 km apart with less than one millisecond of latency. Makes it possible to design sophisticated real-time and near-real-time data-processing systems without data-transfer "bottlenecks". This enterprise network permits transmission of volume of data equivalent to an encyclopedia each second. Facilities benefiting from Universal Memory Network include telemetry stations, simulation facilities, power-plants, and large laboratories or any facility sharing very large volumes of data. Main hub of UMN is reflection center including smaller hubs called Shared Memory Interfaces.

Fifty years since Lashley's In search of the Engram: refutations and conjectures.

PubMed

Bruce, D

2001-12-01

In his well-known article 'In Search of the Engram' published in 1950, Karl Spencer Lashley summarized his 33 years of research and theory on memory and the brain. He concluded that (1) memories are not localized but are instead distributed within functional areas of the cortex and (2) memory traces are not isolated cortical connections between inputs and outputs. Though not the first time he had expressed such convictions, their reiteration in this article was backed by Lashley's estimable reputation and expressive power and they have taken firm root in the collective knowledge of today's memory and neuropsychological research community.

Realization of reliable solid-state quantum memory for photonic polarization qubit.

PubMed

Zhou, Zong-Quan; Lin, Wei-Bin; Yang, Ming; Li, Chuan-Feng; Guo, Guang-Can

2012-05-11

Faithfully storing an unknown quantum light state is essential to advanced quantum communication and distributed quantum computation applications. The required quantum memory must have high fidelity to improve the performance of a quantum network. Here we report the reversible transfer of photonic polarization states into collective atomic excitation in a compact solid-state device. The quantum memory is based on an atomic frequency comb (AFC) in rare-earth ion-doped crystals. We obtain up to 0.999 process fidelity for the storage and retrieval process of single-photon-level coherent pulse. This reliable quantum memory is a crucial step toward quantum networks based on solid-state devices.

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.

Splitting attention across the two visual fields in visual short-term memory.

PubMed

Delvenne, Jean-Francois; Holt, Jessica L

2012-02-01

Humans have the ability to attentionally select the most relevant visual information from their extrapersonal world and to retain it in a temporary buffer, known as visual short-term memory (VSTM). Research suggests that at least two non-contiguous items can be selected simultaneously when they are distributed across the two visual hemifields. In two experiments, we show that attention can also be split between the left and right sides of internal representations held in VSTM. Participants were asked to remember several colors, while cues presented during the delay instructed them to orient their attention to a subset of memorized colors. Experiment 1 revealed that orienting attention to one or two colors strengthened equally participants' memory for those colors, but only when they were from separate hemifields. Experiment 2 showed that in the absence of attentional cues the distribution of the items in the visual field per se had no effect on memory. These findings strongly suggest the existence of independent attentional resources in the two hemifields for selecting and/or consolidating information in VSTM. Copyright © 2011 Elsevier B.V. All rights reserved.

A ferrofluid-based neural network: design of an analogue associative memory

NASA Astrophysics Data System (ADS)

Palm, R.; Korenivski, V.

2009-02-01

We analyse an associative memory based on a ferrofluid, consisting of a system of magnetic nano-particles suspended in a carrier fluid of variable viscosity subject to patterns of magnetic fields from an array of input and output magnetic pads. The association relies on forming patterns in the ferrofluid during a training phase, in which the magnetic dipoles are free to move and rotate to minimize the total energy of the system. Once equilibrated in energy for a given input-output magnetic field pattern pair, the particles are fully or partially immobilized by cooling the carrier liquid. Thus produced particle distributions control the memory states, which are read out magnetically using spin-valve sensors incorporated into the output pads. The actual memory consists of spin distributions that are dynamic in nature, realized only in response to the input patterns that the system has been trained for. Two training algorithms for storing multiple patterns are investigated. Using Monte Carlo simulations of the physical system, we demonstrate that the device is capable of storing and recalling two sets of images, each with an accuracy approaching 100%.

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.

Using distributed partial memories to improve self-organizing collective movements.

PubMed

Winder, Ransom; Reggia, James A

2004-08-01

Past self-organizing models of collectively moving "particles" (simulated bird flocks, fish schools, etc.) have typically been based on purely reflexive agents that have no significant memory of past movements. We hypothesized that giving such individual particles a limited distributed memory of past obstacles they encountered could lead to significantly faster travel between goal destinations. Systematic computational experiments using six terrains that had different arrangements of obstacles demonstrated that, at least in some domains, this conjecture is true. Furthermore, these experiments demonstrated that improved performance over time came not only from the avoidance of previously seen obstacles, but also (surprisingly) immediately after first encountering obstacles due to decreased delays in circumventing those obstacles. Simulations also showed that, of the four strategies we tested for removal of remembered obstacles when memory was full and a new obstacle was to be saved, none was better than random selection. These results may be useful in interpreting future experimental research on group movements in biological populations, and in improving existing methodologies for control of collective movements in computer graphics, robotic teams, particle swarm optimization, and computer games.

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.

Distributed parallel messaging for multiprocessor systems

DOEpatents

Chen, Dong; Heidelberger, Philip; Salapura, Valentina; Senger, Robert M; Steinmacher-Burrow, Burhard; Sugawara, Yutaka

2013-06-04

A method and apparatus for distributed parallel messaging in a parallel computing system. The apparatus includes, at each node of a multiprocessor network, multiple injection messaging engine units and reception messaging engine units, each implementing a DMA engine and each supporting both multiple packet injection into and multiple reception from a network, in parallel. The reception side of the messaging unit (MU) includes a switch interface enabling writing of data of a packet received from the network to the memory system. The transmission side of the messaging unit, includes switch interface for reading from the memory system when injecting packets into the network.

Automatic Data Partitioning on Distributed Memory Multiprocessors

DTIC Science & Technology

1990-10-01

DISTRIBUTED MEMORY MULTIPROCESSORS D 1"’ 1 C . Manish Gupta NOV,1 41990.NOV 1 41990m Prithviraj Banerjee D Coordinated Science Laboratory College of...developed on the partitioning of arrays can as well be applied to other programming languages, such as C . 3 The rest of this paper is organized as follows...value 1, as in Fortran. a) N= 4, N 2 = 1: f(i) = J,(j) = 03 b) =Ni 1, N 2 =4: fA(i) =, f() - c ) NI 2, X) 2: f()=[., f2(j) = [L-.j d) N 1 , N 2 =4: fA(i

Distributed-Memory Computing With the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA)

NASA Technical Reports Server (NTRS)

Riley, Christopher J.; Cheatwood, F. McNeil

1997-01-01

The Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA), a Navier-Stokes solver, has been modified for use in a parallel, distributed-memory environment using the Message-Passing Interface (MPI) standard. A standard domain decomposition strategy is used in which the computational domain is divided into subdomains with each subdomain assigned to a processor. Performance is examined on dedicated parallel machines and a network of desktop workstations. The effect of domain decomposition and frequency of boundary updates on performance and convergence is also examined for several realistic configurations and conditions typical of large-scale computational fluid dynamic analysis.

On the research of time past: the hunt for the substrate of memory

PubMed Central

Queenan, Bridget N.; Ryan, Tomás J.; Gazzaniga, Michael; Gallistel, Charles R.

2017-01-01

The search for memory is one of the oldest quests in written human history. For at least two millennia, we have tried to understand how we learn and remember. We have gradually converged on the brain and looked inside it to find the basis of knowledge, the trace of memory. The search for memory has been conducted on multiple levels, from the organ to the cell to the synapse, and has been distributed across disciplines with less chronological or intellectual overlap than one might hope. Frequently, the study of the mind and its memories has been severely restricted by technological or philosophical limitations. However, in the last few years, certain technologies have emerged, offering new routes of inquiry into the basis of memory. The 2016 Kavli Futures Symposium was devoted to the past and future of memory studies. At the workshop, participants evaluated the logic and data underlying the existing and emerging theories of memory. In this paper, written in the spirit of the workshop, we briefly review the history of the hunt for memory, summarizing some of the key debates at each level of spatial resolution. We then discuss the exciting new opportunities to unravel the mystery of memory. PMID:28548457

Measuring Memory Reactivation With Functional MRI: Implications for Psychological Theory.

PubMed

Levy, Benjamin J; Wagner, Anthony D

2013-01-01

Environmental cues often remind us of earlier experiences by triggering the reactivation of memories of events past. Recent evidence suggests that memory reactivation can be observed using functional MRI and that distributed pattern analyses can even provide evidence of reactivation on individual trials. The ability to measure memory reactivation offers unique and powerful leverage on theoretical issues of long-standing interest in cognitive psychology, providing a means to address questions that have proven difficult to answer with behavioral data alone. In this article, we consider three instances. First, reactivation measures can indicate whether memory-based inferences (i.e., generalization) arise through the encoding of integrated cross-event representations or through the flexible expression of separable event memories. Second, online measures of memory reactivation may inform theories of forgetting by providing information about when competing memories are reactivated during competitive retrieval situations. Finally, neural reactivation may provide a window onto the role of replay in memory consolidation. The ability to track memory reactivation, including at the individual trial level, provides unique leverage that is not afforded by behavioral measures and thus promises to shed light on such varied topics as generalization, integration, forgetting, and consolidation. © The Author(s) 2013.

Hippocampus and Retrograde Amnesia in the Rat Model: A Modest Proposal for the Situation of Systems Consolidation

PubMed Central

Sutherland, Robert J.; Sparks, Fraser; Lehmann, Hugo

2010-01-01

The properties of retrograde amnesia after damage to the hippocampus have been explicated with some success using a rat model of human medial temporal lobe amnesia. We review the results of this experimental work with rats focusing on several areas of consensus in this growing literature. We evaluate the theoretically significant hypothesis that hippocampal retrograde amnesia normally exhibits a temporal gradient, affecting recent, but sparing remote memories. Surprisingly, the evidence does not provide much support for the idea that there is a lengthy process of systems consolidation following a learning episode. Instead, recent and remote memories tend to be equally affected. The extent of damage to the hippocampus is a significant factor in this work since it is likely that spared hippocampal tissue can support at least partial memory retrieval. With extensive hippocampal damage gradients are flat or, in the case of memory tasks with flavour/odour retrieval cues, the retrograde amnesia covers a period of about 1 – 3 days. There is consistent evidence that at the time of learning the hippocampus interferes with or overshadows memory acquisition by other systems. This contributes to the breadth and severity of retrograde amnesia relative to anterograde amnesia in the rat. The fact that multiple, distributed learning episodes can overcome this overshadowing is consistent with a parallel dual-store theory or a Distributed Reinstatement Theory in which each learning episode triggers a short period of memory replay that provides a brief hippocampal-dependent systems consolidation. PMID:20430043

Cognitive neuroepigenetics: the next evolution in our understanding of the molecular mechanisms underlying learning and memory?

NASA Astrophysics Data System (ADS)

Marshall, Paul; Bredy, Timothy W.

2016-07-01

A complete understanding of the fundamental mechanisms of learning and memory continues to elude neuroscientists. Although many important discoveries have been made, the question of how memories are encoded and maintained at the molecular level remains. So far, this issue has been framed within the context of one of the most dominant concepts in molecular biology, the central dogma, and the result has been a protein-centric view of memory. Here, we discuss the evidence supporting a role for neuroepigenetic mechanisms, which constitute dynamic and reversible, state-dependent modifications at all levels of control over cellular function, and their role in learning and memory. This neuroepigenetic view suggests that DNA, RNA and protein each influence one another to produce a holistic cellular state that contributes to the formation and maintenance of memory, and predicts a parallel and distributed system for the consolidation, storage and retrieval of the engram.

Optical interconnection network for parallel access to multi-rank memory in future computing systems.

PubMed

Wang, Kang; Gu, Huaxi; Yang, Yintang; Wang, Kun

2015-08-10

With the number of cores increasing, there is an emerging need for a high-bandwidth low-latency interconnection network, serving core-to-memory communication. In this paper, aiming at the goal of simultaneous access to multi-rank memory, we propose an optical interconnection network for core-to-memory communication. In the proposed network, the wavelength usage is delicately arranged so that cores can communicate with different ranks at the same time and broadcast for flow control can be achieved. A distributed memory controller architecture that works in a pipeline mode is also designed for efficient optical communication and transaction address processes. The scaling method and wavelength assignment for the proposed network are investigated. Compared with traditional electronic bus-based core-to-memory communication, the simulation results based on the PARSEC benchmark show that the bandwidth enhancement and latency reduction are apparent.

Cognitive neuroepigenetics: the next evolution in our understanding of the molecular mechanisms underlying learning and memory?

PubMed Central

Marshall, Paul; Bredy, Timothy W.

2016-01-01

A complete understanding of the fundamental mechanisms of learning and memory continues to elude neuroscientists. Although many important discoveries have been made, the question of how memories are encoded and maintained at the molecular level remains. To date, this issue has been framed within the context of one of the most dominant concepts in molecular biology, the central dogma, and the result has been a protein-centric view of memory. Here we discuss the evidence supporting a role for neuroepigenetic mechanisms, which constitute dynamic and reversible, state-dependent modifications at all levels of control over cellular function, and their role in learning and memory. This neuroepigenetic view suggests that DNA, RNA and protein each influence one another to produce a holistic cellular state that contributes to the formation and maintenance of memory, and predicts a parallel and distributed system for the consolidation, storage and retrieval of the engram. PMID:27512601

Interregional synaptic maps among engram cells underlie memory formation.

PubMed

Choi, Jun-Hyeok; Sim, Su-Eon; Kim, Ji-Il; Choi, Dong Il; Oh, Jihae; Ye, Sanghyun; Lee, Jaehyun; Kim, TaeHyun; Ko, Hyoung-Gon; Lim, Chae-Seok; Kaang, Bong-Kiun

2018-04-27

Memory resides in engram cells distributed across the brain. However, the site-specific substrate within these engram cells remains theoretical, even though it is generally accepted that synaptic plasticity encodes memories. We developed the dual-eGRASP (green fluorescent protein reconstitution across synaptic partners) technique to examine synapses between engram cells to identify the specific neuronal site for memory storage. We found an increased number and size of spines on CA1 engram cells receiving input from CA3 engram cells. In contextual fear conditioning, this enhanced connectivity between engram cells encoded memory strength. CA3 engram to CA1 engram projections strongly occluded long-term potentiation. These results indicate that enhanced structural and functional connectivity between engram cells across two directly connected brain regions forms the synaptic correlate for memory formation. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Utilization of Historic Information in an Optimisation Task

NASA Technical Reports Server (NTRS)

Boesser, T.

1984-01-01

One of the basic components of a discrete model of motor behavior and decision making, which describes tracking and supervisory control in unitary terms, is assumed to be a filtering mechanism which is tied to the representational principles of human memory for time-series information. In a series of experiments subjects used the time-series information with certain significant limitations: there is a range-effect; asymmetric distributions seem to be recognized, but it does not seem to be possible to optimize performance based on skewed distributions. Thus there is a transformation of the displayed data between the perceptual system and representation in memory involving a loss of information. This rules out a number of representational principles for time-series information in memory and fits very well into the framework of a comprehensive discrete model for control of complex systems, modelling continuous control (tracking), discrete responses, supervisory behavior and learning.

Narrow log-periodic modulations in non-Markovian random walks

NASA Astrophysics Data System (ADS)

Diniz, R. M. B.; Cressoni, J. C.; da Silva, M. A. A.; Mariz, A. M.; de Araújo, J. M.

2017-12-01

What are the necessary ingredients for log-periodicity to appear in the dynamics of a random walk model? Can they be subtle enough to be overlooked? Previous studies suggest that long-range damaged memory and negative feedback together are necessary conditions for the emergence of log-periodic oscillations. The role of negative feedback would then be crucial, forcing the system to change direction. In this paper we show that small-amplitude log-periodic oscillations can emerge when the system is driven by positive feedback. Due to their very small amplitude, these oscillations can easily be mistaken for numerical finite-size effects. The models we use consist of discrete-time random walks with strong memory correlations where the decision process is taken from memory profiles based either on a binomial distribution or on a delta distribution. Anomalous superdiffusive behavior and log-periodic modulations are shown to arise in the large time limit for convenient choices of the models parameters.

Volatility return intervals analysis of the Japanese market

NASA Astrophysics Data System (ADS)

Jung, W.-S.; Wang, F. Z.; Havlin, S.; Kaizoji, T.; Moon, H.-T.; Stanley, H. E.

2008-03-01

We investigate scaling and memory effects in return intervals between price volatilities above a certain threshold q for the Japanese stock market using daily and intraday data sets. We find that the distribution of return intervals can be approximated by a scaling function that depends only on the ratio between the return interval τ and its mean <τ>. We also find memory effects such that a large (or small) return interval follows a large (or small) interval by investigating the conditional distribution and mean return interval. The results are similar to previous studies of other markets and indicate that similar statistical features appear in different financial markets. We also compare our results between the period before and after the big crash at the end of 1989. We find that scaling and memory effects of the return intervals show similar features although the statistical properties of the returns are different.

On the simple random-walk models of ion-channel gate dynamics reflecting long-term memory.

PubMed

Wawrzkiewicz, Agata; Pawelek, Krzysztof; Borys, Przemyslaw; Dworakowska, Beata; Grzywna, Zbigniew J

2012-06-01

Several approaches to ion-channel gating modelling have been proposed. Although many models describe the dwell-time distributions correctly, they are incapable of predicting and explaining the long-term correlations between the lengths of adjacent openings and closings of a channel. In this paper we propose two simple random-walk models of the gating dynamics of voltage and Ca(2+)-activated potassium channels which qualitatively reproduce the dwell-time distributions, and describe the experimentally observed long-term memory quite well. Biological interpretation of both models is presented. In particular, the origin of the correlations is associated with fluctuations of channel mass density. The long-term memory effect, as measured by Hurst R/S analysis of experimental single-channel patch-clamp recordings, is close to the behaviour predicted by our models. The flexibility of the models enables their use as templates for other types of ion channel.

High-Performance Computation of Distributed-Memory Parallel 3D Voronoi and Delaunay Tessellation

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

Peterka, Tom; Morozov, Dmitriy; Phillips, Carolyn

2014-11-14

Computing a Voronoi or Delaunay tessellation from a set of points is a core part of the analysis of many simulated and measured datasets: N-body simulations, molecular dynamics codes, and LIDAR point clouds are just a few examples. Such computational geometry methods are common in data analysis and visualization; but as the scale of simulations and observations surpasses billions of particles, the existing serial and shared-memory algorithms no longer suffice. A distributed-memory scalable parallel algorithm is the only feasible approach. The primary contribution of this paper is a new parallel Delaunay and Voronoi tessellation algorithm that automatically determines which neighbormore » points need to be exchanged among the subdomains of a spatial decomposition. Other contributions include periodic and wall boundary conditions, comparison of our method using two popular serial libraries, and application to numerous science datasets.« less

Working Memory: Maintenance, Updating, and the Realization of Intentions

PubMed Central

Nyberg, Lars; Eriksson, Johan

2016-01-01

“Working memory” refers to a vast set of mnemonic processes and associated brain networks, relates to basic intellectual abilities, and underlies many real-world functions. Working-memory maintenance involves frontoparietal regions and distributed representational areas, and can be based on persistent activity in reentrant loops, synchronous oscillations, or changes in synaptic strength. Manipulation of content of working memory depends on the dorsofrontal cortex, and updating is realized by a frontostriatal ‘“gating” function. Goals and intentions are represented as cognitive and motivational contexts in the rostrofrontal cortex. Different working-memory networks are linked via associative reinforcement-learning mechanisms into a self-organizing system. Normal capacity variation, as well as working-memory deficits, can largely be accounted for by the effectiveness and integrity of the basal ganglia and dopaminergic neurotransmission. PMID:26637287

Interacting Brain Systems Modulate Memory Consolidation

PubMed Central

McIntyre, Christa K.; McGaugh, James L.; Williams, Cedric L.

2011-01-01

Emotional arousal influences the consolidation of long-term memory. This review discusses experimental approaches and relevant findings that provide the foundation for current understanding of coordinated interactions between arousal activated peripheral hormones and the brain processes that modulate memory formation. Rewarding or aversive experiences release the stress hormones epinephrine (adrenalin) and glucocorticoids from the adrenal glands into the bloodstream. The effect of these hormones on memory consolidation depends upon binding of norepinephrine to beta-adrenergic receptors in the basolateral complex of the amygdala (BLA). Much evidence indicates that the stress hormones influence release of norepinephrine in the BLA through peripheral actions on the vagus nerve which stimulates, through polysynaptic connections, cells of the locus coeruleus to release norepinephrine. The BLA influences memory storage by actions on synapses, distributed throughout the brain, that are engaged in sensory and cognitive processing at the time of amygdala activation. The implications of the activation of these stress-activated memory processes are discussed in relation to stress-related memory disorders. PMID:22085800

Support for non-locking parallel reception of packets belonging to a single memory reception FIFO

DOEpatents

Chen, Dong [Yorktown Heights, NY; Heidelberger, Philip [Yorktown Heights, NY; Salapura, Valentina [Yorktown Heights, NY; Senger, Robert M [Yorktown Heights, NY; Steinmacher-Burow, Burkhard [Boeblingen, DE; Sugawara, Yutaka [Yorktown Heights, NY

2011-01-27

A method and apparatus for distributed parallel messaging in a parallel computing system. A plurality of DMA engine units are configured in a multiprocessor system to operate in parallel, one DMA engine unit for transferring a current packet received at a network reception queue to a memory location in a memory FIFO (rmFIFO) region of a memory. A control unit implements logic to determine whether any prior received packet destined for that rmFIFO is still in a process of being stored in the associated memory by another DMA engine unit of the plurality, and prevent the one DMA engine unit from indicating completion of storing the current received packet in the reception memory FIFO (rmFIFO) until all prior received packets destined for that rmFIFO are completely stored by the other DMA engine units. Thus, there is provided non-locking support so that multiple packets destined for a single rmFIFO are transferred and stored in parallel to predetermined locations in a memory.

Factors affecting graded and ungraded memory loss following hippocampal lesions.

PubMed

Winocur, Gordon; Moscovitch, Morris; Sekeres, Melanie J

2013-11-01

This review evaluates three current theories--Standard Consolidation (Squire & Wixted, 2011), Overshadowing (Sutherland, Sparks, & Lehmann, 2010), and Multiple Trace-Transformation (Winocur, Moscovitch, & Bontempi, 2010)--in terms of their ability to account for the role of the hippocampus in recent and remote memory in animals. Evidence, based on consistent findings from tests of spatial memory and memory for acquired food preferences, favours the transformation account, but this conclusion is undermined by inconsistent results from studies that measured contextual fear memory, probably the most commonly used test of hippocampal involvement in anterograde and retrograde memory. Resolution of this issue may depend on exercising greater control over critical factors (e.g., contextual environment, amount of pre-exposure to the conditioning chamber, the number and distribution of foot-shocks) that can affect the representation of the memory shortly after learning and over the long-term. Research strategies aimed at characterizing the neural basis of long-term consolidation/transformation, as well as other outstanding issues are discussed. Copyright © 2013 Elsevier Inc. All rights reserved.

The neural substrates of recognition memory for verbal information: spanning the divide between short- and long-term memory.

PubMed

Buchsbaum, Bradley R; Padmanabhan, Aarthi; Berman, Karen Faith

2011-04-01

One of the classic categorical divisions in the history of memory research is that between short-term and long-term memory. Indeed, because memory for the immediate past (a few seconds) and memory for the relatively more remote past (several seconds and beyond) are assumed to rely on distinct neural systems, more often than not, memory research has focused either on short- (or "working memory") or on long-term memory. Using an auditory-verbal continuous recognition paradigm designed for fMRI, we examined how the neural signatures of recognition memory change across an interval of time (from 2.5 to 30 sec) that spans this hypothetical division between short- and long-term memory. The results revealed that activity during successful auditory-verbal item recognition in inferior parietal cortex and the posterior superior temporal lobe was maximal for early lags, whereas, conversely, activity in the left inferior frontal gyrus increased as a function of lag. Taken together, the results reveal that as the interval between item repetitions increases, there is a shift in the distribution of memory-related activity that moves from posterior temporo-parietal cortex (lags 1-4) to inferior frontal regions (lags 5-10), indicating that as time advances, the burden of recognition memory is increasingly placed on top-down retrieval mechanisms that are mediated by structures in inferior frontal cortex.

A dual-trace model for visual sensory memory.

PubMed

Cappiello, Marcus; Zhang, Weiwei

2016-11-01

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

Effects of Healthy Aging and Early-Stage Dementia of the Alzheimer’s Type on Components of Response Time Distributions in Three Attention Tasks

PubMed Central

Tse, Chi-Shing; Balota, David A.; Yap, Melvin J.; Duchek, Janet M.; McCabe, David P.

2009-01-01

Objective The characteristics of response time (RT) distributions beyond measures of central tendency were explored in three attention tasks across groups of young, healthy older adults and individuals with very mild dementia of the Alzheimer’s type (DAT). Method Participants were administered computerized Stroop, Simon, and Switching tasks, along with psychometric tasks that tap various cognitive abilities, and a standard personality inventory (NEO-FFI). Ex-Gaussian (and Vincentile) analyses were used to capture the characteristics of the RT distributions for each participant across the three tasks, which afforded three components: Mu, Sigma (mean and standard deviation of the modal portion of the distribution), and Tau (the positive tail of the distribution). Results The results indicated that across all three attention tasks, healthy aging produced large changes in the central tendency Mu parameter of the distribution along with some change in Sigma and Tau (mean ηp2=.17, .08, and .04, respectively). In contrast, early stage DAT primarily produced an increase in the Tau component (mean ηp2=.06). Tau was also correlated with the psychometric measures of episodic/semantic memory, working memory, and processing speed, and with the personality traits of Neuroticism and Conscientiousness. Structural equation modeling indicated a unique relation between a latent Tau construct (−.90), as opposed to Sigma (−.09) and Mu constructs (.24), with working memory measures. Conclusions The results suggest a critical role of attentional control systems in discriminating healthy aging from early stage DAT and the utility of reaction time distribution analyses to better specify the nature of such change. PMID:20438208

The Histone Deacetylase HDAC4 Regulates Long-Term Memory in Drosophila

PubMed Central

Fitzsimons, Helen L.; Schwartz, Silvia; Given, Fiona M.; Scott, Maxwell J.

2013-01-01

A growing body of research indicates that pharmacological inhibition of histone deacetylases (HDACs) correlates with enhancement of long-term memory and current research is concentrated on determining the roles that individual HDACs play in cognitive function. Here, we investigate the role of HDAC4 in long-term memory formation in Drosophila. We show that overexpression of HDAC4 in the adult mushroom body, an important structure for memory formation, resulted in a specific impairment in long-term courtship memory, but had no affect on short-term memory. Overexpression of an HDAC4 catalytic mutant also abolished LTM, suggesting a mode of action independent of catalytic activity. We found that overexpression of HDAC4 resulted in a redistribution of the transcription factor MEF2 from a relatively uniform distribution through the nucleus into punctate nuclear bodies, where it colocalized with HDAC4. As MEF2 has also been implicated in regulation of long-term memory, these data suggest that the repressive effects of HDAC4 on long-term memory may be through interaction with MEF2. In the same genetic background, we also found that RNAi-mediated knockdown of HDAC4 impairs long-term memory, therefore we demonstrate that HDAC4 is not only a repressor of long-term memory, but also modulates normal memory formation. PMID:24349558

Working memory accuracy for multiple targets is driven by reward expectation and stimulus contrast with different time-courses.

PubMed

Klink, P Christiaan; Jeurissen, Danique; Theeuwes, Jan; Denys, Damiaan; Roelfsema, Pieter R

2017-08-22

The richness of sensory input dictates that the brain must prioritize and select information for further processing and storage in working memory. Stimulus salience and reward expectations influence this prioritization but their relative contributions and underlying mechanisms are poorly understood. Here we investigate how the quality of working memory for multiple stimuli is determined by priority during encoding and later memory phases. Selective attention could, for instance, act as the primary gating mechanism when stimuli are still visible. Alternatively, observers might still be able to shift priorities across memories during maintenance or retrieval. To distinguish between these possibilities, we investigated how and when reward cues determine working memory accuracy and found that they were only effective during memory encoding. Previously learned, but currently non-predictive, color-reward associations had a similar influence, which gradually weakened without reinforcement. Finally, we show that bottom-up salience, manipulated through varying stimulus contrast, influences memory accuracy during encoding with a fundamentally different time-course than top-down reward cues. While reward-based effects required long stimulus presentation, the influence of contrast was strongest with brief presentations. Our results demonstrate how memory resources are distributed over memory targets and implicates selective attention as a main gating mechanism between sensory and memory systems.

Splitting Attention across the Two Visual Fields in Visual Short-Term Memory

ERIC Educational Resources Information Center

Delvenne, Jean-Francois; Holt, Jessica L.

2012-01-01

Humans have the ability to attentionally select the most relevant visual information from their extrapersonal world and to retain it in a temporary buffer, known as visual short-term memory (VSTM). Research suggests that at least two non-contiguous items can be selected simultaneously when they are distributed across the two visual hemifields. In…

Individual Differences in Components of Reaction Time Distributions and Their Relations to Working Memory and Intelligence

ERIC Educational Resources Information Center

Schmiedek, Florian; Oberauer, Klaus; Wilhelm, Oliver; Suss, Heinz-Martin; Wittmann, Werner W.

2007-01-01

The authors bring together approaches from cognitive and individual differences psychology to model characteristics of reaction time distributions beyond measures of central tendency. Ex-Gaussian distributions and a diffusion model approach are used to describe individuals' reaction time data. The authors identified common latent factors for each…

Task Assignment Heuristics for Distributed CFD Applications

NASA Technical Reports Server (NTRS)

Lopez-Benitez, N.; Djomehri, M. J.; Biswas, R.; Biegel, Bryan (Technical Monitor)

2001-01-01

CFD applications require high-performance computational platforms: 1. Complex physics and domain configuration demand strongly coupled solutions; 2. Applications are CPU and memory intensive; and 3. Huge resource requirements can only be satisfied by teraflop-scale machines or distributed computing.

A voting-based star identification algorithm utilizing local and global distribution

NASA Astrophysics Data System (ADS)

Fan, Qiaoyun; Zhong, Xuyang; Sun, Junhua

2018-03-01

A novel star identification algorithm based on voting scheme is presented in this paper. In the proposed algorithm, the global distribution and local distribution of sensor stars are fully utilized, and the stratified voting scheme is adopted to obtain the candidates for sensor stars. The database optimization is employed to reduce its memory requirement and improve the robustness of the proposed algorithm. The simulation shows that the proposed algorithm exhibits 99.81% identification rate with 2-pixel standard deviations of positional noises and 0.322-Mv magnitude noises. Compared with two similar algorithms, the proposed algorithm is more robust towards noise, and the average identification time and required memory is less. Furthermore, the real sky test shows that the proposed algorithm performs well on the real star images.

Directions in parallel programming: HPF, shared virtual memory and object parallelism in pC++

NASA Technical Reports Server (NTRS)

Bodin, Francois; Priol, Thierry; Mehrotra, Piyush; Gannon, Dennis

1994-01-01

Fortran and C++ are the dominant programming languages used in scientific computation. Consequently, extensions to these languages are the most popular for programming massively parallel computers. We discuss two such approaches to parallel Fortran and one approach to C++. The High Performance Fortran Forum has designed HPF with the intent of supporting data parallelism on Fortran 90 applications. HPF works by asking the user to help the compiler distribute and align the data structures with the distributed memory modules in the system. Fortran-S takes a different approach in which the data distribution is managed by the operating system and the user provides annotations to indicate parallel control regions. In the case of C++, we look at pC++ which is based on a concurrent aggregate parallel model.

Event boundaries and memory improvement.

PubMed

Pettijohn, Kyle A; Thompson, Alexis N; Tamplin, Andrea K; Krawietz, Sabine A; Radvansky, Gabriel A

2016-03-01

The structure of events can influence later memory for information that is embedded in them, with evidence indicating that event boundaries can both impair and enhance memory. The current study explored whether the presence of event boundaries during encoding can structure information to improve memory. In Experiment 1, memory for a list of words was tested in which event structure was manipulated by having participants walk through a doorway, or not, halfway through the word list. In Experiment 2, memory for lists of words was tested in which event structure was manipulated using computer windows. Finally, in Experiments 3 and 4, event structure was manipulated by having event shifts described in narrative texts. The consistent finding across all of these methods and materials was that memory was better when the information was distributed across two events rather than combined into a single event. Moreover, Experiment 4 demonstrated that increasing the number of event boundaries from one to two increased the memory benefit. These results are interpreted in the context of the Event Horizon Model of event cognition. Copyright © 2015 Elsevier B.V. All rights reserved.

Modality specificity in the cerebro-cerebellar neurocircuitry during working memory.

PubMed

Ng, H B Tommy; Kao, K-L Cathy; Chan, Y C; Chew, Effie; Chuang, K H; Chen, S H Annabel

2016-05-15

Previous studies have suggested cerebro-cerebellar circuitry in working memory. The present fMRI study aims to distinguish differential cerebro-cerebellar activation patterns in verbal and visual working memory, and employs a quantitative analysis to deterimine lateralization of the activation patterns observed. Consistent with Chen and Desmond (2005a,b) predictions, verbal working memory activated a cerebro-cerebellar circuitry that comprised left-lateralized language-related brain regions including the inferior frontal and posterior parietal areas, and subcortically, right-lateralized superior (lobule VI) and inferior cerebellar (lobule VIIIA/VIIB) areas. In contrast, a distributed network of bilateral inferior frontal and inferior temporal areas, and bilateral superior (lobule VI) and inferior (lobule VIIB) cerebellar areas, was recruited during visual working memory. Results of the study verified that a distinct cross cerebro-cerebellar circuitry underlies verbal working memory. However, a neural circuitry involving specialized brain areas in bilateral neocortical and bilateral cerebellar hemispheres subserving visual working memory is observed. Findings are discussed in the light of current models of working memory and data from related neuroimaging studies. Copyright © 2016 Elsevier B.V. All rights reserved.

qPR: An adaptive partial-report procedure based on Bayesian inference.

PubMed

Baek, Jongsoo; Lesmes, Luis Andres; Lu, Zhong-Lin

2016-08-01

Iconic memory is best assessed with the partial report procedure in which an array of letters appears briefly on the screen and a poststimulus cue directs the observer to report the identity of the cued letter(s). Typically, 6-8 cue delays or 600-800 trials are tested to measure the iconic memory decay function. Here we develop a quick partial report, or qPR, procedure based on a Bayesian adaptive framework to estimate the iconic memory decay function with much reduced testing time. The iconic memory decay function is characterized by an exponential function and a joint probability distribution of its three parameters. Starting with a prior of the parameters, the method selects the stimulus to maximize the expected information gain in the next test trial. It then updates the posterior probability distribution of the parameters based on the observer's response using Bayesian inference. The procedure is reiterated until either the total number of trials or the precision of the parameter estimates reaches a certain criterion. Simulation studies showed that only 100 trials were necessary to reach an average absolute bias of 0.026 and a precision of 0.070 (both in terms of probability correct). A psychophysical validation experiment showed that estimates of the iconic memory decay function obtained with 100 qPR trials exhibited good precision (the half width of the 68.2% credible interval = 0.055) and excellent agreement with those obtained with 1,600 trials of the conventional method of constant stimuli procedure (RMSE = 0.063). Quick partial-report relieves the data collection burden in characterizing iconic memory and makes it possible to assess iconic memory in clinical populations.

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

PubMed

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

2017-10-01

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

qPR: An adaptive partial-report procedure based on Bayesian inference

PubMed Central

Baek, Jongsoo; Lesmes, Luis Andres; Lu, Zhong-Lin

2016-01-01

Iconic memory is best assessed with the partial report procedure in which an array of letters appears briefly on the screen and a poststimulus cue directs the observer to report the identity of the cued letter(s). Typically, 6–8 cue delays or 600–800 trials are tested to measure the iconic memory decay function. Here we develop a quick partial report, or qPR, procedure based on a Bayesian adaptive framework to estimate the iconic memory decay function with much reduced testing time. The iconic memory decay function is characterized by an exponential function and a joint probability distribution of its three parameters. Starting with a prior of the parameters, the method selects the stimulus to maximize the expected information gain in the next test trial. It then updates the posterior probability distribution of the parameters based on the observer's response using Bayesian inference. The procedure is reiterated until either the total number of trials or the precision of the parameter estimates reaches a certain criterion. Simulation studies showed that only 100 trials were necessary to reach an average absolute bias of 0.026 and a precision of 0.070 (both in terms of probability correct). A psychophysical validation experiment showed that estimates of the iconic memory decay function obtained with 100 qPR trials exhibited good precision (the half width of the 68.2% credible interval = 0.055) and excellent agreement with those obtained with 1,600 trials of the conventional method of constant stimuli procedure (RMSE = 0.063). Quick partial-report relieves the data collection burden in characterizing iconic memory and makes it possible to assess iconic memory in clinical populations. PMID:27580045

A fault-tolerant information processing concept for space vehicles.

NASA Technical Reports Server (NTRS)

Hopkins, A. L., Jr.

1971-01-01

A distributed fault-tolerant information processing system is proposed, comprising a central multiprocessor, dedicated local processors, and multiplexed input-output buses connecting them together. The processors in the multiprocessor are duplicated for error detection, which is felt to be less expensive than using coded redundancy of comparable effectiveness. Error recovery is made possible by a triplicated scratchpad memory in each processor. The main multiprocessor memory uses replicated memory for error detection and correction. Local processors use any of three conventional redundancy techniques: voting, duplex pairs with backup, and duplex pairs in independent subsystems.

A new approach for implementation of associative memory using volume holographic materials

NASA Astrophysics Data System (ADS)

Habibi, Mohammad; Pashaie, Ramin

2012-02-01

Associative memory, also known as fault tolerant or content-addressable memory, has gained considerable attention in last few decades. This memory possesses important advantages over the more common random access memories since it provides the capability to correct faults and/or partially missing information in a given input pattern. There is general consensus that optical implementation of connectionist models and parallel processors including associative memory has a better record of success compared to their electronic counterparts. In this article, we describe a novel optical implementation of associative memory which not only has the advantage of all optical learning and recalling capabilities, it can also be realized easily. We present a new approach, inspired by tomographic imaging techniques, for holographic implementation of associative memories. In this approach, a volume holographic material is sandwiched within a matrix of inputs (optical point sources) and outputs (photodetectors). The memory capacity is realized by the spatial modulation of refractive index of the holographic material. Constructing the spatial distribution of the refractive index from an array of known inputs and outputs is formulated as an inverse problem consisting a set of linear integral equations.

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

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.

Goal-Directed Modulation of Neural Memory Patterns: Implications for fMRI-Based Memory Detection.

PubMed

Uncapher, Melina R; Boyd-Meredith, J Tyler; Chow, Tiffany E; Rissman, Jesse; Wagner, Anthony D

2015-06-03

Remembering a past event elicits distributed neural patterns that can be distinguished from patterns elicited when encountering novel information. These differing patterns can be decoded with relatively high diagnostic accuracy for individual memories using multivoxel pattern analysis (MVPA) of fMRI data. Brain-based memory detection--if valid and reliable--would have clear utility beyond the domain of cognitive neuroscience, in the realm of law, marketing, and beyond. However, a significant boundary condition on memory decoding validity may be the deployment of "countermeasures": strategies used to mask memory signals. Here we tested the vulnerability of fMRI-based memory detection to countermeasures, using a paradigm that bears resemblance to eyewitness identification. Participants were scanned while performing two tasks on previously studied and novel faces: (1) a standard recognition memory task; and (2) a task wherein they attempted to conceal their true memory state. Univariate analyses revealed that participants were able to strategically modulate neural responses, averaged across trials, in regions implicated in memory retrieval, including the hippocampus and angular gyrus. Moreover, regions associated with goal-directed shifts of attention and thought substitution supported memory concealment, and those associated with memory generation supported novelty concealment. Critically, whereas MVPA enabled reliable classification of memory states when participants reported memory truthfully, the ability to decode memory on individual trials was compromised, even reversing, during attempts to conceal memory. Together, these findings demonstrate that strategic goal states can be deployed to mask memory-related neural patterns and foil memory decoding technology, placing a significant boundary condition on their real-world utility. Copyright © 2015 the authors 0270-6474/15/358531-15$15.00/0.

Interactions and reversal-field memory in complex magnetic nanowire arrays

NASA Astrophysics Data System (ADS)

Rotaru, Aurelian; Lim, Jin-Hee; Lenormand, Denny; Diaconu, Andrei; Wiley, John. B.; Postolache, Petronel; Stancu, Alexandru; Spinu, Leonard

2011-10-01

Interactions and magnetization reversal of Ni nanowire arrays have been investigated by the first-order reversal curve (FORC) method. Several series of samples with controlled spatial distribution were considered including simple wires of different lengths and diameters (70 and 110 nm) and complex wires with a single modulated diameter along their length. Subtle features of magnetic interactions are revealed through a quantitative analysis of the local interaction field profile distributions obtained from the FORC method. In addition, the FORC analysis indicates that the nanowire systems with a mean diameter of 70 nm appear to be organized in symmetric clusters indicative of a reversal-field memory effect.

Livermore Big Artificial Neural Network Toolkit

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

Essen, Brian Van; Jacobs, Sam; Kim, Hyojin

2016-07-01

LBANN is a toolkit that is designed to train artificial neural networks efficiently on high performance computing architectures. It is optimized to take advantages of key High Performance Computing features to accelerate neural network training. Specifically it is optimized for low-latency, high bandwidth interconnects, node-local NVRAM, node-local GPU accelerators, and high bandwidth parallel file systems. It is built on top of the open source Elemental distributed-memory dense and spars-direct linear algebra and optimization library that is released under the BSD license. The algorithms contained within LBANN are drawn from the academic literature and implemented to work within a distributed-memory framework.

Parallel discrete event simulation using shared memory

NASA Technical Reports Server (NTRS)

Reed, Daniel A.; Malony, Allen D.; Mccredie, Bradley D.

1988-01-01

With traditional event-list techniques, evaluating a detailed discrete-event simulation-model can often require hours or even days of computation time. By eliminating the event list and maintaining only sufficient synchronization to ensure causality, parallel simulation can potentially provide speedups that are linear in the numbers of processors. A set of shared-memory experiments, using the Chandy-Misra distributed-simulation algorithm, to simulate networks of queues is presented. Parameters of the study include queueing network topology and routing probabilities, number of processors, and assignment of network nodes to processors. These experiments show that Chandy-Misra distributed simulation is a questionable alternative to sequential-simulation of most queueing network models.

Entanglement distribution schemes employing coherent photon-to-spin conversion in semiconductor quantum dot circuits

NASA Astrophysics Data System (ADS)

Gaudreau, Louis; Bogan, Alex; Korkusinski, Marek; Studenikin, Sergei; Austing, D. Guy; Sachrajda, Andrew S.

2017-09-01

Long distance entanglement distribution is an important problem for quantum information technologies to solve. Current optical schemes are known to have fundamental limitations. A coherent photon-to-spin interface built with quantum dots (QDs) in a direct bandgap semiconductor can provide a solution for efficient entanglement distribution. QD circuits offer integrated spin processing for full Bell state measurement (BSM) analysis and spin quantum memory. Crucially the photo-generated spins can be heralded by non-destructive charge detection techniques. We review current schemes to transfer a polarization-encoded state or a time-bin-encoded state of a photon to the state of a spin in a QD. The spin may be that of an electron or that of a hole. We describe adaptations of the original schemes to employ heavy holes which have a number of attractive properties including a g-factor that is tunable to zero for QDs in an appropriately oriented external magnetic field. We also introduce simple throughput scaling models to demonstrate the potential performance advantage of full BSM capability in a QD scheme, even when the quantum memory is imperfect, over optical schemes relying on linear optical elements and ensemble quantum memories.

A matrix-algebraic formulation of distributed-memory maximal cardinality matching algorithms in bipartite graphs

DOE PAGES

Azad, Ariful; Buluç, Aydın

2016-05-16

We describe parallel algorithms for computing maximal cardinality matching in a bipartite graph on distributed-memory systems. Unlike traditional algorithms that match one vertex at a time, our algorithms process many unmatched vertices simultaneously using a matrix-algebraic formulation of maximal matching. This generic matrix-algebraic framework is used to develop three efficient maximal matching algorithms with minimal changes. The newly developed algorithms have two benefits over existing graph-based algorithms. First, unlike existing parallel algorithms, cardinality of matching obtained by the new algorithms stays constant with increasing processor counts, which is important for predictable and reproducible performance. Second, relying on bulk-synchronous matrix operations,more » these algorithms expose a higher degree of parallelism on distributed-memory platforms than existing graph-based algorithms. We report high-performance implementations of three maximal matching algorithms using hybrid OpenMP-MPI and evaluate the performance of these algorithm using more than 35 real and randomly generated graphs. On real instances, our algorithms achieve up to 200 × speedup on 2048 cores of a Cray XC30 supercomputer. Even higher speedups are obtained on larger synthetically generated graphs where our algorithms show good scaling on up to 16,384 cores.« less

Nanophotonic rare-earth quantum memory with optically controlled retrieval.

PubMed

Zhong, Tian; Kindem, Jonathan M; Bartholomew, John G; Rochman, Jake; Craiciu, Ioana; Miyazono, Evan; Bettinelli, Marco; Cavalli, Enrico; Verma, Varun; Nam, Sae Woo; Marsili, Francesco; Shaw, Matthew D; Beyer, Andrew D; Faraon, Andrei

2017-09-29

Optical quantum memories are essential elements in quantum networks for long-distance distribution of quantum entanglement. Scalable development of quantum network nodes requires on-chip qubit storage functionality with control of the readout time. We demonstrate a high-fidelity nanophotonic quantum memory based on a mesoscopic neodymium ensemble coupled to a photonic crystal cavity. The nanocavity enables >95% spin polarization for efficient initialization of the atomic frequency comb memory and time bin-selective readout through an enhanced optical Stark shift of the comb frequencies. Our solid-state memory is integrable with other chip-scale photon source and detector devices for multiplexed quantum and classical information processing at the network nodes. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Towards a Quantum Memory assisted MDI-QKD node

NASA Astrophysics Data System (ADS)

Namazi, Mehdi; Vallone, Giuseppe; Jordaan, Bertus; Goham, Connor; Shahrokhshahi, Reihaneh; Villoresi, Paolo; Figueroa, Eden

2017-04-01

The creation of large quantum network that permits the communication of quantum states and the secure distribution of cryptographic keys requires multiple operational quantum memories. In this work we present our progress towards building a prototypical quantum network that performs the memory-assisted measurement device independent QKD protocol. Currently our network combines the quantum part of the BB84 protocol with room-temperature quantum memory operation, while still maintaining relevant quantum bit error rates for single-photon level operation. We will also discuss our efforts to use a network of two room temperature quantum memories, receiving, storing and transforming randomly polarized photons in order to realize Bell state measurements. The work was supported by the US-Navy Office of Naval Research, Grant Number N00141410801, the National Science Foundation, Grant Number PHY-1404398 and the Simons Foundation, Grant Number SBF241180.

Arc expression identifies the lateral amygdala fear memory trace

PubMed Central

Gouty-Colomer, L A; Hosseini, B; Marcelo, I M; Schreiber, J; Slump, D E; Yamaguchi, S; Houweling, A R; Jaarsma, D; Elgersma, Y; Kushner, S A

2016-01-01

Memories are encoded within sparsely distributed neuronal ensembles. However, the defining cellular properties of neurons within a memory trace remain incompletely understood. Using a fluorescence-based Arc reporter, we were able to visually identify the distinct subset of lateral amygdala (LA) neurons activated during auditory fear conditioning. We found that Arc-expressing neurons have enhanced intrinsic excitability and are preferentially recruited into newly encoded memory traces. Furthermore, synaptic potentiation of thalamic inputs to the LA during fear conditioning is learning-specific, postsynaptically mediated and highly localized to Arc-expressing neurons. Taken together, our findings validate the immediate-early gene Arc as a molecular marker for the LA neuronal ensemble recruited during fear learning. Moreover, these results establish a model of fear memory formation in which intrinsic excitability determines neuronal selection, whereas learning-related encoding is governed by synaptic plasticity. PMID:25802982

Stimulus-specific variability in color working memory with delayed estimation.

PubMed

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

2014-04-08

Working memory for color has been the central focus in an ongoing debate concerning the structure and limits of visual working memory. Within this area, the delayed estimation task has played a key role. An implicit assumption in color working memory research generally, and delayed estimation in particular, is that the fidelity of memory does not depend on color value (and, relatedly, that experimental colors have been sampled homogeneously with respect to discriminability). This assumption is reflected in the common practice of collapsing across trials with different target colors when estimating memory precision and other model parameters. Here we investigated whether or not this assumption is secure. To do so, we conducted delayed estimation experiments following standard practice with a memory load of one. We discovered that different target colors evoked response distributions that differed widely in dispersion and that these stimulus-specific response properties were correlated across observers. Subsequent experiments demonstrated that stimulus-specific responses persist under higher memory loads and that at least part of the specificity arises in perception and is eventually propagated to working memory. Posthoc stimulus measurement revealed that rendered stimuli differed from nominal stimuli in both chromaticity and luminance. We discuss the implications of these deviations for both our results and those from other working memory studies.

Impaired short-term memory for pitch in congenital amusia.

PubMed

Tillmann, Barbara; Lévêque, Yohana; Fornoni, Lesly; Albouy, Philippe; Caclin, Anne

2016-06-01

Congenital amusia is a neuro-developmental disorder of music perception and production. The hypothesis is that the musical deficits arise from altered pitch processing, with impairments in pitch discrimination (i.e., pitch change detection, pitch direction discrimination and identification) and short-term memory. The present review article focuses on the deficit of short-term memory for pitch. Overall, the data discussed here suggest impairments at each level of processing in short-term memory tasks; starting with the encoding of the pitch information and the creation of the adequate memory trace, the retention of the pitch traces over time as well as the recollection and comparison of the stored information with newly incoming information. These impairments have been related to altered brain responses in a distributed fronto-temporal network, associated with decreased connectivity between these structures, as well as in abnormalities in the connectivity between the two auditory cortices. In contrast, amusic participants׳ short-term memory abilities for verbal material are preserved. These findings show that short-term memory deficits in congenital amusia are specific to pitch, suggesting a pitch-memory system that is, at least partly, separated from verbal memory. This article is part of a Special Issue entitled SI: Auditory working memory. Copyright © 2015 Elsevier B.V. All rights reserved.

On the research of time past: the hunt for the substrate of memory.

PubMed

Queenan, Bridget N; Ryan, Tomás J; Gazzaniga, Michael S; Gallistel, Charles R

2017-05-01

The search for memory is one of the oldest quests in written human history. For at least two millennia, we have tried to understand how we learn and remember. We have gradually converged on the brain and looked inside it to find the basis of knowledge, the trace of memory. The search for memory has been conducted on multiple levels, from the organ to the cell to the synapse, and has been distributed across disciplines with less chronological or intellectual overlap than one might hope. Frequently, the study of the mind and its memories has been severely restricted by technological or philosophical limitations. However, in the last few years, certain technologies have emerged, offering new routes of inquiry into the basis of memory. The 2016 Kavli Futures Symposium was devoted to the past and future of memory studies. At the workshop, participants evaluated the logic and data underlying the existing and emerging theories of memory. In this paper, written in the spirit of the workshop, we briefly review the history of the hunt for memory, summarizing some of the key debates at each level of spatial resolution. We then discuss the exciting new opportunities to unravel the mystery of memory. © 2017 New York Academy of Sciences.

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.

Neural networks and MIMD-multiprocessors

NASA Technical Reports Server (NTRS)

Vanhala, Jukka; Kaski, Kimmo

1990-01-01

Two artificial neural network models are compared. They are the Hopfield Neural Network Model and the Sparse Distributed Memory model. Distributed algorithms for both of them are designed and implemented. The run time characteristics of the algorithms are analyzed theoretically and tested in practice. The storage capacities of the networks are compared. Implementations are done using a distributed multiprocessor system.

Three Tests and Three Corrections: Comment on Koen and Yonelinas (2010)

ERIC Educational Resources Information Center

Jang, Yoonhee; Mickes, Laura; Wixted, John T.

2012-01-01

The slope of the z-transformed receiver-operating characteristic (zROC) in recognition memory experiments is usually less than 1, which has long been interpreted to mean that the variance of the target distribution is greater than the variance of the lure distribution. The greater variance of the target distribution could arise because the…

Learning to Control Actions: Transfer Effects following a Procedural Cognitive Control Computerized Training

PubMed Central

Shahar, Nitzan; Meiran, Nachshon

2015-01-01

Few studies have addressed action control training. In the current study, participants were trained over 19 days in an adaptive training task that demanded constant switching, maintenance and updating of novel action rules. Participants completed an executive functions battery before and after training that estimated processing speed, working memory updating, set-shifting, response inhibition and fluid intelligence. Participants in the training group showed greater improvement than a no-contact control group in processing speed, indicated by reduced reaction times in speeded classification tasks. No other systematic group differences were found across the different pre-post measurements. Ex-Gaussian fitting of the reaction-time distribution revealed that the reaction time reduction observed among trained participants was restricted to the right tail of the distribution, previously shown to be related to working memory. Furthermore, training effects were only found in classification tasks that required participants to maintain novel stimulus-response rules in mind, supporting the notion that the training improved working memory abilities. Training benefits were maintained in a 10-month follow-up, indicating relatively long-lasting effects. The authors conclude that training improved action-related working memory abilities. PMID:25799443

Entanglement of spin waves among four quantum memories.

PubMed

Choi, K S; Goban, A; Papp, S B; van Enk, S J; Kimble, H J

2010-11-18

Quantum networks are composed of quantum nodes that interact coherently through quantum channels, and open a broad frontier of scientific opportunities. For example, a quantum network can serve as a 'web' for connecting quantum processors for computation and communication, or as a 'simulator' allowing investigations of quantum critical phenomena arising from interactions among the nodes mediated by the channels. The physical realization of quantum networks generically requires dynamical systems capable of generating and storing entangled states among multiple quantum memories, and efficiently transferring stored entanglement into quantum channels for distribution across the network. Although such capabilities have been demonstrated for diverse bipartite systems, entangled states have not been achieved for interconnects capable of 'mapping' multipartite entanglement stored in quantum memories to quantum channels. Here we demonstrate measurement-induced entanglement stored in four atomic memories; user-controlled, coherent transfer of the atomic entanglement to four photonic channels; and characterization of the full quadripartite entanglement using quantum uncertainty relations. Our work therefore constitutes an advance in the distribution of multipartite entanglement across quantum networks. We also show that our entanglement verification method is suitable for studying the entanglement order of condensed-matter systems in thermal equilibrium.

Quantum teleportation between remote atomic-ensemble quantum memories.

PubMed

Bao, Xiao-Hui; Xu, Xiao-Fan; Li, Che-Ming; Yuan, Zhen-Sheng; Lu, Chao-Yang; Pan, Jian-Wei

2012-12-11

Quantum teleportation and quantum memory are two crucial elements for large-scale quantum networks. With the help of prior distributed entanglement as a "quantum channel," quantum teleportation provides an intriguing means to faithfully transfer quantum states among distant locations without actual transmission of the physical carriers [Bennett CH, et al. (1993) Phys Rev Lett 70(13):1895-1899]. Quantum memory enables controlled storage and retrieval of fast-flying photonic quantum bits with stationary matter systems, which is essential to achieve the scalability required for large-scale quantum networks. Combining these two capabilities, here we realize quantum teleportation between two remote atomic-ensemble quantum memory nodes, each composed of ∼10(8) rubidium atoms and connected by a 150-m optical fiber. The spin wave state of one atomic ensemble is mapped to a propagating photon and subjected to Bell state measurements with another single photon that is entangled with the spin wave state of the other ensemble. Two-photon detection events herald the success of teleportation with an average fidelity of 88(7)%. Besides its fundamental interest as a teleportation between two remote macroscopic objects, our technique may be useful for quantum information transfer between different nodes in quantum networks and distributed quantum computing.

Experience-Driven Formation of Parts-Based Representations in a Model of Layered Visual Memory

PubMed Central

Jitsev, Jenia; von der Malsburg, Christoph

2009-01-01

Growing neuropsychological and neurophysiological evidence suggests that the visual cortex uses parts-based representations to encode, store and retrieve relevant objects. In such a scheme, objects are represented as a set of spatially distributed local features, or parts, arranged in stereotypical fashion. To encode the local appearance and to represent the relations between the constituent parts, there has to be an appropriate memory structure formed by previous experience with visual objects. Here, we propose a model how a hierarchical memory structure supporting efficient storage and rapid recall of parts-based representations can be established by an experience-driven process of self-organization. The process is based on the collaboration of slow bidirectional synaptic plasticity and homeostatic unit activity regulation, both running at the top of fast activity dynamics with winner-take-all character modulated by an oscillatory rhythm. These neural mechanisms lay down the basis for cooperation and competition between the distributed units and their synaptic connections. Choosing human face recognition as a test task, we show that, under the condition of open-ended, unsupervised incremental learning, the system is able to form memory traces for individual faces in a parts-based fashion. On a lower memory layer the synaptic structure is developed to represent local facial features and their interrelations, while the identities of different persons are captured explicitly on a higher layer. An additional property of the resulting representations is the sparseness of both the activity during the recall and the synaptic patterns comprising the memory traces. PMID:19862345

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

PubMed Central

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

2015-01-01

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

A Distributed Operating System for BMD Applications.

DTIC Science & Technology

1982-01-01

Defense) applications executing on distributed hardware with local and shared memories. The objective was to develop real - time operating system functions...make the Basic Real - Time Operating System , and the set of new EPL language primitives that provide BMD application processes with efficient mechanisms

A procedure for removing the effect of response bias errors from waterfowl hunter questionnaire responses

USGS Publications Warehouse

Atwood, E.L.

1958-01-01

Response bias errors are studied by comparing questionnaire responses from waterfowl hunters using four large public hunting areas with actual hunting data from these areas during two hunting seasons. To the extent that the data permit, the sources of the error in the responses were studied and the contribution of each type to the total error was measured. Response bias errors, including both prestige and memory bias, were found to be very large as compared to non-response and sampling errors. Good fits were obtained with the seasonal kill distribution of the actual hunting data and the negative binomial distribution and a good fit was obtained with the distribution of total season hunting activity and the semi-logarithmic curve. A comparison of the actual seasonal distributions with the questionnaire response distributions revealed that the prestige and memory bias errors are both positive. The comparisons also revealed the tendency for memory bias errors to occur at digit frequencies divisible by five and for prestige bias errors to occur at frequencies which are multiples of the legal daily bag limit. A graphical adjustment of the response distributions was carried out by developing a smooth curve from those frequency classes not included in the predictable biased frequency classes referred to above. Group averages were used in constructing the curve, as suggested by Ezekiel [1950]. The efficiency of the technique described for reducing response bias errors in hunter questionnaire responses on seasonal waterfowl kill is high in large samples. The graphical method is not as efficient in removing response bias errors in hunter questionnaire responses on seasonal hunting activity where an average of 60 percent was removed.

PCI bus content-addressable-memory (CAM) implementation on FPGA for pattern recognition/image retrieval in a distributed environment

NASA Astrophysics Data System (ADS)

Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.

2004-11-01

Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.

Long memory behavior of returns after intraday financial jumps

NASA Astrophysics Data System (ADS)

Behfar, Stefan Kambiz

2016-11-01

In this paper, characterization of intraday financial jumps and time dynamics of returns after jumps is investigated, and will be analytically and empirically shown that intraday jumps are power-law distributed with the exponent 1 < μ < 2; in addition, returns after jumps show long-memory behavior. In the theory of finance, it is important to be able to distinguish between jumps and continuous sample path price movements, and this can be achieved by introducing a statistical test via calculating sums of products of returns over small period of time. In the case of having jump, the null hypothesis for normality test is rejected; this is based on the idea that returns are composed of mixture of normally-distributed and power-law distributed data (∼ 1 /r 1 + μ). Probability of rejection of null hypothesis is a function of μ, which is equal to one for 1 < μ < 2 within large intraday sample size M. To test this idea empirically, we downloaded S&P500 index data for both periods of 1997-1998 and 2014-2015, and showed that the Complementary Cumulative Distribution Function of jump return is power-law distributed with the exponent 1 < μ < 2. There are far more jumps in 1997-1998 as compared to 2015-2016; and it represents a power law exponent in 2015-2016 greater than one in 1997-1998. Assuming that i.i.d returns generally follow Poisson distribution, if the jump is a causal factor, high returns after jumps are the effect; we show that returns caused by jump decay as power-law distribution. To test this idea empirically, we average over the time dynamics of all days; therefore the superposed time dynamics after jump represent a power-law, which indicates that there is a long memory with a power-law distribution of return after jump.

The Episodic Memory System: Neurocircuitry and Disorders

PubMed Central

Dickerson, Bradford C; Eichenbaum, Howard

2010-01-01

The ability to encode and retrieve our daily personal experiences, called episodic memory, is supported by the circuitry of the medial temporal lobe (MTL), including the hippocampus, which interacts extensively with a number of specific distributed cortical and subcortical structures. In both animals and humans, evidence from anatomical, neuropsychological, and physiological studies indicates that cortical components of this system have key functions in several aspects of perception and cognition, whereas the MTL structures mediate the organization and persistence of the network of memories whose details are stored in those cortical areas. Structures within the MTL, and particularly the hippocampus, have distinct functions in combining information from multiple cortical streams, supporting our ability to encode and retrieve details of events that compose episodic memories. Conversely, selective damage in the hippocampus, MTL, and other structures of the large-scale memory system, or deterioration of these areas in several diseases and disorders, compromises episodic memory. A growing body of evidence is converging on a functional organization of the cortical, subcortical, and MTL structures that support the fundamental features of episodic memory in humans and animals. PMID:19776728

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

NASA Astrophysics Data System (ADS)

Wang, Lili

2018-02-01

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

Episodic and working memory deficits in alcoholic Korsakoff patients: the continuity theory revisited.

PubMed

Pitel, Anne Lise; Beaunieux, Hélène; Witkowski, Thomas; Vabret, François; de la Sayette, Vincent; Viader, Fausto; Desgranges, Béatrice; Eustache, Francis

2008-07-01

The exact nature of episodic and working memory impairments in alcoholic Korsakoff patients (KS) remains unclear, as does the specificity of these neuropsychological deficits compared with those of non-Korsakoff alcoholics (AL). The goals of the present study were therefore to (1) specify the nature of episodic and working memory impairments in KS, (2) determine the specificity of the KS neuropsychological profile compared with the AL profile, and (3) observe the distribution of individual performances within the 2 patient groups. We investigated episodic memory (encoding and retrieval abilities, contextual memory and state of consciousness associated with memories), the slave systems of working memory (phonological loop, visuospatial sketchpad and episodic buffer) and executive functions (inhibition, flexibility, updating and integration abilities) in 14 strictly selected KS, 40 AL and 55 control subjects (CS). Compared with CS, KS displayed impairments of episodic memory encoding and retrieval, contextual memory, recollection, the slave systems of working memory and executive functions. Although episodic memory was more severely impaired in KS than in AL, the single specificity of the KS profile was a disproportionately large encoding deficit. Apart from organizational and updating abilities, the slave systems of working memory and inhibition, flexibility and integration abilities were impaired to the same extent in both alcoholic groups. However, some KS were unable to complete the most difficult executive tasks. There was only a partial overlap of individual performances by KS and AL for episodic memory and a total mixture of the 2 groups for working memory. Korsakoff's syndrome encompasses impairments of the different episodic and working memory components. AL and KS displayed similar profiles of episodic and working memory deficits, in accordance with neuroimaging investigations showing similar patterns of brain damage in both alcoholic groups.

Astrocytic β2-adrenergic receptors mediate hippocampal long-term memory consolidation.

PubMed

Gao, Virginia; Suzuki, Akinobu; Magistretti, Pierre J; Lengacher, Sylvain; Pollonini, Gabriella; Steinman, Michael Q; Alberini, Cristina M

2016-07-26

Emotionally relevant experiences form strong and long-lasting memories by critically engaging the stress hormone/neurotransmitter noradrenaline, which mediates and modulates the consolidation of these memories. Noradrenaline acts through adrenergic receptors (ARs), of which β2-adrenergic receptors (βARs) are of particular importance. The differential anatomical and cellular distribution of βAR subtypes in the brain suggests that they play distinct roles in memory processing, although much about their specific contributions and mechanisms of action remains to be understood. Here we show that astrocytic rather than neuronal β2ARs in the hippocampus play a key role in the consolidation of a fear-based contextual memory. These hippocampal β2ARs, but not β1ARs, are coupled to the training-dependent release of lactate from astrocytes, which is necessary for long-term memory formation and for underlying molecular changes. This key metabolic role of astrocytic β2ARs may represent a novel target mechanism for stress-related psychopathologies and neurodegeneration.

Object-based benefits without object-based representations.

PubMed

Fougnie, Daryl; Cormiea, Sarah M; Alvarez, George A

2013-08-01

Influential theories of visual working memory have proposed that the basic units of memory are integrated object representations. Key support for this proposal is provided by the same object benefit: It is easier to remember multiple features of a single object than the same set of features distributed across multiple objects. Here, we replicate the object benefit but demonstrate that features are not stored as single, integrated representations. Specifically, participants could remember 10 features better when arranged in 5 objects compared to 10 objects, yet memory for one object feature was largely independent of memory for the other object feature. These results rule out the possibility that integrated representations drive the object benefit and require a revision of the concept of object-based memory representations. We propose that working memory is object-based in regard to the factors that enhance performance but feature based in regard to the level of representational failure. PsycINFO Database Record (c) 2013 APA, all rights reserved.

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

NASA Astrophysics Data System (ADS)

Wang, Peng; Ma, Qiang

2017-05-01

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

Impact of Spatial and Verbal Short-Term Memory Load on Auditory Spatial Attention Gradients.

PubMed

Golob, Edward J; Winston, Jenna; Mock, Jeffrey R

2017-01-01

Short-term memory load can impair attentional control, but prior work shows that the extent of the effect ranges from being very general to very specific. One factor for the mixed results may be reliance on point estimates of memory load effects on attention. Here we used auditory attention gradients as an analog measure to map-out the impact of short-term memory load over space. Verbal or spatial information was maintained during an auditory spatial attention task and compared to no-load. Stimuli were presented from five virtual locations in the frontal azimuth plane, and subjects focused on the midline. Reaction times progressively increased for lateral stimuli, indicating an attention gradient. Spatial load further slowed responses at lateral locations, particularly in the left hemispace, but had little effect at midline. Verbal memory load had no (Experiment 1), or a minimal (Experiment 2) influence on reaction times. Spatial and verbal load increased switch costs between memory encoding and attention tasks relative to the no load condition. The findings show that short-term memory influences the distribution of auditory attention over space; and that the specific pattern depends on the type of information in short-term memory.

Impact of Spatial and Verbal Short-Term Memory Load on Auditory Spatial Attention Gradients

PubMed Central

Golob, Edward J.; Winston, Jenna; Mock, Jeffrey R.

2017-01-01

Short-term memory load can impair attentional control, but prior work shows that the extent of the effect ranges from being very general to very specific. One factor for the mixed results may be reliance on point estimates of memory load effects on attention. Here we used auditory attention gradients as an analog measure to map-out the impact of short-term memory load over space. Verbal or spatial information was maintained during an auditory spatial attention task and compared to no-load. Stimuli were presented from five virtual locations in the frontal azimuth plane, and subjects focused on the midline. Reaction times progressively increased for lateral stimuli, indicating an attention gradient. Spatial load further slowed responses at lateral locations, particularly in the left hemispace, but had little effect at midline. Verbal memory load had no (Experiment 1), or a minimal (Experiment 2) influence on reaction times. Spatial and verbal load increased switch costs between memory encoding and attention tasks relative to the no load condition. The findings show that short-term memory influences the distribution of auditory attention over space; and that the specific pattern depends on the type of information in short-term memory. PMID:29218024

Multiple transient memories in sheared suspensions: Robustness, structure, and routes to plasticity

NASA Astrophysics Data System (ADS)

Keim, Nathan C.; Paulsen, Joseph D.; Nagel, Sidney R.

2013-09-01

Multiple transient memories, originally discovered in charge-density-wave conductors, are a remarkable and initially counterintuitive example of how a system can store information about its driving. In this class of memories, a system can learn multiple driving inputs, nearly all of which are eventually forgotten despite their continual input. If sufficient noise is present, the system regains plasticity so that it can continue to learn new memories indefinitely. Recently, Keim and Nagel [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.107.010603 107, 010603 (2011)] showed how multiple transient memories could be generalized to a generic driven disordered system with noise, giving as an example simulations of a simple model of a sheared non-Brownian suspension. Here, we further explore simulation models of suspensions under cyclic shear, focusing on three main themes: robustness, structure, and overdriving. We show that multiple transient memories are a robust feature independent of many details of the model. The steady-state spatial distribution of the particles is sensitive to the driving algorithm; nonetheless, the memory formation is independent of such a change in particle correlations. Finally, we demonstrate that overdriving provides another means for controlling memory formation and retention.

Mechanisms of Translation Control Underlying Long-lasting Synaptic Plasticity and the Consolidation of Long-term Memory

PubMed Central

Santini, Emanuela; Huynh, Thu N.; Klann, Eric

2018-01-01

The complexity of memory formation and its persistence is a phenomenon that has been studied intensely for centuries. Memory exists in many forms and is stored in various brain regions. Generally speaking, memories are reorganized into broadly distributed cortical networks over time through systems level consolidation. At the cellular level, storage of information is believed to initially occur via altered synaptic strength by processes such as long-term potentiation (LTP). New protein synthesis is required for long-lasting synaptic plasticity as well as for the formation of long-term memory. The mammalian target of rapamycin complex 1 (mTORC1) is a critical regulator of cap-dependent protein synthesis and is required for numerous forms of long-lasting synaptic plasticity and long-term memory. As such, the study of mTORC1 and protein factors that control translation initiation and elongation have enhanced our understanding of how the process of protein synthesis is regulated during memory formation. Herein we will discuss the molecular mechanisms that regulate protein synthesis as well as pharmacological and genetic manipulations that demonstrate the requirement for proper translational control in long-lasting synaptic plasticity and long-term memory formation. PMID:24484700

Bounds of memory strength for power-law series.

PubMed

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

2017-05-01

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

Bounds of memory strength for power-law series

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

A fuzzy discrete harmony search algorithm applied to annual cost reduction in radial distribution systems

NASA Astrophysics Data System (ADS)

Ameli, Kazem; Alfi, Alireza; Aghaebrahimi, Mohammadreza

2016-09-01

Similarly to other optimization algorithms, harmony search (HS) is quite sensitive to the tuning parameters. Several variants of the HS algorithm have been developed to decrease the parameter-dependency character of HS. This article proposes a novel version of the discrete harmony search (DHS) algorithm, namely fuzzy discrete harmony search (FDHS), for optimizing capacitor placement in distribution systems. In the FDHS, a fuzzy system is employed to dynamically adjust two parameter values, i.e. harmony memory considering rate and pitch adjusting rate, with respect to normalized mean fitness of the harmony memory. The key aspect of FDHS is that it needs substantially fewer iterations to reach convergence in comparison with classical discrete harmony search (CDHS). To the authors' knowledge, this is the first application of DHS to specify appropriate capacitor locations and their best amounts in the distribution systems. Simulations are provided for 10-, 34-, 85- and 141-bus distribution systems using CDHS and FDHS. The results show the effectiveness of FDHS over previous related studies.

Superstatistical generalised Langevin equation: non-Gaussian viscoelastic anomalous diffusion

NASA Astrophysics Data System (ADS)

Ślęzak, Jakub; Metzler, Ralf; Magdziarz, Marcin

2018-02-01

Recent advances in single particle tracking and supercomputing techniques demonstrate the emergence of normal or anomalous, viscoelastic diffusion in conjunction with non-Gaussian distributions in soft, biological, and active matter systems. We here formulate a stochastic model based on a generalised Langevin equation in which non-Gaussian shapes of the probability density function and normal or anomalous diffusion have a common origin, namely a random parametrisation of the stochastic force. We perform a detailed analysis demonstrating how various types of parameter distributions for the memory kernel result in exponential, power law, or power-log law tails of the memory functions. The studied system is also shown to exhibit a further unusual property: the velocity has a Gaussian one point probability density but non-Gaussian joint distributions. This behaviour is reflected in the relaxation from a Gaussian to a non-Gaussian distribution observed for the position variable. We show that our theoretical results are in excellent agreement with stochastic simulations.

Neuropeptide S enhances memory and mitigates memory impairment induced by MK801, scopolamine or Aβ₁₋₄₂ in mice novel object and object location recognition tasks.

PubMed

Han, Ren-Wen; Zhang, Rui-San; Xu, Hong-Jiao; Chang, Min; Peng, Ya-Li; Wang, Rui

2013-07-01

Neuropeptide S (NPS), the endogenous ligand of NPSR, has been shown to promote arousal and anxiolytic-like effects. According to the predominant distribution of NPSR in brain tissues associated with learning and memory, NPS has been reported to modulate cognitive function in rodents. Here, we investigated the role of NPS in memory formation, and determined whether NPS could mitigate memory impairment induced by selective N-methyl-D-aspartate receptor antagonist MK801, muscarinic cholinergic receptor antagonist scopolamine or Aβ₁₋₄₂ in mice, using novel object and object location recognition tasks. Intracerebroventricular (i.c.v.) injection of 1 nmol NPS 5 min after training not only facilitated object recognition memory formation, but also prolonged memory retention in both tasks. The improvement of object recognition memory induced by NPS could be blocked by the selective NPSR antagonist SHA 68, indicating pharmacological specificity. Then, we found that i.c.v. injection of NPS reversed memory disruption induced by MK801, scopolamine or Aβ₁₋₄₂ in both tasks. In summary, our results indicate that NPS facilitates memory formation and prolongs the retention of memory through activation of the NPSR, and mitigates amnesia induced by blockage of glutamatergic or cholinergic system or by Aβ₁₋₄₂, suggesting that NPS/NPSR system may be a new target for enhancing memory and treating amnesia. Copyright © 2013 Elsevier Ltd. All rights reserved.

Long-term pitch memory for music recordings is related to auditory working memory precision.

PubMed

Van Hedger, Stephen C; Heald, Shannon Lm; Nusbaum, Howard C

2018-04-01

Most individuals have reliable long-term memories for the pitch of familiar music recordings. This pitch memory (1) appears to be normally distributed in the population, (2) does not depend on explicit musical training and (3) only seems to be weakly related to differences in listening frequency estimates. The present experiment was designed to assess whether individual differences in auditory working memory could explain variance in long-term pitch memory for music recordings. In Experiment 1, participants first completed a musical note adjustment task that has been previously used to assess working memory of musical pitch. Afterward, participants were asked to judge the pitch of well-known music recordings, which either had or had not been shifted in pitch. We found that performance on the pitch working memory task was significantly related to performance in the pitch memory task using well-known recordings, even when controlling for overall musical experience and familiarity with each recording. In Experiment 2, we replicated these findings in a separate group of participants while additionally controlling for fluid intelligence and non-pitch-based components of auditory working memory. In Experiment 3, we demonstrated that participants could not accurately judge the pitch of unfamiliar recordings, suggesting that our method of pitch shifting did not result in unwanted acoustic cues that could have aided participants in Experiments 1 and 2. These results, taken together, suggest that the ability to maintain pitch information in working memory might lead to more accurate long-term pitch memory.

Repetition and lag effects in movement recognition.

PubMed

Hall, C R; Buckolz, E

1982-03-01

Whether repetition and lag improve the recognition of movement patterns was investigated. Recognition memory was tested for one repetition, two-repetitions massed, and two-repetitions distributed with movement patterns at lags of 3, 5, 7, and 13. Recognition performance was examined both immediately afterwards and following a 48 hour delay. Both repetition and lag effects failed to be demonstrated, providing some support for the claim that memory is unaffected by repetition at a constant level of processing (Craik & Lockhart, 1972). There was, as expected, a significant decrease in recognition memory following the retention interval, but this appeared unrelated to repetition or lag.

Memory-Based Multiagent Coevolution Modeling for Robust Moving Object Tracking

PubMed Central

Wang, Yanjiang; Qi, Yujuan; Li, Yongping

2013-01-01

The three-stage human brain memory model is incorporated into a multiagent coevolutionary process for finding the best match of the appearance of an object, and a memory-based multiagent coevolution algorithm for robust tracking the moving objects is presented in this paper. Each agent can remember, retrieve, or forget the appearance of the object through its own memory system by its own experience. A number of such memory-based agents are randomly distributed nearby the located object region and then mapped onto a 2D lattice-like environment for predicting the new location of the object by their coevolutionary behaviors, such as competition, recombination, and migration. Experimental results show that the proposed method can deal with large appearance changes and heavy occlusions when tracking a moving object. It can locate the correct object after the appearance changed or the occlusion recovered and outperforms the traditional particle filter-based tracking methods. PMID:23843739

Memory-based multiagent coevolution modeling for robust moving object tracking.

PubMed

Wang, Yanjiang; Qi, Yujuan; Li, Yongping

2013-01-01

The three-stage human brain memory model is incorporated into a multiagent coevolutionary process for finding the best match of the appearance of an object, and a memory-based multiagent coevolution algorithm for robust tracking the moving objects is presented in this paper. Each agent can remember, retrieve, or forget the appearance of the object through its own memory system by its own experience. A number of such memory-based agents are randomly distributed nearby the located object region and then mapped onto a 2D lattice-like environment for predicting the new location of the object by their coevolutionary behaviors, such as competition, recombination, and migration. Experimental results show that the proposed method can deal with large appearance changes and heavy occlusions when tracking a moving object. It can locate the correct object after the appearance changed or the occlusion recovered and outperforms the traditional particle filter-based tracking methods.

A reservoir of time constants for memory traces in cortical neurons

PubMed Central

Bernacchia, Alberto; Seo, Hyojung; Lee, Daeyeol; Wang, Xiao-Jing

2011-01-01

According to reinforcement learning theory of decision making, reward expectation is computed by integrating past rewards with a fixed timescale. By contrast, we found that a wide range of time constants is available across cortical neurons recorded from monkeys performing a competitive game task. By recognizing that reward modulates neural activity multiplicatively, we found that one or two time constants of reward memory can be extracted for each neuron in prefrontal, cingulate, and parietal cortex. These timescales ranged from hundreds of milliseconds to tens of seconds, according to a power-law distribution, which is consistent across areas and reproduced by a “reservoir” neural network model. These neuronal memory timescales were weakly but significantly correlated with those of monkey's decisions. Our findings suggest a flexible memory system, where neural subpopulations with distinct sets of long or short memory timescales may be selectively deployed according to the task demands. PMID:21317906

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

PubMed Central

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

2011-01-01

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

Quantitative Analysis of Charge Injection and Discharging of Si Nanocrystals and Arrays by Electrostatic Force Microscopy

NASA Technical Reports Server (NTRS)

Bell, L. D.; Boer, E.; Ostraat, M.; Brongersma, M. L.; Flagan, R. C.; Atwater, H. A.

2000-01-01

NASA requirements for computing and memory for microspacecraft emphasize high density, low power, small size, and radiation hardness. The distributed nature of storage elements in nanocrystal floating-gate memories leads to intrinsic fault tolerance and radiation hardness. Conventional floating-gate non-volatile memories are more susceptible to radiation damage. Nanocrystal-based memories also offer the possibility of faster, lower power operation. In the pursuit of filling these requirements, the following tasks have been accomplished: (1) Si nanocrystal charging has been accomplished with conducting-tip AFM; (2) Both individual nanocrystals on an oxide surface and nanocrystals formed by implantation have been charged; (3) Discharging is consistent with tunneling through a field-lowered oxide barrier; (4) Modeling of the response of the AFM to trapped charge has allowed estimation of the quantity of trapped charge; and (5) Initial attempts to fabricate competitive nanocrystal non-volatile memories have been extremely successful.

A Distributed Representation of Remembered Time

DTIC Science & Technology

2015-11-19

hippocampus , time, and memory across scales. Journal of Experimental Psychology: General., 142(4), 1211-30. doi: 10.1037/a0033621 Howard, M. W...The hippocampus , time, and memory across scales. Journal of Experimental Psychology: General., 142(4), 1211-30. doi: 10.1037/a0033621 Howard, M. W...accomplished this goal by developing a computational framework that describes a wide range of functional cellular correlates in the hippocampus and

Predicting remembering and forgetting of autobiographical memories in children and adults: A 4-year prospective study

PubMed Central

Bauer, Patricia J.; Larkina, Marina

2015-01-01

Preservation and loss to forgetting of autobiographical memories is a focus in both the adult and developmental literatures. In both, there are comparative arguments regarding rates of forgetting. Children are assumed to forget autobiographical memories more rapidly than adults, and younger children are assumed to forget more rapidly than older children. Yet few studies can directly inform these comparisons: few feature children and adults, and few prospectively track the survival of specific autobiographical memories over time. In a 4-year prospective study, we obtained autobiographical memories from children 4, 6, and 8 years, and adults. We tested recall of different subsets of the events after 1, 2, and 3 years. Accelerated rates of forgetting were apparent among all child groups relative to adults; within the child groups, 4- and 6-year-olds had accelerated forgetting relative to 8-year-olds. The differences were especially pronounced in open-ended recall. The thematic coherence of initial memory reports also was a significant predictor of the survival of specific memories. The pattern of findings is consistent with suggestions that the adult distribution of autobiographical memories is achieved as the quality of memory traces increases (here measured by thematic coherence) and the rate of forgetting decreases. PMID:26566236

A Screen Space GPGPU Surface LIC Algorithm for Distributed Memory Data Parallel Sort Last Rendering Infrastructures

NASA Astrophysics Data System (ADS)

Loring, B.; Karimabadi, H.; Rortershteyn, V.

2015-10-01

The surface line integral convolution(LIC) visualization technique produces dense visualization of vector fields on arbitrary surfaces. We present a screen space surface LIC algorithm for use in distributed memory data parallel sort last rendering infrastructures. The motivations for our work are to support analysis of datasets that are too large to fit in the main memory of a single computer and compatibility with prevalent parallel scientific visualization tools such as ParaView and VisIt. By working in screen space using OpenGL we can leverage the computational power of GPUs when they are available and run without them when they are not. We address efficiency and performance issues that arise from the transformation of data from physical to screen space by selecting an alternate screen space domain decomposition. We analyze the algorithm's scaling behavior with and without GPUs on two high performance computing systems using data from turbulent plasma simulations.

A mixed parallel strategy for the solution of coupled multi-scale problems at finite strains

NASA Astrophysics Data System (ADS)

Lopes, I. A. Rodrigues; Pires, F. M. Andrade; Reis, F. J. P.

2018-02-01

A mixed parallel strategy for the solution of homogenization-based multi-scale constitutive problems undergoing finite strains is proposed. The approach aims to reduce the computational time and memory requirements of non-linear coupled simulations that use finite element discretization at both scales (FE^2). In the first level of the algorithm, a non-conforming domain decomposition technique, based on the FETI method combined with a mortar discretization at the interface of macroscopic subdomains, is employed. A master-slave scheme, which distributes tasks by macroscopic element and adopts dynamic scheduling, is then used for each macroscopic subdomain composing the second level of the algorithm. This strategy allows the parallelization of FE^2 simulations in computers with either shared memory or distributed memory architectures. The proposed strategy preserves the quadratic rates of asymptotic convergence that characterize the Newton-Raphson scheme. Several examples are presented to demonstrate the robustness and efficiency of the proposed parallel strategy.

Parallelization of NAS Benchmarks for Shared Memory Multiprocessors

NASA Technical Reports Server (NTRS)

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

1998-01-01

This paper presents our experiences of parallelizing the sequential implementation of NAS benchmarks using compiler directives on SGI Origin2000 distributed shared memory (DSM) system. Porting existing applications to new high performance parallel and distributed computing platforms is a challenging task. Ideally, a user develops a sequential version of the application, leaving the task of porting to new generations of high performance computing systems to parallelization tools and compilers. Due to the simplicity of programming shared-memory multiprocessors, compiler developers have provided various facilities to allow the users to exploit parallelism. Native compilers on SGI Origin2000 support multiprocessing directives to allow users to exploit loop-level parallelism in their programs. Additionally, supporting tools can accomplish this process automatically and present the results of parallelization to the users. We experimented with these compiler directives and supporting tools by parallelizing sequential implementation of NAS benchmarks. Results reported in this paper indicate that with minimal effort, the performance gain is comparable with the hand-parallelized, carefully optimized, message-passing implementations of the same benchmarks.

A Screen Space GPGPU Surface LIC Algorithm for Distributed Memory Data Parallel Sort Last Rendering Infrastructures

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

Loring, Burlen; Karimabadi, Homa; Rortershteyn, Vadim

2014-07-01

The surface line integral convolution(LIC) visualization technique produces dense visualization of vector fields on arbitrary surfaces. We present a screen space surface LIC algorithm for use in distributed memory data parallel sort last rendering infrastructures. The motivations for our work are to support analysis of datasets that are too large to fit in the main memory of a single computer and compatibility with prevalent parallel scientific visualization tools such as ParaView and VisIt. By working in screen space using OpenGL we can leverage the computational power of GPUs when they are available and run without them when they are not.more » We address efficiency and performance issues that arise from the transformation of data from physical to screen space by selecting an alternate screen space domain decomposition. We analyze the algorithm's scaling behavior with and without GPUs on two high performance computing systems using data from turbulent plasma simulations.« less

Repetition and brain potentials when recognizing natural scenes: task and emotion differences

PubMed Central

Bradley, Margaret M.; Codispoti, Maurizio; Karlsson, Marie; Lang, Peter J.

2013-01-01

Repetition has long been known to facilitate memory performance, but its effects on event-related potentials (ERPs), measured as an index of recognition memory, are less well characterized. In Experiment 1, effects of both massed and distributed repetition on old–new ERPs were assessed during an immediate recognition test that followed incidental encoding of natural scenes that also varied in emotionality. Distributed repetition at encoding enhanced both memory performance and the amplitude of an old–new ERP difference over centro-parietal sensors. To assess whether these repetition effects reflect encoding or retrieval differences, the recognition task was replaced with passive viewing of old and new pictures in Experiment 2. In the absence of an explicit recognition task, ERPs were completely unaffected by repetition at encoding, and only emotional pictures prompted a modestly enhanced old–new difference. Taken together, the data suggest that repetition facilitates retrieval processes and that, in the absence of an explicit recognition task, differences in old–new ERPs are only apparent for affective cues. PMID:22842817

Examining reference frame interaction in spatial memory using a distribution analysis.

PubMed

Street, Whitney N; Wang, Ranxiao Frances

2016-02-01

Previous research showed competition among reference frames in spatial attention and language. The present studies developed a new distribution analysis to examine reference frame interactions in spatial memory. Participants viewed virtual arrays of colored pegs and were instructed to remember them either from their own perspective or from the perspective aligned with the rectangular floor. Then they made judgments of relative directions from their respective encoding orientation. Those taking the floor-axis perspective showed systematic bias in the signed errors toward their egocentric perspective, while those taking their own perspective showed no systematic bias, both for random and symmetrical object arrays. The bias toward the egocentric perspective was observed when learning a real symmetric regular object array with strong environmental cues for the aligned axis. These results indicate automatic processing of the self reference while taking the floor-axis perspective but not vice versa, and suggest that research on spatial memory needs to consider the implications of competition effects in reference frame use.

Full Parallel Implementation of an All-Electron Four-Component Dirac-Kohn-Sham Program.

PubMed

Rampino, Sergio; Belpassi, Leonardo; Tarantelli, Francesco; Storchi, Loriano

2014-09-09

A full distributed-memory implementation of the Dirac-Kohn-Sham (DKS) module of the program BERTHA (Belpassi et al., Phys. Chem. Chem. Phys. 2011, 13, 12368-12394) is presented, where the self-consistent field (SCF) procedure is replicated on all the parallel processes, each process working on subsets of the global matrices. The key feature of the implementation is an efficient procedure for switching between two matrix distribution schemes, one (integral-driven) optimal for the parallel computation of the matrix elements and another (block-cyclic) optimal for the parallel linear algebra operations. This approach, making both CPU-time and memory scalable with the number of processors used, virtually overcomes at once both time and memory barriers associated with DKS calculations. Performance, portability, and numerical stability of the code are illustrated on the basis of test calculations on three gold clusters of increasing size, an organometallic compound, and a perovskite model. The calculations are performed on a Beowulf and a BlueGene/Q system.

Parallel Navier-Stokes computations on shared and distributed memory architectures

NASA Technical Reports Server (NTRS)

Hayder, M. Ehtesham; Jayasimha, D. N.; Pillay, Sasi Kumar

1995-01-01

We study a high order finite difference scheme to solve the time accurate flow field of a jet using the compressible Navier-Stokes equations. As part of our ongoing efforts, we have implemented our numerical model on three parallel computing platforms to study the computational, communication, and scalability characteristics. The platforms chosen for this study are a cluster of workstations connected through fast networks (the LACE experimental testbed at NASA Lewis), a shared memory multiprocessor (the Cray YMP), and a distributed memory multiprocessor (the IBM SPI). Our focus in this study is on the LACE testbed. We present some results for the Cray YMP and the IBM SP1 mainly for comparison purposes. On the LACE testbed, we study: (1) the communication characteristics of Ethernet, FDDI, and the ALLNODE networks and (2) the overheads induced by the PVM message passing library used for parallelizing the application. We demonstrate that clustering of workstations is effective and has the potential to be computationally competitive with supercomputers at a fraction of the cost.

A petabyte size electronic library using the N-Gram memory engine

NASA Technical Reports Server (NTRS)

Bugajski, Joseph M.

1993-01-01

A model library containing petabytes of data is proposed by Triada, Ltd., Ann Arbor, Michigan. The library uses the newly patented N-Gram Memory Engine (Neurex), for storage, compression, and retrieval. Neurex splits data into two parts: a hierarchical network of associative memories that store 'information' from data and a permutation operator that preserves sequence. Neurex is expected to offer four advantages in mass storage systems. Neurex representations are dense, fully reversible, hence less expensive to store. Neurex becomes exponentially more stable with increasing data flow; thus its contents and the inverting algorithm may be mass produced for low cost distribution. Only a small permutation operator would be recalled from the library to recover data. Neurex may be enhanced to recall patterns using a partial pattern. Neurex nodes are measures of their pattern. Researchers might use nodes in statistical models to avoid costly sorting and counting procedures. Neurex subsumes a theory of learning and memory that the author believes extends information theory. Its first axiom is a symmetry principle: learning creates memory and memory evidences learning. The theory treats an information store that evolves from a null state to stationarity. A Neurex extracts information data without a priori knowledge; i.e., unlike neural networks, neither feedback nor training is required. The model consists of an energetically conservative field of uniformly distributed events with variable spatial and temporal scale, and an observer walking randomly through this field. A bank of band limited transducers (an 'eye'), each transducer in a bank being tuned to a sub-band, outputs signals upon registering events. Output signals are 'observed' by another transducer bank (a mid-brain), except the band limit of the second bank is narrower than the band limit of the first bank. The banks are arrayed as n 'levels' or 'time domains, td.' The banks are the hierarchical network (a cortex) and transducers are (associative) memories. A model Neurex was built and studied. Data were 50 MB to 10 GB samples of text, data base, and images: black/white, grey scale, and high resolution in several spectral bands. Memories at td, S(m(sub td)), were plotted against outputs of memories at td-1. S(m(sub td)) was Boltzman distributed, and memory frequencies exhibited self-organized criticality (SOC); i.e., 'l/f(sup beta)' after long exposures to data. Whereas output signals from level n may be encoded with B(sub output) = O(-log(2)f(sup beta)) bits, and input data encoded with B(sub input) = O((S(td)/S(td-1))(sup n)), B(sup output)/B(sub input) is much less than 1 always, the Neurex determines a canonical code for data and it is a lossless data compressor. Further tests are underway to confirm these results with more data types and larger samples.

The Cortex Transform as an image preprocessor for sparse distributed memory: An initial study

NASA Technical Reports Server (NTRS)

Olshausen, Bruno; Watson, Andrew

1990-01-01

An experiment is described which was designed to evaluate the use of the Cortex Transform as an image processor for Sparse Distributed Memory (SDM). In the experiment, a set of images were injected with Gaussian noise, preprocessed with the Cortex Transform, and then encoded into bit patterns. The various spatial frequency bands of the Cortex Transform were encoded separately so that they could be evaluated based on their ability to properly cluster patterns belonging to the same class. The results of this study indicate that by simply encoding the low pass band of the Cortex Transform, a very suitable input representation for the SDM can be achieved.

Event parallelism: Distributed memory parallel computing for high energy physics experiments

NASA Astrophysics Data System (ADS)

Nash, Thomas

1989-12-01

This paper describes the present and expected future development of distributed memory parallel computers for high energy physics experiments. It covers the use of event parallel microprocessor farms, particularly at Fermilab, including both ACP multiprocessors and farms of MicroVAXES. These systems have proven very cost effective in the past. A case is made for moving to the more open environment of UNIX and RISC processors. The 2nd Generation ACP Multiprocessor System, which is based on powerful RISC system, is described. Given the promise of still more extraordinary increases in processor performance, a new emphasis on point to point, rather than bussed, communication will be required. Developments in this direction are described.

Evaluation of the non-Gaussianity of two-mode entangled states over a bosonic memory channel via cumulant theory and quadrature detection

NASA Astrophysics Data System (ADS)

Xiang, Shao-Hua; Wen, Wei; Zhao, Yu-Jing; Song, Ke-Hui

2018-04-01

We study the properties of the cumulants of multimode boson operators and introduce the phase-averaged quadrature cumulants as the measure of the non-Gaussianity of multimode quantum states. Using this measure, we investigate the non-Gaussianity of two classes of two-mode non-Gaussian states: photon-number entangled states and entangled coherent states traveling in a bosonic memory quantum channel. We show that such a channel can skew the distribution of two-mode quadrature variables, giving rise to a strongly non-Gaussian correlation. In addition, we provide a criterion to determine whether the distributions of these states are super- or sub-Gaussian.

Simulation of radiation effects on three-dimensional computer optical memories

NASA Technical Reports Server (NTRS)

Moscovitch, M.; Emfietzoglou, D.

1997-01-01

A model was developed to simulate the effects of heavy charged-particle (HCP) radiation on the information stored in three-dimensional computer optical memories. The model is based on (i) the HCP track radial dose distribution, (ii) the spatial and temporal distribution of temperature in the track, (iii) the matrix-specific radiation-induced changes that will affect the response, and (iv) the kinetics of transition of photochromic molecules from the colored to the colorless isomeric form (bit flip). It is shown that information stored in a volume of several nanometers radius around the particle's track axis may be lost. The magnitude of the effect is dependent on the particle's track structure.

Reducing Interprocessor Dependence in Recoverable Distributed Shared Memory

NASA Technical Reports Server (NTRS)

Janssens, Bob; Fuchs, W. Kent

1994-01-01

Checkpointing techniques in parallel systems use dependency tracking and/or message logging to ensure that a system rolls back to a consistent state. Traditional dependency tracking in distributed shared memory (DSM) systems is expensive because of high communication frequency. In this paper we show that, if designed correctly, a DSM system only needs to consider dependencies due to the transfer of blocks of data, resulting in reduced dependency tracking overhead and reduced potential for rollback propagation. We develop an ownership timestamp scheme to tolerate the loss of block state information and develop a passive server model of execution where interactions between processors are considered atomic. With our scheme, dependencies are significantly reduced compared to the traditional message-passing model.

The impact of interference on short-term memory for visual orientation.

PubMed

Rademaker, Rosanne L; Bloem, Ilona M; De Weerd, Peter; Sack, Alexander T

2015-12-01

Visual short-term memory serves as an efficient buffer for maintaining no longer directly accessible information. How robust are visual memories against interference? Memory for simple visual features has proven vulnerable to distractors containing conflicting information along the relevant stimulus dimension, leading to the idea that interacting feature-specific channels at an early stage of visual processing support memory for simple visual features. Here we showed that memory for a single randomly orientated grating was susceptible to interference from a to-be-ignored distractor grating presented midway through a 3-s delay period. Memory for the initially presented orientation became noisier when it differed from the distractor orientation, and response distributions were shifted toward the distractor orientation (by ∼3°). Interestingly, when the distractor was rendered task-relevant by making it a second memory target, memory for both retained orientations showed reduced reliability as a function of increased orientation differences between them. However, the degree to which responses to the first grating shifted toward the orientation of the task-relevant second grating was much reduced. Finally, using a dichoptic display, we demonstrated that these systematic biases caused by a consciously perceived distractor disappeared once the distractor was presented outside of participants' awareness. Together, our results show that visual short-term memory for orientation can be systematically biased by interfering information that is consciously perceived. (c) 2015 APA, all rights reserved).

A new model for CD8+ T cell memory inflation based upon a recombinant adenoviral vector1

PubMed Central

Bolinger, Beatrice; Sims, Stuart; O’Hara, Geraldine; de Lara, Catherine; Tchilian, Elma; Firner, Sonja; Engeler, Daniel; Ludewig, Burkhard; Klenerman, Paul

2013-01-01

CD8+ T cell memory inflation, first described in murine cytomegalovirus (MCMV) infection, is characterized by the accumulation of high-frequency, functional antigen-specific CD8+ T cell pools with an effector-memory phenotype and enrichment in peripheral organs. Although persistence of antigen is considered essential, the rules underpinning memory inflation are still unclear. The MCMV model is, however, complicated by the virus’s low-level persistence, and stochastic reactivation. We developed a new model of memory inflation based upon a βgal-recombinant adenovirus vector (Ad-LacZ). After i.v. administration in C57BL/6 mice we observe marked memory inflation in the βgal96 epitope, while a second epitope, βgal497, undergoes classical memory formation. The inflationary T cell responses show kinetics, distribution, phenotype and functions similar to those seen in MCMV and are reproduced using alternative routes of administration. Memory inflation in this model is dependent on MHC Class II. As in MCMV, only the inflating epitope showed immunoproteasome-independence. These data define a new model for memory inflation, which is fully replication-independent, internally controlled and reproduces the key immunologic features of the CD8+ T cell response. This model provides insight into the mechanisms responsible for memory inflation, and since it is based on a vaccine vector, also is relevant to novel T cell-inducing vaccines in humans. PMID:23509359

Stress as a mnemonic filter: Interactions between medial temporal lobe encoding processes and post-encoding stress

PubMed Central

Ritchey, Maureen; McCullough, Andrew M.; Ranganath, Charan; Yonelinas, Andrew P.

2016-01-01

Acute stress has been shown to modulate memory for recently learned information, an effect attributed to the influence of stress hormones on medial temporal lobe (MTL) consolidation processes. However, little is known about which memories will be affected when stress follows encoding. One possibility is that stress interacts with encoding processes to selectively protect memories that had elicited responses in the hippocampus and amygdala, two MTL structures important for memory formation. There is limited evidence for interactions between encoding processes and consolidation effects in humans, but recent studies of consolidation in rodents have emphasized the importance of encoding “tags” for determining the impact of consolidation manipulations on memory. Here, we used fMRI in humans to test the hypothesis that the effects of post-encoding stress depend on MTL processes observed during encoding. We found that changes in stress hormone levels were associated with an increase in the contingency of memory outcomes on hippocampal and amygdala encoding responses. That is, for participants showing high cortisol reactivity, memories became more dependent on MTL activity observed during encoding, thereby shifting the distribution of recollected events toward those that had elicited relatively high activation. Surprisingly, this effect was generally larger for neutral, compared to emotionally negative, memories. The results suggest that stress does not uniformly enhance memory, but instead selectively preserves memories tagged during encoding, effectively acting as mnemonic filter. PMID:27774683

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Integrated-Circuit Pseudorandom-Number Generator

NASA Technical Reports Server (NTRS)

Steelman, James E.; Beasley, Jeff; Aragon, Michael; Ramirez, Francisco; Summers, Kenneth L.; Knoebel, Arthur

1992-01-01

Integrated circuit produces 8-bit pseudorandom numbers from specified probability distribution, at rate of 10 MHz. Use of Boolean logic, circuit implements pseudorandom-number-generating algorithm. Circuit includes eight 12-bit pseudorandom-number generators, outputs are uniformly distributed. 8-bit pseudorandom numbers satisfying specified nonuniform probability distribution are generated by processing uniformly distributed outputs of eight 12-bit pseudorandom-number generators through "pipeline" of D flip-flops, comparators, and memories implementing conditional probabilities on zeros and ones.

Substructure analysis using NICE/SPAR and applications of force to linear and nonlinear structures. [spacecraft masts

NASA Technical Reports Server (NTRS)

Razzaq, Zia; Prasad, Venkatesh; Darbhamulla, Siva Prasad; Bhati, Ravinder; Lin, Cai

1987-01-01

Parallel computing studies are presented for a variety of structural analysis problems. Included are the substructure planar analysis of rectangular panels with and without a hole, the static analysis of space mast, using NICE/SPAR and FORCE, and substructure analysis of plane rigid-jointed frames using FORCE. The computations are carried out on the Flex/32 MultiComputer using one to eighteen processors. The NICE/SPAR runstream samples are documented for the panel problem. For the substructure analysis of plane frames, a computer program is developed to demonstrate the effectiveness of a substructuring technique when FORCE is enforced. Ongoing research activities for an elasto-plastic stability analysis problem using FORCE, and stability analysis of the focus problem using NICE/SPAR are briefly summarized. Speedup curves for the panel, the mast, and the frame problems provide a basic understanding of the effectiveness of parallel computing procedures utilized or developed, within the domain of the parameters considered. Although the speedup curves obtained exhibit various levels of computational efficiency, they clearly demonstrate the excellent promise which parallel computing holds for the structural analysis problem. Source code is given for the elasto-plastic stability problem and the FORCE program.

Evaluating the application of research-based guidance to the design of an emergency preparedness leaflet.

PubMed

Hellier, E; Edworthy, J; Newbold, L; Titchener, K; Tucker, M; Gabe-Thomas, E

2014-09-01

Guidelines for the design of emergency communications were derived from primary research and interrogation of the literature. The guidelines were used to re-design a nuclear emergency preparedness leaflet routinely distributed to households in the local area. Pre-test measures of memory for, and self-reported understanding of, nuclear safety information were collected. The findings revealed high levels of non-receipt of the leaflet, and among those who did receive it, memory for safety advice was poor. Subjective evaluations of the trial leaflet suggested that it was preferred and judged easier to understand than the original. Objective measures of memory for the two leaflets were also recorded, once after the study period, and again one week or four weeks later. Memory for the advice was better, at all time periods, when participants studied the trial leaflet. The findings showcase evaluation of emergency preparedness literature and suggest that extant research findings can be applied to the design of communications to improve memory and understandability. Studies are described that showcase the use of research-based guidelines to design emergency communications and provide both subjective and objective data to support designing emergency communications in this way. In addition, the research evaluates the effectiveness of emergency preparedness leaflets that are routinely distributed to households. This work is of relevance to academics interested in risk communication and to practitioners involved in civil protection and emergency preparedness. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Surface Engineering of ITO Substrates to Improve the Memory Performance of an Asymmetric Conjugated Molecule with a Side Chain.

PubMed

Hou, Xiang; Cheng, Xue-Feng; Xiao, Xin; He, Jing-Hui; Xu, Qing-Feng; Li, Hua; Li, Na-Jun; Chen, Dong-Yun; Lu, Jian-Mei

2017-09-05

Organic multilevel random resistive access memory (RRAM) devices with an electrode/organic layer/electrode sandwich-like structure suffer from poor reproducibility, such as low effective ternary device yields and a wide threshold voltage distribution, and improvements through organic material renovation are rather limited. In contrast, engineering of the electrode surfaces rather than molecule design has been demonstrated to boost the performance of organic electronics effectively. Herein, we introduce surface engineering into organic multilevel RRAMs to enhance their ternary memory performance. A new asymmetric conjugated molecule composed of phenothiazine and malononitrile with a side chain (PTZ-PTZO-CN) was fabricated in an indium tin oxide (ITO)/PTZ-PTZO-CN/Al sandwich-like memory device. Modification of the ITO substrate with a phosphonic acid (PA) prior to device fabrication increased the ternary device yield (the ratio of effective ternary device) and narrowed the threshold voltage distribution. The crystallinity analysis revealed that PTZ-PTZO-CN grown on untreated ITO crystallized into two phases. After the surface engineering of ITO, this crystalline ambiguity was eliminated and a sole crystal phase was obtained that was the same as in the powder state. The unified crystal structure and improved grain mosaicity resulted in a lower threshold voltage and, therefore, a higher ternary device yield. Our result demonstrated that PA modification also improved the memory performance of an asymmetric conjugated molecule with a side chain. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

The art of war: beyond memory-one strategies in population games.

PubMed

Lee, Christopher; Harper, Marc; Fryer, Dashiell

2015-01-01

We show that the history of play in a population game contains exploitable information that can be successfully used by sophisticated strategies to defeat memory-one opponents, including zero determinant strategies. The history allows a player to label opponents by their strategies, enabling a player to determine the population distribution and to act differentially based on the opponent's strategy in each pairwise interaction. For the Prisoner's Dilemma, these advantages lead to the natural formation of cooperative coalitions among similarly behaving players and eventually to unilateral defection against opposing player types. We show analytically and empirically that optimal play in population games depends strongly on the population distribution. For example, the optimal strategy for a minority player type against a resident TFT population is ALLC, while for a majority player type the optimal strategy versus TFT players is ALLD. Such behaviors are not accessible to memory-one strategies. Drawing inspiration from Sun Tzu's the Art of War, we implemented a non-memory-one strategy for population games based on techniques from machine learning and statistical inference that can exploit the history of play in this manner. Via simulation we find that this strategy is essentially uninvadable and can successfully invade (significantly more likely than a neutral mutant) essentially all known memory-one strategies for the Prisoner's Dilemma, including ALLC (always cooperate), ALLD (always defect), tit-for-tat (TFT), win-stay-lose-shift (WSLS), and zero determinant (ZD) strategies, including extortionate and generous strategies.

Paying attention to working memory: Similarities in the spatial distribution of attention in mental and physical space.

PubMed

Sahan, Muhammet Ikbal; Verguts, Tom; Boehler, Carsten Nicolas; Pourtois, Gilles; Fias, Wim

2016-08-01

Selective attention is not limited to information that is physically present in the external world, but can also operate on mental representations in the internal world. However, it is not known whether the mechanisms of attentional selection operate in similar fashions in physical and mental space. We studied the spatial distributions of attention for items in physical and mental space by comparing how successfully distractors were rejected at varying distances from the attended location. The results indicated very similar distribution characteristics of spatial attention in physical and mental space. Specifically, we found that performance monotonically improved with increasing distractor distance relative to the attended location, suggesting that distractor confusability is particularly pronounced for nearby distractors, relative to distractors farther away. The present findings suggest that mental representations preserve their spatial configuration in working memory, and that similar mechanistic principles underlie selective attention in physical and in mental space.

Bringing memory fMRI to the clinic: comparison of seven memory fMRI protocols in temporal lobe epilepsy.

PubMed

Towgood, Karren; Barker, Gareth J; Caceres, Alejandro; Crum, William R; Elwes, Robert D C; Costafreda, Sergi G; Mehta, Mitul A; Morris, Robin G; von Oertzen, Tim J; Richardson, Mark P

2015-04-01

fMRI is increasingly implemented in the clinic to assess memory function. There are multiple approaches to memory fMRI, but limited data on advantages and reliability of different methods. Here, we compared effect size, activation lateralisation, and between-sessions reliability of seven memory fMRI protocols: Hometown Walking (block design), Scene encoding (block design and event-related design), Picture encoding (block and event-related), and Word encoding (block and event-related). All protocols were performed on three occasions in 16 patients with temporal lobe epilepsy (TLE). Group T-maps showed activity bilaterally in medial temporal lobe for all protocols. Using ANOVA, there was an interaction between hemisphere and seizure-onset lateralisation (P = 0.009) and between hemisphere, protocol and seizure-onset lateralisation (P = 0.002), showing that the distribution of memory-related activity between left and right temporal lobes differed between protocols and between patients with left-onset and right-onset seizures. Using voxelwise intraclass Correlation Coefficient, between-sessions reliability was best for Hometown and Scenes (block and event). The between-sessions spatial overlap of activated voxels was also greatest for Hometown and Scenes. Lateralisation of activity between hemispheres was most reliable for Scenes (block and event) and Words (event). Using receiver operating characteristic analysis to explore the ability of each fMRI protocol to classify patients as left-onset or right-onset TLE, only the Words (event) protocol achieved a significantly above-chance classification of patients at all three sessions. We conclude that Words (event) protocol shows the best combination of between-sessions reliability of the distribution of activity between hemispheres and reliable ability to distinguish between left-onset and right-onset patients. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Phenotypes and distribution of mucosal memory B-cell populations in the SIV/SHIV Rhesus macaque model

PubMed Central

Demberg, Thorsten; Mohanram, Venkatramanan; Venzon, David; Robert-Guroff, Marjorie

2014-01-01

As vaccine-elicited antibodies have now been associated with HIV protective efficacy, a thorough understanding of mucosal and systemic B-cell development and maturation is needed. We phenotyped mucosal memory B-cells, investigated isotype expression and homing patterns, and defined plasmablasts and plasma cells at three mucosal sites (duodenum, jejunum and rectum) in rhesus macaques, the commonly used animal model for pre-clinical vaccine studies. Unlike humans, macaque mucosal memory B-cells lacked CD27 expression; only two sub-populations were present: naïve (CD21+CD27−) and tissue-like (CD21−CD27−) memory. Similar to humans, IgA was the dominant isotype expressed. The homing markers CXCR4, CCR6, CCR9 and α4β7 were differentially expressed between naïve and tissue-like memory B-cells. Mucosal plasmablasts were identified as CD19+CD20+/−HLA-DR+Ki-67+IRF4+CD138+/− and mucosal plasma cells as CD19+CD20−HLA-DR−Ki-67−IRF4+CD138+. Both populations were CD39+/−CD27−. Plasma cell phenotype was confirmed by spontaneous IgA secretion by ELISpot of positively-selected cells and J-chain expression by real-time PCR. Duodenal, jejunal and rectal samples were similar in B-cell memory phenotype, isotype expression, homing receptors and plasmablast/plasma cell distribution among the three tissues. Thus rectal biopsies adequately monitor B-cell dynamics in the gut mucosa, and provide a critical view of mucosal B-cell events associated with development of vaccine-elicited protective immune responses and SIV/SHIV pathogenesis and disease control. PMID:24814239

Does prediction error drive one-shot declarative learning?

PubMed

Greve, Andrea; Cooper, Elisa; Kaula, Alexander; Anderson, Michael C; Henson, Richard

2017-06-01

The role of prediction error (PE) in driving learning is well-established in fields such as classical and instrumental conditioning, reward learning and procedural memory; however, its role in human one-shot declarative encoding is less clear. According to one recent hypothesis, PE reflects the divergence between two probability distributions: one reflecting the prior probability (from previous experiences) and the other reflecting the sensory evidence (from the current experience). Assuming unimodal probability distributions, PE can be manipulated in three ways: (1) the distance between the mode of the prior and evidence, (2) the precision of the prior, and (3) the precision of the evidence. We tested these three manipulations across five experiments, in terms of peoples' ability to encode a single presentation of a scene-item pairing as a function of previous exposures to that scene and/or item. Memory was probed by presenting the scene together with three choices for the previously paired item, in which the two foil items were from other pairings within the same condition as the target item. In Experiment 1, we manipulated the evidence to be either consistent or inconsistent with prior expectations, predicting PE to be larger, and hence memory better, when the new pairing was inconsistent. In Experiments 2a-c, we manipulated the precision of the priors, predicting better memory for a new pairing when the (inconsistent) priors were more precise. In Experiment 3, we manipulated both visual noise and prior exposure for unfamiliar faces, before pairing them with scenes, predicting better memory when the sensory evidence was more precise. In all experiments, the PE hypotheses were supported. We discuss alternative explanations of individual experiments, and conclude the Predictive Interactive Multiple Memory Signals (PIMMS) framework provides the most parsimonious account of the full pattern of results.

Simulating Non-Fickian Transport across Péclet Regimes by doing Lévy Flights in the Rank Space of Velocity

NASA Astrophysics Data System (ADS)

Most, S.; Dentz, M.; Bolster, D.; Bijeljic, B.; Nowak, W.

2017-12-01

Transport in real porous media shows non-Fickian characteristics. In the Lagrangian perspective this leads to skewed distributions of particle arrival times. The skewness is triggered by particles' memory of velocity that persists over a characteristic length. Capturing process memory is essential to represent non-Fickianity thoroughly. Classical non-Fickian models (e.g., CTRW models) simulate the effects of memory but not the mechanisms leading to process memory. CTRWs have been applied successfully in many studies but nonetheless they have drawbacks. In classical CTRWs each particle makes a spatial transition for which each particle adapts a random transit time. Consecutive transit times are drawn independently from each other, and this is only valid for sufficiently large spatial transitions. If we want to apply a finer numerical resolution than that, we have to implement memory into the simulation. Recent CTRW methods use transitions matrices to simulate correlated transit times. However, deriving such transition matrices require transport data of a fine-scale transport simulation, and the obtained transition matrix is solely valid for this single Péclet regime. The CTRW method we propose overcomes all three drawbacks: 1) We simulate transport without restrictions in transition length. 2) We parameterize our CTRW without requiring a transport simulation. 3) Our parameterization scales across Péclet regimes. We do so by sampling the pore-scale velocity distribution to generate correlated transit times as a Lévy flight on the CDF-axis of velocities with reflection at 0 and 1. The Lévy flight is parametrized only by the correlation length. We explicitly model memory including the evolution and decay of non-Fickianity, so it extends from local via pre-asymptotic to asymptotic scales.

Synaptic tagging, evaluation of memories, and the distal reward problem.

PubMed

Päpper, Marc; Kempter, Richard; Leibold, Christian

2011-01-01

Long-term synaptic plasticity exhibits distinct phases. The synaptic tagging hypothesis suggests an early phase in which synapses are prepared, or "tagged," for protein capture, and a late phase in which those proteins are integrated into the synapses to achieve memory consolidation. The synapse specificity of the tags is consistent with conventional neural network models of associative memory. Memory consolidation through protein synthesis, however, is neuron specific, and its functional role in those models has not been assessed. Here, using a theoretical network model, we test the tagging hypothesis on its potential to prolong memory lifetimes in an online-learning paradigm. We find that protein synthesis, though not synapse specific, prolongs memory lifetimes if it is used to evaluate memory items on a cellular level. In our model we assume that only "important" memory items evoke protein synthesis such that these become more stable than "unimportant" items, which do not evoke protein synthesis. The network model comprises an equilibrium distribution of synaptic states that is very susceptible to the storage of new items: Most synapses are in a state in which they are plastic and can be changed easily, whereas only those synapses that are essential for the retrieval of the important memory items are in the stable late phase. The model can solve the distal reward problem, where the initial exposure of a memory item and its evaluation are temporally separated. Synaptic tagging hence provides a viable mechanism to consolidate and evaluate memories on a synaptic basis.

Hippocampal Administration of Levothyroxine Impairs Contextual Fear Memory Consolidation in Rats.

PubMed

Yu, Dafu; Zhou, Heng; Zou, Lin; Jiang, Yong; Wu, Xiaoqun; Jiang, Lizhu; Zhou, Qixin; Yang, Yuexiong; Xu, Lin; Mao, Rongrong

2017-01-01

Thyroid hormone (TH) receptors are highly distributed in the hippocampus, which plays a vital role in memory processes. However, how THs are involved in the different stages of memory process is little known. Herein, we used hippocampus dependent contextual fear conditioning to address the effects of hippocampal THs on the different stages of fear memory. First, we found that a single systemic levothyroxine (LT 4 ) administration increased the level of free triiodothyronine (FT 3 ) and free tetraiodothyroxine (FT 4 ) not only in serum but also in hippocampus. In addition, a single systemic LT 4 administration immediately after fear conditioning significantly impaired fear memory. These results indicated the important role of hippocampal THs in fear memory process. To further confirm the effects of hippocampal THs on the different stages of fear memory, LT 4 (0.4 μg/μl, 1 μl/side) was injected bilaterally into hippocampus. Rats given LT 4 into hippocampus before training or tests had no effect on the acquisition or retrieval of fear memory, however rats given LT 4 into hippocampus either immediately or 2 h after training showed being significantly impaired fear memory, which demonstrated LT 4 administration into hippocampus impairs the consolidation but has no effect on the acquisition and retrieval of fear memory. Furthermore, hippocampal injection of LT 4 did not affect rats' locomotor activity, thigmotaxis and THs level in prefrontal cortex (PFC) and serum. These findings may have important implications for understanding mechanisms underlying contribution of THs to memory disorders.

[Neuroscience and collective memory: memory schemas linking brain, societies and cultures].

PubMed

Legrand, Nicolas; Gagnepain, Pierre; Peschanski, Denis; Eustache, Francis

2015-01-01

During the last two decades, the effect of intersubjective relationships on cognition has been an emerging topic in cognitive neurosciences leading through a so-called "social turn" to the formation of new domains integrating society and cultures to this research area. Such inquiry has been recently extended to collective memory studies. Collective memory refers to shared representations that are constitutive of the identity of a group and distributed among all its members connected by a common history. After briefly describing those evolutions in the study of human brain and behaviors, we review recent researches that have brought together cognitive psychology, neuroscience and social sciences into collective memory studies. Using the reemerging concept of memory schema, we propose a theoretical framework allowing to account for collective memories formation with a specific focus on the encoding process of historical events. We suggest that (1) if the concept of schema has been mainly used to describe rather passive framework of knowledge, such structure may also be implied in more active fashions in the understanding of significant collective events. And, (2) if some schema researches have restricted themselves to the individual level of inquiry, we describe a strong coherence between memory and cultural frameworks. Integrating the neural basis and properties of memory schema to collective memory studies may pave the way toward a better understanding of the reciprocal interaction between individual memories and cultural resources such as media or education. © Société de Biologie, 2016.

Hippocampal Administration of Levothyroxine Impairs Contextual Fear Memory Consolidation in Rats

PubMed Central

Yu, Dafu; Zhou, Heng; Zou, Lin; Jiang, Yong; Wu, Xiaoqun; Jiang, Lizhu; Zhou, Qixin; Yang, Yuexiong; Xu, Lin; Mao, Rongrong

2017-01-01

Thyroid hormone (TH) receptors are highly distributed in the hippocampus, which plays a vital role in memory processes. However, how THs are involved in the different stages of memory process is little known. Herein, we used hippocampus dependent contextual fear conditioning to address the effects of hippocampal THs on the different stages of fear memory. First, we found that a single systemic levothyroxine (LT4) administration increased the level of free triiodothyronine (FT3) and free tetraiodothyroxine (FT4) not only in serum but also in hippocampus. In addition, a single systemic LT4 administration immediately after fear conditioning significantly impaired fear memory. These results indicated the important role of hippocampal THs in fear memory process. To further confirm the effects of hippocampal THs on the different stages of fear memory, LT4 (0.4 μg/μl, 1 μl/side) was injected bilaterally into hippocampus. Rats given LT4 into hippocampus before training or tests had no effect on the acquisition or retrieval of fear memory, however rats given LT4 into hippocampus either immediately or 2 h after training showed being significantly impaired fear memory, which demonstrated LT4 administration into hippocampus impairs the consolidation but has no effect on the acquisition and retrieval of fear memory. Furthermore, hippocampal injection of LT4 did not affect rats’ locomotor activity, thigmotaxis and THs level in prefrontal cortex (PFC) and serum. These findings may have important implications for understanding mechanisms underlying contribution of THs to memory disorders. PMID:28824379

Distributed Patterns of Brain Activity that Lead to Forgetting

PubMed Central

Öztekin, Ilke; Badre, David

2011-01-01

Proactive interference (PI), in which irrelevant information from prior learning disrupts memory performance, is widely viewed as a major cause of forgetting. However, the hypothesized spontaneous recovery (i.e., automatic retrieval) of interfering information presumed to be at the base of PI remains to be demonstrated directly. Moreover, it remains unclear at what point during learning and/or retrieval interference impacts memory performance. In order to resolve these open questions, we employed a machine-learning algorithm to identify distributed patterns of brain activity associated with retrieval of interfering information that engenders PI and causes forgetting. Participants were scanned using functional magnetic resonance imaging during an item recognition task. We induced PI by constructing sets of three consecutive study lists from the same semantic category. The classifier quantified the magnitude of category-related activity at encoding and retrieval. Category-specific activity during retrieval increased across lists, consistent with the category information becoming increasingly available and producing interference. Critically, this increase was correlated with individual differences in forgetting and the deployment of frontal lobe mechanisms that resolve interference. Collectively, these findings suggest that distributed patterns of brain activity pertaining to the interfering information during retrieval contribute to forgetting. The prefrontal cortex mediates the relationship between the spontaneous recovery of interfering information at retrieval and individual differences in memory performance. PMID:21897814

System for Measuring Conditional Amplitude, Phase, or Time Distributions of Pulsating Phenomena

PubMed Central

Van Brunt, Richard J.; Cernyar, Eric W.

1992-01-01

A detailed description is given of an electronic stochastic analyzer for use with direct “real-time” measurements of the conditional distributions needed for a complete stochastic characterization of pulsating phenomena that can be represented as random point processes. The measurement system described here is designed to reveal and quantify effects of pulse-to-pulse or phase-to-phase memory propagation. The unraveling of memory effects is required so that the physical basis for observed statistical properties of pulsating phenomena can be understood. The individual unique circuit components that comprise the system and the combinations of these components for various measurements, are thoroughly documented. The system has been applied to the measurement of pulsating partial discharges generated by applying alternating or constant voltage to a discharge gap. Examples are shown of data obtained for conditional and unconditional amplitude, time interval, and phase-of-occurrence distributions of partial-discharge pulses. The results unequivocally show the existence of significant memory effects as indicated, for example, by the observations that the most probable amplitudes and phases-of-occurrence of discharge pulses depend on the amplitudes and/or phases of the preceding pulses. Sources of error and fundamental limitations of the present measurement approach are analyzed. Possible extensions of the method are also discussed. PMID:28053450

A Distributed-Memory Package for Dense Hierarchically Semi-Separable Matrix Computations Using Randomization

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

Rouet, François-Henry; Li, Xiaoye S.; Ghysels, Pieter

In this paper, we present a distributed-memory library for computations with dense structured matrices. A matrix is considered structured if its off-diagonal blocks can be approximated by a rank-deficient matrix with low numerical rank. Here, we use Hierarchically Semi-Separable (HSS) representations. Such matrices appear in many applications, for example, finite-element methods, boundary element methods, and so on. Exploiting this structure allows for fast solution of linear systems and/or fast computation of matrix-vector products, which are the two main building blocks of matrix computations. The compression algorithm that we use, that computes the HSS form of an input dense matrix, reliesmore » on randomized sampling with a novel adaptive sampling mechanism. We discuss the parallelization of this algorithm and also present the parallelization of structured matrix-vector product, structured factorization, and solution routines. The efficiency of the approach is demonstrated on large problems from different academic and industrial applications, on up to 8,000 cores. Finally, this work is part of a more global effort, the STRUctured Matrices PACKage (STRUMPACK) software package for computations with sparse and dense structured matrices. Hence, although useful on their own right, the routines also represent a step in the direction of a distributed-memory sparse solver.« less

A Distributed-Memory Package for Dense Hierarchically Semi-Separable Matrix Computations Using Randomization

DOE PAGES

Rouet, François-Henry; Li, Xiaoye S.; Ghysels, Pieter; ...

2016-06-30

In this paper, we present a distributed-memory library for computations with dense structured matrices. A matrix is considered structured if its off-diagonal blocks can be approximated by a rank-deficient matrix with low numerical rank. Here, we use Hierarchically Semi-Separable (HSS) representations. Such matrices appear in many applications, for example, finite-element methods, boundary element methods, and so on. Exploiting this structure allows for fast solution of linear systems and/or fast computation of matrix-vector products, which are the two main building blocks of matrix computations. The compression algorithm that we use, that computes the HSS form of an input dense matrix, reliesmore » on randomized sampling with a novel adaptive sampling mechanism. We discuss the parallelization of this algorithm and also present the parallelization of structured matrix-vector product, structured factorization, and solution routines. The efficiency of the approach is demonstrated on large problems from different academic and industrial applications, on up to 8,000 cores. Finally, this work is part of a more global effort, the STRUctured Matrices PACKage (STRUMPACK) software package for computations with sparse and dense structured matrices. Hence, although useful on their own right, the routines also represent a step in the direction of a distributed-memory sparse solver.« less

Multiprocessor shared-memory information exchange

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

Santoline, L.L.; Bowers, M.D.; Crew, A.W.

1989-02-01

In distributed microprocessor-based instrumentation and control systems, the inter-and intra-subsystem communication requirements ultimately form the basis for the overall system architecture. This paper describes a software protocol which addresses the intra-subsystem communications problem. Specifically the protocol allows for multiple processors to exchange information via a shared-memory interface. The authors primary goal is to provide a reliable means for information to be exchanged between central application processor boards (masters) and dedicated function processor boards (slaves) in a single computer chassis. The resultant Multiprocessor Shared-Memory Information Exchange (MSMIE) protocol, a standard master-slave shared-memory interface suitable for use in nuclear safety systems, ismore » designed to pass unidirectional buffers of information between the processors while providing a minimum, deterministic cycle time for this data exchange.« less

Aging selectively impairs recollection in recognition memory for pictures: Evidence from modeling and ROC curves

PubMed Central

Howard, Marc W.; Bessette-Symons, Brandy; Zhang, Yaofei; Hoyer, William J.

2006-01-01

Younger and older adults were tested on recognition memory for pictures. The Yonelinas high threshold (YHT) model, a formal implementation of two-process theory, fit the response distribution data of both younger and older adults significantly better than a normal unequal variance signal detection model. Consistent with this finding, non-linear zROC curves were obtained for both groups. Estimates of recollection from the YHT model were significantly higher for younger than older adults. This deficit was not a consequence of a general decline in memory; older adults showed comparable overall accuracy and in fact a non-significant increase in their familiarity scores. Implications of these results for theories of recognition memory and the mnemonic deficit associated with aging are discussed. PMID:16594795

Enabling the High Level Synthesis of Data Analytics Accelerators

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

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

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

Quantum Electronic Solids

DTIC Science & Technology

2012-03-07

signal processing with smaller sizes and unique properties Nanoelectronics: NTs, graphene, diamond, SiC for sensing, logic & memory storage 3...synthesized i-n graphene heterojunctions 19 DISTRIBUTION A: Approved for public release; distribution is unlimited. Electrical Properties of...boundaries in polycrystalline samples Polycrystalline graphene can have similar (as much as 90%) electrical properties (conductance and mobility

Implicit Learning of Complex Visual Contexts Under Non-Optimal Conditions

DTIC Science & Technology

2007-07-27

Perception & Performance, 31(6), 1439-1448. 3. Jiang Y, Song J-H, Rigas A (2005). High-capacity spatial contextual memory. Psychonomic Bulletin & Review , 12...Makovski T., & Jiang YV (in press). Distributing versus focusing attention in visual short-term memory. Psychonomic Bulletin & Review . 8. Rausei V...Implicit learning of ignored visual context. Psychonomic Bulletin & Review , 12(1), 100-106. Jiang, Y. H., & Song, J. H. (2005). Spatial context

Coherent-state information concentration and purification in atomic memory

NASA Astrophysics Data System (ADS)

Herec, Jiří; Filip, Radim

2006-12-01

We propose a feasible method of coherent-state information concentration and purification utilizing quantum memory. The method allows us to optimally concentrate and purify information carried by many noisy copies of an unknown coherent state (randomly distributed in time) to a single copy. Thus nonclassical resources and operations can be saved, if we compare information processing with many noisy copies and a single copy with concentrated and purified information.

The Representation of Knowledge in Image Understanding.

DTIC Science & Technology

1985-03-01

for memory traces? It’s been quite a few years since Lashley wrote his famous paper "Search for the Engram ." That paper pinpointed the fundamental...34 engram hunters," mostly empirical neurobiologists guided by their own often powerful working hypotheses, ensued and has continued that search with...progress. What is an Engram ? (Some Informal Considerations) Memory, viewed as traces of experience, is necessarily massively . distributed. As an example

Twin Neurons for Efficient Real-World Data Distribution in Networks of Neural Cliques: Applications in Power Management in Electronic Circuits.

PubMed

Boguslawski, Bartosz; Gripon, Vincent; Seguin, Fabrice; Heitzmann, Frédéric

2016-02-01

Associative memories are data structures that allow retrieval of previously stored messages given part of their content. They, thus, behave similarly to the human brain's memory that is capable, for instance, of retrieving the end of a song, given its beginning. Among different families of associative memories, sparse ones are known to provide the best efficiency (ratio of the number of bits stored to that of the bits used). Recently, a new family of sparse associative memories achieving almost optimal efficiency has been proposed. Their structure, relying on binary connections and neurons, induces a direct mapping between input messages and stored patterns. Nevertheless, it is well known that nonuniformity of the stored messages can lead to a dramatic decrease in performance. In this paper, we show the impact of nonuniformity on the performance of this recent model, and we exploit the structure of the model to improve its performance in practical applications, where data are not necessarily uniform. In order to approach the performance of networks with uniformly distributed messages presented in theoretical studies, twin neurons are introduced. To assess the adapted model, twin neurons are used with the real-world data to optimize power consumption of electronic circuits in practical test cases.

Quantum teleportation between remote atomic-ensemble quantum memories

PubMed Central

Bao, Xiao-Hui; Xu, Xiao-Fan; Li, Che-Ming; Yuan, Zhen-Sheng; Lu, Chao-Yang; Pan, Jian-Wei

2012-01-01

Quantum teleportation and quantum memory are two crucial elements for large-scale quantum networks. With the help of prior distributed entanglement as a “quantum channel,” quantum teleportation provides an intriguing means to faithfully transfer quantum states among distant locations without actual transmission of the physical carriers [Bennett CH, et al. (1993) Phys Rev Lett 70(13):1895–1899]. Quantum memory enables controlled storage and retrieval of fast-flying photonic quantum bits with stationary matter systems, which is essential to achieve the scalability required for large-scale quantum networks. Combining these two capabilities, here we realize quantum teleportation between two remote atomic-ensemble quantum memory nodes, each composed of ∼108 rubidium atoms and connected by a 150-m optical fiber. The spin wave state of one atomic ensemble is mapped to a propagating photon and subjected to Bell state measurements with another single photon that is entangled with the spin wave state of the other ensemble. Two-photon detection events herald the success of teleportation with an average fidelity of 88(7)%. Besides its fundamental interest as a teleportation between two remote macroscopic objects, our technique may be useful for quantum information transfer between different nodes in quantum networks and distributed quantum computing. PMID:23144222

Technical support for digital systems technology development. Task order 1: ISP contention analysis and control

NASA Technical Reports Server (NTRS)

Stehle, Roy H.; Ogier, Richard G.

1993-01-01

Alternatives for realizing a packet-based network switch for use on a frequency division multiple access/time division multiplexed (FDMA/TDM) geostationary communication satellite were investigated. Each of the eight downlink beams supports eight directed dwells. The design needed to accommodate multicast packets with very low probability of loss due to contention. Three switch architectures were designed and analyzed. An output-queued, shared bus system yielded a functionally simple system, utilizing a first-in, first-out (FIFO) memory per downlink dwell, but at the expense of a large total memory requirement. A shared memory architecture offered the most efficiency in memory requirements, requiring about half the memory of the shared bus design. The processing requirement for the shared-memory system adds system complexity that may offset the benefits of the smaller memory. An alternative design using a shared memory buffer per downlink beam decreases circuit complexity through a distributed design, and requires at most 1000 packets of memory more than the completely shared memory design. Modifications to the basic packet switch designs were proposed to accommodate circuit-switched traffic, which must be served on a periodic basis with minimal delay. Methods for dynamically controlling the downlink dwell lengths were developed and analyzed. These methods adapt quickly to changing traffic demands, and do not add significant complexity or cost to the satellite and ground station designs. Methods for reducing the memory requirement by not requiring the satellite to store full packets were also proposed and analyzed. In addition, optimal packet and dwell lengths were computed as functions of memory size for the three switch architectures.

The aftermath of memory retrieval for recycling visual working memory representations.

PubMed

Park, Hyung-Bum; Zhang, Weiwei; Hyun, Joo-Seok

2017-07-01

We examined the aftermath of accessing and retrieving a subset of information stored in visual working memory (VWM)-namely, whether detection of a mismatch between memory and perception can impair the original memory of an item while triggering recognition-induced forgetting for the remaining, untested items. For this purpose, we devised a consecutive-change detection task wherein two successive testing probes were displayed after a single set of memory items. Across two experiments utilizing different memory-testing methods (whole vs. single probe), we observed a reliable pattern of poor performance in change detection for the second test when the first test had exhibited a color change. The impairment after a color change was evident even when the same memory item was repeatedly probed; this suggests that an attention-driven, salient visual change made it difficult to reinstate the previously remembered item. The second change detection, for memory items untested during the first change detection, was also found to be inaccurate, indicating that recognition-induced forgetting had occurred for the unprobed items in VWM. In a third experiment, we conducted a task that involved change detection plus continuous recall, wherein a memory recall task was presented after the change detection task. The analyses of the distributions of recall errors with a probabilistic mixture model revealed that the memory impairments from both visual changes and recognition-induced forgetting are explained better by the stochastic loss of memory items than by their degraded resolution. These results indicate that attention-driven visual change and recognition-induced forgetting jointly influence the "recycling" of VWM representations.

Fast associative memory + slow neural circuitry = the computational model of the brain.

NASA Astrophysics Data System (ADS)

Berkovich, Simon; Berkovich, Efraim; Lapir, Gennady

1997-08-01

We propose a computational model of the brain based on a fast associative memory and relatively slow neural processors. In this model, processing time is expensive but memory access is not, and therefore most algorithmic tasks would be accomplished by using large look-up tables as opposed to calculating. The essential feature of an associative memory in this context (characteristic for a holographic type memory) is that it works without an explicit mechanism for resolution of multiple responses. As a result, the slow neuronal processing elements, overwhelmed by the flow of information, operate as a set of templates for ranking of the retrieved information. This structure addresses the primary controversy in the brain architecture: distributed organization of memory vs. localization of processing centers. This computational model offers an intriguing explanation of many of the paradoxical features in the brain architecture, such as integration of sensors (through DMA mechanism), subliminal perception, universality of software, interrupts, fault-tolerance, certain bizarre possibilities for rapid arithmetics etc. In conventional computer science the presented type of a computational model did not attract attention as it goes against the technological grain by using a working memory faster than processing elements.

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

The frontal eye fields limit the capacity of visual short-term memory in rhesus monkeys.

PubMed

Lee, Kyoung-Min; Ahn, Kyung-Ha

2013-01-01

The frontal eye fields (FEF) in rhesus monkeys have been implicated in visual short-term memory (VSTM) as well as control of visual attention. Here we examined the importance of the area in the VSTM capacity and the relationship between VSTM and attention, using the chemical inactivation technique and multi-target saccade tasks with or without the need of target-location memory. During FEF inactivation, serial saccades to targets defined by color contrast were unaffected, but saccades relying on short-term memory were impaired when the target count was at the capacity limit of VSTM. The memory impairment was specific to the FEF-coded retinotopic locations, and subject to competition among targets distributed across visual fields. These results together suggest that the FEF plays a crucial role during the entry of information into VSTM, by enabling attention deployment on targets to be remembered. In this view, the memory capacity results from the limited availability of attentional resources provided by FEF: The FEF can concurrently maintain only a limited number of activations to register the targets into memory. When lesions render part of the area unavailable for activation, the number would decrease, further reducing the capacity of VSTM.

Unconditional polarization qubit quantum memory at room temperature

NASA Astrophysics Data System (ADS)

Namazi, Mehdi; Kupchak, Connor; Jordaan, Bertus; Shahrokhshahi, Reihaneh; Figueroa, Eden

2016-05-01

The creation of global quantum key distribution and quantum communication networks requires multiple operational quantum memories. Achieving a considerable reduction in experimental and cost overhead in these implementations is thus a major challenge. Here we present a polarization qubit quantum memory fully-operational at 330K, an unheard frontier in the development of useful qubit quantum technology. This result is achieved through extensive study of how optical response of cold atomic medium is transformed by the motion of atoms at room temperature leading to an optimal characterization of room temperature quantum light-matter interfaces. Our quantum memory shows an average fidelity of 86.6 +/- 0.6% for optical pulses containing on average 1 photon per pulse, thereby defeating any classical strategy exploiting the non-unitary character of the memory efficiency. Our system significantly decreases the technological overhead required to achieve quantum memory operation and will serve as a building block for scalable and technologically simpler many-memory quantum machines. The work was supported by the US-Navy Office of Naval Research, Grant Number N00141410801 and the Simons Foundation, Grant Number SBF241180. B. J. acknowledges financial assistance of the National Research Foundation (NRF) of South Africa.

The Focus of Spatial Attention Determines the Number and Precision of Face Representations in Working Memory.

PubMed

Towler, John; Kelly, Maria; Eimer, Martin

2016-06-01

The capacity of visual working memory for faces is extremely limited, but the reasons for these limitations remain unknown. We employed event-related brain potential measures to demonstrate that individual faces have to be focally attended in order to be maintained in working memory, and that attention is allocated to only a single face at a time. When 2 faces have to be memorized simultaneously in a face identity-matching task, the focus of spatial attention during encoding predicts which of these faces can be successfully maintained in working memory and matched to a subsequent test face. We also show that memory representations of attended faces are maintained in a position-dependent fashion. These findings demonstrate that the limited capacity of face memory is directly linked to capacity limits of spatial attention during the encoding and maintenance of individual face representations. We suggest that the capacity and distribution of selective spatial attention is a dynamic resource that constrains the capacity and fidelity of working memory for faces. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Age-related impairment of visual recognition memory correlates with impaired synaptic distribution of GluA2 and protein kinase Mζ in the dentate gyrus.

PubMed

Aicardi, Giorgio

2012-10-01

Age-related functional alterations in the perforant path projection from the entorhinal cortex to the dentate gyrus (DG) of the hippocampus play a major role in age-related memory impairments, but little is known about the molecular mechanisms responsible for these changes. In a recent study, young and aged monkeys were tested on the visual recognition memory test "delayed nonmatching-to-sample"; then, electron microscopic immunocytochemistry was performed in the hippocampal DG to determine the subcellular localization of the GluA2 subunit of the glutamate α-amino-3-hydroxy-5-methyl-4- isoxazole-propionic acid receptor (AMPAR) and protein kinase Mζ (PKMζ), which promotes memory storage by regulating GluA2-containing AMPAR trafficking. The results obtained suggest that age-related deficits in visual recognition memory are coupled with impairment in PKMζ-dependent maintenance of GluA2 at the synapse. Together with previous evidences of the critical role of PKMζ in memory consolidation, these data render this enzyme an attractive potential therapeutic target for treating age-related memory decline, and support the view that the pharmacological manipulation of AMPAR trafficking in the synapses may provide new insights in the search of memory enhancers for aged individuals, including those affected by Alzheimer disease.

An Ideal Observer Analysis of Visual Working Memory

PubMed Central

Sims, Chris R.; Jacobs, Robert A.; Knill, David C.

2013-01-01

Limits in visual working memory (VWM) strongly constrain human performance across many tasks. However, the nature of these limits is not well understood. In this paper we develop an ideal observer analysis of human visual working memory, by deriving the expected behavior of an optimally performing, but limited-capacity memory system. This analysis is framed around rate–distortion theory, a branch of information theory that provides optimal bounds on the accuracy of information transmission subject to a fixed information capacity. The result of the ideal observer analysis is a theoretical framework that provides a task-independent and quantitative definition of visual memory capacity and yields novel predictions regarding human performance. These predictions are subsequently evaluated and confirmed in two empirical studies. Further, the framework is general enough to allow the specification and testing of alternative models of visual memory (for example, how capacity is distributed across multiple items). We demonstrate that a simple model developed on the basis of the ideal observer analysis—one which allows variability in the number of stored memory representations, but does not assume the presence of a fixed item limit—provides an excellent account of the empirical data, and further offers a principled re-interpretation of existing models of visual working memory. PMID:22946744

Remembered or Forgotten?—An EEG-Based Computational Prediction Approach

PubMed Central

Sun, Xuyun; Qian, Cunle; Chen, Zhongqin; Wu, Zhaohui; Luo, Benyan; Pan, Gang

2016-01-01

Prediction of memory performance (remembered or forgotten) has various potential applications not only for knowledge learning but also for disease diagnosis. Recently, subsequent memory effects (SMEs)—the statistical differences in electroencephalography (EEG) signals before or during learning between subsequently remembered and forgotten events—have been found. This finding indicates that EEG signals convey the information relevant to memory performance. In this paper, based on SMEs we propose a computational approach to predict memory performance of an event from EEG signals. We devise a convolutional neural network for EEG, called ConvEEGNN, to predict subsequently remembered and forgotten events from EEG recorded during memory process. With the ConvEEGNN, prediction of memory performance can be achieved by integrating two main stages: feature extraction and classification. To verify the proposed approach, we employ an auditory memory task to collect EEG signals from scalp electrodes. For ConvEEGNN, the average prediction accuracy was 72.07% by using EEG data from pre-stimulus and during-stimulus periods, outperforming other approaches. It was observed that signals from pre-stimulus period and those from during-stimulus period had comparable contributions to memory performance. Furthermore, the connection weights of ConvEEGNN network can reveal prominent channels, which are consistent with the distribution of SME studied previously. PMID:27973531

Automated quantitative muscle biopsy analysis system

NASA Technical Reports Server (NTRS)

Castleman, Kenneth R. (Inventor)

1980-01-01

An automated system to aid the diagnosis of neuromuscular diseases by producing fiber size histograms utilizing histochemically stained muscle biopsy tissue. Televised images of the microscopic fibers are processed electronically by a multi-microprocessor computer, which isolates, measures, and classifies the fibers and displays the fiber size distribution. The architecture of the multi-microprocessor computer, which is iterated to any required degree of complexity, features a series of individual microprocessors P.sub.n each receiving data from a shared memory M.sub.n-1 and outputing processed data to a separate shared memory M.sub.n+1 under control of a program stored in dedicated memory M.sub.n.

Parallel performance investigations of an unstructured mesh Navier-Stokes solver

NASA Technical Reports Server (NTRS)

Mavriplis, Dimitri J.

2000-01-01

A Reynolds-averaged Navier-Stokes solver based on unstructured mesh techniques for analysis of high-lift configurations is described. The method makes use of an agglomeration multigrid solver for convergence acceleration. Implicit line-smoothing is employed to relieve the stiffness associated with highly stretched meshes. A GMRES technique is also implemented to speed convergence at the expense of additional memory usage. The solver is cache efficient and fully vectorizable, and is parallelized using a two-level hybrid MPI-OpenMP implementation suitable for shared and/or distributed memory architectures, as well as clusters of shared memory machines. Convergence and scalability results are illustrated for various high-lift cases.

Likelihood ratio decisions in memory: three implied regularities.

PubMed

Glanzer, Murray; Hilford, Andrew; Maloney, Laurence T

2009-06-01

We analyze four general signal detection models for recognition memory that differ in their distributional assumptions. Our analyses show that a basic assumption of signal detection theory, the likelihood ratio decision axis, implies three regularities in recognition memory: (1) the mirror effect, (2) the variance effect, and (3) the z-ROC length effect. For each model, we present the equations that produce the three regularities and show, in computed examples, how they do so. We then show that the regularities appear in data from a range of recognition studies. The analyses and data in our study support the following generalization: Individuals make efficient recognition decisions on the basis of likelihood ratios.

Personal semantics: Is it distinct from episodic and semantic memory? An electrophysiological study of memory for autobiographical facts and repeated events in honor of Shlomo Bentin.

PubMed

Renoult, Louis; Tanguay, Annick; Beaudry, Myriam; Tavakoli, Paniz; Rabipour, Sheida; Campbell, Kenneth; Moscovitch, Morris; Levine, Brian; Davidson, Patrick S R

2016-03-01

Declarative memory is thought to consist of two independent systems: episodic and semantic. Episodic memory represents personal and contextually unique events, while semantic memory represents culturally-shared, acontextual factual knowledge. Personal semantics refers to aspects of declarative memory that appear to fall somewhere in between the extremes of episodic and semantic. Examples include autobiographical knowledge and memories of repeated personal events. These two aspects of personal semantics have been studied little and rarely compared to both semantic and episodic memory. We recorded the event-related potentials (ERPs) of 27 healthy participants while they verified the veracity of sentences probing four types of questions: general (i.e., semantic) facts, autobiographical facts, repeated events, and unique (i.e., episodic) events. Behavioral results showed equivalent reaction times in all 4 conditions. True sentences were verified faster than false sentences, except for unique events for which no significant difference was observed. Electrophysiological results showed that the N400 (which is classically associated with retrieval from semantic memory) was maximal for general facts and the LPC (which is classically associated with retrieval from episodic memory) was maximal for unique events. For both ERP components, the two personal semantic conditions (i.e., autobiographical facts and repeated events) systematically differed from semantic memory. In addition, N400 amplitudes also differentiated autobiographical facts from unique events. Autobiographical facts and repeated events did not differ significantly from each other but their corresponding scalp distributions differed from those associated with general facts. Our results suggest that the neural correlates of personal semantics can be distinguished from those of semantic and episodic memory, and may provide clues as to how unique events are transformed to semantic memory. Copyright © 2015 Elsevier Ltd. All rights reserved.

Distributed multiport memory architecture

NASA Technical Reports Server (NTRS)

Kohl, W. H. (Inventor)

1983-01-01

A multiport memory architecture is diclosed for each of a plurality of task centers connected to a command and data bus. Each task center, includes a memory and a plurality of devices which request direct memory access as needed. The memory includes an internal data bus and an internal address bus to which the devices are connected, and direct timing and control logic comprised of a 10-state ring counter for allocating memory devices by enabling AND gates connected to the request signal lines of the devices. The outputs of AND gates connected to the same device are combined by OR gates to form an acknowledgement signal that enables the devices to address the memory during the next clock period. The length of the ring counter may be effectively lengthened to any multiple of ten to allow for more direct memory access intervals in one repetitive sequence. One device is a network bus adapter which serially shifts onto the command and data bus, a data word (8 bits plus control and parity bits) during the next ten direct memory access intervals after it has been granted access. The NBA is therefore allocated only one access in every ten intervals, which is a predetermined interval for all centers. The ring counters of all centers are periodically synchronized by DMA SYNC signal to assure that all NBAs be able to function in synchronism for data transfer from one center to another.

Location-Unbound Color-Shape Binding Representations in Visual Working Memory.

PubMed

Saiki, Jun

2016-02-01

The mechanism by which nonspatial features, such as color and shape, are bound in visual working memory, and the role of those features' location in their binding, remains unknown. In the current study, I modified a redundancy-gain paradigm to investigate these issues. A set of features was presented in a two-object memory display, followed by a single object probe. Participants judged whether the probe contained any features of the memory display, regardless of its location. Response time distributions revealed feature coactivation only when both features of a single object in the memory display appeared together in the probe, regardless of the response time benefit from the probe and memory objects sharing the same location. This finding suggests that a shared location is necessary in the formation of bound representations but unnecessary in their maintenance. Electroencephalography data showed that amplitude modulations reflecting location-unbound feature coactivation were different from those reflecting the location-sharing benefit, consistent with the behavioral finding that feature-location binding is unnecessary in the maintenance of color-shape binding. © The Author(s) 2015.

Kinetic energy classification and smoothing for compact B-spline basis sets in quantum Monte Carlo

DOE PAGES

Krogel, Jaron T.; Reboredo, Fernando A.

2018-01-25

Quantum Monte Carlo calculations of defect properties of transition metal oxides have become feasible in recent years due to increases in computing power. As the system size has grown, availability of on-node memory has become a limiting factor. Saving memory while minimizing computational cost is now a priority. The main growth in memory demand stems from the B-spline representation of the single particle orbitals, especially for heavier elements such as transition metals where semi-core states are present. Despite the associated memory costs, splines are computationally efficient. In this paper, we explore alternatives to reduce the memory usage of splined orbitalsmore » without significantly affecting numerical fidelity or computational efficiency. We make use of the kinetic energy operator to both classify and smooth the occupied set of orbitals prior to splining. By using a partitioning scheme based on the per-orbital kinetic energy distributions, we show that memory savings of about 50% is possible for select transition metal oxide systems. Finally, for production supercells of practical interest, our scheme incurs a performance penalty of less than 5%.« less

Kinetic energy classification and smoothing for compact B-spline basis sets in quantum Monte Carlo

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

Krogel, Jaron T.; Reboredo, Fernando A.

Quantum Monte Carlo calculations of defect properties of transition metal oxides have become feasible in recent years due to increases in computing power. As the system size has grown, availability of on-node memory has become a limiting factor. Saving memory while minimizing computational cost is now a priority. The main growth in memory demand stems from the B-spline representation of the single particle orbitals, especially for heavier elements such as transition metals where semi-core states are present. Despite the associated memory costs, splines are computationally efficient. In this paper, we explore alternatives to reduce the memory usage of splined orbitalsmore » without significantly affecting numerical fidelity or computational efficiency. We make use of the kinetic energy operator to both classify and smooth the occupied set of orbitals prior to splining. By using a partitioning scheme based on the per-orbital kinetic energy distributions, we show that memory savings of about 50% is possible for select transition metal oxide systems. Finally, for production supercells of practical interest, our scheme incurs a performance penalty of less than 5%.« less

RNG105/caprin1, an RNA granule protein for dendritic mRNA localization, is essential for long-term memory formation.

PubMed

Nakayama, Kei; Ohashi, Rie; Shinoda, Yo; Yamazaki, Maya; Abe, Manabu; Fujikawa, Akihiro; Shigenobu, Shuji; Futatsugi, Akira; Noda, Masaharu; Mikoshiba, Katsuhiko; Furuichi, Teiichi; Sakimura, Kenji; Shiina, Nobuyuki

2017-11-21

Local regulation of synaptic efficacy is thought to be important for proper networking of neurons and memory formation. Dysregulation of global translation influences long-term memory in mice, but the relevance of the regulation specific for local translation by RNA granules remains elusive. Here, we demonstrate roles of RNG105/caprin1 in long-term memory formation. RNG105 deletion in mice impaired synaptic strength and structural plasticity in hippocampal neurons. Furthermore, RNG105-deficient mice displayed unprecedentedly severe defects in long-term memory formation in spatial and contextual learning tasks. Genome-wide profiling of mRNA distribution in the hippocampus revealed an underlying mechanism: RNG105 deficiency impaired the asymmetric somato-dendritic localization of mRNAs. Particularly, RNG105 deficiency reduced the dendritic localization of mRNAs encoding regulators of AMPAR surface expression, which was consistent with attenuated homeostatic AMPAR scaling in dendrites and reduced synaptic strength. Thus, RNG105 has an essential role, as a key regulator of dendritic mRNA localization, in long-term memory formation.