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

Discrete Resource Allocation in Visual Working Memory

ERIC Educational Resources Information Center

Barton, Brian; Ester, Edward F.; Awh, Edward

2009-01-01

Are resources in visual working memory allocated in a continuous or a discrete fashion? On one hand, flexible resource models suggest that capacity is determined by a central resource pool that can be flexibly divided such that items of greater complexity receive a larger share of resources. On the other hand, if capacity in working memory is…

Global robust stability of bidirectional associative memory neural networks with multiple time delays.

PubMed

Senan, Sibel; Arik, Sabri

2007-10-01

This correspondence presents a sufficient condition for the existence, uniqueness, and global robust asymptotic stability of the equilibrium point for bidirectional associative memory neural networks with discrete time delays. The results impose constraint conditions on the network parameters of the neural system independently of the delay parameter, and they are applicable to all bounded continuous nonmonotonic neuron activation functions. Some numerical examples are given to compare our results with the previous robust stability results derived in the literature.

Random Boolean networks for autoassociative memory: Optimization and sequential learning

NASA Astrophysics Data System (ADS)

Sherrington, D.; Wong, K. Y. M.

Conventional neural networks are based on synaptic storage of information, even when the neural states are discrete and bounded. In general, the set of potential local operations is much greater. Here we discuss some aspects of the properties of networks of binary neurons with more general Boolean functions controlling the local dynamics. Two specific aspects are emphasised; (i) optimization in the presence of noise and (ii) a simple model for short-term memory exhibiting primacy and recency in the recall of sequentially taught patterns.

Tail shortening by discrete hydrodynamics

NASA Astrophysics Data System (ADS)

Kiefer, J.; Visscher, P. B.

1982-02-01

A discrete formulation of hydrodynamics was recently introduced, whose most important feature is that it is exactly renormalizable. Previous numerical work has found that it provides a more efficient and rapidly convergent method for calculating transport coefficients than the usual Green-Kubo method. The latter's convergence difficulties are due to the well-known "long-time tail" of the time correlation function which must be integrated over time. The purpose of the present paper is to present additional evidence that these difficulties are really absent in the discrete equation of motion approach. The "memory" terms in the equation of motion are calculated accurately, and shown to decay much more rapidly with time than the equilibrium time correlations do.

Frontal lobe function in temporal lobe epilepsy

PubMed Central

Stretton, J.; Thompson, P.J.

2012-01-01

Summary Temporal lobe epilepsy (TLE) is typically associated with long-term memory dysfunction. The frontal lobes support high-level cognition comprising executive skills and working memory that is vital for daily life functioning. Deficits in these functions have been increasingly reported in TLE. Evidence from both the neuropsychological and neuroimaging literature suggests both executive function and working memory are compromised in the presence of TLE. In relation to executive impairment, particular focus has been paid to set shifting as measured by the Wisconsin Card Sorting Task. Other discrete executive functions such as decision-making and theory of mind also appear vulnerable but have received little attention. With regard to working memory, the medial temporal lobe structures appear have a more critical role, but with emerging evidence of hippocampal dependent and independent processes. The relative role of underlying pathology and seizure spread is likely to have considerable bearing upon the cognitive phenotype and trajectory in TLE. The identification of the nature of frontal lobe dysfunction in TLE thus has important clinical implications for prognosis and surgical management. Longitudinal neuropsychological and neuroimaging studies assessing frontal lobe function in TLE patients pre- and postoperatively will improve our understanding further. PMID:22100147

On reinitializing level set functions

NASA Astrophysics Data System (ADS)

Min, Chohong

2010-04-01

In this paper, we consider reinitializing level functions through equation ϕt+sgn(ϕ0)(‖∇ϕ‖-1)=0[16]. The method of Russo and Smereka [11] is taken in the spatial discretization of the equation. The spatial discretization is, simply speaking, the second order ENO finite difference with subcell resolution near the interface. Our main interest is on the temporal discretization of the equation. We compare the three temporal discretizations: the second order Runge-Kutta method, the forward Euler method, and a Gauss-Seidel iteration of the forward Euler method. The fact that the time in the equation is fictitious makes a hypothesis that all the temporal discretizations result in the same result in their stationary states. The fact that the absolute stability region of the forward Euler method is not wide enough to include all the eigenvalues of the linearized semi-discrete system of the second order ENO spatial discretization makes another hypothesis that the forward Euler temporal discretization should invoke numerical instability. Our results in this paper contradict both the hypotheses. The Runge-Kutta and Gauss-Seidel methods obtain the second order accuracy, and the forward Euler method converges with order between one and two. Examining all their properties, we conclude that the Gauss-Seidel method is the best among the three. Compared to the Runge-Kutta, it is twice faster and requires memory two times less with the same accuracy.

Unified random access memory (URAM) by integration of a nanocrystal floating gate for nonvolatile memory and a partially depleted floating body for capacitorless 1T-DRAM

NASA Astrophysics Data System (ADS)

Ryu, Seong-Wan; Han, Jin-Woo; Kim, Chung-Jin; Kim, Sungho; Choi, Yang-Kyu

2009-03-01

This paper describes a unified memory (URAM) that utilizes a nanocrystal SOI MOSFET for multi-functional applications of both nonvolatile memory (NVM) and capacitorless 1T-DRAM. By using a discrete storage node (Ag nanocrystal) as the floating gate of the NVM, high defect immunity and 2-bit/cell operation were achieved. The embedded nanocrystal NVM also showed 1T-DRAM operation (program/erase time = 100 ns) characteristics, which were realized by storing holes in the floating body of the SOI MOSFET, without requiring an external capacitor. Three-bit/cell operation was accomplished for different applications - 2-bits for nonvolatility and 1-bit for fast operation.

Transition from Target to Gaze Coding in Primate Frontal Eye Field during Memory Delay and Memory-Motor Transformation.

PubMed

Sajad, Amirsaman; Sadeh, Morteza; Yan, Xiaogang; Wang, Hongying; Crawford, John Douglas

2016-01-01

The frontal eye fields (FEFs) participate in both working memory and sensorimotor transformations for saccades, but their role in integrating these functions through time remains unclear. Here, we tracked FEF spatial codes through time using a novel analytic method applied to the classic memory-delay saccade task. Three-dimensional recordings of head-unrestrained gaze shifts were made in two monkeys trained to make gaze shifts toward briefly flashed targets after a variable delay (450-1500 ms). A preliminary analysis of visual and motor response fields in 74 FEF neurons eliminated most potential models for spatial coding at the neuron population level, as in our previous study (Sajad et al., 2015). We then focused on the spatiotemporal transition from an eye-centered target code (T; preferred in the visual response) to an eye-centered intended gaze position code (G; preferred in the movement response) during the memory delay interval. We treated neural population codes as a continuous spatiotemporal variable by dividing the space spanning T and G into intermediate T-G models and dividing the task into discrete steps through time. We found that FEF delay activity, especially in visuomovement cells, progressively transitions from T through intermediate T-G codes that approach, but do not reach, G. This was followed by a final discrete transition from these intermediate T-G delay codes to a "pure" G code in movement cells without delay activity. These results demonstrate that FEF activity undergoes a series of sensory-memory-motor transformations, including a dynamically evolving spatial memory signal and an imperfect memory-to-motor transformation.

Pricing European option with transaction costs under the fractional long memory stochastic volatility model

NASA Astrophysics Data System (ADS)

Wang, Xiao-Tian; Wu, Min; Zhou, Ze-Min; Jing, Wei-Shu

2012-02-01

This paper deals with the problem of discrete time option pricing using the fractional long memory stochastic volatility model with transaction costs. Through the 'anchoring and adjustment' argument in a discrete time setting, a European call option pricing formula is obtained.

The Memory Function of Noradrenergic Activity in Non-REM Sleep

ERIC Educational Resources Information Center

Gais, Steffen; Rasch, Bjorn; Dahmen, Johannes C.; Sara, Susan; Born, Jan

2011-01-01

There is a long-standing assumption that low noradrenergic activity during sleep reflects mainly the low arousal during this brain state. Nevertheless, recent research has demonstrated that the locus coeruleus, which is the main source of cortical noradrenaline, displays discrete periods of intense firing during non-REM sleep, without any signs of…

Accounting for stimulus-specific variation in precision reveals a discrete capacity limit in visual working memory

PubMed Central

Pratte, Michael S.; Park, Young Eun; Rademaker, Rosanne L.; Tong, Frank

2016-01-01

If we view a visual scene that contains many objects, then momentarily close our eyes, some details persist while others seem to fade. Discrete models of visual working memory (VWM) assume that only a few items can be actively maintained in memory, beyond which pure guessing will emerge. Alternatively, continuous resource models assume that all items in a visual scene can be stored with some precision. Distinguishing between these competing models is challenging, however, as resource models that allow for stochastically variable precision (across items and trials) can produce error distributions that resemble random guessing behavior. Here, we evaluated the hypothesis that a major source of variability in VWM performance arises from systematic variation in precision across the stimuli themselves; such stimulus-specific variability can be incorporated into both discrete-capacity and variable-precision resource models. Participants viewed multiple oriented gratings, and then reported the orientation of a cued grating from memory. When modeling the overall distribution of VWM errors, we found that the variable-precision resource model outperformed the discrete model. However, VWM errors revealed a pronounced “oblique effect”, with larger errors for oblique than cardinal orientations. After this source of variability was incorporated into both models, we found that the discrete model provided a better account of VWM errors. Our results demonstrate that variable precision across the stimulus space can lead to an unwarranted advantage for resource models that assume stochastically variable precision. When these deterministic sources are adequately modeled, human working memory performance reveals evidence of a discrete capacity limit. PMID:28004957

Accounting for stimulus-specific variation in precision reveals a discrete capacity limit in visual working memory.

PubMed

Pratte, Michael S; Park, Young Eun; Rademaker, Rosanne L; Tong, Frank

2017-01-01

If we view a visual scene that contains many objects, then momentarily close our eyes, some details persist while others seem to fade. Discrete models of visual working memory (VWM) assume that only a few items can be actively maintained in memory, beyond which pure guessing will emerge. Alternatively, continuous resource models assume that all items in a visual scene can be stored with some precision. Distinguishing between these competing models is challenging, however, as resource models that allow for stochastically variable precision (across items and trials) can produce error distributions that resemble random guessing behavior. Here, we evaluated the hypothesis that a major source of variability in VWM performance arises from systematic variation in precision across the stimuli themselves; such stimulus-specific variability can be incorporated into both discrete-capacity and variable-precision resource models. Participants viewed multiple oriented gratings, and then reported the orientation of a cued grating from memory. When modeling the overall distribution of VWM errors, we found that the variable-precision resource model outperformed the discrete model. However, VWM errors revealed a pronounced "oblique effect," with larger errors for oblique than cardinal orientations. After this source of variability was incorporated into both models, we found that the discrete model provided a better account of VWM errors. Our results demonstrate that variable precision across the stimulus space can lead to an unwarranted advantage for resource models that assume stochastically variable precision. When these deterministic sources are adequately modeled, human working memory performance reveals evidence of a discrete capacity limit. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The Dopamine D5 Receptor Is Involved in Working Memory

PubMed Central

Carr, Gregory V.; Maltese, Federica; Sibley, David R.; Weinberger, Daniel R.; Papaleo, Francesco

2017-01-01

Pharmacological studies indicate that dopamine D1-like receptors (D1 and D5) are critically involved in cognitive function. However, the lack of pharmacological ligands selective for either the D1 or D5 receptors has made it difficult to determine the unique contributions of the D1-like family members. To circumvent these pharmacological limitations, we used D5 receptor homozygous (-/-) and heterozygous (+/-) knockout mice, to identify the specific role of this receptor in higher order cognitive functions. We identified a novel role for D5 receptors in the regulation of spatial working memory and temporal order memory function. The D5 mutant mice acquired a discrete paired-trial variable-delay T-maze task at normal rates. However, both D5+/- and D5-/- mice exhibited impaired performance compared to D5+/+ littermates when a higher burden on working memory faculties was imposed. In a temporal order object recognition task, D5+/- exhibited significant memory deficits. No D5-dependent differences in locomotor functions and interest in exploring objects were evident. Molecular biomarkers of dopaminergic functions within the prefrontal cortex (PFC) revealed a selective gene-dose effect on Akt phosphorylation at Ser473 with increased levels in D5-/- knockout mice. A trend toward reduced levels in CaMKKbeta brain-specific band (64 kDa) in D5-/- compared to D5+/+ was also evident. These findings highlight a previously unidentified role for D5 receptors in working memory function and associated molecular signatures within the PFC. PMID:29056909

Memory and cognitive control circuits in mathematical cognition and learning.

PubMed

Menon, V

2016-01-01

Numerical cognition relies on interactions within and between multiple functional brain systems, including those subserving quantity processing, working memory, declarative memory, and cognitive control. This chapter describes recent advances in our understanding of memory and control circuits in mathematical cognition and learning. The working memory system involves multiple parietal-frontal circuits which create short-term representations that allow manipulation of discrete quantities over several seconds. In contrast, hippocampal-frontal circuits underlying the declarative memory system play an important role in formation of associative memories and binding of new and old information, leading to the formation of long-term memories that allow generalization beyond individual problem attributes. The flow of information across these systems is regulated by flexible cognitive control systems which facilitate the integration and manipulation of quantity and mnemonic information. The implications of recent research for formulating a more comprehensive systems neuroscience view of the neural basis of mathematical learning and knowledge acquisition in both children and adults are discussed. © 2016 Elsevier B.V. All rights reserved.

Memory and cognitive control circuits in mathematical cognition and learning

PubMed Central

Menon, V.

2018-01-01

Numerical cognition relies on interactions within and between multiple functional brain systems, including those subserving quantity processing, working memory, declarative memory, and cognitive control. This chapter describes recent advances in our understanding of memory and control circuits in mathematical cognition and learning. The working memory system involves multiple parietal–frontal circuits which create short-term representations that allow manipulation of discrete quantities over several seconds. In contrast, hippocampal–frontal circuits underlying the declarative memory system play an important role in formation of associative memories and binding of new and old information, leading to the formation of long-term memories that allow generalization beyond individual problem attributes. The flow of information across these systems is regulated by flexible cognitive control systems which facilitate the integration and manipulation of quantity and mnemonic information. The implications of recent research for formulating a more comprehensive systems neuroscience view of the neural basis of mathematical learning and knowledge acquisition in both children and adults are discussed. PMID:27339012

Portraying the unique contribution of the default mode network to internally driven mnemonic processes

PubMed Central

Shapira-Lichter, Irit; Oren, Noga; Jacob, Yael; Gruberger, Michal; Hendler, Talma

2013-01-01

Numerous neuroimaging studies have implicated default mode network (DMN) involvement in both internally driven processes and memory. Nevertheless, it is unclear whether memory operations reflect a particular case of internally driven processing or alternatively involve the DMN in a distinct manner, possibly depending on memory type. This question is critical for refining neurocognitive memory theorem in the context of other endogenic processes and elucidating the functional significance of this key network. We used functional MRI to examine DMN activity and connectivity patterns while participants overtly generated words according to nonmnemonic (phonemic) or mnemonic (semantic or episodic) cues. Overall, mnemonic word fluency was found to elicit greater DMN activity and stronger within-network functional connectivity compared with nonmnemonic fluency. Furthermore, two levels of functional organization of memory retrieval were shown. First, across both mnemonic tasks, activity was greater mainly in the posterior cingulate cortex, implying selective contribution to generic aspects of memory beyond its general involvement in endogenous processes. Second, parts of the DMN showed distinct selectivity for each of the mnemonic conditions; greater recruitment of the anterior prefrontal cortex, retroesplenial cortex, and hippocampi and elevated connectivity between anterior and posterior medial DMN nodes characterized the semantic condition, whereas increased recruitment of posterior DMN components and elevated connectivity between them characterized the episodic condition. This finding emphasizes the involvement of DMN elements in discrete aspects of memory retrieval. Altogether, our results show a specific contribution of the DMN to memory processes, corresponding to the specific type of memory retrieval. PMID:23479650

Fabry-Perot confocal resonator optical associative memory

NASA Astrophysics Data System (ADS)

Burns, Thomas J.; Rogers, Steven K.; Vogel, George A.

1993-03-01

A unique optical associative memory architecture is presented that combines the optical processing environment of a Fabry-Perot confocal resonator with the dynamic storage and recall properties of volume holograms. The confocal resonator reduces the size and complexity of previous associative memory architectures by folding a large number of discrete optical components into an integrated, compact optical processing environment. Experimental results demonstrate the system is capable of recalling a complete object from memory when presented with partial information about the object. A Fourier optics model of the system's operation shows it implements a spatially continuous version of a discrete, binary Hopfield neural network associative memory.

Identification of Linear and Nonlinear Aerodynamic Impulse Responses Using Digital Filter Techniques

NASA Technical Reports Server (NTRS)

Silva, Walter A.

1997-01-01

This paper discusses the mathematical existence and the numerically-correct identification of linear and nonlinear aerodynamic impulse response functions. Differences between continuous-time and discrete-time system theories, which permit the identification and efficient use of these functions, will be detailed. Important input/output definitions and the concept of linear and nonlinear systems with memory will also be discussed. It will be shown that indicial (step or steady) responses (such as Wagner's function), forced harmonic responses (such as Theodorsen's function or those from doublet lattice theory), and responses to random inputs (such as gusts) can all be obtained from an aerodynamic impulse response function. This paper establishes the aerodynamic impulse response function as the most fundamental, and, therefore, the most computationally efficient, aerodynamic function that can be extracted from any given discrete-time, aerodynamic system. The results presented in this paper help to unify the understanding of classical two-dimensional continuous-time theories with modern three-dimensional, discrete-time theories. First, the method is applied to the nonlinear viscous Burger's equation as an example. Next the method is applied to a three-dimensional aeroelastic model using the CAP-TSD (Computational Aeroelasticity Program - Transonic Small Disturbance) code and then to a two-dimensional model using the CFL3D Navier-Stokes code. Comparisons of accuracy and computational cost savings are presented. Because of its mathematical generality, an important attribute of this methodology is that it is applicable to a wide range of nonlinear, discrete-time problems.

Identification of Linear and Nonlinear Aerodynamic Impulse Responses Using Digital Filter Techniques

NASA Technical Reports Server (NTRS)

Silva, Walter A.

1997-01-01

This paper discusses the mathematical existence and the numerically-correct identification of linear and nonlinear aerodynamic impulse response functions. Differences between continuous-time and discrete-time system theories, which permit the identification and efficient use of these functions, will be detailed. Important input/output definitions and the concept of linear and nonlinear systems with memory will also be discussed. It will be shown that indicial (step or steady) responses (such as Wagner's function), forced harmonic responses (such as Tbeodorsen's function or those from doublet lattice theory), and responses to random inputs (such as gusts) can all be obtained from an aerodynamic impulse response function. This paper establishes the aerodynamic impulse response function as the most fundamental, and, therefore, the most computationally efficient, aerodynamic function that can be extracted from any given discrete-time, aerodynamic system. The results presented in this paper help to unify the understanding of classical two-dimensional continuous-time theories with modem three-dimensional, discrete-time theories. First, the method is applied to the nonlinear viscous Burger's equation as an example. Next the method is applied to a three-dimensional aeroelastic model using the CAP-TSD (Computational Aeroelasticity Program - Transonic Small Disturbance) code and then to a two-dimensional model using the CFL3D Navier-Stokes code. Comparisons of accuracy and computational cost savings are presented. Because of its mathematical generality, an important attribute of this methodology is that it is applicable to a wide range of nonlinear, discrete-time problems.

Discrete-State and Continuous Models of Recognition Memory: Testing Core Properties under Minimal Assumptions

ERIC Educational Resources Information Center

Kellen, David; Klauer, Karl Christoph

2014-01-01

A classic discussion in the recognition-memory literature concerns the question of whether recognition judgments are better described by continuous or discrete processes. These two hypotheses are instantiated by the signal detection theory model (SDT) and the 2-high-threshold model, respectively. Their comparison has almost invariably relied on…

The different oscillation patterns of alpha band in the early and later stages of working memory maintenance.

PubMed

Xie, Yuanjun; Feng, Zhengquan; Xu, Yuanyuan; Bian, Chen; Li, Min

2016-10-28

A putative functional role for alpha oscillations in working memory remains controversial. However, recent evidence suggests that such oscillation may reflect distinct phases of working memory processing. The present study investigated alpha band (8-13Hz) activity during the maintenance stage of working memory using a modified Sternberg working memory task. Our results reveal that alpha power was concentrated primarily in the occipital cortex and was decreased during the early stage of maintenance (0-600ms), and subsequently increased during the later stage of maintenance (1000-1600ms). We suggest that reduced alpha power may be involved in focused attention during the working memory maintenance, whereas increased alpha power may reflect suppression of visual stimuli to facilitate internal processing related to the task. This interpretation is generally consistent with recent reports suggesting that variations in alpha power are associated with the representation and processing of information in the discrete time intervals during the working memory maintenance. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Does the Cambridge Automated Neuropsychological Test Battery (CANTAB) Distinguish Between Cognitive Domains in Healthy Older Adults?

PubMed

Lenehan, Megan E; Summers, Mathew J; Saunders, Nichole L; Summers, Jeffery J; Vickers, James C

2016-04-01

The Cambridge Neuropsychological Test Automated Battery (CANTAB) is a semiautomated computer interface for assessing cognitive function. We examined whether CANTAB tests measured specific cognitive functions, using established neuropsychological tests as a reference point. A sample of 500 healthy older (M = 60.28 years, SD = 6.75) participants in the Tasmanian Healthy Brain Project completed battery of CANTAB subtests and standard paper-based neuropsychological tests. Confirmatory factor analysis identified four factors: processing speed, verbal ability, episodic memory, and working memory. However, CANTAB tests did not consistently load onto the cognitive domain factors derived from traditional measures of the same function. These results indicate that five of the six CANTAB subtests examined did not load onto single cognitive functions. These CANTAB tests may lack the sensitivity to measure discrete cognitive functions in healthy populations or may measure other cognitive domains not included in the traditional neuropsychological battery. © The Author(s) 2015.

Tracking the fear memory engram: discrete populations of neurons within amygdala, hypothalamus, and lateral septum are specifically activated by auditory fear conditioning

PubMed Central

Wilson, Yvette M.; Gunnersen, Jenny M.; Murphy, Mark

2015-01-01

Memory formation is thought to occur via enhanced synaptic connectivity between populations of neurons in the brain. However, it has been difficult to localize and identify the neurons that are directly involved in the formation of any specific memory. We have previously used fos-tau-lacZ (FTL) transgenic mice to identify discrete populations of neurons in amygdala and hypothalamus, which were specifically activated by fear conditioning to a context. Here we have examined neuronal activation due to fear conditioning to a more specific auditory cue. Discrete populations of learning-specific neurons were identified in only a small number of locations in the brain, including those previously found to be activated in amygdala and hypothalamus by context fear conditioning. These populations, each containing only a relatively small number of neurons, may be directly involved in fear learning and memory. PMID:26179231

Elephant random walks and their connection to Pólya-type urns

NASA Astrophysics Data System (ADS)

Baur, Erich; Bertoin, Jean

2016-11-01

In this paper, we explain the connection between the elephant random walk (ERW) and an urn model à la Pólya and derive functional limit theorems for the former. The ERW model was introduced in [Phys. Rev. E 70, 045101 (2004), 10.1103/PhysRevE.70.045101] to study memory effects in a highly non-Markovian setting. More specifically, the ERW is a one-dimensional discrete-time random walk with a complete memory of its past. The influence of the memory is measured in terms of a memory parameter p between zero and one. In the past years, a considerable effort has been undertaken to understand the large-scale behavior of the ERW, depending on the choice of p . Here, we use known results on urns to explicitly solve the ERW in all memory regimes. The method works as well for ERWs in higher dimensions and is widely applicable to related models.

Temporal Organization of Sound Information in Auditory Memory.

PubMed

Song, Kun; Luo, Huan

2017-01-01

Memory is a constructive and organizational process. Instead of being stored with all the fine details, external information is reorganized and structured at certain spatiotemporal scales. It is well acknowledged that time plays a central role in audition by segmenting sound inputs into temporal chunks of appropriate length. However, it remains largely unknown whether critical temporal structures exist to mediate sound representation in auditory memory. To address the issue, here we designed an auditory memory transferring study, by combining a previously developed unsupervised white noise memory paradigm with a reversed sound manipulation method. Specifically, we systematically measured the memory transferring from a random white noise sound to its locally temporal reversed version on various temporal scales in seven experiments. We demonstrate a U-shape memory-transferring pattern with the minimum value around temporal scale of 200 ms. Furthermore, neither auditory perceptual similarity nor physical similarity as a function of the manipulating temporal scale can account for the memory-transferring results. Our results suggest that sounds are not stored with all the fine spectrotemporal details but are organized and structured at discrete temporal chunks in long-term auditory memory representation.

Discrete-time bidirectional associative memory neural networks with variable delays

NASA Astrophysics Data System (ADS)

Liang, variable delays [rapid communication] J.; Cao, J.; Ho, D. W. C.

2005-02-01

Based on the linear matrix inequality (LMI), some sufficient conditions are presented in this Letter for the existence, uniqueness and global exponential stability of the equilibrium point of discrete-time bidirectional associative memory (BAM) neural networks with variable delays. Some of the stability criteria obtained in this Letter are delay-dependent, and some of them are delay-independent, they are less conservative than the ones reported so far in the literature. Furthermore, the results provide one more set of easily verified criteria for determining the exponential stability of discrete-time BAM neural networks.

Exponential lag function projective synchronization of memristor-based multidirectional associative memory neural networks via hybrid control

NASA Astrophysics Data System (ADS)

Yuan, Manman; Wang, Weiping; Luo, Xiong; Li, Lixiang; Kurths, Jürgen; Wang, Xiao

2018-03-01

This paper is concerned with the exponential lag function projective synchronization of memristive multidirectional associative memory neural networks (MMAMNNs). First, we propose a new model of MMAMNNs with mixed time-varying delays. In the proposed approach, the mixed delays include time-varying discrete delays and distributed time delays. Second, we design two kinds of hybrid controllers. Traditional control methods lack the capability of reflecting variable synaptic weights. In this paper, the controllers are carefully designed to confirm the process of different types of synchronization in the MMAMNNs. Third, sufficient criteria guaranteeing the synchronization of system are derived based on the derive-response concept. Finally, the effectiveness of the proposed mechanism is validated with numerical experiments.

Exploring the Use of Discrete Gestures for Authentication

NASA Astrophysics Data System (ADS)

Chong, Ming Ki; Marsden, Gary

Research in user authentication has been a growing field in HCI. Previous studies have shown that peoples’ graphical memory can be used to increase password memorability. On the other hand, with the increasing number of devices with built-in motion sensors, kinesthetic memory (or muscle memory) can also be exploited for authentication. This paper presents a novel knowledge-based authentication scheme, called gesture password, which uses discrete gestures as password elements. The research presents a study of multiple password retention using PINs and gesture passwords. The study reports that although participants could use kinesthetic memory to remember gesture passwords, retention of PINs is far superior to retention of gesture passwords.

Solutions of large-scale electromagnetics problems involving dielectric objects with the parallel multilevel fast multipole algorithm.

PubMed

Ergül, Özgür

2011-11-01

Fast and accurate solutions of large-scale electromagnetics problems involving homogeneous dielectric objects are considered. Problems are formulated with the electric and magnetic current combined-field integral equation and discretized with the Rao-Wilton-Glisson functions. Solutions are performed iteratively by using the multilevel fast multipole algorithm (MLFMA). For the solution of large-scale problems discretized with millions of unknowns, MLFMA is parallelized on distributed-memory architectures using a rigorous technique, namely, the hierarchical partitioning strategy. Efficiency and accuracy of the developed implementation are demonstrated on very large problems involving as many as 100 million unknowns.

Multipronged CD4 T cell effector and memory responses cooperate to provide potent immunity against respiratory virus

PubMed Central

Strutt, Tara M.; McKinstry, K. Kai; Marshall, Nikki B.; Vong, Allen M.; Dutton, Richard W.; Swain, Susan L.

2014-01-01

Summary Over the last decade, the known spectrum of CD4 T cell effect or subsets has become much broader and it has become clear that there are multiple dimensions by which subsets with a particular cytokine commitment can be further defined, including their stage of differentiation, their location and most importantly, their ability to carryout discrete functions. Here we focus on our studies that highlight the synergy among discrete subsets, especially those defined by helper and cytotoxic function, in mediating viral protection and on distinctions between CD4 T cell effectors located in spleen, draining lymph node, and in tissue sites of infection. What emerges is a surprising multiplicity of CD4 T cell functions that indicate a large arsenal of mechanisms by which CD4 T cells act to combat viruses. PMID:23947353

Socioemotional selectivity in older adults: Evidence from the subjective experience of angry memories.

PubMed

Uzer, Tugba; Gulgoz, Sami

2015-01-01

Few studies have compared the phenomenological properties of younger and older adults' memories for emotional events. Some studies suggest that younger adults remember negative information more vividly than positive information whereas other studies suggest that positive emotion yields phenomenologically richer memories than negative emotion for both younger and older adults. One problem with previous studies is a tendency to treat emotion as a dichotomous variable. In contrast, emotional richness demands inclusion of assessments beyond just a positive and negative dimension (e.g., assessing specific emotions like anger, fear and happiness). The present study investigated different properties of autobiographical remembering as a function of discrete emotions and age. Thirty-two younger and thirty-one older adults participated by recalling recent and remote memories associated with six emotional categories and completed the Memory Characteristics Questionnaire for each. Results demonstrated that older adults' angry memories received lower ratings on some phenomenological properties than other emotional memories whereas younger adults' angry memories did not show this same pattern. These results are discussed within the context of socioemotional selectivity theory.

A neural basis for category and modality specificity of semantic knowledge.

PubMed

Thompson-Schill, S L; Aguirre, G K; D'Esposito, M; Farah, M J

1999-06-01

Prevalent theories hold that semantic memory is organized by sensorimotor modality (e.g., visual knowledge, motor knowledge). While some neuroimaging studies support this idea, it cannot account for the category specific (e.g., living things) knowledge impairments seen in some brain damaged patients that cut across modalities. In this article we test an alternative model of how damage to interactive, modality-specific neural regions might give rise to these categorical impairments. Functional MRI was used to examine a cortical area with a known modality-specific function during the retrieval of visual and non-visual knowledge about living and non-living things. The specific predictions of our model regarding the signal observed in this area were confirmed, supporting the notion that semantic memory is functionally segregated into anatomically discrete, but highly interactive, modality-specific regions.

Attention restores discrete items to visual short-term memory.

PubMed

Murray, Alexandra M; Nobre, Anna C; Clark, Ian A; Cravo, André M; Stokes, Mark G

2013-04-01

When a memory is forgotten, is it lost forever? Our study shows that selective attention can restore forgotten items to visual short-term memory (VSTM). In our two experiments, all stimuli presented in a memory array were designed to be equally task relevant during encoding. During the retention interval, however, participants were sometimes given a cue predicting which of the memory items would be probed at the end of the delay. This shift in task relevance improved recall for that item. We found that this type of cuing improved recall for items that otherwise would have been irretrievable, providing critical evidence that attention can restore forgotten information to VSTM. Psychophysical modeling of memory performance has confirmed that restoration of information in VSTM increases the probability that the cued item is available for recall but does not improve the representational quality of the memory. We further suggest that attention can restore discrete items to VSTM.

Nanocrystalline Si pathway induced unipolar resistive switching behavior from annealed Si-rich SiNx/SiNy multilayers

NASA Astrophysics Data System (ADS)

Jiang, Xiaofan; Ma, Zhongyuan; Yang, Huafeng; Yu, Jie; Wang, Wen; Zhang, Wenping; Li, Wei; Xu, Jun; Xu, Ling; Chen, Kunji; Huang, Xinfan; Feng, Duan

2014-09-01

Adding a resistive switching functionality to a silicon microelectronic chip is a new challenge in materials research. Here, we demonstrate that unipolar and electrode-independent resistive switching effects can be realized in the annealed Si-rich SiNx/SiNy multilayers with high on/off ratio of 109. High resolution transmission electron microscopy reveals that for the high resistance state broken pathways composed of discrete nanocrystalline silicon (nc-Si) exist in the Si nitride multilayers. While for the low resistance state the discrete nc-Si regions is connected, forming continuous nc-Si pathways. Based on the analysis of the temperature dependent I-V characteristics and HRTEM photos, we found that the break-and-bridge evolution of nc-Si pathway is the origin of resistive switching memory behavior. Our findings provide insights into the mechanism of the resistive switching behavior in nc-Si films, opening a way for it to be utilized as a material in Si-based memories.

The Pivotal Role of Semantic Memory in Remembering the Past and Imagining the Future

PubMed Central

Irish, Muireann; Piguet, Olivier

2013-01-01

Episodic memory refers to a complex and multifaceted process which enables the retrieval of richly detailed evocative memories from the past. In contrast, semantic memory is conceptualized as the retrieval of general conceptual knowledge divested of a specific spatiotemporal context. The neural substrates of the episodic and semantic memory systems have been dissociated in healthy individuals during functional imaging studies, and in clinical cohorts, leading to the prevailing view that episodic and semantic memory represent functionally distinct systems subtended by discrete neurobiological substrates. Importantly, however, converging evidence focusing on widespread neural networks now points to significant overlap between those regions essential for retrieval of autobiographical memories, episodic learning, and semantic processing. Here we review recent advances in episodic memory research focusing on neurodegenerative populations which has proved revelatory for our understanding of the complex interplay between episodic and semantic memory. Whereas episodic memory research has traditionally focused on retrieval of autobiographical events from the past, we also include evidence from the recent paradigm shift in which episodic memory is viewed as an adaptive and constructive process which facilitates the imagining of possible events in the future. We examine the available evidence which converges to highlight the pivotal role of semantic memory in providing schemas and meaning whether one is engaged in autobiographical retrieval for the past, or indeed, is endeavoring to construct a plausible scenario of an event in the future. It therefore seems plausible to contend that semantic processing may underlie most, if not all, forms of episodic memory, irrespective of temporal condition. PMID:23565081

Selection and Storage of Perceptual Groups Is Constrained by a Discrete Resource in Working Memory

ERIC Educational Resources Information Center

Anderson, David E.; Vogel, Edward K.; Awh, Edward

2013-01-01

Perceptual grouping can lead observers to perceive a multielement scene as a smaller number of hierarchical units. Past work has shown that grouping enables more elements to be stored in visual working memory (WM). Although this may appear to contradict so-called discrete resource models that argue for fixed item limits in WM storage, it is also…

Tracking the fear memory engram: discrete populations of neurons within amygdala, hypothalamus, and lateral septum are specifically activated by auditory fear conditioning.

PubMed

Butler, Christopher W; Wilson, Yvette M; Gunnersen, Jenny M; Murphy, Mark

2015-08-01

Memory formation is thought to occur via enhanced synaptic connectivity between populations of neurons in the brain. However, it has been difficult to localize and identify the neurons that are directly involved in the formation of any specific memory. We have previously used fos-tau-lacZ (FTL) transgenic mice to identify discrete populations of neurons in amygdala and hypothalamus, which were specifically activated by fear conditioning to a context. Here we have examined neuronal activation due to fear conditioning to a more specific auditory cue. Discrete populations of learning-specific neurons were identified in only a small number of locations in the brain, including those previously found to be activated in amygdala and hypothalamus by context fear conditioning. These populations, each containing only a relatively small number of neurons, may be directly involved in fear learning and memory. © 2015 Butler et al.; Published by Cold Spring Harbor Laboratory Press.

A fast semi-discrete Kansa method to solve the two-dimensional spatiotemporal fractional diffusion equation

NASA Astrophysics Data System (ADS)

Sun, HongGuang; Liu, Xiaoting; Zhang, Yong; Pang, Guofei; Garrard, Rhiannon

2017-09-01

Fractional-order diffusion equations (FDEs) extend classical diffusion equations by quantifying anomalous diffusion frequently observed in heterogeneous media. Real-world diffusion can be multi-dimensional, requiring efficient numerical solvers that can handle long-term memory embedded in mass transport. To address this challenge, a semi-discrete Kansa method is developed to approximate the two-dimensional spatiotemporal FDE, where the Kansa approach first discretizes the FDE, then the Gauss-Jacobi quadrature rule solves the corresponding matrix, and finally the Mittag-Leffler function provides an analytical solution for the resultant time-fractional ordinary differential equation. Numerical experiments are then conducted to check how the accuracy and convergence rate of the numerical solution are affected by the distribution mode and number of spatial discretization nodes. Applications further show that the numerical method can efficiently solve two-dimensional spatiotemporal FDE models with either a continuous or discrete mixing measure. Hence this study provides an efficient and fast computational method for modeling super-diffusive, sub-diffusive, and mixed diffusive processes in large, two-dimensional domains with irregular shapes.

Human skin is protected by four functionally and phenotypically discrete populations of resident and recirculating memory T cells.

PubMed

Watanabe, Rei; Gehad, Ahmed; Yang, Chao; Scott, Laura L; Teague, Jessica E; Schlapbach, Christoph; Elco, Christopher P; Huang, Victor; Matos, Tiago R; Kupper, Thomas S; Clark, Rachael A

2015-03-18

The skin of an adult human contains about 20 billion memory T cells. Epithelial barrier tissues are infiltrated by a combination of resident and recirculating T cells in mice, but the relative proportions and functional activities of resident versus recirculating T cells have not been evaluated in human skin. We discriminated resident from recirculating T cells in human-engrafted mice and lymphoma patients using alemtuzumab, a medication that depletes recirculating T cells from skin, and then analyzed these T cell populations in healthy human skin. All nonrecirculating resident memory T cells (TRM) expressed CD69, but most were CD4(+), CD103(-), and located in the dermis, in contrast to studies in mice. Both CD4(+) and CD8(+) CD103(+) TRM were enriched in the epidermis, had potent effector functions, and had a limited proliferative capacity compared to CD103(-) TRM. TRM of both types had more potent effector functions than recirculating T cells. We observed two distinct populations of recirculating T cells, CCR7(+)/L-selectin(+) central memory T cells (TCM) and CCR7(+)/L-selectin(-) T cells, which we term migratory memory T cells (TMM). Circulating skin-tropic TMM were intermediate in cytokine production between TCM and effector memory T cells. In patients with cutaneous T cell lymphoma, malignant TCM and TMM induced distinct inflammatory skin lesions, and TMM were depleted more slowly from skin after alemtuzumab, suggesting that TMM may recirculate more slowly. In summary, human skin is protected by four functionally distinct populations of T cells, two resident and two recirculating, with differing territories of migration and distinct functional activities. Copyright © 2015, American Association for the Advancement of Science.

Parallel Discrete Molecular Dynamics Simulation With Speculation and In-Order Commitment*†

PubMed Central

Khan, Md. Ashfaquzzaman; Herbordt, Martin C.

2011-01-01

Discrete molecular dynamics simulation (DMD) uses simplified and discretized models enabling simulations to advance by event rather than by timestep. DMD is an instance of discrete event simulation and so is difficult to scale: even in this multi-core era, all reported DMD codes are serial. In this paper we discuss the inherent difficulties of scaling DMD and present our method of parallelizing DMD through event-based decomposition. Our method is microarchitecture inspired: speculative processing of events exposes parallelism, while in-order commitment ensures correctness. We analyze the potential of this parallelization method for shared-memory multiprocessors. Achieving scalability required extensive experimentation with scheduling and synchronization methods to mitigate serialization. The speed-up achieved for a variety of system sizes and complexities is nearly 6× on an 8-core and over 9× on a 12-core processor. We present and verify analytical models that account for the achieved performance as a function of available concurrency and architectural limitations. PMID:21822327

Parallel Discrete Molecular Dynamics Simulation With Speculation and In-Order Commitment.

PubMed

Khan, Md Ashfaquzzaman; Herbordt, Martin C

2011-07-20

Discrete molecular dynamics simulation (DMD) uses simplified and discretized models enabling simulations to advance by event rather than by timestep. DMD is an instance of discrete event simulation and so is difficult to scale: even in this multi-core era, all reported DMD codes are serial. In this paper we discuss the inherent difficulties of scaling DMD and present our method of parallelizing DMD through event-based decomposition. Our method is microarchitecture inspired: speculative processing of events exposes parallelism, while in-order commitment ensures correctness. We analyze the potential of this parallelization method for shared-memory multiprocessors. Achieving scalability required extensive experimentation with scheduling and synchronization methods to mitigate serialization. The speed-up achieved for a variety of system sizes and complexities is nearly 6× on an 8-core and over 9× on a 12-core processor. We present and verify analytical models that account for the achieved performance as a function of available concurrency and architectural limitations.

Transition from Target to Gaze Coding in Primate Frontal Eye Field during Memory Delay and Memory–Motor Transformation123

PubMed Central

Sajad, Amirsaman; Sadeh, Morteza; Yan, Xiaogang; Wang, Hongying

2016-01-01

Abstract The frontal eye fields (FEFs) participate in both working memory and sensorimotor transformations for saccades, but their role in integrating these functions through time remains unclear. Here, we tracked FEF spatial codes through time using a novel analytic method applied to the classic memory-delay saccade task. Three-dimensional recordings of head-unrestrained gaze shifts were made in two monkeys trained to make gaze shifts toward briefly flashed targets after a variable delay (450-1500 ms). A preliminary analysis of visual and motor response fields in 74 FEF neurons eliminated most potential models for spatial coding at the neuron population level, as in our previous study (Sajad et al., 2015). We then focused on the spatiotemporal transition from an eye-centered target code (T; preferred in the visual response) to an eye-centered intended gaze position code (G; preferred in the movement response) during the memory delay interval. We treated neural population codes as a continuous spatiotemporal variable by dividing the space spanning T and G into intermediate T–G models and dividing the task into discrete steps through time. We found that FEF delay activity, especially in visuomovement cells, progressively transitions from T through intermediate T–G codes that approach, but do not reach, G. This was followed by a final discrete transition from these intermediate T–G delay codes to a “pure” G code in movement cells without delay activity. These results demonstrate that FEF activity undergoes a series of sensory–memory–motor transformations, including a dynamically evolving spatial memory signal and an imperfect memory-to-motor transformation. PMID:27092335

The Effect of Executive Function on Science Achievement Among Normally Developing 10-Year Olds

NASA Astrophysics Data System (ADS)

Lederman, Sheri G.

Executive function (EF) is an umbrella term used to identify a set of discrete but interrelated cognitive abilities that enable individuals to engage in goal-directed, future-oriented action in response to a novel context. Developmental studies indicate that EF is predictive of reading and math achievement in middle childhood. The purpose of this study was to identify the association between EF and science achievement among normally developing 10 year olds. A sample of fifth grade students from a Northeastern suburban community participated in tests of EF, science, and intelligence. Consistent with adult models of EF, principal components analysis identified a three-factor model of EF organization in middle childhood, including cognitive flexibility, working memory, and inhibition. Multiple regression analyses revealed that executive function processes of cognitive flexibility, working memory, and inhibition were all predictive of science performance. Post hoc analyses revealed that high-performing science students differed significantly from low-performing students in both cognitive flexibility and working memory. These findings suggest that complex academic demands specific to science achievement rely on the emergence and maturation of EF components.

Never forget a name: white matter connectivity predicts person memory

PubMed Central

Metoki, Athanasia; Alm, Kylie H.; Wang, Yin; Ngo, Chi T.; Olson, Ingrid R.

2018-01-01

Through learning and practice, we can acquire numerous skills, ranging from the simple (whistling) to the complex (memorizing operettas in a foreign language). It has been proposed that complex learning requires a network of brain regions that interact with one another via white matter pathways. One candidate white matter pathway, the uncinate fasciculus (UF), has exhibited mixed results for this hypothesis: some studies have shown UF involvement across a range of memory tasks, while other studies report null results. Here, we tested the hypothesis that the UF supports associative memory processes and that this tract can be parcellated into subtracts that support specific types of memory. Healthy young adults performed behavioral tasks (two face-name learning tasks, one word pair memory task) and underwent a diffusion-weighted imaging scan. Our results revealed that variation in UF microstructure was significantly associated with individual differences in performance on both face-name tasks, as well as the word association memory task. A UF sub-tract, functionally defined by its connectivity between face-selective regions in the anterior temporal lobe and orbitofrontal cortex, selectively predicted face-name learning. In contrast, connectivity between the fusiform face patch and both anterior face patches had no predictive validity. These findings suggest that there is a robust and replicable relationship between the UF and associative learning and memory. Moreover, this large white matter pathway can be subdivided to reveal discrete functional profiles. PMID:28646241

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.

Discrete emotion-congruent false memories in the DRM paradigm.

PubMed

Bland, Cassandra E; Howe, Mark L; Knott, Lauren

2016-08-01

Research has shown that false-memory production is enhanced for material that is emotionally congruent with the mood of the participant at the time of encoding. So far this research has only been conducted to examine the influence of generic negative affective mood states and generic negative stimuli on false-memory production. In addition, much of the research is limited as it focuses on valence and arousal dimensions, and fails to take into account the more comprehensive nature of emotions. The current study demonstrates that this effect goes beyond general negative or positive moods and acts at a more discrete emotional level. Participants underwent a standard emotion-induction procedure before listening to negative emotional or neutral associative word lists. The emotions induced, negative word lists, and associated nonpresented critical lures, were related to either fear or anger, 2 negative valence emotions that are also both high in arousal. Results showed that when valence and arousal are controlled for, false memories are more likely to be produced for discrete emotionally congruent compared with incongruent materials. These results support spreading activation theories of false remembering and add to our understanding of the adaptive nature of false-memory production. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Multimodal MRI reveals structural connectivity differences in 22q11 deletion syndrome related to impaired spatial working memory.

PubMed

O'Hanlon, Erik; Howley, Sarah; Prasad, Sarah; McGrath, Jane; Leemans, Alexander; McDonald, Colm; Garavan, Hugh; Murphy, Kieran C

2016-12-01

Impaired spatial working memory is a core cognitive deficit observed in people with 22q11 Deletion syndrome (22q11DS) and has been suggested as a candidate endophenotype for schizophrenia. However, to date, the neuroanatomical mechanisms describing its structural and functional underpinnings in 22q11DS remain unclear. We quantitatively investigate the cognitive processes and associated neuroanatomy of spatial working memory in people with 22q11DS compared to matched controls. We examine whether there are significant between-group differences in spatial working memory using task related fMRI, Voxel based morphometry and white matter fiber tractography. Multimodal magnetic resonance imaging employing functional, diffusion and volumetric techniques were used to quantitatively assess the cognitive and neuroanatomical features of spatial working memory processes in 22q11DS. Twenty-six participants with genetically confirmed 22q11DS aged between 9 and 52 years and 26 controls aged between 8 and 46 years, matched for age, gender, and handedness were recruited. People with 22q11DS have significant differences in spatial working memory functioning accompanied by a gray matter volume reduction in the right precuneus. Gray matter volume was significantly correlated with task performance scores in these areas. Tractography revealed extensive differences along fibers between task-related cortical activations with pronounced differences localized to interhemispheric commissural fibers within the parietal section of the corpus callosum. Abnormal spatial working memory in 22q11DS is associated with aberrant functional activity in conjunction with gray and white matter structural abnormalities. These anomalies in discrete brain regions may increase susceptibility to the development of psychiatric disorders such as schizophrenia. Hum Brain Mapp 37:4689-4705, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Neurocognition in College-Aged Daily Marijuana Users

PubMed Central

Becker, Mary P.; Collins, Paul F.; Luciana, Monica

2014-01-01

Background Marijuana is the most commonly used illicit substance in the United States. Use, particularly when it occurs early, has been associated with cognitive impairments in executive functioning, learning, and memory. Methods This study comprehensively measured cognitive ability as well as comorbid psychopathology and substance use history to determine the neurocognitive profile associated with young adult marijuana use. College-aged marijuana users who initiated use prior to age 17 (n=35) were compared to demographically-matched controls (n=35). Results Marijuana users were high functioning, demonstrating comparable IQs to controls and relatively better processing speed. Marijuana users demonstrated relative cognitive impairments in verbal memory, spatial working memory, spatial planning, and motivated decision-making. Comorbid use of alcohol, which was heavier in marijuana users, was unexpectedly found to be associated with better performance in some of these areas. Conclusions This study provides additional evidence of neurocognitive impairment in the context of adolescent and young adult marijuana use. Findings are discussed in relation to marijuana’s effects on intrinsic motivation and discrete aspects of cognition. PMID:24620756

Approximation for discrete Fourier transform and application in study of three-dimensional interacting electron gas.

PubMed

Yan, Xin-Zhong

2011-07-01

The discrete Fourier transform is approximated by summing over part of the terms with corresponding weights. The approximation reduces significantly the requirement for computer memory storage and enhances the numerical computation efficiency with several orders without losing accuracy. As an example, we apply the algorithm to study the three-dimensional interacting electron gas under the renormalized-ring-diagram approximation where the Green's function needs to be self-consistently solved. We present the results for the chemical potential, compressibility, free energy, entropy, and specific heat of the system. The ground-state energy obtained by the present calculation is compared with the existing results of Monte Carlo simulation and random-phase approximation.

Reconsolidation of Declarative Memory in Humans

ERIC Educational Resources Information Center

Forcato, Cecilia; Burgos, Valeria L.; Argibay, Pablo F.; Molina, Victor A.; Pedreira, Maria E.; Maldonado, Hector

2007-01-01

The reconsolidation hypothesis states that a consolidated memory could again become unstable and susceptible to facilitation or impairment for a discrete period of time after a reminder presentation. The phenomenon has been demonstrated in very diverse species and types of memory, including the human procedural memory of a motor skill task but not…

Event Segmentation Improves Event Memory up to One Month Later

ERIC Educational Resources Information Center

Flores, Shaney; Bailey, Heather R.; Eisenberg, Michelle L.; Zacks, Jeffrey M.

2017-01-01

When people observe everyday activity, they spontaneously parse it into discrete meaningful events. Individuals who segment activity in a more normative fashion show better subsequent memory for the events. If segmenting events effectively leads to better memory, does asking people to attend to segmentation improve subsequent memory? To answer…

Predicting story goodness performance from cognitive measures following traumatic brain injury.

PubMed

Lê, Karen; Coelho, Carl; Mozeiko, Jennifer; Krueger, Frank; Grafman, Jordan

2012-05-01

This study examined the prediction of performance on measures of the Story Goodness Index (SGI; Lê, Coelho, Mozeiko, & Grafman, 2011) from executive function (EF) and memory measures following traumatic brain injury (TBI). It was hypothesized that EF and memory measures would significantly predict SGI outcomes. One hundred sixty-seven individuals with TBI participated in the study. Story retellings were analyzed using the SGI protocol. Three cognitive measures--Delis-Kaplan Executive Function System (D-KEFS; Delis, Kaplan, & Kramer, 2001) Sorting Test, Wechsler Memory Scale--Third Edition (WMS-III; Wechsler, 1997) Working Memory Primary Index (WMI), and WMS-III Immediate Memory Primary Index (IMI)--were entered into a multiple linear regression model for each discourse measure. Two sets of regression analyses were performed, the first with the Sorting Test as the first predictor and the second with it as the last. The first set of regression analyses identified the Sorting Test and IMI as the only significant predictors of performance on measures of the SGI. The second set identified all measures as significant predictors when evaluating each step of the regression function. The cognitive variables predicted performance on the SGI measures, although there were differences in the amount of explained variance. The results (a) suggest that storytelling ability draws on a number of underlying skills and (b) underscore the importance of using discrete cognitive tasks rather than broad cognitive indices to investigate the cognitive substrates of discourse.

A discrete Fourier transform for virtual memory machines

NASA Technical Reports Server (NTRS)

Galant, David C.

1992-01-01

An algebraic theory of the Discrete Fourier Transform is developed in great detail. Examination of the details of the theory leads to a computationally efficient fast Fourier transform for the use on computers with virtual memory. Such an algorithm is of great use on modern desktop machines. A FORTRAN coded version of the algorithm is given for the case when the sequence of numbers to be transformed is a power of two.

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.

Functional cross‐hemispheric shift between object‐place paired associate memory and spatial memory in the human hippocampus

PubMed Central

Lee, Choong‐Hee; Ryu, Jungwon; Lee, Sang‐Hun; Kim, Hakjin

2016-01-01

ABSTRACT The hippocampus plays critical roles in both object‐based event memory and spatial navigation, but it is largely unknown whether the left and right hippocampi play functionally equivalent roles in these cognitive domains. To examine the hemispheric symmetry of human hippocampal functions, we used an fMRI scanner to measure BOLD activity while subjects performed tasks requiring both object‐based event memory and spatial navigation in a virtual environment. Specifically, the subjects were required to form object‐place paired associate memory after visiting four buildings containing discrete objects in a virtual plus maze. The four buildings were visually identical, and the subjects used distal visual cues (i.e., scenes) to differentiate the buildings. During testing, the subjects were required to identify one of the buildings when cued with a previously associated object, and when shifted to a random place, the subject was expected to navigate to the previously chosen building. We observed that the BOLD activity foci changed from the left hippocampus to the right hippocampus as task demand changed from identifying a previously seen object (object‐cueing period) to searching for its paired‐associate place (object‐cued place recognition period). Furthermore, the efficient retrieval of object‐place paired associate memory (object‐cued place recognition period) was correlated with the BOLD response of the left hippocampus, whereas the efficient retrieval of relatively pure spatial memory (spatial memory period) was correlated with the right hippocampal BOLD response. These findings suggest that the left and right hippocampi in humans might process qualitatively different information for remembering episodic events in space. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc. PMID:27009679

Attention and working memory: two basic mechanisms for constructing temporal experiences

PubMed Central

Marchetti, Giorgio

2014-01-01

Various kinds of observations show that the ability of human beings to both consciously relive past events – episodic memory – and conceive future events, entails an active process of construction. This construction process also underpins many other important aspects of conscious human life, such as perceptions, language, and conscious thinking. This article provides an explanation of what makes the constructive process possible and how it works. The process mainly relies on attentional activity, which has a discrete and periodic nature, and working memory, which allows for the combination of discrete attentional operations. An explanation is also provided of how past and future events are constructed. PMID:25177305

Optimal region of latching activity in an adaptive Potts model for networks of neurons

NASA Astrophysics Data System (ADS)

Abdollah-nia, Mohammad-Farshad; Saeedghalati, Mohammadkarim; Abbassian, Abdolhossein

2012-02-01

In statistical mechanics, the Potts model is a model for interacting spins with more than two discrete states. Neural networks which exhibit features of learning and associative memory can also be modeled by a system of Potts spins. A spontaneous behavior of hopping from one discrete attractor state to another (referred to as latching) has been proposed to be associated with higher cognitive functions. Here we propose a model in which both the stochastic dynamics of Potts models and an adaptive potential function are present. A latching dynamics is observed in a limited region of the noise(temperature)-adaptation parameter space. We hence suggest noise as a fundamental factor in such alternations alongside adaptation. From a dynamical systems point of view, the noise-adaptation alternations may be the underlying mechanism for multi-stability in attractor-based models. An optimality criterion for realistic models is finally inferred.

Nanocrystalline Si pathway induced unipolar resistive switching behavior from annealed Si-rich SiN{sub x}/SiN{sub y} multilayers

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

Jiang, Xiaofan; Ma, Zhongyuan, E-mail: zyma@nju.edu.cn; Yang, Huafeng

2014-09-28

Adding a resistive switching functionality to a silicon microelectronic chip is a new challenge in materials research. Here, we demonstrate that unipolar and electrode-independent resistive switching effects can be realized in the annealed Si-rich SiN{sub x}/SiN{sub y} multilayers with high on/off ratio of 10{sup 9}. High resolution transmission electron microscopy reveals that for the high resistance state broken pathways composed of discrete nanocrystalline silicon (nc-Si) exist in the Si nitride multilayers. While for the low resistance state the discrete nc-Si regions is connected, forming continuous nc-Si pathways. Based on the analysis of the temperature dependent I-V characteristics and HRTEM photos,more » we found that the break-and-bridge evolution of nc-Si pathway is the origin of resistive switching memory behavior. Our findings provide insights into the mechanism of the resistive switching behavior in nc-Si films, opening a way for it to be utilized as a material in Si-based memories.« less

Toughness and Matching Extension in Graphs,

DTIC Science & Technology

1986-05-01

New York, 1977. V. CHVATAL 1973a. Tough graphs and Hamiltonian circuits, Discrete Math . 5, 1973, 215- 228. 1973b. New directions in Hamiltonian...PLUMMER 1986. Matching Theory, Ann. Discrete Math ., North-Holland, Amsterdam, 1986 (to appear). M. D. PLUMMER 1980. On n-extendable graphs, Discrete ... Math . 31, 1980, 201-210. 1985. A theorem on matchings in the plane, Conference in memory of Gabriel Dirac, Ann. Discrete Math ., North-Holland, Amsterdam

Application of a simple cerebellar model to geologic surface mapping

USGS Publications Warehouse

Hagens, A.; Doveton, J.H.

1991-01-01

Neurophysiological research into the structure and function of the cerebellum has inspired computational models that simulate information processing associated with coordination and motor movement. The cerebellar model arithmetic computer (CMAC) has a design structure which makes it readily applicable as an automated mapping device that "senses" a surface, based on a sample of discrete observations of surface elevation. The model operates as an iterative learning process, where cell weights are continuously modified by feedback to improve surface representation. The storage requirements are substantially less than those of a conventional memory allocation, and the model is extended easily to mapping in multidimensional space, where the memory savings are even greater. ?? 1991.

Dissociation of working memory processing associated with native and second languages: PET investigation.

PubMed

Kim, Jae-Jin; Kim, Myung Sun; Lee, Jae Sung; Lee, Dong Soo; Lee, Myung Chul; Kwon, Jun Soo

2002-04-01

Verbal working memory plays a significant role in language comprehension and problem-solving. The prefrontal cortex has been suggested as a critical area in working memory. Given that domain-specific dissociations of working memory may exist within the prefrontal cortex, it is possible that there may also be further functional divisions within the verbal working memory processing. While differences in the areas of the brain engaged in native and second languages have been demonstrated, little is known about the dissociation of verbal working memory associated with native and second languages. We have used H2(15)O positron emission tomography in 14 normal subjects in order to identify the neural correlates selectively involved in working memory of native (Korean) and second (English) languages. All subjects were highly proficient in the native language but poorly proficient in the second language. Cognitive tasks were a two-back task for three kinds of visually presented objects: simple pictures, English words, and Korean words. The anterior portion of the right dorsolateral prefrontal cortex and the left superior temporal gyrus were activated in working memory for the native language, whereas the posterior portion of the right dorsolateral prefrontal cortex and the left inferior temporal gyrus were activated in working memory for the second language. The results suggest that the right dorsolateral prefrontal cortex and left temporal lobe may be organized into two discrete, language-related functional systems. Internal phonological processing seems to play a predominant role in working memory processing for the native language with a high proficiency, whereas visual higher order control does so for the second language with a low proficiency. (C)2002 Elsevier Science (USA).

Human skin is protected by four functionally and phenotypically discrete populations of resident and recirculating memory T cells

PubMed Central

Watanabe, Rei; Gehad, Ahmed; Yang, Chao; Campbell, Laura; Teague, Jessica E.; Schlapbach, Christoph; Elco, Christopher; Huang, Victor; Matos, Tiago R.; Kupper, Thomas S.; Clark, Rachael A.

2015-01-01

The skin of an adult human contains approximately 20 billion memory T cells. Epithelial barrier tissues are infiltrated by a combination of resident and recirculating T cells in mice but the relative proportions and functional activities of resident versus recirculating T cells have not been evaluated in human skin. We discriminated resident from recirculating T cells in human engrafted mice and lymphoma patients using alemtuzumab, a medication that depletes recirculating T cells from skin, and then analyzed these T cell populations in healthy human skin. All non-recirculating resident memory T cells (TRM) expressed CD69, but the majority were CD4+, CD103− and located in the dermis, in contrast to studies in mice. Both CD4+ and CD8+ CD103+ TRM were enriched in the epidermis, had potent effector functions and had a limited proliferative capacity compared to CD103− TRM. TRM of both types had more potent effector functions than recirculating T cells. Induction of CD103 on human T cells was enhanced by keratinocyte contact, depended on TGFβ and was independent of T cell keratinocyte adhesive interactions. We observed two distinct populations of recirculating T cells, CCR7+/L-selectin+ central memory T cells (TCM) and CCR7+/L-selectin− T cells, which we term migratory memory T cells (TMM). Circulating skin-tropic TMM were intermediate in cytokine production between TCM and effector memory T cells. In patients with cutaneous T cell lymphoma, malignant TCM and TMM induced distinct inflammatory skin lesions and TMM were depleted more slowly from skin after alemtuzumab, suggesting TMM may recirculate more slowly. In summary, human skin is protected by four functionally distinct populations of T cells, two resident and two recirculating, with differing territories of migration and distinct functional activities. PMID:25787765

Fine motor movements while drawing during the encoding phase of a serial verbal recall task reduce working memory performance.

PubMed

Tindle, Richard; Longstaff, Mitchell G

2016-02-01

The time-based resource-sharing (TBRS) model of working memory indicates that secondary tasks that capture attention for relatively long periods can result in the interference of working memory processing and maintenance. The current study investigates if discrete and continuous movements have differing effects on a concurrent, verbal serial recall task. In the listening condition, participants were asked to recall spoken words presented in lists of six. In the drawing conditions, participants performed the same task while producing discrete (star) or continuous (circle) movements. As hypothesised, participants recalled more words overall in the listening condition compared to the combined drawing conditions. The prediction that the continuous movement condition would reduce recall compared to listening was also supported. Fine-grained analysis at each serial position revealed significantly more words were recalled at mid serial positions in the listening condition, with worst recall for the continuous condition at position 5 compared to the listening and discrete conditions. Kinematic analysis showed that participants increased the size and speed of the continuous movements resulting in a similar duration and number of strokes for each condition. The duration of brief pauses in the discrete condition was associated with the number of words recalled. The results indicate that fine motor movements reduced working memory performance; however, it was not merely performing a movement but the type of the movement that determined how resources were diverted. In the context of the TBRS, continuous movements could be capturing attention for longer periods relative to discrete movements, reducing verbal serial recall. Copyright © 2016 Elsevier B.V. All rights reserved.

On the form of ROCs constructed from confidence ratings.

PubMed

Malmberg, Kenneth J

2002-03-01

A classical question for memory researchers is whether memories vary in an all-or-nothing, discrete manner (e.g., stored vs. not stored, recalled vs. not recalled), or whether they vary along a continuous dimension (e.g., strength, similarity, or familiarity). For yes-no classification tasks, continuous- and discrete-state models predict nonlinear and linear receiver operating characteristics (ROCs), respectively (D. M. Green & J. A. Swets, 1966; N. A. Macmillan & C. D. Creelman, 1991). Recently, several authors have assumed that these predictions are generalizable to confidence ratings tasks (J. Qin, C. L. Raye, M. K. Johnson, & K. J. Mitchell, 2001; S. D. Slotnick, S. A. Klein, C. S. Dodson, & A. P. Shimamura, 2000, and A. P. Yonelinas, 1999). This assumption is shown to be unwarranted by showing that discrete-state ratings models predict both linear and nonlinear ROCs. The critical factor determining the form of the discrete-state ROC is the response strategy adopted by the classifier.

Long memory analysis by using maximal overlapping discrete wavelet transform

NASA Astrophysics Data System (ADS)

Shafie, Nur Amalina binti; Ismail, Mohd Tahir; Isa, Zaidi

2015-05-01

Long memory process is the asymptotic decay of the autocorrelation or spectral density around zero. The main objective of this paper is to do a long memory analysis by using the Maximal Overlapping Discrete Wavelet Transform (MODWT) based on wavelet variance. In doing so, stock market of Malaysia, China, Singapore, Japan and United States of America are used. The risk of long term and short term investment are also being looked into. MODWT can be analyzed with time domain and frequency domain simultaneously and decomposing wavelet variance to different scales without loss any information. All countries under studied show that they have long memory. Subprime mortgage crisis in 2007 is occurred in the United States of America are possible affect to the major trading countries. Short term investment is more risky than long term investment.

The hippocampus and inferential reasoning: building memories to navigate future decisions

PubMed Central

Zeithamova, Dagmar; Schlichting, Margaret L.; Preston, Alison R.

2012-01-01

A critical aspect of inferential reasoning is the ability to form relationships between items or events that were not experienced together. This review considers different perspectives on the role of the hippocampus in successful inferential reasoning during both memory encoding and retrieval. Intuitively, inference can be thought of as a logical process by which elements of individual existing memories are retrieved and recombined to answer novel questions. Such flexible retrieval is sub-served by the hippocampus and is thought to require specialized hippocampal encoding mechanisms that discretely code events such that event elements are individually accessible from memory. In addition to retrieval-based inference, recent research has also focused on hippocampal processes that support the combination of information acquired across multiple experiences during encoding. This mechanism suggests that by recalling past events during new experiences, connections can be created between newly formed and existing memories. Such hippocampally mediated memory integration would thus underlie the formation of networks of related memories that extend beyond direct experience to anticipate future judgments about the relationships between items and events. We also discuss integrative encoding in the context of emerging evidence linking the hippocampus to the formation of schemas as well as prospective theories of hippocampal function that suggest memories are actively constructed to anticipate future decisions and actions. PMID:22470333

An experimental distributed microprocessor implementation with a shared memory communications and control medium

NASA Technical Reports Server (NTRS)

Mejzak, R. S.

1980-01-01

The distributed processing concept is defined in terms of control primitives, variables, and structures and their use in performing a decomposed discrete Fourier transform (DET) application function. The design assumes interprocessor communications to be anonymous. In this scheme, all processors can access an entire common database by employing control primitives. Access to selected areas within the common database is random, enforced by a hardware lock, and determined by task and subtask pointers. This enables the number of processors to be varied in the configuration without any modifications to the control structure. Decompositional elements of the DFT application function in terms of tasks and subtasks are also described. The experimental hardware configuration consists of IMSAI 8080 chassis which are independent, 8 bit microcomputer units. These chassis are linked together to form a multiple processing system by means of a shared memory facility. This facility consists of hardware which provides a bus structure to enable up to six microcomputers to be interconnected. It provides polling and arbitration logic so that only one processor has access to shared memory at any one time.

Functional neuroanatomy of amygdalohippocampal interconnections and their role in learning and memory.

PubMed

McDonald, Alexander J; Mott, David D

2017-03-01

The amygdalar nuclear complex and hippocampal/parahippocampal region are key components of the limbic system that play a critical role in emotional learning and memory. This Review discusses what is currently known about the neuroanatomy and neurotransmitters involved in amygdalo-hippocampal interconnections, their functional roles in learning and memory, and their involvement in mnemonic dysfunctions associated with neuropsychiatric and neurological diseases. Tract tracing studies have shown that the interconnections between discrete amygdalar nuclei and distinct layers of individual hippocampal/parahippocampal regions are robust and complex. Although it is well established that glutamatergic pyramidal cells in the amygdala and hippocampal region are the major players mediating interconnections between these regions, recent studies suggest that long-range GABAergic projection neurons are also involved. Whereas neuroanatomical studies indicate that the amygdala only has direct interconnections with the ventral hippocampal region, electrophysiological studies and behavioral studies investigating fear conditioning and extinction, as well as amygdalar modulation of hippocampal-dependent mnemonic functions, suggest that the amygdala interacts with dorsal hippocampal regions via relays in the parahippocampal cortices. Possible pathways for these indirect interconnections, based on evidence from previous tract tracing studies, are discussed in this Review. Finally, memory disorders associated with dysfunction or damage to the amygdala, hippocampal region, and/or their interconnections are discussed in relation to Alzheimer's disease, posttraumatic stress disorder (PTSD), and temporal lobe epilepsy. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Cognitive functioning after subthalamic nucleotomy for refractory Parkinson's disease

PubMed Central

McCarter, R.; Walton, N.; Rowan, A.; Gill, S.; Palomo, M.

2000-01-01

OBJECTIVE—To evaluate whether subthalamic nucleotomy produces adverse cognitive effects in patients with Parkinson's disease.
METHOD—Twelve patients with Parkinson's disease underwent stereotactic surgery to the subthalamic nucleus. Presurgical and postsurgical neuropsychological assessment of attention, memory, executive function, language, and verbal intellect were undertaken with a battery of tests designed to minimise potential contamination of cognitive effects by motor symptoms.
RESULTS—There was no statistically significant difference in the cognitive tests results after operation for the group as a whole. Reliable change indexes were generated for the cognitive tests. Reliable change postoperatively was found on specific tests of verbal memory, attention, and planning. Left sided operations were associated with greater incidence of deterioration postsurgery.
CONCLUSIONS—Preliminary data on the first reported cognitive changes after subthalamic nucleotomy suggested few adverse cognitive effects of the surgery although discrete neuropsychological changes were seen in some patients. These effects were consistent with current theories on the cognitive functions of the basal ganglia.

 PMID:10864605

Introduction and Terminology 2-Extendability in 3-Polytopes.

DTIC Science & Technology

1985-01-01

and D.A. Holton, On defect-d matchings in graphs, Discrete Math ., 13, 1975, 41-54. [LGH2] (-), Erratum: "On defect-d matchings, Discrete Mlath., 14...Matching Theory, Vol. 29, knn. Discrete Math ., North- Holland, Amsterdam, 1986. [Plell J. Plesnik, Connectivity of regular graphs and the existence of 1...Plu2] -- ), A theorem on mnatchings in the plane, Graph Theo~ry in Memory of G..4. Dirac, Ann. Discrete Math ., North-Holland. Amisterdarni. to appear

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.

Decoding Overlapping Memories in the Medial Temporal Lobes Using High-Resolution fMRI

ERIC Educational Resources Information Center

Chadwick, Martin J.; Hassabis, Demis; Maguire, Eleanor A.

2011-01-01

The hippocampus is proposed to process overlapping episodes as discrete memory traces, although direct evidence for this in human episodic memory is scarce. Using green-screen technology we created four highly overlapping movies of everyday events. Participants were scanned using high-resolution fMRI while recalling the movies. Multivariate…

Statistical Learning Induces Discrete Shifts in the Allocation of Working Memory Resources

ERIC Educational Resources Information Center

Umemoto, Akina; Scolari, Miranda; Vogel, Edward K.; Awh, Edward

2010-01-01

Observers can voluntarily select which items are encoded into working memory, and the efficiency of this process strongly predicts memory capacity. Nevertheless, the present work suggests that voluntary intentions do not exclusively determine what is encoded into this online workspace. Observers indicated whether any items from a briefly stored…

The Shape of Things to Come: Evaluating Word Frequency as a Continuous Variable in Recognition Memory

ERIC Educational Resources Information Center

Hemmer, Pernille; Criss, Amy H.

2013-01-01

The role of experience in memory, specifically the word frequency (WF) mirror effect showing higher hit rates and lower false alarm rates for low-frequency words, is one of the hallmarks of memory. However, this "regularity of memory" is limited because normative WF has been treated as discrete (low vs. high). We evaluate the extent to…

Visual Working Memory Capacity: From Psychophysics and Neurobiology to Individual Differences

PubMed Central

Luck, Steven J.; Vogel, Edward K.

2013-01-01

Visual working memory capacity is of great interest because it is strongly correlated with overall cognitive ability, can be understood at the level of neural circuits, and is easily measured. Recent studies have shown that capacity influences tasks ranging from saccade targeting to analogical reasoning. A debate has arisen over whether capacity is constrained by a limited number of discrete representations or by an infinitely divisible resource, but the empirical evidence and neural network models currently favor a discrete item limit. Capacity differs markedly across individuals and groups, and recent research indicates that some of these differences reflect true differences in storage capacity whereas others reflect variations in the ability to use memory capacity efficiently. PMID:23850263

Vectorization and parallelization of the finite strip method for dynamic Mindlin plate problems

NASA Technical Reports Server (NTRS)

Chen, Hsin-Chu; He, Ai-Fang

1993-01-01

The finite strip method is a semi-analytical finite element process which allows for a discrete analysis of certain types of physical problems by discretizing the domain of the problem into finite strips. This method decomposes a single large problem into m smaller independent subproblems when m harmonic functions are employed, thus yielding natural parallelism at a very high level. In this paper we address vectorization and parallelization strategies for the dynamic analysis of simply-supported Mindlin plate bending problems and show how to prevent potential conflicts in memory access during the assemblage process. The vector and parallel implementations of this method and the performance results of a test problem under scalar, vector, and vector-concurrent execution modes on the Alliant FX/80 are also presented.

Meditation and Music Improve Memory and Cognitive Function in Adults with Subjective Cognitive Decline: A Pilot Randomized Controlled Trial.

PubMed

Innes, Kim E; Selfe, Terry Kit; Khalsa, Dharma Singh; Kandati, Sahiti

2017-01-01

While effective therapies for preventing or slowing cognitive decline in at-risk populations remain elusive, evidence suggests mind-body interventions may hold promise. In this study, we assessed the effects of Kirtan Kriya meditation (KK) and music listening (ML) on cognitive outcomes in adults experiencing subjective cognitive decline (SCD), a strong predictor of Alzheimer's disease. Sixty participants with SCD were randomized to a KK or ML program and asked to practice 12 minutes/day for 3 months, then at their discretion for the ensuing 3 months. At baseline, 3 months, and 6 months we measured memory and cognitive functioning [Memory Functioning Questionnaire (MFQ), Trail-making Test (TMT-A/B), and Digit-Symbol Substitution Test (DSST)]. The 6-month study was completed by 53 participants (88%). Participants performed an average of 93% (91% KK, 94% ML) of sessions in the first 3 months, and 71% (68% KK, 74% ML) during the 3-month, practice-optional, follow-up period. Both groups showed marked and significant improvements at 3 months in memory and cognitive performance (MFQ, DSST, TMT-A/B; p's≤0.04). At 6 months, overall gains were maintained or improved (p's≤0.006), with effect sizes ranging from medium (DSST, ML group) to large (DSST, KK group; TMT-A/B, MFQ). Changes were unrelated to treatment expectancies and did not differ by age, gender, baseline cognition scores, or other factors. Findings of this preliminary randomized controlled trial suggest practice of meditation or ML can significantly enhance both subjective memory function and objective cognitive performance in adults with SCD, and may offer promise for improving outcomes in this population.

The theta/gamma discrete phase code occuring during the hippocampal phase precession may be a more general brain coding scheme.

PubMed

Lisman, John

2005-01-01

In the hippocampus, oscillations in the theta and gamma frequency range occur together and interact in several ways, indicating that they are part of a common functional system. It is argued that these oscillations form a coding scheme that is used in the hippocampus to organize the readout from long-term memory of the discrete sequence of upcoming places, as cued by current position. This readout of place cells has been analyzed in several ways. First, plots of the theta phase of spikes vs. position on a track show a systematic progression of phase as rats run through a place field. This is termed the phase precession. Second, two cells with nearby place fields have a systematic difference in phase, as indicated by a cross-correlation having a peak with a temporal offset that is a significant fraction of a theta cycle. Third, several different decoding algorithms demonstrate the information content of theta phase in predicting the animal's position. It appears that small phase differences corresponding to jitter within a gamma cycle do not carry information. This evidence, together with the finding that principle cells fire preferentially at a given gamma phase, supports the concept of theta/gamma coding: a given place is encoded by the spatial pattern of neurons that fire in a given gamma cycle (the exact timing within a gamma cycle being unimportant); sequential places are encoded in sequential gamma subcycles of the theta cycle (i.e., with different discrete theta phase). It appears that this general form of coding is not restricted to readout of information from long-term memory in the hippocampus because similar patterns of theta/gamma oscillations have been observed in multiple brain regions, including regions involved in working memory and sensory integration. It is suggested that dual oscillations serve a general function: the encoding of multiple units of information (items) in a way that preserves their serial order. The relationship of such coding to that proposed by Singer and von der Malsburg is discussed; in their scheme, theta is not considered. It is argued that what theta provides is the absolute phase reference needed for encoding order. Theta/gamma coding therefore bears some relationship to the concept of "word" in digital computers, with word length corresponding to the number of gamma cycles within a theta cycle, and discrete phase corresponding to the ordered "place" within a word. Copyright 2005 Wiley-Liss, Inc.

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.

The Selectivity of Aversive Memory Reconsolidation and Extinction Processes Depends on the Initial Encoding of the Pavlovian Association

ERIC Educational Resources Information Center

Debiec, Jacek; Diaz-Mataix, Lorenzo; Bush, David E. A.; Doyère, Valérie; LeDoux, Joseph E.

2013-01-01

In reconsolidation studies, memories are typically retrieved by an exposure to a single conditioned stimulus (CS). We have previously demonstrated that reconsolidation processes are CS-selective, suggesting that memories retrieved by the CS exposure are discrete and reconsolidate separately. Here, using a compound stimulus in which two distinct…

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.

Distinguishing discrete and gradient category structure in language: Insights from verb-particle constructions.

PubMed

Brehm, Laurel; Goldrick, Matthew

2017-10-01

The current work uses memory errors to examine the mental representation of verb-particle constructions (VPCs; e.g., make up the story, cut up the meat). Some evidence suggests that VPCs are represented by a cline in which the relationship between the VPC and its component elements ranges from highly transparent (cut up) to highly idiosyncratic (make up). Other evidence supports a multiple class representation, characterizing VPCs as belonging to discretely separated classes differing in semantic and syntactic structure. We outline a novel paradigm to investigate the representation of VPCs in which we elicit illusory conjunctions, or memory errors sensitive to syntactic structure. We then use a novel application of piecewise regression to demonstrate that the resulting error pattern follows a cline rather than discrete classes. A preregistered replication verifies these findings, and a final preregistered study verifies that these errors reflect syntactic structure. This provides evidence for gradient rather than discrete representations across levels of representation in language processing. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Collaborative activity between parietal and dorso-lateral prefrontal cortex in dynamic spatial working memory revealed by fMRI.

PubMed

Diwadkar, V A; Carpenter, P A; Just, M A

2000-07-01

Functional MRI was used to determine how the constituents of the cortical network subserving dynamic spatial working memory respond to two types of increases in task complexity. Participants mentally maintained the most recent location of either one or three objects as the three objects moved discretely in either a two- or three-dimensional array. Cortical activation in the dorsolateral prefrontal (DLPFC) and the parietal cortex increased as a function of the number of object locations to be maintained and the dimensionality of the display. An analysis of the response characteristics of the individual voxels showed that a large proportion were activated only when both the variables imposed the higher level of demand. A smaller proportion were activated specifically in response to increases in task demand associated with each of the independent variables. A second experiment revealed the same effect of dimensionality in the parietal cortex when the movement of objects was signaled auditorily rather than visually, indicating that the additional representational demands induced by 3-D space are independent of input modality. The comodulation of activation in the prefrontal and parietal areas by the amount of computational demand suggests that the collaboration between areas is a basic feature underlying much of the functionality of spatial working memory. Copyright 2000 Academic Press.

Augmentation of the noradrenergic system in alpha-2 adrenergic receptor deficient mice: anatomical changes associated with enhanced fear memory.

PubMed

Davies, M Frances; Tsui, Janet Y; Flannery, Judy A; Li, Xiangqi; DeLorey, Timothy M; Hoffman, Brian B

2003-10-03

We have investigated sensitivity to the conditioned fear procedure of mice is influenced by the genetic deletion of alpha2A adrenoceptors (ARs). We observed a heightened freezing response in the discrete cue memory test in alpha2A AR knockout (alpha2A AR KO) mice and in D79N mice, a transgenic mouse strain with functionally impaired alpha2A ARs. No significant differences in contextual memory were observed between control and alpha2A AR KO or D79N mice suggesting a minimal role for the noradrenergic system in contextual memory. We speculated that the increased freezing response of the alpha2A AR KO and D79N mice in the discrete cue setting was due to increased release of norepinephrine evoked by the unconditioned footshock stimulus. In alpha2A AR KO mice we measured a doubling in the number of noradrenergic neurons in the locus coeruleus (LC) and a large increase in the cell volume of tyrosine hydroxylase positive neurons, likely due to selective preservation of large, multipolar neurons in the subcoeruleus. Hyperplasia of the noradrenergic neurons in the nucleus tractus solitarius, A5 and A7, was also observed. Alpha2A AR KO mice exhibit greater c-Fos expression in the LC compared to wild type mice suggesting that the LC neurons in the alpha2A AR KO mice were spontaneously more active. This study suggests that alpha2A ARs are involved in the development of the central noradrenergic system and raises the possibility that alterations in alpha2A AR expression may contribute to variations in fear and stress responses.

Fear conditioning leads to alteration in specific genes expression in cortical and thalamic neurons that project to the lateral amygdala.

PubMed

Katz, Ira K; Lamprecht, Raphael

2015-02-01

RNA transcription is needed for memory formation. However, the ability to identify genes whose expression is altered by learning is greatly impaired because of methodological difficulties in profiling gene expression in specific neurons involved in memory formation. Here, we report a novel approach to monitor the expression of genes after learning in neurons in specific brain pathways needed for memory formation. In this study, we aimed to monitor gene expression after fear learning. We retrogradely labeled discrete thalamic neurons that project to the lateral amygdala (LA) of rats. The labeled neurons were dissected, using laser microdissection microscopy, after fear conditioning learning or unpaired training. The RNAs from the dissected neurons were subjected to microarray analysis. The levels of selected RNAs detected by the microarray analysis to be altered by fear conditioning were also assessed by nanostring analysis. We observed that the expression of genes involved in the regulation of translation, maturation and degradation of proteins was increased 6 h after fear conditioning compared to unpaired or naïve trained rats. These genes were not expressed 24 h after training or in cortical neurons that project to the LA. The expression of genes involved in transcription regulation and neuronal development was altered after fear conditioning learning in the cortical-LA pathway. The present study provides key information on the identity of genes expressed in discrete thalamic and cortical neurons that project to the LA after fear conditioning. Such an approach could also serve to identify gene products as targets for the development of a new generation of therapeutic agents that could be aimed to functionally identified brain circuits to treat memory-related disorders. © 2014 International Society for Neurochemistry.

ERP evaluation of auditory sensory memory systems in adults with intellectual disability.

PubMed

Ikeda, Kazunari; Hashimoto, Souichi; Hayashi, Akiko; Kanno, Atsushi

2009-01-01

Auditory sensory memory stage can be functionally divided into two subsystems; transient-detector system and permanent feature-detector system (Naatanen, 1992). We assessed these systems in persons with intellectual disability by measuring event-related potentials (ERPs) N1 and mismatch negativity (MMN), which reflect the two auditory subsystems, respectively. Added to these, P3a (an ERP reflecting stage after sensory memory) was evaluated. Either synthesized vowels or simple tones were delivered during a passive oddball paradigm to adults with and without intellectual disability. ERPs were recorded from midline scalp sites (Fz, Cz, and Pz). Relative to control group, participants with the disability exhibited greater N1 latency and less MMN amplitude. The results for N1 amplitude and MMN latency were basically comparable between both groups. IQ scores in participants with the disability revealed no significant relation with N1 and MMN measures, whereas the IQ scores tended to increase significantly as P3a latency reduced. These outcomes suggest that persons with intellectual disability might own discrete malfunctions for the two detector systems in auditory sensory-memory stage. Moreover, the processes following sensory memory might be partly related to a determinant of mental development.

Inhomogeneous diffusion and ergodicity breaking induced by global memory effects

NASA Astrophysics Data System (ADS)

Budini, Adrián A.

2016-11-01

We introduce a class of discrete random-walk model driven by global memory effects. At any time, the right-left transitions depend on the whole previous history of the walker, being defined by an urnlike memory mechanism. The characteristic function is calculated in an exact way, which allows us to demonstrate that the ensemble of realizations is ballistic. Asymptotically, each realization is equivalent to that of a biased Markovian diffusion process with transition rates that strongly differs from one trajectory to another. Using this "inhomogeneous diffusion" feature, the ergodic properties of the dynamics are analytically studied through the time-averaged moments. Even in the long-time regime, they remain random objects. While their average over realizations recovers the corresponding ensemble averages, departure between time and ensemble averages is explicitly shown through their probability densities. For the density of the second time-averaged moment, an ergodic limit and the limit of infinite lag times do not commutate. All these effects are induced by the memory effects. A generalized Einstein fluctuation-dissipation relation is also obtained for the time-averaged moments.

Deletion of the GluA1 AMPA Receptor Subunit Alters the Expression of Short-Term Memory

ERIC Educational Resources Information Center

Sanderson, David J.; Sprengel, Rolf; Seeburg, Peter H.; Bannerman, David M.

2011-01-01

Deletion of the GluA1 AMPA receptor subunit selectively impairs short-term memory for spatial locations. We further investigated this deficit by examining memory for discrete nonspatial visual stimuli in an operant chamber. Unconditioned suppression of magazine responding to visual stimuli was measured in wild-type and GluA1 knockout mice.…

Reconsolidation and update of morphine-associated contextual memory in mice.

PubMed

Escosteguy-Neto, Joao Carlos; Varela, Patricia; Correa-Neto, Nelson Francisco; Coelho, Laura Segismundo; Onaivi, Emmanuel S; Santos-Junior, Jair Guilherme

2016-04-01

Drug addiction can be viewed as a pathological memory that is constantly retrieved and reconsolidated. Since drug abuse takes place in different contexts, it could be considered that reconsolidation plays a role in memory updating. There is consistent evidence supporting the role of reconsolidation in the strength and maintenance of contextual memories induced by drugs of abuse. However, this role is not well established in memory update. The purpose of the current study was to assess the reconsolidation process over memory update. C57BL6 mice were subjected to a morphine-induced, conditioned place preference (CPP) paradigm. Based on CPP results, animals were divided into distinct experimental groups, according to the contextual characteristics of the re-exposure and a second CPP Test. Re-exposure in the original context was important for memory maintenance and re-exposure under discrete contextual changes resulted in memory updating, although original memory was maintained. Interestingly, cycloheximide, an inhibitor of protein synthesis, had different outcomes in our protocol. When the re-exposure was done under discrete contextual changes, cycloheximide treatment just after re-exposure blocked memory updating, without changes in memory maintenance. When re-exposure was done under the original context, only two subsequent cycloheximide injections (3 and 6h) disrupted later CPP expression. Considering the temporal window of protein synthesis in consolidation and reconsolidation, these findings suggest that re-exposure, according to the contextual characteristics in our protocol, could trigger both phenomena. Furthermore, when new information is present on retrieval, reconsolidation plays a pivotal role in memory updating. Copyright © 2016 Elsevier Inc. All rights reserved.

Matching Extension and Connectivity in Graphs. 1. Introduction and Terminology,

DTIC Science & Technology

1986-01-01

minimal elementary bipartite graphs, J. Combin. Theory Ser. B 23, 1977, 127-138. 1986. Matching Theory, Ann. Discrete Math ., North-Holland, Amsterdam, 1986...to appear). M. D. PLUMMER 1980. On n-extendable graphs, Discrete Math . 31, 1980, 201-210. 1985. A theorem on matchings in the plane, Conference in...memory of Gabriel Dirac, Ann. Discrete Math ., North-Holland, Amsterdam, to appear. 1986a. Matching extension in bipartite graphs, preprint, 1986. 1986b

Neurocognitive impairment and psychosis in bipolar I disorder during early remission from an acute episode of mood disturbance.

PubMed

Levy, Boaz; Weiss, Roger D

2010-02-01

Recent studies have reported greater neurocognitive impairment in euthymic bipolar disorder patients with a history of psychosis relative to patients without such a history. To further explore the relation between psychosis and cognitive dysfunction in bipolar disorder, the current study examined the cognitive functioning of patients during early remission from a discrete episode of mood disturbance. The study aimed to determine whether the presence of psychosis during inpatient hospitalization was associated with greater cognitive impairment at the time of hospital discharge. Fifty-nine inpatients who met DSM-IV criteria for bipolar disorder (24 admitted with psychosis, 35 admitted without psychosis), ages 18-59 years, completed a neuropsychological battery and mood measures 24-48 hours before discharge. The cognitive battery included standardized tests of IQ, attention and working memory, visual memory, verbal memory, and executive functioning. A multivariate analysis of variance detected group differences on measures of verbal memory (P < .001) and executive functioning (P < .003), using mood measures and previous number of psychiatric admissions as covariates. Post hoc analysis of between-subjects effects revealed significantly poorer performance on the California Verbal Learning Test-Second Edition, logical memory subtest from Wechsler Memory Scale-Revised, Stroop Word/Color Interference test, and the Wisconsin Card Sorting Test for patients who were admitted to the hospital with psychosis. These results remained significant after matching the groups for past psychosis, with the exception of the logical memory subtest. The results of this study indicate that patients with bipolar disorder who were admitted to the hospital due to psychosis exhibited significantly more severe cognitive impairment at the time of discharge than patients admitted for an acute mood disturbance without psychosis. These findings may be important for improving discharge planning and the development of more effective outpatient services. Copyright 2010 Physicians Postgraduate Press, Inc.

On the fractional Eulerian numbers and equivalence of maps with long term power-law memory (integral Volterra equations of the second kind) to Grünvald-Letnikov fractional difference (differential) equations.

PubMed

Edelman, Mark

2015-07-01

In this paper, we consider a simple general form of a deterministic system with power-law memory whose state can be described by one variable and evolution by a generating function. A new value of the system's variable is a total (a convolution) of the generating functions of all previous values of the variable with weights, which are powers of the time passed. In discrete cases, these systems can be described by difference equations in which a fractional difference on the left hand side is equal to a total (also a convolution) of the generating functions of all previous values of the system's variable with the fractional Eulerian number weights on the right hand side. In the continuous limit, the considered systems can be described by the Grünvald-Letnikov fractional differential equations, which are equivalent to the Volterra integral equations of the second kind. New properties of the fractional Eulerian numbers and possible applications of the results are discussed.

Tracking the Fear Memory Engram: Discrete Populations of Neurons within Amygdala, Hypothalamus, and Lateral Septum Are Specifically Activated by Auditory Fear Conditioning

ERIC Educational Resources Information Center

Butler, Christopher W.; Wilson, Yvette M.; Gunnersen, Jenny M.; Murphy, Mark

2015-01-01

Memory formation is thought to occur via enhanced synaptic connectivity between populations of neurons in the brain. However, it has been difficult to localize and identify the neurons that are directly involved in the formation of any specific memory. We have previously used "fos-tau-lacZ" ("FTL") transgenic mice to identify…

Exponential H(infinity) synchronization of general discrete-time chaotic neural networks with or without time delays.

PubMed

Qi, Donglian; Liu, Meiqin; Qiu, Meikang; Zhang, Senlin

2010-08-01

This brief studies exponential H(infinity) synchronization of a class of general discrete-time chaotic neural networks with external disturbance. On the basis of the drive-response concept and H(infinity) control theory, and using Lyapunov-Krasovskii (or Lyapunov) functional, state feedback controllers are established to not only guarantee exponential stable synchronization between two general chaotic neural networks with or without time delays, but also reduce the effect of external disturbance on the synchronization error to a minimal H(infinity) norm constraint. The proposed controllers can be obtained by solving the convex optimization problems represented by linear matrix inequalities. Most discrete-time chaotic systems with or without time delays, such as Hopfield neural networks, cellular neural networks, bidirectional associative memory networks, recurrent multilayer perceptrons, Cohen-Grossberg neural networks, Chua's circuits, etc., can be transformed into this general chaotic neural network to be H(infinity) synchronization controller designed in a unified way. Finally, some illustrated examples with their simulations have been utilized to demonstrate the effectiveness of the proposed methods.

Prefrontal consolidation supports the attainment of fear memory accuracy

PubMed Central

Vieira, Philip A.; Lovelace, Jonathan W.; Corches, Alex; Rashid, Asim J.; Josselyn, Sheena A.

2014-01-01

The neural mechanisms underlying the attainment of fear memory accuracy for appropriate discriminative responses to aversive and nonaversive stimuli are unclear. Considerable evidence indicates that coactivator of transcription and histone acetyltransferase cAMP response element binding protein (CREB) binding protein (CBP) is critically required for normal neural function. CBP hypofunction leads to severe psychopathological symptoms in human and cognitive abnormalities in genetic mutant mice with severity dependent on the neural locus and developmental time of the gene inactivation. Here, we showed that an acute hypofunction of CBP in the medial prefrontal cortex (mPFC) results in a disruption of fear memory accuracy in mice. In addition, interruption of CREB function in the mPFC also leads to a deficit in auditory discrimination of fearful stimuli. While mice with deficient CBP/CREB signaling in the mPFC maintain normal responses to aversive stimuli, they exhibit abnormal responses to similar but nonrelevant stimuli when compared to control animals. These data indicate that improvement of fear memory accuracy involves mPFC-dependent suppression of fear responses to nonrelevant stimuli. Evidence from a context discriminatory task and a newly developed task that depends on the ability to distinguish discrete auditory cues indicated that CBP-dependent neural signaling within the mPFC circuitry is an important component of the mechanism for disambiguating the meaning of fear signals with two opposing values: aversive and nonaversive. PMID:25031365

Matching Theory - A Sampler: From Denes Koenig to the Present

DTIC Science & Technology

1991-01-01

1079. [1131 , Matching Theory, Ann. Discrete Math . 29, North- Holland, Amsterdam, 1986. [114 ] M. Luby, A simple parallel algorithm for the maximal...311. [135 ]M.D. Plummer, On n-extendable graphs, Discrete Math . 31, 1980, 201-210. [1361 , Matching extension and the genus of a graph, J. Combin...Theory Ser. B, 44, 1988, 329-837. [137] , A theorem on matchings in the plane, Graph Theory in Memory of G.A. Dirac, Ann. Discrete Math . 41, North

On the 2-Extendability of Planar Graphs

DTIC Science & Technology

1989-01-01

connectivity for n-extend- ability of regular graphs, 1988, submitted. [6] L. Lov~isz and M.D. Plummer, Matching Theory, Ann. Discrete Math . 29, North...Holland, Amsterdam, 1986. [7] M.D. Plummer, On n-extendable graphs, Discrete Math . 31, 1980, 201-210. [8] M.D. Plummer, A theorem on matchings in the...plane, Graph Theory in Memory of G.A. Dirac, Ann. Discrete Math . 41, North-Holland, Amsterdam, 1989, 347-354. [9] C. Thomassen, Girth in graphs, J

Claw-Free Maximal Planar Graphs

DTIC Science & Technology

1989-01-01

1976, 212-223. 110] M.D. Plummer, On n-extendable graphs, Discrete Math . 31, 1980, 201-210. 1111 , A theorem on matchings in the plane, Graph Theory...in Memory of G.A. Dirac, Ann. Discrete Math . 41, North-Holland, Amsterdam, 1989, 347-354. 1121 N. Sbihi, Algorithme de recherche d’un stable de...cardinalitA maximum dans un graphe sans 6toile, Discrete Math . 29, 1980, 53-76. 1131 D. Sumner, On Tutte’s factorization theorem, Graphs and Combinatorics

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.

Fast maximum likelihood estimation using continuous-time neural point process models.

PubMed

Lepage, Kyle Q; MacDonald, Christopher J

2015-06-01

A recent report estimates that the number of simultaneously recorded neurons is growing exponentially. A commonly employed statistical paradigm using discrete-time point process models of neural activity involves the computation of a maximum-likelihood estimate. The time to computate this estimate, per neuron, is proportional to the number of bins in a finely spaced discretization of time. By using continuous-time models of neural activity and the optimally efficient Gaussian quadrature, memory requirements and computation times are dramatically decreased in the commonly encountered situation where the number of parameters p is much less than the number of time-bins n. In this regime, with q equal to the quadrature order, memory requirements are decreased from O(np) to O(qp), and the number of floating-point operations are decreased from O(np(2)) to O(qp(2)). Accuracy of the proposed estimates is assessed based upon physiological consideration, error bounds, and mathematical results describing the relation between numerical integration error and numerical error affecting both parameter estimates and the observed Fisher information. A check is provided which is used to adapt the order of numerical integration. The procedure is verified in simulation and for hippocampal recordings. It is found that in 95 % of hippocampal recordings a q of 60 yields numerical error negligible with respect to parameter estimate standard error. Statistical inference using the proposed methodology is a fast and convenient alternative to statistical inference performed using a discrete-time point process model of neural activity. It enables the employment of the statistical methodology available with discrete-time inference, but is faster, uses less memory, and avoids any error due to discretization.

Protein Kinase A Deregulation in the Medial Prefrontal Cortex Impairs Working Memory in Murine Oligophrenin-1 Deficiency.

PubMed

Zhang, Chun-Lei; Aime, Mattia; Laheranne, Emilie; Houbaert, Xander; El Oussini, Hajer; Martin, Christelle; Lepleux, Marilyn; Normand, Elisabeth; Chelly, Jamel; Herzog, Etienne; Billuart, Pierre; Humeau, Yann

2017-11-15

Classical and systems genetics have identified wide networks of genes associated with cognitive and neurodevelopmental diseases. In parallel to deciphering the role of each of these genes in neuronal or synaptic function, evaluating the response of neuronal and molecular networks to gene loss of function could reveal some pathophysiological mechanisms potentially accessible to nongenetic therapies. Loss of function of the Rho-GAP oligophrenin-1 is associated with cognitive impairments in both human and mouse. Upregulation of both PKA and ROCK has been reported in Ophn1 -/ y mice, but it remains unclear whether kinase hyperactivity contributes to the behavioral phenotypes. In this study, we thoroughly characterized a prominent perseveration phenotype displayed by Ophn1 -deficient mice using a Y-maze spatial working memory (SWM) test. We report that Ophn1 deficiency in the mouse generated severe cognitive impairments, characterized by both a high occurrence of perseverative behaviors and a lack of deliberation during the SWM test. In vivo and in vitro pharmacological experiments suggest that PKA dysregulation in the mPFC underlies cognitive dysfunction in Ophn1 -deficient mice, as assessed using a delayed spatial alternation task results. Functionally, mPFC neuronal networks appeared to be affected in a PKA-dependent manner, whereas hippocampal-PFC projections involved in SWM were not affected in Ophn1 -/y mice. Thus, we propose that discrete gene mutations in intellectual disability might generate "secondary" pathophysiological mechanisms, which are prone to become pharmacological targets for curative strategies in adult patients. SIGNIFICANCE STATEMENT Here we report that Ophn1 deficiency generates severe impairments in performance at spatial working memory tests, characterized by a high occurrence of perseverative behaviors and a lack of decision making. This cognitive deficit is consecutive to PKA deregulation in the mPFC that prevents Ophn1 KO mice to exploit a correctly acquired rule. Functionally, mPFC neuronal networks appear to be affected in a PKA-dependent manner, whereas behaviorally important hippocampal projections were preserved by the mutation. Thus, we propose that discrete gene mutations in intellectual disability can generate "secondary" pathophysiological mechanisms prone to become pharmacological targets for curative strategies in adults. Copyright © 2017 the authors 0270-6474/17/3711114-13$15.00/0.

Weaknesses in executive functioning predict the initiating of adolescents' alcohol use.

PubMed

Peeters, Margot; Janssen, Tim; Monshouwer, Karin; Boendermaker, Wouter; Pronk, Thomas; Wiers, Reinout; Vollebergh, Wilma

2015-12-01

Recently, it has been suggested that impairments in executive functioning might be risk factors for the onset of alcohol use rather than a result of heavy alcohol use. In the present study, we examined whether two aspects of executive functioning, working memory and response inhibition, predicted the first alcoholic drink and first binge drinking episode in young adolescents using discrete survival analyses. Adolescents were selected from several Dutch secondary schools including both mainstream and special education (externalizing behavioral problems). Participants were 534 adolescents between 12 and 14 years at baseline. Executive functioning and alcohol use were assessed four times over a period of two years. Working memory uniquely predicted the onset of first drink (p=.01) and first binge drinking episode (p=.04) while response inhibition only uniquely predicted the initiating of the first drink (p=.01). These results suggest that the association of executive functioning and alcohol consumption found in former studies cannot simply be interpreted as an effect of alcohol consumption, as weaknesses in executive functioning, found in alcohol naïve adolescents, predict the initiating of (binge) drinking. Though, prolonged and heavy alcohol use might further weaken already existing deficiencies. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Unified implicit kinetic scheme for steady multiscale heat transfer based on the phonon Boltzmann transport equation

NASA Astrophysics Data System (ADS)

Zhang, Chuang; Guo, Zhaoli; Chen, Songze

2017-12-01

An implicit kinetic scheme is proposed to solve the stationary phonon Boltzmann transport equation (BTE) for multiscale heat transfer problem. Compared to the conventional discrete ordinate method, the present method employs a macroscopic equation to accelerate the convergence in the diffusive regime. The macroscopic equation can be taken as a moment equation for phonon BTE. The heat flux in the macroscopic equation is evaluated from the nonequilibrium distribution function in the BTE, while the equilibrium state in BTE is determined by the macroscopic equation. These two processes exchange information from different scales, such that the method is applicable to the problems with a wide range of Knudsen numbers. Implicit discretization is implemented to solve both the macroscopic equation and the BTE. In addition, a memory reduction technique, which is originally developed for the stationary kinetic equation, is also extended to phonon BTE. Numerical comparisons show that the present scheme can predict reasonable results both in ballistic and diffusive regimes with high efficiency, while the memory requirement is on the same order as solving the Fourier law of heat conduction. The excellent agreement with benchmark and the rapid converging history prove that the proposed macro-micro coupling is a feasible solution to multiscale heat transfer problems.

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

Spiking neural network simulation: memory-optimal synaptic event scheduling.

PubMed

Stewart, Robert D; Gurney, Kevin N

2011-06-01

Spiking neural network simulations incorporating variable transmission delays require synaptic events to be scheduled prior to delivery. Conventional methods have memory requirements that scale with the total number of synapses in a network. We introduce novel scheduling algorithms for both discrete and continuous event delivery, where the memory requirement scales instead with the number of neurons. Superior algorithmic performance is demonstrated using large-scale, benchmarking network simulations.

Fast transient digitizer

DOEpatents

Villa, Francesco

1982-01-01

Method and apparatus for sequentially scanning a plurality of target elements with an electron scanning beam modulated in accordance with variations in a high-frequency analog signal to provide discrete analog signal samples representative of successive portions of the analog signal; coupling the discrete analog signal samples from each of the target elements to a different one of a plurality of high speed storage devices; converting the discrete analog signal samples to equivalent digital signals; and storing the digital signals in a digital memory unit for subsequent measurement or display.

Application of dynamic programming to control khuzestan water resources system

USGS Publications Warehouse

Jamshidi, M.; Heidari, M.

1977-01-01

An approximate optimization technique based on discrete dynamic programming called discrete differential dynamic programming (DDDP), is employed to obtain the near optimal operation policies of a water resources system in the Khuzestan Province of Iran. The technique makes use of an initial nominal state trajectory for each state variable, and forms corridors around the trajectories. These corridors represent a set of subdomains of the entire feasible domain. Starting with such a set of nominal state trajectories, improvements in objective function are sought within the corridors formed around them. This leads to a set of new nominal trajectories upon which more improvements may be sought. Since optimization is confined to a set of subdomains, considerable savings in memory and computer time are achieved over that of conventional dynamic programming. The Kuzestan water resources system considered in this study is located in southwest Iran, and consists of two rivers, three reservoirs, three hydropower plants, and three irrigable areas. Data and cost benefit functions for the analysis were obtained either from the historical records or from similar studies. ?? 1977.

Designer Receptors Enhance Memory in a Mouse Model of Down Syndrome

PubMed Central

Fortress, Ashley M.; Hamlett, Eric D.; Vazey, Elena M.; Aston-Jones, Gary; Cass, Wayne A.; Boger, Heather A.

2015-01-01

Designer receptors exclusively activated by designer drugs (DREADDs) are novel and powerful tools to investigate discrete neuronal populations in the brain. We have used DREADDs to stimulate degenerating neurons in a Down syndrome (DS) model, Ts65Dn mice. Individuals with DS develop Alzheimer's disease (AD) neuropathology and have elevated risk for dementia starting in their 30s and 40s. Individuals with DS often exhibit working memory deficits coupled with degeneration of the locus coeruleus (LC) norepinephrine (NE) neurons. It is thought that LC degeneration precedes other AD-related neuronal loss, and LC noradrenergic integrity is important for executive function, working memory, and attention. Previous studies have shown that LC-enhancing drugs can slow the progression of AD pathology, including amyloid aggregation, oxidative stress, and inflammation. We have shown that LC degeneration in Ts65Dn mice leads to exaggerated memory loss and neuronal degeneration. We used a DREADD, hM3Dq, administered via adeno-associated virus into the LC under a synthetic promoter, PRSx8, to selectively stimulate LC neurons by exogenous administration of the inert DREADD ligand clozapine-N-oxide. DREADD stimulation of LC-NE enhanced performance in a novel object recognition task and reduced hyperactivity in Ts65Dn mice, without significant behavioral effects in controls. To confirm that the noradrenergic transmitter system was responsible for the enhanced memory function, the NE prodrug l-threo-dihydroxyphenylserine was administered in Ts65Dn and normosomic littermate control mice, and produced similar behavioral results. Thus, NE stimulation may prevent memory loss in Ts65Dn mice, and may hold promise for treatment in individuals with DS and dementia. PMID:25632113

Are planning, working memory, and inhibition associated with individual differences in preschool ADHD symptoms?

PubMed

Sonuga-Barke, Edmund J S; Dalen, Lindy; Daley, Dave; Remington, Bob

2002-01-01

The association between executive function (EF; planning, working memory, and inhibition) and individual differences in symptoms of attention deficit hyperactivity disorder (ADHD) was explored in a sample of preschool children. One hundred sixty children (between the ages of 3 years, 0 months and 5 years, 6 months), selected so as to oversample high ADHD scorers, performed 3 tasks previously shown to measure planning (Tower of London), working memory (Noisy Book) and inhibition ("Puppet Says..."). EF measures were reliable (kappa > .77) and were correlated with IQ (rs > .38) and age (rs > .59). Once IQ and age were controlled, planning and working memory (r = .41) were correlated. Planning and working memory were not correlated with inhibition (rs < .20). There was no association between ADHD and working memory or planning (rs < .12). There was a significant negative association between ADHD and conduct problems and inhibition (r = -.30 and r = -.25, respectively). Only the link with ADHD persisted after the effects of other factors were controlled for in a multiple regression. Specific deficits in inhibitory control rather than general EF deficits are associated with ADHD in the preschool period. This association is linear in nature, supporting the idea that ADHD is better seen as a continuum rather than a discrete category. This association provides evidence for Barkley's (1997) view that ADHD is underpinned by inhibitory deficits in the preschool period.

Stability of discrete memory states to stochastic fluctuations in neuronal systems

PubMed Central

Miller, Paul; Wang, Xiao-Jing

2014-01-01

Noise can degrade memories by causing transitions from one memory state to another. For any biological memory system to be useful, the time scale of such noise-induced transitions must be much longer than the required duration for memory retention. Using biophysically-realistic modeling, we consider two types of memory in the brain: short-term memories maintained by reverberating neuronal activity for a few seconds, and long-term memories maintained by a molecular switch for years. Both systems require persistence of (neuronal or molecular) activity self-sustained by an autocatalytic process and, we argue, that both have limited memory lifetimes because of significant fluctuations. We will first discuss a strongly recurrent cortical network model endowed with feedback loops, for short-term memory. Fluctuations are due to highly irregular spike firing, a salient characteristic of cortical neurons. Then, we will analyze a model for long-term memory, based on an autophosphorylation mechanism of calcium/calmodulin-dependent protein kinase II (CaMKII) molecules. There, fluctuations arise from the fact that there are only a small number of CaMKII molecules at each postsynaptic density (putative synaptic memory unit). Our results are twofold. First, we demonstrate analytically and computationally the exponential dependence of stability on the number of neurons in a self-excitatory network, and on the number of CaMKII proteins in a molecular switch. Second, for each of the two systems, we implement graded memory consisting of a group of bistable switches. For the neuronal network we report interesting ramping temporal dynamics as a result of sequentially switching an increasing number of discrete, bistable, units. The general observation of an exponential increase in memory stability with the system size leads to a trade-off between the robustness of memories (which increases with the size of each bistable unit) and the total amount of information storage (which decreases with increasing unit size), which may be optimized in the brain through biological evolution. PMID:16822041

Episodic Memory Retrieval Benefits from a Less Modular Brain Network Organization

PubMed Central

2017-01-01

Most complex cognitive tasks require the coordinated interplay of multiple brain networks, but the act of retrieving an episodic memory may place especially heavy demands for communication between the frontoparietal control network (FPCN) and the default mode network (DMN), two networks that do not strongly interact with one another in many task contexts. We applied graph theoretical analysis to task-related fMRI functional connectivity data from 20 human participants and found that global brain modularity—a measure of network segregation—is markedly reduced during episodic memory retrieval relative to closely matched analogical reasoning and visuospatial perception tasks. Individual differences in modularity were correlated with memory task performance, such that lower modularity levels were associated with a lower false alarm rate. Moreover, the FPCN and DMN showed significantly elevated coupling with each other during the memory task, which correlated with the global reduction in brain modularity. Both networks also strengthened their functional connectivity with the hippocampus during the memory task. Together, these results provide a novel demonstration that reduced modularity is conducive to effective episodic retrieval, which requires close collaboration between goal-directed control processes supported by the FPCN and internally oriented self-referential processing supported by the DMN. SIGNIFICANCE STATEMENT Modularity, an index of the degree to which nodes of a complex system are organized into discrete communities, has emerged as an important construct in the characterization of brain connectivity dynamics. We provide novel evidence that the modularity of the human brain is reduced when individuals engage in episodic memory retrieval, relative to other cognitive tasks, and that this state of lower modularity is associated with improved memory performance. We propose a neural systems mechanism for this finding where the nodes of the frontoparietal control network and default mode network strengthen their interaction with one another during episodic retrieval. Such across-network communication likely facilitates effective access to internally generated representations of past event knowledge. PMID:28242796

Episodic Memory Retrieval Benefits from a Less Modular Brain Network Organization.

PubMed

Westphal, Andrew J; Wang, Siliang; Rissman, Jesse

2017-03-29

Most complex cognitive tasks require the coordinated interplay of multiple brain networks, but the act of retrieving an episodic memory may place especially heavy demands for communication between the frontoparietal control network (FPCN) and the default mode network (DMN), two networks that do not strongly interact with one another in many task contexts. We applied graph theoretical analysis to task-related fMRI functional connectivity data from 20 human participants and found that global brain modularity-a measure of network segregation-is markedly reduced during episodic memory retrieval relative to closely matched analogical reasoning and visuospatial perception tasks. Individual differences in modularity were correlated with memory task performance, such that lower modularity levels were associated with a lower false alarm rate. Moreover, the FPCN and DMN showed significantly elevated coupling with each other during the memory task, which correlated with the global reduction in brain modularity. Both networks also strengthened their functional connectivity with the hippocampus during the memory task. Together, these results provide a novel demonstration that reduced modularity is conducive to effective episodic retrieval, which requires close collaboration between goal-directed control processes supported by the FPCN and internally oriented self-referential processing supported by the DMN. SIGNIFICANCE STATEMENT Modularity, an index of the degree to which nodes of a complex system are organized into discrete communities, has emerged as an important construct in the characterization of brain connectivity dynamics. We provide novel evidence that the modularity of the human brain is reduced when individuals engage in episodic memory retrieval, relative to other cognitive tasks, and that this state of lower modularity is associated with improved memory performance. We propose a neural systems mechanism for this finding where the nodes of the frontoparietal control network and default mode network strengthen their interaction with one another during episodic retrieval. Such across-network communication likely facilitates effective access to internally generated representations of past event knowledge. Copyright © 2017 the authors 0270-6474/17/373523-09$15.00/0.

Layered reward signalling through octopamine and dopamine in Drosophila.

PubMed

Burke, Christopher J; Huetteroth, Wolf; Owald, David; Perisse, Emmanuel; Krashes, Michael J; Das, Gaurav; Gohl, Daryl; Silies, Marion; Certel, Sarah; Waddell, Scott

2012-12-20

Dopamine is synonymous with reward and motivation in mammals. However, only recently has dopamine been linked to motivated behaviour and rewarding reinforcement in fruitflies. Instead, octopamine has historically been considered to be the signal for reward in insects. Here we show, using temporal control of neural function in Drosophila, that only short-term appetitive memory is reinforced by octopamine. Moreover, octopamine-dependent memory formation requires signalling through dopamine neurons. Part of the octopamine signal requires the α-adrenergic-like OAMB receptor in an identified subset of mushroom-body-targeted dopamine neurons. Octopamine triggers an increase in intracellular calcium in these dopamine neurons, and their direct activation can substitute for sugar to form appetitive memory, even in flies lacking octopamine. Analysis of the β-adrenergic-like OCTβ2R receptor reveals that octopamine-dependent reinforcement also requires an interaction with dopamine neurons that control appetitive motivation. These data indicate that sweet taste engages a distributed octopamine signal that reinforces memory through discrete subsets of mushroom-body-targeted dopamine neurons. In addition, they reconcile previous findings with octopamine and dopamine and suggest that reinforcement systems in flies are more similar to mammals than previously thought.

Recollection and Familiarity in Recognition Memory: Evidence from ROC Curves

ERIC Educational Resources Information Center

Heathcote, Andrew; Raymond, Frances; Dunn, John

2006-01-01

Does recognition memory rely on discrete recollection, continuous evidence, or both? Is continuous evidence sensitive to only the recency and duration of study (familiarity), or is it also sensitive to details of the study episode? Dual process theories assume recognition is based on recollection and familiarity, with only recollection providing…

Binary ROCs in Perception and Recognition Memory Are Curved

ERIC Educational Resources Information Center

Dube, Chad; Rotello, Caren M.

2012-01-01

In recognition memory, a classic finding is that receiver operating characteristics (ROCs) are curvilinear. This has been taken to support the fundamental assumptions of signal detection theory (SDT) over discrete-state models such as the double high-threshold model (2HTM), which predicts linear ROCs. Recently, however, Broder and Schutz (2009)…

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

NASA Astrophysics Data System (ADS)

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

2003-05-01

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

Fractional discrete-time consensus models for single- and double-summator dynamics

NASA Astrophysics Data System (ADS)

Wyrwas, Małgorzata; Mozyrska, Dorota; Girejko, Ewa

2018-04-01

The leader-following consensus problem of fractional-order multi-agent discrete-time systems is considered. In the systems, interactions between opinions are defined like in Krause and Cucker-Smale models but the memory is included by taking the fractional-order discrete-time operator on the left-hand side of the nonlinear systems. In this paper, we investigate fractional-order models of opinions for the single- and double-summator dynamics of discrete-time by analytical methods as well as by computer simulations. The necessary and sufficient conditions for the leader-following consensus are formulated by proposing a consensus control law for tracking the virtual leader.

Differential modulation of changes in hippocampal-septal synaptic excitability by the amygdala as a function of either elemental or contextual fear conditioning in mice.

PubMed

Desmedt, A; Garcia, R; Jaffard, R

1998-01-01

Recent data obtained using a classic fear conditioning paradigm showed a dissociation between the retention of associations relative to contextual information (dependent on the hippocampal formation) and the retention of elemental associations (dependent on the amygdala). Furthermore, it was reported that conditioned emotional responses (CERs) could be dissociated from the recollection of the learning experience (declarative memory) in humans and from modifications of the hippocampal-septal excitability in animals. Our aim was to determine whether these two systems ("behavioral expression" system and "factual memory" system) interact by examining the consequences of amygdalar lesions (1) on the modifications of hippocampal-septal excitability and (2) on the behavioral expression of fear (freezing) resulting from an aversive conditioning during reexposure to conditional stimuli (CSs). During conditioning, to modulate the predictive nature of the context and of a discrete stimulus (tone) on the unconditional stimulus (US) occurrence, the phasic discrete CS was paired with the US or randomly distributed with regard to the US. After the lesion, the CER was dramatically reduced during reexposure to the CSs, whatever the type of acquisition. However, the changes in hippocampal-septal excitability persisted but were altered. For controls, a decrease in septal excitability was observed during reexposure to the conditioning context only for the "unpaired group" (predictive context case). Conversely, among lesioned subjects this decrease was observed in the "paired group" (predictive discrete CS case), whereas this decrease was significantly reduced in the unpaired group with respect to the matched control group. The amplitude and the direction of these modifications suggest a differential modulation of hippocampal-septal excitability by the amygdala to amplify the contribution of the more predictive association signaling the occurrence of the aversive event.

Prefrontal consolidation supports the attainment of fear memory accuracy.

PubMed

Vieira, Philip A; Lovelace, Jonathan W; Corches, Alex; Rashid, Asim J; Josselyn, Sheena A; Korzus, Edward

2014-08-01

The neural mechanisms underlying the attainment of fear memory accuracy for appropriate discriminative responses to aversive and nonaversive stimuli are unclear. Considerable evidence indicates that coactivator of transcription and histone acetyltransferase cAMP response element binding protein (CREB) binding protein (CBP) is critically required for normal neural function. CBP hypofunction leads to severe psychopathological symptoms in human and cognitive abnormalities in genetic mutant mice with severity dependent on the neural locus and developmental time of the gene inactivation. Here, we showed that an acute hypofunction of CBP in the medial prefrontal cortex (mPFC) results in a disruption of fear memory accuracy in mice. In addition, interruption of CREB function in the mPFC also leads to a deficit in auditory discrimination of fearful stimuli. While mice with deficient CBP/CREB signaling in the mPFC maintain normal responses to aversive stimuli, they exhibit abnormal responses to similar but nonrelevant stimuli when compared to control animals. These data indicate that improvement of fear memory accuracy involves mPFC-dependent suppression of fear responses to nonrelevant stimuli. Evidence from a context discriminatory task and a newly developed task that depends on the ability to distinguish discrete auditory cues indicated that CBP-dependent neural signaling within the mPFC circuitry is an important component of the mechanism for disambiguating the meaning of fear signals with two opposing values: aversive and nonaversive. © 2014 Vieira et al.; Published by Cold Spring Harbor Laboratory Press.

FPGA Accelerated Discrete-SURF for Real-Time Homography Estimation

DTIC Science & Technology

2015-03-26

allows for the sum of a group of pixels to be found with only four memory accesses, and a single calculation...of pixels are retrieved from memory and their Hessian determinant values are compared. If the center pixel of the 3x3 block is greater than the other...process- ing on the FPGA[5][24][31]. Third, previous approaches rely heavily on external memory and other components external to the FPGA, while a logic

Evidence for Hippocampus-Dependent Contextual Learning at Postnatal Day 17 in the Rat

ERIC Educational Resources Information Center

Foster, Jennifer A.; Burman, Michael A.

2010-01-01

Long-term memory for fear of an environment (contextual fear conditioning) emerges later in development (postnatal day; PD 23) than long-term memory for fear of discrete stimuli (PD 17). As contextual, but not explicit cue, fear conditioning relies on the hippocampus; this has been interpreted as evidence that the hippocampus is not fully…

A Discussion of the Discrete Fourier Transform Execution on a Typical Desktop PC

NASA Technical Reports Server (NTRS)

White, Michael J.

2006-01-01

This paper will discuss and compare the execution times of three examples of the Discrete Fourier Transform (DFT). The first two examples will demonstrate the direct implementation of the algorithm. In the first example, the Fourier coefficients are generated at the execution of the DFT. In the second example, the coefficients are generated prior to execution and the DFT coefficients are indexed at execution. The last example will demonstrate the Cooley- Tukey algorithm, better known as the Fast Fourier Transform. All examples were written in C executed on a PC using a Pentium 4 running at 1.7 Ghz. As a function of N, the total complex data size, the direct implementation DFT executes, as expected at order of N2 and the FFT executes at order of N log2 N. At N=16K, there is an increase in processing time beyond what is expected. This is not caused by implementation but is a consequence of the effect that machine architecture and memory hierarchy has on implementation. This paper will include a brief overview of digital signal processing, along with a discussion of contemporary work with discrete Fourier processing.

Iconic Memories Die a Sudden Death.

PubMed

Pratte, Michael S

2018-06-01

Iconic memory is characterized by its large storage capacity and brief storage duration, whereas visual working memory is characterized by its small storage capacity. The limited information stored in working memory is often modeled as an all-or-none process in which studied information is either successfully stored or lost completely. This view raises a simple question: If almost all viewed information is stored in iconic memory, yet one second later most of it is completely absent from working memory, what happened to it? Here, I characterized how the precision and capacity of iconic memory changed over time and observed a clear dissociation: Iconic memory suffered from a complete loss of visual items, while the precision of items retained in memory was only marginally affected by the passage of time. These results provide new evidence for the discrete-capacity view of working memory and a new characterization of iconic memory decay.

Anatomical Modularity of Verbal Working Memory? Functional Anatomical Evidence from a Famous Patient with Short-Term Memory Deficits.

PubMed

Paulesu, Eraldo; Shallice, Tim; Danelli, Laura; Sberna, Maurizio; Frackowiak, Richard S J; Frith, Chris D

2017-01-01

Cognitive skills are the emergent property of distributed neural networks. The distributed nature of these networks does not necessarily imply a lack of specialization of the individual brain structures involved. However, it remains questionable whether discrete aspects of high-level behavior might be the result of localized brain activity of individual nodes within such networks. The phonological loop of working memory, with its simplicity, seems ideally suited for testing this possibility. Central to the development of the phonological loop model has been the description of patients with focal lesions and specific deficits. As much as the detailed description of their behavior has served to refine the phonological loop model, a classical anatomoclinical correlation approach with such cases falls short in telling whether the observed behavior is based on the functions of a neural system resembling that seen in normal subjects challenged with phonological loop tasks or whether different systems have taken over. This is a crucial issue for the cross correlation of normal cognition, normal physiology, and cognitive neuropsychology. Here we describe the functional anatomical patterns of JB, a historical patient originally described by Warrington et al. (1971), a patient with a left temporo-parietal lesion and selective short phonological store deficit. JB was studied with the H 2 15 O PET activation technique during a rhyming task, which primarily depends on the rehearsal system of the phonological loop. No residual function was observed in the left temporo-parietal junction, a region previously associated with the phonological buffer of working memory. However, Broca's area, the major counterpart of the rehearsal system, was the major site of activation during the rhyming task. Specific and autonomous activation of Broca's area in the absence of afferent inputs from the other major anatomical component of the phonological loop shows that a certain degree of functional independence or modularity exists in this distributed anatomical-cognitive system.

Anatomical Modularity of Verbal Working Memory? Functional Anatomical Evidence from a Famous Patient with Short-Term Memory Deficits

PubMed Central

Paulesu, Eraldo; Shallice, Tim; Danelli, Laura; Sberna, Maurizio; Frackowiak, Richard S. J.; Frith, Chris D.

2017-01-01

Cognitive skills are the emergent property of distributed neural networks. The distributed nature of these networks does not necessarily imply a lack of specialization of the individual brain structures involved. However, it remains questionable whether discrete aspects of high-level behavior might be the result of localized brain activity of individual nodes within such networks. The phonological loop of working memory, with its simplicity, seems ideally suited for testing this possibility. Central to the development of the phonological loop model has been the description of patients with focal lesions and specific deficits. As much as the detailed description of their behavior has served to refine the phonological loop model, a classical anatomoclinical correlation approach with such cases falls short in telling whether the observed behavior is based on the functions of a neural system resembling that seen in normal subjects challenged with phonological loop tasks or whether different systems have taken over. This is a crucial issue for the cross correlation of normal cognition, normal physiology, and cognitive neuropsychology. Here we describe the functional anatomical patterns of JB, a historical patient originally described by Warrington et al. (1971), a patient with a left temporo-parietal lesion and selective short phonological store deficit. JB was studied with the H215O PET activation technique during a rhyming task, which primarily depends on the rehearsal system of the phonological loop. No residual function was observed in the left temporo-parietal junction, a region previously associated with the phonological buffer of working memory. However, Broca's area, the major counterpart of the rehearsal system, was the major site of activation during the rhyming task. Specific and autonomous activation of Broca's area in the absence of afferent inputs from the other major anatomical component of the phonological loop shows that a certain degree of functional independence or modularity exists in this distributed anatomical-cognitive system. PMID:28567009

Discrete Serotonin Systems Mediate Memory Enhancement and Escape Latencies after Unpredicted Aversive Experience in Drosophila Place Memory

PubMed Central

Sitaraman, Divya; Kramer, Elizabeth F.; Kahsai, Lily; Ostrowski, Daniela; Zars, Troy

2017-01-01

Feedback mechanisms in operant learning are critical for animals to increase reward or reduce punishment. However, not all conditions have a behavior that can readily resolve an event. Animals must then try out different behaviors to better their situation through outcome learning. This form of learning allows for novel solutions and with positive experience can lead to unexpected behavioral routines. Learned helplessness, as a type of outcome learning, manifests in part as increases in escape latency in the face of repeated unpredicted shocks. Little is known about the mechanisms of outcome learning. When fruit fly Drosophila melanogaster are exposed to unpredicted high temperatures in a place learning paradigm, flies both increase escape latencies and have a higher memory when given control of a place/temperature contingency. Here we describe discrete serotonin neuronal circuits that mediate aversive reinforcement, escape latencies, and memory levels after place learning in the presence and absence of unexpected aversive events. The results show that two features of learned helplessness depend on the same modulatory system as aversive reinforcement. Moreover, changes in aversive reinforcement and escape latency depend on local neural circuit modulation, while memory enhancement requires larger modulation of multiple behavioral control circuits. PMID:29321732

Mutual information identifies spurious Hurst phenomena in resting state EEG and fMRI data

NASA Astrophysics Data System (ADS)

von Wegner, Frederic; Laufs, Helmut; Tagliazucchi, Enzo

2018-02-01

Long-range memory in time series is often quantified by the Hurst exponent H , a measure of the signal's variance across several time scales. We analyze neurophysiological time series from electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) resting state experiments with two standard Hurst exponent estimators and with the time-lagged mutual information function applied to discretized versions of the signals. A confidence interval for the mutual information function is obtained from surrogate Markov processes with equilibrium distribution and transition matrix identical to the underlying signal. For EEG signals, we construct an additional mutual information confidence interval from a short-range correlated, tenth-order autoregressive model. We reproduce the previously described Hurst phenomenon (H >0.5 ) in the analytical amplitude of alpha frequency band oscillations, in EEG microstate sequences, and in fMRI signals, but we show that the Hurst phenomenon occurs without long-range memory in the information-theoretical sense. We find that the mutual information function of neurophysiological data behaves differently from fractional Gaussian noise (fGn), for which the Hurst phenomenon is a sufficient condition to prove long-range memory. Two other well-characterized, short-range correlated stochastic processes (Ornstein-Uhlenbeck, Cox-Ingersoll-Ross) also yield H >0.5 , whereas their mutual information functions lie within the Markovian confidence intervals, similar to neural signals. In these processes, which do not have long-range memory by construction, a spurious Hurst phenomenon occurs due to slow relaxation times and heteroscedasticity (time-varying conditional variance). In summary, we find that mutual information correctly distinguishes long-range from short-range dependence in the theoretical and experimental cases discussed. Our results also suggest that the stationary fGn process is not sufficient to describe neural data, which seem to belong to a more general class of stochastic processes, in which multiscale variance effects produce Hurst phenomena without long-range dependence. In our experimental data, the Hurst phenomenon and long-range memory appear as different system properties that should be estimated and interpreted independently.

Very Large Scale Optimization

NASA Technical Reports Server (NTRS)

Vanderplaats, Garrett; Townsend, James C. (Technical Monitor)

2002-01-01

The purpose of this research under the NASA Small Business Innovative Research program was to develop algorithms and associated software to solve very large nonlinear, constrained optimization tasks. Key issues included efficiency, reliability, memory, and gradient calculation requirements. This report describes the general optimization problem, ten candidate methods, and detailed evaluations of four candidates. The algorithm chosen for final development is a modern recreation of a 1960s external penalty function method that uses very limited computer memory and computational time. Although of lower efficiency, the new method can solve problems orders of magnitude larger than current methods. The resulting BIGDOT software has been demonstrated on problems with 50,000 variables and about 50,000 active constraints. For unconstrained optimization, it has solved a problem in excess of 135,000 variables. The method includes a technique for solving discrete variable problems that finds a "good" design, although a theoretical optimum cannot be guaranteed. It is very scalable in that the number of function and gradient evaluations does not change significantly with increased problem size. Test cases are provided to demonstrate the efficiency and reliability of the methods and software.

Importance of stimulation paradigm in determining facilitation and effects of neuromodulation.

PubMed

Crider, M E; Cooper, R L

1999-09-25

Evoked synaptic activity within the CNS and at the neuromuscular junction in most in vivo preparations studied occurs not with single isolated stimuli, but with trains, or bursts, of stimuli. Although for ease in studying the mechanisms of vesicular synaptic transmission one often uses single discrete stimuli, the true mechanisms in the animal may be far more complex. When repetitive stimuli are present at a nerve terminal, often a heightened (i.e., facilitated) postsynaptic potential can be as a result. Facilitation is commonly used as an index of synaptic function and plasticity induced by chronic stimulation or by neuromodulation. The mechanisms that give rise to facilitation are thought to be the same that may underlie short-term learning and memory [C.H. Bailey, E.R. Kandel, Structural changes accompanying memory storage. Annu. Rev. Physiol. 55 (1993) 397-426.]. Differences in short term facilitation (STF) are seen depending on the conventional stimulation paradigm (twin pulse, train, or continuous) used to induce facilitation. Thus, a battery of paradigms should be used to characterize synaptic function to obtain a closer understanding of the possible in vivo conditions.

Deep Brain Stimulation Frequency—A Divining Rod for New and Novel Concepts of Nervous System Function and Therapy

PubMed Central

Montgomery, Erwin B.; He, Huang

2016-01-01

The efficacy of Deep Brain Stimulation (DBS) for an expanding array of neurological and psychiatric disorders demonstrates directly that DBS affects the basic electroneurophysiological mechanisms of the brain. The increasing array of active electrode configurations, stimulation currents, pulse widths, frequencies, and pulse patterns provides valuable tools to probe electroneurophysiological mechanisms. The extension of basic electroneurophysiological and anatomical concepts using sophisticated computational modeling and simulation has provided relatively straightforward explanations of all the DBS parameters except frequency. This article summarizes current thought about frequency and relevant observations. Current methodological and conceptual errors are critically examined in the hope that future work will not replicate these errors. One possible alternative theory is presented to provide a contrast to many current theories. DBS, conceptually, is a noisy discrete oscillator interacting with the basal ganglia–thalamic–cortical system of multiple re-entrant, discrete oscillators. Implications for positive and negative resonance, stochastic resonance and coherence, noisy synchronization, and holographic memory (related to movement generation) are presented. The time course of DBS neuronal responses demonstrates evolution of the DBS response consistent with the dynamics of re-entrant mechanisms. Finally, computational modeling demonstrates identical dynamics as seen by neuronal activities recorded from human and nonhuman primates, illustrating the differences of discrete from continuous harmonic oscillators and the power of conceptualizing the nervous system as composed on interacting discrete nonlinear oscillators. PMID:27548234

Parallel discrete event simulation: A shared memory approach

NASA Technical Reports Server (NTRS)

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

1987-01-01

With traditional event list techniques, evaluating a detailed discrete event simulation model can often require hours or even days of computation time. Parallel simulation mimics the interacting servers and queues of a real system by assigning each simulated entity to a processor. By eliminating the event list and maintaining only sufficient synchronization to insure causality, parallel simulation can potentially provide speedups that are linear in the number of processors. A set of shared memory experiments is presented using the Chandy-Misra distributed simulation algorithm to simulate networks of queues. Parameters 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.

Application of the Cluster Expansion to a Mathematical Model of the Long Memory Phenomenon in a Financial Market

NASA Astrophysics Data System (ADS)

Kuroda, Koji; Maskawa, Jun-ichi; Murai, Joshin

2013-08-01

Empirical studies of the high frequency data in stock markets show that the time series of trade signs or signed volumes has a long memory property. In this paper, we present a discrete time stochastic process for polymer model which describes trader's trading strategy, and show that a scale limit of the process converges to superposition of fractional Brownian motions with Hurst exponents and Brownian motion, provided that the index γ of the time scale about the trader's investment strategy coincides with the index δ of the interaction range in the discrete time process. The main tool for the investigation is the method of cluster expansion developed in the mathematical study of statistical mechanics.

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.

On the Importance of Both Dimensional and Discrete Models of Emotion.

PubMed

Harmon-Jones, Eddie; Harmon-Jones, Cindy; Summerell, Elizabeth

2017-09-29

We review research on the structure and functions of emotions that has benefitted from a serious consideration of both discrete and dimensional perspectives on emotion. To illustrate this point, we review research that demonstrates: (1) how affective valence within discrete emotions differs as a function of individuals and situations, and how these differences relate to various functions; (2) that anger (and other emotional states) should be considered as a discrete emotion but there are dimensions around and within anger; (3) that similarities exist between approach-related positive and negative discrete emotions and they have unique motivational functions; (4) that discrete emotions and broad dimensions of emotions both have unique functions; and (5) evidence that a "new" discrete emotion with discrete functions exists within a broader emotion family. We hope that this consideration of both discrete and dimensional perspectives on emotion will assist in understanding the functions of emotions.

On the Importance of Both Dimensional and Discrete Models of Emotion

PubMed Central

Harmon-Jones, Eddie

2017-01-01

We review research on the structure and functions of emotions that has benefitted from a serious consideration of both discrete and dimensional perspectives on emotion. To illustrate this point, we review research that demonstrates: (1) how affective valence within discrete emotions differs as a function of individuals and situations, and how these differences relate to various functions; (2) that anger (and other emotional states) should be considered as a discrete emotion but there are dimensions around and within anger; (3) that similarities exist between approach-related positive and negative discrete emotions and they have unique motivational functions; (4) that discrete emotions and broad dimensions of emotions both have unique functions; and (5) evidence that a “new” discrete emotion with discrete functions exists within a broader emotion family. We hope that this consideration of both discrete and dimensional perspectives on emotion will assist in understanding the functions of emotions. PMID:28961185

Progression to dementia in memory clinic patients without dementia: a latent profile analysis.

PubMed

Köhler, Sebastian; Hamel, Renske; Sistermans, Nicole; Koene, Ted; Pijnenburg, Yolande A L; van der Flier, Wiesje M; Scheltens, Philip; Visser, Pieter-Jelle; Aalten, Pauline; Verhey, Frans R J; Ramakers, Inez

2013-10-08

To identify the existence of discrete cognitive subtypes among memory clinic patients without dementia and test their prognostic values. In a retrospective cohort study of 635 patients without dementia visiting the Alzheimer centers in Maastricht or Amsterdam, latent profile analysis identified cognitive subtypes based on immediate and delayed memory recall, delayed recognition, information-processing speed, attention, verbal fluency, and executive functions. Time to dementia was tested in weighted Cox proportional hazard models adjusted for confounders. Five latent classes represented participants with high-normal cognition (15%), low-normal cognition (37%), primary memory impairment in recall (MI) (36%), memory impairment in recall and recognition (MI+) (5%), and primary nonmemory impairment (NMI) (6%). Compared with low-normal cognition, participants with NMI had the highest risk of dementia (hazard ratio [HR] = 5.94, 95% confidence interval [CI] = 3.46-10.18) followed by MI (HR = 3.05, 95% CI = 2.09-4.46) and MI+ (HR = 3.26, 95% CI = 1.72-6.17), while participants with high-normal cognition had the lowest risk (HR = 0.24, 95% CI = 0.07-0.80). Subtypes further showed differential relationships with dementia types, with MI and MI+ most often converting to Alzheimer-type dementia and NMI to other forms of dementia. Cognitive subtypes can be empirically identified in otherwise heterogeneous samples of memory clinic patients and largely confirm current strategies to distinguish between amnestic and nonamnestic impairment. Studying more homogeneous cognitive subtypes may improve understanding of disease mechanisms and outcomes.

Post-Retrieval [beta]-Adrenergic Receptor Blockade: Effects on Extinction and Reconsolidation of Cocaine-Cue Memories

ERIC Educational Resources Information Center

Fricks-Gleason, Ashley N.; Marshall, John F.

2008-01-01

Contexts and discrete cues associated with drug-taking are often responsible for relapse among addicts. Animal models have shown that interference with the reconsolidation of drug-cue memories can reduce seeking of drugs or drug-paired stimuli. One such model is conditioned place preference (CPP) in which an animal is trained to associate a…

Identification and optogenetic manipulation of memory engrams in the hippocampus

PubMed Central

Ramirez, Steve; Tonegawa, Susumu; Liu, Xu

2014-01-01

With the accumulation of our knowledge about how memories are formed, consolidated, retrieved, and updated, neuroscience is now reaching a point where discrete memories can be identified and manipulated at rapid timescales. Here, we start with historical studies that lead to the modern memory engram theory. Then, we will review recent advances in memory engram research that combine transgenic and optogenetic approaches to reveal the underlying neuronal substrates sufficient for activating mnemonic processes. We will focus on three concepts: (1) isolating memory engrams at the level of single cells to tag them for subsequent manipulation; (2) testing the sufficiency of these engrams for memory recall by artificially activating them; and (3) presenting new stimuli during the artificial activation of these engrams to induce an association between the two to form a false memory. We propose that hippocampal cells that show activity-dependent changes during learning construct a cellular basis for contextual memory engrams. PMID:24478647

A History and Overview of the Behavioral Neuroscience of Learning and Memory.

PubMed

Clark, Robert E

2018-01-01

Here, I provide a basic history of important milestones in the development of theories for how the brain accomplishes the phenomenon of learning and memory. Included are the ideas of Plato, René Descartes, Théodule Ribot, William James, Ivan Pavlov, John Watson, Karl Lashley, and others. The modern era of learning and memory research begins with the description of H.M. by Brenda Milner and the gradual discovery that the brain contains multiple learning and memory systems that are supported by anatomically discrete brain structures. Finally, a brief overview is provided for the chapters that are included in current topics in Behavioral Neuroscience-Learning and Memory.

A History and Overview of the Behavioral Neuroscience of Learning and Memory.

PubMed

Clark, Robert E

2018-01-05

Here, I provide a basic history of important milestones in the development of theories for how the brain accomplishes the phenomenon of learning and memory. Included are the ideas of Plato, René Descartes, Théodule Ribot, William James, Ivan Pavlov, John Watson, Karl Lashley, and others. The modern era of learning and memory research begins with the description of H.M. by Brenda Milner and the gradual discovery that the brain contains multiple learning and memory systems that are supported by anatomically discrete brain structures. Finally, a brief overview is provided for the chapters that are included in current topics in Behavioral Neuroscience-Learning and Memory.

Attention mediates the flexible allocation of visual working memory resources.

PubMed

Emrich, Stephen M; Lockhart, Holly A; Al-Aidroos, Naseem

2017-07-01

Though it is clear that it is impossible to store an unlimited amount of information in visual working memory (VWM), the limiting mechanisms remain elusive. While several models of VWM limitations exist, these typically characterize changes in performance as a function of the number of to-be-remembered items. Here, we examine whether changes in spatial attention could better account for VWM performance, independent of load. Across 2 experiments, performance was better predicted by the prioritization of memory items (i.e., attention) than by the number of items to be remembered (i.e., memory load). This relationship followed a power law, and held regardless of whether performance was assessed based on overall precision or any of 3 measures in a mixture model. Moreover, at large set sizes, even minimally attended items could receive a small proportion of resources, without any evidence for a discrete-capacity on the number of items that could be maintained in VWM. Finally, the observed data were best fit by a variable-precision model in which response error was related to the proportion of resources allocated to each item, consistent with a model of VWM in which performance is determined by the continuous allocation of attentional resources during encoding. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Voltage-Dependent Charge Storage in Cladded Zn0.56Cd0.44Se Quantum Dot MOS Capacitors for Multibit Memory Applications

NASA Astrophysics Data System (ADS)

Khan, J.; Lingalugari, M.; Al-Amoody, F.; Jain, F.

2013-11-01

As conventional memories approach scaling limitations, new storage methods must be utilized to increase Si yield and produce higher on-chip memory density. Use of II-VI Zn0.56Cd0.44Se quantum dots (QDs) is compatible with epitaxial gate insulators such as ZnS-ZnMgS. Voltage-dependent charging effects in cladded Zn0.56Cd0.44Se QDs are presented in a conventional metal-oxide-semiconductor capacitor structure. Charge storage capabilities in Si and ZnMgS QDs have been reported by various researchers; this work is focused on II-VI material Zn0.56Cd0.44Se QDs nucleated using photoassisted microwave plasma metalorganic chemical vapor deposition. Using capacitance-voltage hysteresis characterization, the multistep charging and discharging capabilities of the QDs at room temperature are presented. Three charging states are presented within a 10 V charging voltage range. These characteristics exemplify discrete charge states in the QD layer, perfect for multibit, QD-functionalized high-density memory applications. Multiple charge states with low operating voltage provide device characteristics that can be used for multibit storage by allowing varying charges to be stored in a QD layer based on the applied "write" voltage.

A Review of Three Commonly Used Herbs Which Enhance Memory and New Evidences Which Show Their Combination Could Improve Memory in Young Animals.

PubMed

Hong, Fei; Wang, Liju; Wu, Sharon L; Tang, H C; Sha, Ou; Wai, Maria S M; Yew, David T

2017-01-01

This review looks into the herbs Gingko biloba, Polygala tenuifolia, and Lycii fructus for their widely studied neuroprotective properties. In particular, we investigated memory enhancing effect of these herbs, and their potential synergetic effect on memory with new data. Sixmonth treated mice demonstrated shorter escape latency in water maze and shorter arrival time in a consolidated memory task. Immunochemistry showed evident increase in superoxide dismutase activities in the prefrontal cortex, implying protection against free radicals during aging. Discrete increase of catecholaminergic neurons was found in the prefrontal cortex, hippocampus, corpus striatum, and midbrain, suggesting better memory and better control on mood and behavior. Necrotic cells in the brain decreased as indicated by immunocytochemistry of lactic dehydrogenase. Terminal deoxynucleotidyl transferase dUTP nick end labeling showed no apoptotic cells in most brain areas in high dose group. Biochemistry revealed increase of dopaminergic cells in treatment groups at prefrontal cortex, and in the hippocampus and cerebellum of the high dose group. Most 6-month groups showed increase of serotonin in all three areas. For the high dose group, GABA increased in the hippocampus but not prefrontal cortex, which would help induce sleep at night. Protein kinase C increased in most groups at prefrontal cortex, hippocampus and cerebellum, signifying increase of possible signal transduction pathways for memory or other nervous activations. Our results intimate that the interaction of the three herbs exerts beneficial effects on memory, associated cognitive function, and necrosis. Future investigations based on the present data shall aid development of clinically relevant medication. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A reduction in hippocampal GABAA receptor alpha5 subunits disrupts the memory for location of objects in mice.

PubMed

Prut, L; Prenosil, G; Willadt, S; Vogt, K; Fritschy, J-M; Crestani, F

2010-07-01

The memory for location of objects, which binds information about objects to discrete positions or spatial contexts of occurrence, is a form of episodic memory particularly sensitive to hippocampal damage. Its early decline is symptomatic for elderly dementia. Substances that selectively reduce alpha5-GABA(A) receptor function are currently developed as potential cognition enhancers for Alzheimer's syndrome and other dementia, consistent with genetic studies implicating these receptors that are highly expressed in hippocampus in learning performance. Here we explored the consequences of reduced GABA(A)alpha5-subunit contents, as occurring in alpha5(H105R) knock-in mice, on the memory for location of objects. This required the behavioral characterization of alpha5(H105R) and wild-type animals in various tasks examining learning and memory retrieval strategies for objects, locations, contexts and their combinations. In mutants, decreased amounts of alpha5-subunits and retained long-term potentiation in hippocampus were confirmed. They exhibited hyperactivity with conserved circadian rhythm in familiar actimeters, and normal exploration and emotional reactivity in novel places, allocentric spatial guidance, and motor pattern learning acquisition, inhibition and flexibility in T- and eight-arm mazes. Processing of object, position and context memories and object-guided response learning were spared. Genotype difference in object-in-place memory retrieval and in encoding and response learning strategies for object-location combinations manifested as a bias favoring object-based recognition and guidance strategies over spatial processing of objects in the mutants. These findings identify in alpha5(H105R) mice a behavioral-cognitive phenotype affecting basal locomotion and the memory for location of objects indicative of hippocampal dysfunction resulting from moderately decreased alpha5-subunit contents.

Long-range memory and non-Markov statistical effects in human sensorimotor coordination

NASA Astrophysics Data System (ADS)

M. Yulmetyev, Renat; Emelyanova, Natalya; Hänggi, Peter; Gafarov, Fail; Prokhorov, Alexander

2002-12-01

In this paper, the non-Markov statistical processes and long-range memory effects in human sensorimotor coordination are investigated. The theoretical basis of this study is the statistical theory of non-stationary discrete non-Markov processes in complex systems (Phys. Rev. E 62, 6178 (2000)). The human sensorimotor coordination was experimentally studied by means of standard dynamical tapping test on the group of 32 young peoples with tap numbers up to 400. This test was carried out separately for the right and the left hand according to the degree of domination of each brain hemisphere. The numerical analysis of the experimental results was made with the help of power spectra of the initial time correlation function, the memory functions of low orders and the first three points of the statistical spectrum of non-Markovity parameter. Our observations demonstrate, that with the regard to results of the standard dynamic tapping-test it is possible to divide all examinees into five different dynamic types. We have introduced the conflict coefficient to estimate quantitatively the order-disorder effects underlying life systems. The last one reflects the existence of disbalance between the nervous and the motor human coordination. The suggested classification of the neurophysiological activity represents the dynamic generalization of the well-known neuropsychological types and provides the new approach in a modern neuropsychology.

Discrete-time Markovian stochastic Petri nets

NASA Technical Reports Server (NTRS)

Ciardo, Gianfranco

1995-01-01

We revisit and extend the original definition of discrete-time stochastic Petri nets, by allowing the firing times to have a 'defective discrete phase distribution'. We show that this formalism still corresponds to an underlying discrete-time Markov chain. The structure of the state for this process describes both the marking of the Petri net and the phase of the firing time for each transition, resulting in a large state space. We then modify the well-known power method to perform a transient analysis even when the state space is infinite, subject to the condition that only a finite number of states can be reached in a finite amount of time. Since the memory requirements might still be excessive, we suggest a bounding technique based on truncation.

Time-Domain Evaluation of Fractional Order Controllers’ Direct Discretization Methods

NASA Astrophysics Data System (ADS)

Ma, Chengbin; Hori, Yoichi

Fractional Order Control (FOC), in which the controlled systems and/or controllers are described by fractional order differential equations, has been applied to various control problems. Though it is not difficult to understand FOC’s theoretical superiority, realization issue keeps being somewhat problematic. Since the fractional order systems have an infinite dimension, proper approximation by finite difference equation is needed to realize the designed fractional order controllers. In this paper, the existing direct discretization methods are evaluated by their convergences and time-domain comparison with the baseline case. Proposed sampling time scaling property is used to calculate the baseline case with full memory length. This novel discretization method is based on the classical trapezoidal rule but with scaled sampling time. Comparative studies show good performance and simple algorithm make the Short Memory Principle method most practically superior. The FOC research is still at its primary stage. But its applications in modeling and robustness against non-linearities reveal the promising aspects. Parallel to the development of FOC theories, applying FOC to various control problems is also crucially important and one of top priority issues.

Reflexive aerostructures: increased vehicle survivability

NASA Astrophysics Data System (ADS)

Margraf, Thomas W.; Hemmelgarn, Christopher D.; Barnell, Thomas J.; Franklin, Mark A.

2007-04-01

Aerospace systems stand to benefit significantly from the advancement of reflexive aerostructure technologies for increased vehicle survivability. Cornerstone Research Group Inc. (CRG) is developing lightweight, healable composite systems for use as primary load-bearing aircraft components. The reflexive system is comprised of piezoelectric structural health monitoring systems, localized thermal activation systems, and lightweight, healable composite structures. The reflexive system is designed to mimic the involuntary human response to damage. Upon impact, the structural health monitoring system will identify the location and magnitude of the damage, sending a signal to a discrete thermal activation control system to resistively heat the shape memory polymer (SMP) matrix composite above activation temperature, resulting in localized shape recovery and healing of the damaged areas. CRG has demonstrated SMP composites that can recover 90 percent of flexural yield stress and modulus after postfailure healing. During the development, CRG has overcome issues of discrete activation, structural health monitoring integration, and healable resin systems. This paper will address the challenges associated with development of a reflexive aerostructure, including integration of structural health monitoring, discrete healing, and healable shape memory resin systems.

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.

Efficient scheme for parametric fitting of data in arbitrary dimensions.

PubMed

Pang, Ning-Ning; Tzeng, Wen-Jer; Kao, Hisen-Ching

2008-07-01

We propose an efficient scheme for parametric fitting expressed in terms of the Legendre polynomials. For continuous systems, our scheme is exact and the derived explicit expression is very helpful for further analytical studies. For discrete systems, our scheme is almost as accurate as the method of singular value decomposition. Through a few numerical examples, we show that our algorithm costs much less CPU time and memory space than the method of singular value decomposition. Thus, our algorithm is very suitable for a large amount of data fitting. In addition, the proposed scheme can also be used to extract the global structure of fluctuating systems. We then derive the exact relation between the correlation function and the detrended variance function of fluctuating systems in arbitrary dimensions and give a general scaling analysis.

Motivation Matters: Differing Effects of Pre-Goal and Post-Goal Emotions on Attention and Memory

PubMed Central

Kaplan, Robin L.; Van Damme, Ilse; Levine, Linda J.

2012-01-01

People often show enhanced memory for information that is central to emotional events and impaired memory for peripheral details. The intensity of arousal elicited by an emotional event is commonly held to be the mechanism underlying memory narrowing, with the implication that all sources of emotional arousal should have comparable effects. Discrete emotions differ in their effects on memory, however, with some emotions broadening rather than narrowing the range of information attended to and remembered. Thus, features of emotion other than arousal appear to play a critical role in memory narrowing. We review theory and research on emotional memory narrowing and argue that motivation matters. Recent evidence suggests that emotions experienced prior to goal attainment or loss lead to memory narrowing whereas emotions experienced after goal attainment or loss broaden the range of information encoded in memory. The motivational component of emotion is an important but understudied feature that can help to clarify the conditions under which emotions enhance and impair attention and memory. PMID:23162490

Motivation matters: differing effects of pre-goal and post-goal emotions on attention and memory.

PubMed

Kaplan, Robin L; Van Damme, Ilse; Levine, Linda J

2012-01-01

People often show enhanced memory for information that is central to emotional events and impaired memory for peripheral details. The intensity of arousal elicited by an emotional event is commonly held to be the mechanism underlying memory narrowing, with the implication that all sources of emotional arousal should have comparable effects. Discrete emotions differ in their effects on memory, however, with some emotions broadening rather than narrowing the range of information attended to and remembered. Thus, features of emotion other than arousal appear to play a critical role in memory narrowing. We review theory and research on emotional memory narrowing and argue that motivation matters. Recent evidence suggests that emotions experienced prior to goal attainment or loss lead to memory narrowing whereas emotions experienced after goal attainment or loss broaden the range of information encoded in memory. The motivational component of emotion is an important but understudied feature that can help to clarify the conditions under which emotions enhance and impair attention and memory.

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).

Universal sequence map (USM) of arbitrary discrete sequences

PubMed Central

2002-01-01

Background For over a decade the idea of representing biological sequences in a continuous coordinate space has maintained its appeal but not been fully realized. The basic idea is that any sequence of symbols may define trajectories in the continuous space conserving all its statistical properties. Ideally, such a representation would allow scale independent sequence analysis – without the context of fixed memory length. A simple example would consist on being able to infer the homology between two sequences solely by comparing the coordinates of any two homologous units. Results We have successfully identified such an iterative function for bijective mappingψ of discrete sequences into objects of continuous state space that enable scale-independent sequence analysis. The technique, named Universal Sequence Mapping (USM), is applicable to sequences with an arbitrary length and arbitrary number of unique units and generates a representation where map distance estimates sequence similarity. The novel USM procedure is based on earlier work by these and other authors on the properties of Chaos Game Representation (CGR). The latter enables the representation of 4 unit type sequences (like DNA) as an order free Markov Chain transition table. The properties of USM are illustrated with test data and can be verified for other data by using the accompanying web-based tool:http://bioinformatics.musc.edu/~jonas/usm/. Conclusions USM is shown to enable a statistical mechanics approach to sequence analysis. The scale independent representation frees sequence analysis from the need to assume a memory length in the investigation of syntactic rules. PMID:11895567

Word attributes and lateralization revisited: implications for dual coding and discrete versus continuous processing.

PubMed

Boles, D B

1989-01-01

Three attributes of words are their imageability, concreteness, and familiarity. From a literature review and several experiments, I previously concluded (Boles, 1983a) that only familiarity affects the overall near-threshold recognition of words, and that none of the attributes affects right-visual-field superiority for word recognition. Here these conclusions are modified by two experiments demonstrating a critical mediating influence of intentional versus incidental memory instructions. In Experiment 1, subjects were instructed to remember the words they were shown, for subsequent recall. The results showed effects of both imageability and familiarity on overall recognition, as well as an effect of imageability on lateralization. In Experiment 2, word-memory instructions were deleted and the results essentially reinstated the findings of Boles (1983a). It is concluded that right-hemisphere imagery processes can participate in word recognition under intentional memory instructions. Within the dual coding theory (Paivio, 1971), the results argue that both discrete and continuous processing modes are available, that the modes can be used strategically, and that continuous processing can occur prior to response stages.

Temporal evolution of brain reorganization under cross-modal training: insights into the functional architecture of encoding and retrieval networks

NASA Astrophysics Data System (ADS)

Likova, Lora T.

2015-03-01

This study is based on the recent discovery of massive and well-structured cross-modal memory activation generated in the primary visual cortex (V1) of totally blind people as a result of novel training in drawing without any vision (Likova, 2012). This unexpected functional reorganization of primary visual cortex was obtained after undergoing only a week of training by the novel Cognitive-Kinesthetic Method, and was consistent across pilot groups of different categories of visual deprivation: congenitally blind, late-onset blind and blindfolded (Likova, 2014). These findings led us to implicate V1 as the implementation of the theoretical visuo-spatial 'sketchpad' for working memory in the human brain. Since neither the source nor the subsequent 'recipient' of this non-visual memory information in V1 is known, these results raise a number of important questions about the underlying functional organization of the respective encoding and retrieval networks in the brain. To address these questions, an individual totally blind from birth was given a week of Cognitive-Kinesthetic training, accompanied by functional magnetic resonance imaging (fMRI) both before and just after training, and again after a two-month consolidation period. The results revealed a remarkable temporal sequence of training-based response reorganization in both the hippocampal complex and the temporal-lobe object processing hierarchy over the prolonged consolidation period. In particular, a pattern of profound learning-based transformations in the hippocampus was strongly reflected in V1, with the retrieval function showing massive growth as result of the Cognitive-Kinesthetic memory training and consolidation, while the initially strong hippocampal response during tactile exploration and encoding became non-existent. Furthermore, after training, an alternating patch structure in the form of a cascade of discrete ventral regions underwent radical transformations to reach complete functional specialization in terms of either encoding or retrieval as a function of the stage of learning. Moreover, several distinct patterns of learning-evolution within the patches as a function of their anatomical location, implying a complex reorganization of the object processing sub-networks through the learning period. These first findings of complex patterns of training-based encoding/retrieval reorganization thus have broad implications for a newly emerging view of the perception/memory interactions and their reorganization through the learning process. Note that the temporal evolution of these forms of extended functional reorganization could not be uncovered with conventional assessment paradigms used in the traditional approaches to functional mapping, which may therefore have to be revisited. Moreover, as the present results are obtained in learning under life-long blindness, they imply modality-independent operations, transcending the usual tight association with visual processing. The present approach of memory drawing training in blindness, has the dual-advantage of being both non-visual and causal intervention, which makes it a promising 'scalpel' to disentangle interactions among diverse cognitive functions.

A fast algorithm for forward-modeling of gravitational fields in spherical coordinates with 3D Gauss-Legendre quadrature

NASA Astrophysics Data System (ADS)

Zhao, G.; Liu, J.; Chen, B.; Guo, R.; Chen, L.

2017-12-01

Forward modeling of gravitational fields at large-scale requires to consider the curvature of the Earth and to evaluate the Newton's volume integral in spherical coordinates. To acquire fast and accurate gravitational effects for subsurface structures, subsurface mass distribution is usually discretized into small spherical prisms (called tesseroids). The gravity fields of tesseroids are generally calculated numerically. One of the commonly used numerical methods is the 3D Gauss-Legendre quadrature (GLQ). However, the traditional GLQ integration suffers from low computational efficiency and relatively poor accuracy when the observation surface is close to the source region. We developed a fast and high accuracy 3D GLQ integration based on the equivalence of kernel matrix, adaptive discretization and parallelization using OpenMP. The equivalence of kernel matrix strategy increases efficiency and reduces memory consumption by calculating and storing the same matrix elements in each kernel matrix just one time. In this method, the adaptive discretization strategy is used to improve the accuracy. The numerical investigations show that the executing time of the proposed method is reduced by two orders of magnitude compared with the traditional method that without these optimized strategies. High accuracy results can also be guaranteed no matter how close the computation points to the source region. In addition, the algorithm dramatically reduces the memory requirement by N times compared with the traditional method, where N is the number of discretization of the source region in the longitudinal direction. It makes the large-scale gravity forward modeling and inversion with a fine discretization possible.

Discrete-time Quantum Walks via Interchange Framework and Memory in Quantum Evolution

NASA Astrophysics Data System (ADS)

Dimcovic, Zlatko

One of the newer and rapidly developing approaches in quantum computing is based on "quantum walks," which are quantum processes on discrete space that evolve in either discrete or continuous time and are characterized by mixing of components at each step. The idea emerged in analogy with the classical random walks and stochastic techniques, but these unitary processes are very different even as they have intriguing similarities. This thesis is concerned with study of discrete-time quantum walks. The original motivation from classical Markov chains required for discrete-time quantum walks that one adds an auxiliary Hilbert space, unrelated to the one in which the system evolves, in order to be able to mix components in that space and then take the evolution steps accordingly (based on the state in that space). This additional, "coin," space is very often an internal degree of freedom like spin. We have introduced a general framework for construction of discrete-time quantum walks in a close analogy with the classical random walks with memory that is rather different from the standard "coin" approach. In this method there is no need to bring in a different degree of freedom, while the full state of the system is still described in the direct product of spaces (of states). The state can be thought of as an arrow pointing from the previous to the current site in the evolution, representing the one-step memory. The next step is then controlled by a single local operator assigned to each site in the space, acting quite like a scattering operator. This allows us to probe and solve some problems of interest that have not had successful approaches with "coined" walks. We construct and solve a walk on the binary tree, a structure of great interest but until our result without an explicit discrete time quantum walk, due to difficulties in managing coin spaces necessary in the standard approach. Beyond algorithmic interests, the model based on memory allows one to explore effects of history on the quantum evolution and the subtle emergence of classical features as "memory" is explicitly kept for additional steps. We construct and solve a walk with an additional correlation step, finding interesting new features. On the other hand, the fact that the evolution is driven entirely by a local operator, not involving additional spaces, enables us to choose the Fourier transform as an operator completely controlling the evolution. This in turn allows us to combine the quantum walk approach with Fourier transform based techniques, something decidedly not possible in classical computational physics. We are developing a formalism for building networks manageable by walks constructed with this framework, based on the surprising efficiency of our framework in discovering internals of a simple network that we so far solved. Finally, in line with our expectation that the field of quantum walks can take cues from the rich history of development of the classical stochastic techniques, we establish starting points for the work on non-Abelian quantum walks, with a particular quantum-walk analog of the classical "card shuffling," the walk on the permutation group. In summary, this thesis presents a new framework for construction of discrete time quantum walks, employing and exploring memoried nature of unitary evolution. It is applied to fully solving the problems of: A walk on the binary tree and exploration of the quantum-to-classical transition with increased correlation length (history). It is then used for simple network discovery, and to lay the groundwork for analysis of complex networks, based on combined power of efficient exploration of the Hilbert space (as a walk mixing components) and Fourier transformation (since we can choose this for the evolution operator). We hope to establish this as a general technique as its power would be unmatched by any approaches available in the classical computing. We also looked at the promising and challenging prospect of walks on non-Abelian structures by setting up the problem of "quantum card shuffling," a quantum walk on the permutation group. Relation to other work is thoroughly discussed throughout, along with examination of the context of our work and overviews of our current and future work.

Memory sources of dreams: the incorporation of autobiographical rather than episodic experiences.

PubMed

Malinowski, Josie E; Horton, Caroline L

2014-08-01

The present study aimed to explore autobiographical memories (long-lasting memories about the self) and episodic memories (memories about discrete episodes or events) within dream content. We adapted earlier episodic memory study paradigms and reinvestigated the incorporation of episodic memory sources into dreams, operationalizing episodic memory as featuring autonoetic consciousness, which is the feeling of truly re-experiencing or reliving a past event. Participants (n = 32) recorded daily diaries and dream diaries, and reported on wake-dream relations for 2 weeks. Using a new scale, dreams were rated for their episodic richness, which categorized memory sources of dreams as being truly episodic (featuring autonoetic consciousness), autobiographical (containing segregated features of experiences that pertained to waking life) or otherwise. Only one dream (0.5%) was found to contain an episodic memory. However, the majority of dreams (>80%) were found to contain low to moderate incorporations of autobiographical memory features. These findings demonstrate the inactivity of intact episodic memories, and emphasize the activity of autobiographical memory and processing within dreams. Taken together, this suggests that memories for personal experiences are experienced fragmentarily and selectively during dreaming, perhaps in order to assimilate these memories into the autobiographical memory schema. © 2014 European Sleep Research Society.

Social networks: Evolving graphs with memory dependent edges

NASA Astrophysics Data System (ADS)

Grindrod, Peter; Parsons, Mark

2011-10-01

The plethora of digital communication technologies, and their mass take up, has resulted in a wealth of interest in social network data collection and analysis in recent years. Within many such networks the interactions are transient: thus those networks evolve over time. In this paper we introduce a class of models for such networks using evolving graphs with memory dependent edges, which may appear and disappear according to their recent history. We consider time discrete and time continuous variants of the model. We consider the long term asymptotic behaviour as a function of parameters controlling the memory dependence. In particular we show that such networks may continue evolving forever, or else may quench and become static (containing immortal and/or extinct edges). This depends on the existence or otherwise of certain infinite products and series involving age dependent model parameters. We show how to differentiate between the alternatives based on a finite set of observations. To test these ideas we show how model parameters may be calibrated based on limited samples of time dependent data, and we apply these concepts to three real networks: summary data on mobile phone use from a developing region; online social-business network data from China; and disaggregated mobile phone communications data from a reality mining experiment in the US. In each case we show that there is evidence for memory dependent dynamics, such as that embodied within the class of models proposed here.

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.

Statistical Inference on Memory Structure of Processes and Its Applications to Information Theory

DTIC Science & Technology

2016-05-12

valued times series from a sample. (A practical algorithm to compute the estimator is a work in progress.) Third, finitely-valued spatial processes...ES) U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 mathematical statistics; time series ; Markov chains; random...proved. Second, a statistical method is developed to estimate the memory depth of discrete- time and continuously-valued times series from a sample. (A

Chrestenson transform FPGA embedded factorizations.

PubMed

Corinthios, Michael J

2016-01-01

Chrestenson generalized Walsh transform factorizations for parallel processing imbedded implementations on field programmable gate arrays are presented. This general base transform, sometimes referred to as the Discrete Chrestenson transform, has received special attention in recent years. In fact, the Discrete Fourier transform and Walsh-Hadamard transform are but special cases of the Chrestenson generalized Walsh transform. Rotations of a base-p hypercube, where p is an arbitrary integer, are shown to produce dynamic contention-free memory allocation, in processor architecture. The approach is illustrated by factorizations involving the processing of matrices of the transform which are function of four variables. Parallel operations are implemented matrix multiplications. Each matrix, of dimension N × N, where N = p (n) , n integer, has a structure that depends on a variable parameter k that denotes the iteration number in the factorization process. The level of parallelism, in the form of M = p (m) processors can be chosen arbitrarily by varying m between zero to its maximum value of n - 1. The result is an equation describing the generalised parallelism factorization as a function of the four variables n, p, k and m. Applications of the approach are shown in relation to configuring field programmable gate arrays for digital signal processing applications.

The effects of voice and manual control mode on dual task performance

NASA Technical Reports Server (NTRS)

Wickens, C. D.; Zenyuh, J.; Culp, V.; Marshak, W.

1986-01-01

Two fundamental principles of human performance, compatibility and resource competition, are combined with two structural dichotomies in the human information processing system, manual versus voice output, and left versus right cerebral hemisphere, in order to predict the optimum combination of voice and manual control with either hand, for time-sharing performance of a dicrete and continuous task. Eight right handed male subjected performed a discrete first-order tracking task, time-shared with an auditorily presented Sternberg Memory Search Task. Each task could be controlled by voice, or by the left or right hand, in all possible combinations except for a dual voice mode. When performance was analyzed in terms of a dual-task decrement from single task control conditions, the following variables influenced time-sharing efficiency in diminishing order of magnitude, (1) the modality of control, (discrete manual control of tracking was superior to discrete voice control of tracking and the converse was true with the memory search task), (2) response competition, (performance was degraded when both tasks were responded manually), (3) hemispheric competition, (performance degraded whenever two tasks were controlled by the left hemisphere) (i.e., voice or right handed control). The results confirm the value of predictive models invoice control implementation.

Generalized Reduction Formula for Discrete Wigner Functions of Multiqubit Systems

NASA Astrophysics Data System (ADS)

Srinivasan, K.; Raghavan, G.

2018-03-01

Density matrices and Discrete Wigner Functions are equally valid representations of multiqubit quantum states. For density matrices, the partial trace operation is used to obtain the quantum state of subsystems, but an analogous prescription is not available for discrete Wigner Functions. Further, the discrete Wigner function corresponding to a density matrix is not unique but depends on the choice of the quantum net used for its reconstruction. In the present work, we derive a reduction formula for discrete Wigner functions of a general multiqubit state which works for arbitrary quantum nets. These results would be useful for the analysis and classification of entangled states and the study of decoherence purely in a discrete phase space setting and also in applications to quantum computing.

Computing anticipatory systems with incursion and hyperincursion

NASA Astrophysics Data System (ADS)

Dubois, Daniel M.

1998-07-01

An anticipatory system is a system which contains a model of itself and/or of its environment in view of computing its present state as a function of the prediction of the model. With the concepts of incursion and hyperincursion, anticipatory discrete systems can be modelled, simulated and controlled. By definition an incursion, an inclusive or implicit recursion, can be written as: x(t+1)=F[…,x(t-1),x(t),x(t+1),…] where the value of a variable x(t+1) at time t+1 is a function of this variable at past, present and future times. This is an extension of recursion. Hyperincursion is an incursion with multiple solutions. For example, chaos in the Pearl-Verhulst map model: x(t+1)=a.x(t).[1-x(t)] is controlled by the following anticipatory incursive model: x(t+1)=a.x(t).[1-x(t+1)] which corresponds to the differential anticipatory equation: dx(t)/dt=a.x(t).[1-x(t+1)]-x(t). The main part of this paper deals with the discretisation of differential equation systems of linear and non-linear oscillators. The non-linear oscillator is based on the Lotka-Volterra equations model. The discretisation is made by incursion. The incursive discrete equation system gives the same stability condition than the original differential equations without numerical instabilities. The linearisation of the incursive discrete non-linear Lotka-Volterra equation system gives rise to the classical harmonic oscillator. The incursive discretisation of the linear oscillator is similar to define backward and forward discrete derivatives. A generalized complex derivative is then considered and applied to the harmonic oscillator. Non-locality seems to be a property of anticipatory systems. With some mathematical assumption, the Schrödinger quantum equation is derived for a particle in a uniform potential. Finally an hyperincursive system is given in the case of a neural stack memory.

Some applications of uncertainty relations in quantum information

NASA Astrophysics Data System (ADS)

Majumdar, A. S.; Pramanik, T.

2016-08-01

We discuss some applications of various versions of uncertainty relations for both discrete and continuous variables in the context of quantum information theory. The Heisenberg uncertainty relation enables demonstration of the Einstein, Podolsky and Rosen (EPR) paradox. Entropic uncertainty relations (EURs) are used to reveal quantum steering for non-Gaussian continuous variable states. EURs for discrete variables are studied in the context of quantum memory where fine-graining yields the optimum lower bound of uncertainty. The fine-grained uncertainty relation is used to obtain connections between uncertainty and the nonlocality of retrieval games for bipartite and tripartite systems. The Robertson-Schrödinger (RS) uncertainty relation is applied for distinguishing pure and mixed states of discrete variables.

Weight-lattice discretization of Weyl-orbit functions

NASA Astrophysics Data System (ADS)

Hrivnák, Jiří; Walton, Mark A.

2016-08-01

Weyl-orbit functions have been defined for each simple Lie algebra, and permit Fourier-like analysis on the fundamental region of the corresponding affine Weyl group. They have also been discretized, using a refinement of the coweight lattice, so that digitized data on the fundamental region can be Fourier-analyzed. The discretized orbit function has arguments that are redundant if related by the affine Weyl group, while its labels, the Weyl-orbit representatives, invoke the dual affine Weyl group. Here we discretize the orbit functions in a novel way, by using the weight lattice. A cleaner theory results with symmetry between the arguments and labels of the discretized orbit functions. Orthogonality of the new discretized orbit functions is proved, and leads to the construction of unitary, symmetric matrices with Weyl-orbit-valued elements. For one type of orbit function, the matrix coincides with the Kac-Peterson modular S matrix, important for Wess-Zumino-Novikov-Witten conformal field theory.

Remote Monitor Alarm System

NASA Technical Reports Server (NTRS)

Stute, Robert A. (Inventor); Galloway, F. Houston (Inventor); Medelius, Pedro J. (Inventor); Swindle, Robert W. (Inventor); Bierman, Tracy A. (Inventor)

1996-01-01

A remote monitor alarm system monitors discrete alarm and analog power supply voltage conditions at remotely located communications terminal equipment. A central monitoring unit (CMU) is connected via serial data links to each of a plurality of remote terminal units (RTUS) that monitor the alarm and power supply conditions of the remote terminal equipment. Each RTU can monitor and store condition information of both discrete alarm points and analog power supply voltage points in its associated communications terminal equipment. The stored alarm information is periodically transmitted to the CMU in response to sequential polling of the RTUS. The number of monitored alarm inputs and permissible voltage ranges for the analog inputs can be remotely configured at the CMU and downloaded into programmable memory at each RTU. The CMU includes a video display, a hard disk memory, a line printer and an audio alarm for communicating and storing the alarm information received from each RTU.

Recognition Decisions From Visual Working Memory Are Mediated by Continuous Latent Strengths.

PubMed

Ricker, Timothy J; Thiele, Jonathan E; Swagman, April R; Rouder, Jeffrey N

2017-08-01

Making recognition decisions often requires us to reference the contents of working memory, the information available for ongoing cognitive processing. As such, understanding how recognition decisions are made when based on the contents of working memory is of critical importance. In this work we examine whether recognition decisions based on the contents of visual working memory follow a continuous decision process of graded information about the correct choice or a discrete decision process reflecting only knowing and guessing. We find a clear pattern in favor of a continuous latent strength model of visual working memory-based decision making, supporting the notion that visual recognition decision processes are impacted by the degree of matching between the contents of working memory and the choices given. Relation to relevant findings and the implications for human information processing more generally are discussed. Copyright © 2016 Cognitive Science Society, Inc.

Evaluation of the Utility of a Discrete-Trial Functional Analysis in Early Intervention Classrooms

ERIC Educational Resources Information Center

Kodak, Tiffany; Fisher, Wayne W.; Paden, Amber; Dickes, Nitasha

2013-01-01

We evaluated a discrete-trial functional analysis implemented by regular classroom staff in a classroom setting. The results suggest that the discrete-trial functional analysis identified a social function for each participant and may require fewer staff than standard functional analysis procedures.

New learning and unlearning: strangers or accomplices in threat memory attenuation?

PubMed Central

Clem, Roger L.; Schiller, Daniela

2016-01-01

To achieve greatest efficacy, therapies for attenuating fear and anxiety should preclude the re-emergence of emotional responses. Of relevance to this aim, preclinical models of threat memory reduction are considered to engage one of two discrete neural processes: either establishment of a new behavioral response that competes with, and thereby temporarily interferes with expression of, an intact threat memory (new learning), or one which modifies and thereby disrupts an intact threat memory (unlearning). We contend that a strict dichotomy of new learning and unlearning does not provide a compelling explanation for current data. Instead, we suggest the evidence warrants consideration of alternative models that assume cooperation rather than competition between formation of new cellular traces and the modification of preexisting ones. PMID:27079843

A two-phase model of resource allocation in visual working memory.

PubMed

Ye, Chaoxiong; Hu, Zhonghua; Li, Hong; Ristaniemi, Tapani; Liu, Qiang; Liu, Taosheng

2017-10-01

Two broad theories of visual working memory (VWM) storage have emerged from current research, a discrete slot-based theory and a continuous resource theory. However, neither the discrete slot-based theory or continuous resource theory clearly stipulates how the mental commodity for VWM (discrete slot or continuous resource) is allocated. Allocation may be based on the number of items via stimulus-driven factors, or it may be based on task demands via voluntary control. Previous studies have obtained conflicting results regarding the automaticity versus controllability of such allocation. In the current study, we propose a two-phase allocation model, in which the mental commodity could be allocated only by stimulus-driven factors in the early consolidation phase. However, when there is sufficient time to complete the early phase, allocation can enter the late consolidation phase, where it can be flexibly and voluntarily controlled according to task demands. In an orientation recall task, we instructed participants to store either fewer items at high-precision or more items at low-precision. In 3 experiments, we systematically manipulated memory set size and exposure duration. We did not find an effect of task demands when the set size was high and exposure duration was short. However, when we either decreased the set size or increased the exposure duration, we found a trade-off between the number and precision of VWM representations. These results can be explained by a two-phase model, which can also account for previous conflicting findings in the literature. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Effects of the novel compound aniracetam (Ro 13-5057) upon impaired learning and memory in rodents.

PubMed

Cumin, R; Bandle, E F; Gamzu, E; Haefely, W E

1982-01-01

The effect of aniracetam (Ro 13-5057, 1-anisoyl-2-pyrrolidinone) was studied on various forms of experimentally impaired cognitive functions (learning and memory) in rodents and produced the following effects: (1) almost complete prevention of the incapacity to learn a discrete escape response in rats exposed to sublethal hypercapnia immediately before the acquisition session; (2) partial (rats) or complete (mice) prevention of the scopolamine-induced short-term amnesia for a passive avoidance task; (3) complete protection against amnesia for a passive avoidance task in rats submitted to electroconvulsive shock immediately after avoidance acquisition; (4) prevention of the long-term retention- or retrieval-deficit for a passive avoidance task induced in rats and mice by chloramphenicol or cycloheximide administered immediately after acquisition; (5) reversal, when administered as late as 1 h before the retention test, of the deficit in retention or retrieval of a passive avoidance task induced by cycloheximide injected 2 days previously; (6) prevention of the deficit in the retrieval of an active avoidance task induced in mice by subconvulsant electroshock or hypercapnia applied immediately before retrieval testing (24 h after acquisition). These improvements or normalizations of impaired cognitive functions were seen at oral aniracetam doses of 10-100 mg/kg. Generally, the dose-response curves were bell-shaped. The mechanisms underlying the activity of aniracetam and its 'therapeutic window' are unknown. Piracetam, another pyrrolidinone derivative was used for comparison. It was active only in six of nine tests and had about one-tenth the potency of aniracetam. The results indicate that aniracetam improves cognitive functions which are impaired by different procedure and in different phases of the learning and memory process.

Computations in the deep vs superficial layers of the cerebral cortex.

PubMed

Rolls, Edmund T; Mills, W Patrick C

2017-11-01

A fundamental question is how the cerebral neocortex operates functionally, computationally. The cerebral neocortex with its superficial and deep layers and highly developed recurrent collateral systems that provide a basis for memory-related processing might perform somewhat different computations in the superficial and deep layers. Here we take into account the quantitative connectivity within and between laminae. Using integrate-and-fire neuronal network simulations that incorporate this connectivity, we first show that attractor networks implemented in the deep layers that are activated by the superficial layers could be partly independent in that the deep layers might have a different time course, which might because of adaptation be more transient and useful for outputs from the neocortex. In contrast the superficial layers could implement more prolonged firing, useful for slow learning and for short-term memory. Second, we show that a different type of computation could in principle be performed in the superficial and deep layers, by showing that the superficial layers could operate as a discrete attractor network useful for categorisation and feeding information forward up a cortical hierarchy, whereas the deep layers could operate as a continuous attractor network useful for providing a spatially and temporally smooth output to output systems in the brain. A key advance is that we draw attention to the functions of the recurrent collateral connections between cortical pyramidal cells, often omitted in canonical models of the neocortex, and address principles of operation of the neocortex by which the superficial and deep layers might be specialized for different types of attractor-related memory functions implemented by the recurrent collaterals. Copyright © 2017 Elsevier Inc. All rights reserved.

Discrete-Trial Functional Analysis and Functional Communication Training with Three Adults with Intellectual Disabilities and Problem Behavior

ERIC Educational Resources Information Center

Chezan, Laura C.; Drasgow, Erik; Martin, Christian A.

2014-01-01

We conducted a sequence of two studies on the use of discrete-trial functional analysis and functional communication training. First, we used discrete-trial functional analysis (DTFA) to identify the function of problem behavior in three adults with intellectual disabilities and problem behavior. Results indicated clear patterns of problem…

Fluoride toxicity and status of serum thyroid hormones, brain histopathology, and learning memory in rats: a multigenerational assessment.

PubMed

Basha, Piler Mahaboob; Rai, Puja; Begum, Shabana

2011-12-01

High-fluoride (100 and 200 ppm) water was administered to rats orally to study the fluoride-induced changes on the thyroid hormone status, the histopathology of discrete brain regions, the acetylcholine esterase activity, and the learning and memory abilities in multigeneration rats. Significant decrease in the serum-free thyroxine (FT4) and free triiodothyronine (FT3) levels and decrease in acetylcholine esterase activity in fluoride-treated group were observed. Presence of eosinophilic Purkinje cells, degenerating neurons, decreased granular cells, and vacuolations were noted in discrete brain regions of the fluoride-treated group. In the T-maze experiments, the fluoride-treated group showed poor acquisition and retention and higher latency when compared with the control. The alterations were more profound in the third generation when compared with the first- and second-generation fluoride-treated group. Changes in the thyroid hormone levels in the present study might have imbalanced the oxidant/antioxidant system, which further led to a reduction in learning memory ability. Hence, presence of generational or cumulative effects of fluoride on the development of the offspring when it is ingested continuously through multiple generations is evident from the present study.

An automated maze task for assessing hippocampus-sensitive memory in mice☆

PubMed Central

Pioli, Elsa Y.; Gaskill, Brianna N.; Gilmour, Gary; Tricklebank, Mark D.; Dix, Sophie L.; Bannerman, David; Garner, Joseph P.

2014-01-01

Memory deficits associated with hippocampal dysfunction are a key feature of a number of neurodegenerative and psychiatric disorders. The discrete-trial rewarded alternation T-maze task is highly sensitive to hippocampal dysfunction. Normal mice have spontaneously high levels of alternation, whereas hippocampal-lesioned mice are dramatically impaired. However, this is a hand-run task and handling has been shown to impact crucially on behavioural responses, as well as being labour-intensive and therefore unsuitable for high-throughput studies. To overcome this, a fully automated maze was designed. The maze was attached to the mouse's home cage and the subject earned all of its food by running through the maze. In this study the hippocampal dependence of rewarded alternation in the automated maze was assessed. Bilateral hippocampal-lesioned mice were assessed in the standard, hand-run, discrete-trial rewarded alternation paradigm and in the automated paradigm, according to a cross-over design. A similarly robust lesion effect on alternation performance was found in both mazes, confirming the sensitivity of the automated maze to hippocampal lesions. Moreover, the performance of the animals in the automated maze was not affected by their handling history whereas performance in the hand-run maze was affected by prior testing history. By having more stable performance and by decreasing human contact the automated maze may offer opportunities to reduce extraneous experimental variation and therefore increase the reproducibility within and/or between laboratories. Furthermore, automation potentially allows for greater experimental throughput and hence suitability for use in assessment of cognitive function in drug discovery. PMID:24333574

Double Dissociation of the Roles of Metabotropic Glutamate Receptor 5 and Oxytocin Receptor in Discrete Social Behaviors.

PubMed

Mesic, Ivana; Guzman, Yomayra F; Guedea, Anita L; Jovasevic, Vladimir; Corcoran, Kevin A; Leaderbrand, Katherine; Nishimori, Katsuhiko; Contractor, Anis; Radulovic, Jelena

2015-09-01

Social interactions in vertebrates are complex phenomena based on affective and cognitive processes. Multiple brain regions and neurotransmitter systems are involved in the expression of social behaviors, but their individual roles in specific aspects of social interactions are not well understood. Here we investigated how Gq-protein-coupled metabotropic glutamate receptor 5 (mGluR5) and oxytocin receptor (Oxtr) affect social affiliation and social memory. We used conditional genetic approaches in which the genes coding for these receptors were knocked out in the lateral septum by infusion of recombinant adeno-associated viral vectors containing Cre recombinase (AAV-Cre). Social behavior was assessed 2 weeks later using a three-chamber paradigm for sociability and preference for social novelty. Septal deletion of mGluR5 abolished sociability while leaving preference for social novelty intact. In contrast, deletion of Oxtr did not affect sociability but significantly impaired preference for social novelty. Nonsocial behaviors or memories, including novel object recognition or fear conditioning, were not affected by these genetic manipulations. Immunohistochemical analyses of the distribution of mGluR5 and Oxtr revealed non-overlapping localization of these receptors within the lateral septum, suggesting that not only different neurotransmitters but also different neuronal types contribute to sociability versus preference for social novelty. Our findings identify highly specialized roles of lateral septal mGluR5 and Oxtr in the the regulation of discrete social behaviors, and suggest that deficits in social interactions, which accompany many mental illnesses, would benefit from comprehensive treatments targeting different components of social functioning.

Double Dissociation of the Roles of Metabotropic Glutamate Receptor 5 and Oxytocin Receptor in Discrete Social Behaviors

PubMed Central

Mesic, Ivana; Guzman, Yomayra F; Guedea, Anita L; Jovasevic, Vladimir; Corcoran, Kevin A; Leaderbrand, Katherine; Nishimori, Katsuhiko; Contractor, Anis; Radulovic, Jelena

2015-01-01

Social interactions in vertebrates are complex phenomena based on affective and cognitive processes. Multiple brain regions and neurotransmitter systems are involved in the expression of social behaviors, but their individual roles in specific aspects of social interactions are not well understood. Here we investigated how Gq-protein-coupled metabotropic glutamate receptor 5 (mGluR5) and oxytocin receptor (Oxtr) affect social affiliation and social memory. We used conditional genetic approaches in which the genes coding for these receptors were knocked out in the lateral septum by infusion of recombinant adeno-associated viral vectors containing Cre recombinase (AAV-Cre). Social behavior was assessed 2 weeks later using a three-chamber paradigm for sociability and preference for social novelty. Septal deletion of mGluR5 abolished sociability while leaving preference for social novelty intact. In contrast, deletion of Oxtr did not affect sociability but significantly impaired preference for social novelty. Nonsocial behaviors or memories, including novel object recognition or fear conditioning, were not affected by these genetic manipulations. Immunohistochemical analyses of the distribution of mGluR5 and Oxtr revealed non-overlapping localization of these receptors within the lateral septum, suggesting that not only different neurotransmitters but also different neuronal types contribute to sociability versus preference for social novelty. Our findings identify highly specialized roles of lateral septal mGluR5 and Oxtr in the the regulation of discrete social behaviors, and suggest that deficits in social interactions, which accompany many mental illnesses, would benefit from comprehensive treatments targeting different components of social functioning. PMID:25824423

GXNOR-Net: Training deep neural networks with ternary weights and activations without full-precision memory under a unified discretization framework.

PubMed

Deng, Lei; Jiao, Peng; Pei, Jing; Wu, Zhenzhi; Li, Guoqi

2018-04-01

Although deep neural networks (DNNs) are being a revolutionary power to open up the AI era, the notoriously huge hardware overhead has challenged their applications. Recently, several binary and ternary networks, in which the costly multiply-accumulate operations can be replaced by accumulations or even binary logic operations, make the on-chip training of DNNs quite promising. Therefore there is a pressing need to build an architecture that could subsume these networks under a unified framework that achieves both higher performance and less overhead. To this end, two fundamental issues are yet to be addressed. The first one is how to implement the back propagation when neuronal activations are discrete. The second one is how to remove the full-precision hidden weights in the training phase to break the bottlenecks of memory/computation consumption. To address the first issue, we present a multi-step neuronal activation discretization method and a derivative approximation technique that enable the implementing the back propagation algorithm on discrete DNNs. While for the second issue, we propose a discrete state transition (DST) methodology to constrain the weights in a discrete space without saving the hidden weights. Through this way, we build a unified framework that subsumes the binary or ternary networks as its special cases, and under which a heuristic algorithm is provided at the website https://github.com/AcrossV/Gated-XNOR. More particularly, we find that when both the weights and activations become ternary values, the DNNs can be reduced to sparse binary networks, termed as gated XNOR networks (GXNOR-Nets) since only the event of non-zero weight and non-zero activation enables the control gate to start the XNOR logic operations in the original binary networks. This promises the event-driven hardware design for efficient mobile intelligence. We achieve advanced performance compared with state-of-the-art algorithms. Furthermore, the computational sparsity and the number of states in the discrete space can be flexibly modified to make it suitable for various hardware platforms. Copyright © 2018 Elsevier Ltd. All rights reserved.

Weight-lattice discretization of Weyl-orbit functions

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

Hrivnák, Jiří, E-mail: jiri.hrivnak@fjfi.cvut.cz, E-mail: walton@uleth.ca; Walton, Mark A., E-mail: jiri.hrivnak@fjfi.cvut.cz, E-mail: walton@uleth.ca

Weyl-orbit functions have been defined for each simple Lie algebra, and permit Fourier-like analysis on the fundamental region of the corresponding affine Weyl group. They have also been discretized, using a refinement of the coweight lattice, so that digitized data on the fundamental region can be Fourier-analyzed. The discretized orbit function has arguments that are redundant if related by the affine Weyl group, while its labels, the Weyl-orbit representatives, invoke the dual affine Weyl group. Here we discretize the orbit functions in a novel way, by using the weight lattice. A cleaner theory results with symmetry between the arguments andmore » labels of the discretized orbit functions. Orthogonality of the new discretized orbit functions is proved, and leads to the construction of unitary, symmetric matrices with Weyl-orbit-valued elements. For one type of orbit function, the matrix coincides with the Kac-Peterson modular S matrix, important for Wess-Zumino-Novikov-Witten conformal field theory.« less

High frequency oscillations are associated with cognitive processing in human recognition memory.

PubMed

Kucewicz, Michal T; Cimbalnik, Jan; Matsumoto, Joseph Y; Brinkmann, Benjamin H; Bower, Mark R; Vasoli, Vincent; Sulc, Vlastimil; Meyer, Fred; Marsh, W R; Stead, S M; Worrell, Gregory A

2014-08-01

High frequency oscillations are associated with normal brain function, but also increasingly recognized as potential biomarkers of the epileptogenic brain. Their role in human cognition has been predominantly studied in classical gamma frequencies (30-100 Hz), which reflect neuronal network coordination involved in attention, learning and memory. Invasive brain recordings in animals and humans demonstrate that physiological oscillations extend beyond the gamma frequency range, but their function in human cognitive processing has not been fully elucidated. Here we investigate high frequency oscillations spanning the high gamma (50-125 Hz), ripple (125-250 Hz) and fast ripple (250-500 Hz) frequency bands using intracranial recordings from 12 patients (five males and seven females, age 21-63 years) during memory encoding and recall of a series of affectively charged images. Presentation of the images induced high frequency oscillations in all three studied bands within the primary visual, limbic and higher order cortical regions in a sequence consistent with the visual processing stream. These induced oscillations were detected on individual electrodes localized in the amygdala, hippocampus and specific neocortical areas, revealing discrete oscillations of characteristic frequency, duration and latency from image presentation. Memory encoding and recall significantly modulated the number of induced high gamma, ripple and fast ripple detections in the studied structures, which was greater in the primary sensory areas during the encoding (Wilcoxon rank sum test, P = 0.002) and in the higher-order cortical association areas during the recall (Wilcoxon rank sum test, P = 0.001) of memorized images. Furthermore, the induced high gamma, ripple and fast ripple responses discriminated the encoded and the affectively charged images. In summary, our results show that high frequency oscillations, spanning a wide range of frequencies, are associated with memory processing and generated along distributed cortical and limbic brain regions. These findings support an important role for fast network synchronization in human cognition and extend our understanding of normal physiological brain activity during memory processing. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Discrete capacity limits and neuroanatomical correlates of visual short-term memory for objects and spatial locations.

PubMed

Konstantinou, Nikos; Constantinidou, Fofi; Kanai, Ryota

2017-02-01

Working memory is responsible for keeping information in mind when it is no longer in view, linking perception with higher cognitive functions. Despite such crucial role, short-term maintenance of visual information is severely limited. Research suggests that capacity limits in visual short-term memory (VSTM) are correlated with sustained activity in distinct brain areas. Here, we investigated whether variability in the structure of the brain is reflected in individual differences of behavioral capacity estimates for spatial and object VSTM. Behavioral capacity estimates were calculated separately for spatial and object information using a novel adaptive staircase procedure and were found to be unrelated, supporting domain-specific VSTM capacity limits. Voxel-based morphometry (VBM) analyses revealed dissociable neuroanatomical correlates of spatial versus object VSTM. Interindividual variability in spatial VSTM was reflected in the gray matter density of the inferior parietal lobule. In contrast, object VSTM was reflected in the gray matter density of the left insula. These dissociable findings highlight the importance of considering domain-specific estimates of VSTM capacity and point to the crucial brain regions that limit VSTM capacity for different types of visual information. Hum Brain Mapp 38:767-778, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Evaluation of the utility of a discrete-trial functional analysis in early intervention classrooms.

PubMed

Kodak, Tiffany; Fisher, Wayne W; Paden, Amber; Dickes, Nitasha

2013-01-01

We evaluated a discrete-trial functional analysis implemented by regular classroom staff in a classroom setting. The results suggest that the discrete-trial functional analysis identified a social function for each participant and may require fewer staff than standard functional analysis procedures. © Society for the Experimental Analysis of Behavior.

Mapping Common Aphasia Assessments to Underlying Cognitive Processes and Their Neural Substrates.

PubMed

Lacey, Elizabeth H; Skipper-Kallal, Laura M; Xing, Shihui; Fama, Mackenzie E; Turkeltaub, Peter E

2017-05-01

Understanding the relationships between clinical tests, the processes they measure, and the brain networks underlying them, is critical in order for clinicians to move beyond aphasia syndrome classification toward specification of individual language process impairments. To understand the cognitive, language, and neuroanatomical factors underlying scores of commonly used aphasia tests. Twenty-five behavioral tests were administered to a group of 38 chronic left hemisphere stroke survivors and a high-resolution magnetic resonance image was obtained. Test scores were entered into a principal components analysis to extract the latent variables (factors) measured by the tests. Multivariate lesion-symptom mapping was used to localize lesions associated with the factor scores. The principal components analysis yielded 4 dissociable factors, which we labeled Word Finding/Fluency, Comprehension, Phonology/Working Memory Capacity, and Executive Function. While many tests loaded onto the factors in predictable ways, some relied heavily on factors not commonly associated with the tests. Lesion symptom mapping demonstrated discrete brain structures associated with each factor, including frontal, temporal, and parietal areas extending beyond the classical language network. Specific functions mapped onto brain anatomy largely in correspondence with modern neural models of language processing. An extensive clinical aphasia assessment identifies 4 independent language functions, relying on discrete parts of the left middle cerebral artery territory. A better understanding of the processes underlying cognitive tests and the link between lesion and behavior may lead to improved aphasia diagnosis, and may yield treatments better targeted to an individual's specific pattern of deficits and preserved abilities.

Carbamoylated erythropoietin modulates cognitive outcomes of social defeat and differentially regulates gene expression in the dorsal and ventral hippocampus.

PubMed

Sathyanesan, Monica; Watt, Michael J; Haiar, Jacob M; Scholl, Jamie L; Davies, Shaydel R; Paulsen, Riley T; Wiederin, Jayme; Ciborowski, Pawel; Newton, Samuel S

2018-06-08

Cognitive deficits are widespread in psychiatric disorders and frequently as debilitating as the affective component. Widely prescribed antidepressants for treating depressive disorders have limited efficacy in normalizing cognitive function. Erythropoietin (Epo) has been shown to improve cognitive function in schizophrenia and treatment resistant depressed patients. However, the potent elevation of red blood cell counts by Epo can cause hematological complications in non-anemic patients. We investigated a chemically engineered, posttranslational modification of Epo, carbamoylation, which renders it non-erythropoietic. We conducted mass-spectrometry-based peptide mapping of carbamoylated Epo (Cepo) and tested its ability to improve cognitive function after social defeat stress. Gene expression analysis in discrete brain regions was performed to obtain mechanistic insight of Cepo action. Cepo reversed stress-induced spatial working memory deficits while affecting long-term (24 h) novel object recognition in these rats. Contextual fear conditioning following defeat was enhanced by Cepo, but attenuated in controls. However, Cepo improved fear extinction in all rats compared to vehicle treatment. Cepo induced differential gene expression of BDNF, VGF, Arc, TH. and neuritin in the mPFC and discrete hippocampal subfields, with strongest induction in the dorsal hippocampus. Analysis of gene-brain region-behavior interactions showed that Cepo-induced neurotrophic mechanisms influence cognitive function. Carbamoylated erythropoietin can be developed as a therapeutic neurotrophic agent to treat cognitive dysfunction in neuropsychiatric diseases. Due to its distinct mechanism of action, it is unlikely to cross react with the activity of currently prescribed small molecule drugs and can be used as an add-on biologic drug.

Global exponential periodicity and stability of discrete-time complex-valued recurrent neural networks with time-delays.

PubMed

Hu, Jin; Wang, Jun

2015-06-01

In recent years, complex-valued recurrent neural networks have been developed and analysed in-depth in view of that they have good modelling performance for some applications involving complex-valued elements. In implementing continuous-time dynamical systems for simulation or computational purposes, it is quite necessary to utilize a discrete-time model which is an analogue of the continuous-time system. In this paper, we analyse a discrete-time complex-valued recurrent neural network model and obtain the sufficient conditions on its global exponential periodicity and exponential stability. Simulation results of several numerical examples are delineated to illustrate the theoretical results and an application on associative memory is also given. Copyright © 2015 Elsevier Ltd. All rights reserved.

Real-Time and Memory Correlation via Acousto-Optic Processing,

DTIC Science & Technology

1978-06-01

acousto - optic technology as an answer to these requirements appears very attractive. Three fundamental signal-processing schemes using the acousto ... optic interaction have been investigated: (i) real-time correlation and convolution, (ii) Fourier and discrete Fourier transformation, and (iii

Dimers in Piecewise Temperleyan Domains

NASA Astrophysics Data System (ADS)

Russkikh, Marianna

2018-03-01

We study the large-scale behavior of the height function in the dimer model on the square lattice. Richard Kenyon has shown that the fluctuations of the height function on Temperleyan discretizations of a planar domain converge in the scaling limit (as the mesh size tends to zero) to the Gaussian Free Field with Dirichlet boundary conditions. We extend Kenyon's result to a more general class of discretizations. Moreover, we introduce a new factorization of the coupling function of the double-dimer model into two discrete holomorphic functions, which are similar to discrete fermions defined in Smirnov (Proceedings of the international congress of mathematicians (ICM), Madrid, Spain, 2006; Ann Math (2) 172:1435-1467, 2010). For Temperleyan discretizations with appropriate boundary modifications, the results of Kenyon imply that the expectation of the double-dimer height function converges to a harmonic function in the scaling limit. We use the above factorization to extend this result to the class of all polygonal discretizations, that are not necessarily Temperleyan. Furthermore, we show that, quite surprisingly, the expectation of the double-dimer height function in the Temperleyan case is exactly discrete harmonic (for an appropriate choice of Laplacian) even before taking the scaling limit.

Discrete Dynamics Lab

NASA Astrophysics Data System (ADS)

Wuensche, Andrew

DDLab is interactive graphics software for creating, visualizing, and analyzing many aspects of Cellular Automata, Random Boolean Networks, and Discrete Dynamical Networks in general and studying their behavior, both from the time-series perspective — space-time patterns, and from the state-space perspective — attractor basins. DDLab is relevant to research, applications, and education in the fields of complexity, self-organization, emergent phenomena, chaos, collision-based computing, neural networks, content addressable memory, genetic regulatory networks, dynamical encryption, generative art and music, and the study of the abstract mathematical/physical/dynamical phenomena in their own right.

Developmental amnesia: Fractionation of developing memory systems.

PubMed

Temple, Christine M; Richardson, Paul

2006-07-01

Study of the developmental amnesias utilizing a cognitive neuropsychological methodology has highlighted the dissociations that may occur between the development of components of memory. M.M., a new case of developmental amnesia, was identified after screening from the normal population on cognitive and memory measures. Retrospective investigation found that he was of low birthweight. M.M. had impaired semantic memory for knowledge of facts and words. There was impaired episodic memory for words and stories but intact episodic memory for visual designs and features. This forms a double dissociation with Dr S. (Temple, 1992), who had intact verbal but impaired visual episodic memory. M.M. also had impaired autobiographical episodic memory. Nevertheless, learning over repeated trials occurred, consistent with previous theorizing that learning is not simply the effect of recurrent episodic memory. Nor is it the same as establishing semantic memory, since for M.M. semantic memory is also impaired. Within reading, there was an impaired lexico-semantic system, elevated levels of homophone confusion, but intact phonological reading, consistent with surface dyslexia and raising issues about the interrelationship of the semantic system and literacy development. The results are compatible with discrete semi-independent components within memory development, whereby deficits are associated with residual normality, but there may also be an explicit relationship between the semantic memory system and both vocabulary and reading acquisition.

Extension of the frequency-domain pFFT method for wave structure interaction in finite depth

NASA Astrophysics Data System (ADS)

Teng, Bin; Song, Zhi-jie

2017-06-01

To analyze wave interaction with a large scale body in the frequency domain, a precorrected Fast Fourier Transform (pFFT) method has been proposed for infinite depth problems with the deep water Green function, as it can form a matrix with Toeplitz and Hankel properties. In this paper, a method is proposed to decompose the finite depth Green function into two terms, which can form matrices with the Toeplitz and a Hankel properties respectively. Then, a pFFT method for finite depth problems is developed. Based on the pFFT method, a numerical code pFFT-HOBEM is developed with the discretization of high order elements. The model is validated, and examinations on the computing efficiency and memory requirement of the new method have also been carried out. It shows that the new method has the same advantages as that for infinite depth.

Asymmetries in the Processing of Vowel Height

ERIC Educational Resources Information Center

Scharinger, Mathias; Monahan, Philip J.; Idsardi, William J.

2012-01-01

Purpose: Speech perception can be described as the transformation of continuous acoustic information into discrete memory representations. Therefore, research on neural representations of speech sounds is particularly important for a better understanding of this transformation. Speech perception models make specific assumptions regarding the…

Electrically Variable Resistive Memory Devices

NASA Technical Reports Server (NTRS)

Liu, Shangqing; Wu, Nai-Juan; Ignatiev, Alex; Charlson, E. J.

2010-01-01

Nonvolatile electronic memory devices that store data in the form of electrical- resistance values, and memory circuits based on such devices, have been invented. These devices and circuits exploit an electrically-variable-resistance phenomenon that occurs in thin films of certain oxides that exhibit the colossal magnetoresistive (CMR) effect. It is worth emphasizing that, as stated in the immediately preceding article, these devices function at room temperature and do not depend on externally applied magnetic fields. A device of this type is basically a thin film resistor: it consists of a thin film of a CMR material located between, and in contact with, two electrical conductors. The application of a short-duration, low-voltage current pulse via the terminals changes the electrical resistance of the film. The amount of the change in resistance depends on the size of the pulse. The direction of change (increase or decrease of resistance) depends on the polarity of the pulse. Hence, a datum can be written (or a prior datum overwritten) in the memory device by applying a pulse of size and polarity tailored to set the resistance at a value that represents a specific numerical value. To read the datum, one applies a smaller pulse - one that is large enough to enable accurate measurement of resistance, but small enough so as not to change the resistance. In writing, the resistance can be set to any value within the dynamic range of the CMR film. Typically, the value would be one of several discrete resistance values that represent logic levels or digits. Because the number of levels can exceed 2, a memory device of this type is not limited to binary data. Like other memory devices, devices of this type can be incorporated into a memory integrated circuit by laying them out on a substrate in rows and columns, along with row and column conductors for electrically addressing them individually or collectively.

On E-discretization of tori of compact simple Lie groups. II

NASA Astrophysics Data System (ADS)

Hrivnák, Jiří; Juránek, Michal

2017-10-01

Ten types of discrete Fourier transforms of Weyl orbit functions are developed. Generalizing one-dimensional cosine, sine, and exponential, each type of the Weyl orbit function represents an exponential symmetrized with respect to a subgroup of the Weyl group. Fundamental domains of even affine and dual even affine Weyl groups, governing the argument and label symmetries of the even orbit functions, are determined. The discrete orthogonality relations are formulated on finite sets of points from the refinements of the dual weight lattices. Explicit counting formulas for the number of points of the discrete transforms are deduced. Real-valued Hartley orbit functions are introduced, and all ten types of the corresponding discrete Hartley transforms are detailed.

A Theoretical Understanding of Circular Polarization Memory in Random Media

NASA Astrophysics Data System (ADS)

Dark, Julia

Radiative transport theory describes the propagation of light in random media that absorb, scatter, and emit radiation. To describe the propagation of light, the full polarization state is quantified using the Stokes parameters. For the sake of mathematical convenience, the polarization state of light is often neglected leading to the scalar radiative transport equation for the intensity only. For scalar transport theory, there is a well-established body of literature on numerical and analytic approximations to the radiative transport equation. We extend the scalar theory to the vector radiative transport equation (vRTE). In particular, we are interested in the theoretical basis for a phenomena called circular polarization memory. Circular polarization memory is the physical phenomena whereby circular polarization retains its ellipticity and handedness when propagating in random media. This is in contrast to the propagation of linear polarization in random media, which depolarizes at a faster rate, and specular reflection of circular polarization, whereby the circular polarization handedness flips. We investigate two limits that are of known interest in the phenomena of circular polarization memory. The first limit we investigate is that of forward-peaked scattering, i.e. the limit where most scattering events occur in the forward or near-forward directions. The second limit we consider is that of strong scattering and weak absorption. In the forward-peaked scattering limit we approximate the vRTE by a system of partial differential equations motivated by the scalar Fokker-Planck approximation. We call the leading order approximation the vector Fokker-Planck approximation. The vector Fokker Planck approximation predicts that strongly forward-peaked media exhibit circular polarization memory where the strength of the effect can be calculated from the expansion of the scattering matrix in special functions. In addition, we find in this limit that total intensity, linear polarization, and circular polarization decouple. From this result we conclude, that in the Fokker-Planck limit the scalar approximation is an appropriate leading order approximation. In the strong scattering and weak absorbing limit the vector radiative transport equation can be analyzed using boundary layer theory. In this case, the problem of light scattering in an optically thick medium is reduced to a 1D vRTE near the boundary and a 3D diffusion equation in the interior. We develop and implement a numerical solver for the boundary layer problem by using a discrete ordinate solver in the boundary layer and a spectral method to solve the diffusion approximation in the interior. We implement the method in Fortran 95 with external dependencies on BLAS, LAPACK, and FFTW. By analyzing the spectrum of the discretized vRTE in the boundary layer, we are able to predict the presence of circular polarization memory in a given medium.

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.

Memory trace replay: the shaping of memory consolidation by neuromodulation

PubMed Central

Atherton, Laura A.; Dupret, David; Mellor, Jack R.

2015-01-01

The consolidation of memories for places and events is thought to rely, at the network level, on the replay of spatially tuned neuronal firing patterns representing discrete places and spatial trajectories. This occurs in the hippocampal-entorhinal circuit during sharp wave ripple events (SWRs) that occur during sleep or rest. Here, we review theoretical models of lingering place cell excitability and behaviorally induced synaptic plasticity within cell assemblies to explain which sequences or places are replayed. We further provide new insights into how fluctuations in cholinergic tone during different behavioral states might shape the direction of replay and how dopaminergic release in response to novelty or reward can modulate which cell assemblies are replayed. PMID:26275935

Expertise for upright faces improves the precision but not the capacity of visual working memory.

PubMed

Lorenc, Elizabeth S; Pratte, Michael S; Angeloni, Christopher F; Tong, Frank

2014-10-01

Considerable research has focused on how basic visual features are maintained in working memory, but little is currently known about the precision or capacity of visual working memory for complex objects. How precisely can an object be remembered, and to what extent might familiarity or perceptual expertise contribute to working memory performance? To address these questions, we developed a set of computer-generated face stimuli that varied continuously along the dimensions of age and gender, and we probed participants' memories using a method-of-adjustment reporting procedure. This paradigm allowed us to separately estimate the precision and capacity of working memory for individual faces, on the basis of the assumptions of a discrete capacity model, and to assess the impact of face inversion on memory performance. We found that observers could maintain up to four to five items on average, with equally good memory capacity for upright and upside-down faces. In contrast, memory precision was significantly impaired by face inversion at every set size tested. Our results demonstrate that the precision of visual working memory for a complex stimulus is not strictly fixed but, instead, can be modified by learning and experience. We find that perceptual expertise for upright faces leads to significant improvements in visual precision, without modifying the capacity of working memory.

A Barnes maze for juvenile rats delineates the emergence of spatial navigation ability.

PubMed

McHail, Daniel G; Valibeigi, Nazanin; Dumas, Theodore C

2018-03-01

The neural bases of cognition may be greatly informed by relating temporally defined developmental changes in behavior with concurrent alterations in neural function. A robust improvement in performance in spatial learning and memory tasks occurs at 3 wk of age in rodents. We reported that the developmental increase of spontaneous alternation in a Y-maze was related to changes in temporal dynamics of fast glutamatergic synaptic transmission in the hippocampus. We also showed that, during allothetic behaviors in the Y-maze, network oscillation power increased at frequency bands known to support spatial learning and memory in adults. However, there are no discrete learning and memory phases during free exploration in the Y-maze. Thus, we adapted the Barnes maze for use with juvenile rats. Following a single platform exposure in dim light on the day before training (to encourage exploration), animals were trained on the subsequent 2 d in bright light to find a hidden escape box and then underwent a memory test 24 h later. During escape training, the older animals learned the task in 1 d, while the younger animals required 2 d and did not reach the performance of older animals. Long-term memory performance was also superior in the older animals. Thus, we have validated the use of the Barnes maze for this developmental period and established a timeline for the ontogeny of spatial navigation ability in this maze around 3 wk of age. Subsequent work will pair in vivo recording of hippocampal oscillations and single units with this task to help identify how hippocampal maturation might relate to performance improvements. © 2018 McHail et al.; Published by Cold Spring Harbor Laboratory Press.

Is There Natural Killer Cell Memory and Can It Be Harnessed by Vaccination? Natural Killer Cells in Vaccination.

PubMed

Neely, Harold R; Mazo, Irina B; Gerlach, Carmen; von Andrian, Ulrich H

2017-12-18

Natural killer (NK) cells have historically been considered to be a part of the innate immune system, exerting a rapid response against pathogens and tumors in an antigen (Ag)-independent manner. However, over the past decade, evidence has accumulated suggesting that at least some NK cells display certain characteristics of adaptive immune cells. Indeed, NK cells can learn and remember encounters with a variety of Ags, including chemical haptens and viruses. Upon rechallenge, memory NK cells mount potent recall responses selectively to those Ags. This phenomenon, traditionally termed "immunological memory," has been reported in mice, nonhuman primates, and even humans and appears to be concentrated in discrete NK cell subsets. Because immunological memory protects against recurrent infections and is the central goal of active vaccination, it is crucial to define the mechanisms and consequences of NK cell memory. Here, we summarize the different kinds of memory responses that have been attributed to specific NK cell subsets and discuss the possibility to harness NK cell memory for vaccination purposes. Copyright © 2017 Cold Spring Harbor Laboratory Press; all rights reserved.

An update on contextual fear memory mechanisms: Transition between Amygdala and Hippocampus.

PubMed

Chaaya, Nicholas; Battle, Andrew R; Johnson, Luke R

2018-05-09

Context is an ever-present combination of discrete environmental elements capable of influencing many psychological processes. When context is associated with an aversive stimulus, a permanent contextual fear memory is formed. Context is hypothesized to greatly influence the treatability of various fear-based pathologies, in particular, post-traumatic stress disorder (PTSD). In order to understand how contextual fear memories are encoded and impact underlying fear pathology, delineation of the underlying neural circuitry of contextual fear memory consolidation and maintenance is essential. Past understandings of contextual fear suggest that the hippocampus only creates a unitary, or single, representation of context. This representation is sent to the amygdala, which creates the associative contextual fear memory. In contrast, here we review new evidence from the literature showing contextual fear memories to be consolidated and maintained by both amygdala and hippocampus. Based on this evidence, we revise the current model of contextual fear memory consolidation, highlighting a larger role for hippocampus. This new model may better explain the role of the hippocampus in PTSD. Copyright © 2018 Elsevier Ltd. All rights reserved.

Remarks on a New Possible Discretization Scheme for Gauge Theories

NASA Astrophysics Data System (ADS)

Magnot, Jean-Pierre

2018-03-01

We propose here a new discretization method for a class of continuum gauge theories which action functionals are polynomials of the curvature. Based on the notion of holonomy, this discretization procedure appears gauge-invariant for discretized analogs of Yang-Mills theories, and hence gauge-fixing is fully rigorous for these discretized action functionals. Heuristic parts are forwarded to the quantization procedure via Feynman integrals and the meaning of the heuristic infinite dimensional Lebesgue integral is questioned.

Remarks on a New Possible Discretization Scheme for Gauge Theories

NASA Astrophysics Data System (ADS)

Magnot, Jean-Pierre

2018-07-01

We propose here a new discretization method for a class of continuum gauge theories which action functionals are polynomials of the curvature. Based on the notion of holonomy, this discretization procedure appears gauge-invariant for discretized analogs of Yang-Mills theories, and hence gauge-fixing is fully rigorous for these discretized action functionals. Heuristic parts are forwarded to the quantization procedure via Feynman integrals and the meaning of the heuristic infinite dimensional Lebesgue integral is questioned.

Evolution of cellular automata with memory: The Density Classification Task.

PubMed

Stone, Christopher; Bull, Larry

2009-08-01

The Density Classification Task is a well known test problem for two-state discrete dynamical systems. For many years researchers have used a variety of evolutionary computation approaches to evolve solutions to this problem. In this paper, we investigate the evolvability of solutions when the underlying Cellular Automaton is augmented with a type of memory based on the Least Mean Square algorithm. To obtain high performance solutions using a simple non-hybrid genetic algorithm, we design a novel representation based on the ternary representation used for Learning Classifier Systems. The new representation is found able to produce superior performance to the bit string traditionally used for representing Cellular automata. Moreover, memory is shown to improve evolvability of solutions and appropriate memory settings are able to be evolved as a component part of these solutions.

Non-Markovian properties and multiscale hidden Markovian network buried in single molecule time series

NASA Astrophysics Data System (ADS)

Sultana, Tahmina; Takagi, Hiroaki; Morimatsu, Miki; Teramoto, Hiroshi; Li, Chun-Biu; Sako, Yasushi; Komatsuzaki, Tamiki

2013-12-01

We present a novel scheme to extract a multiscale state space network (SSN) from single-molecule time series. The multiscale SSN is a type of hidden Markov model that takes into account both multiple states buried in the measurement and memory effects in the process of the observable whenever they exist. Most biological systems function in a nonstationary manner across multiple timescales. Combined with a recently established nonlinear time series analysis based on information theory, a simple scheme is proposed to deal with the properties of multiscale and nonstationarity for a discrete time series. We derived an explicit analytical expression of the autocorrelation function in terms of the SSN. To demonstrate the potential of our scheme, we investigated single-molecule time series of dissociation and association kinetics between epidermal growth factor receptor (EGFR) on the plasma membrane and its adaptor protein Ash/Grb2 (Grb2) in an in vitro reconstituted system. We found that our formula successfully reproduces their autocorrelation function for a wide range of timescales (up to 3 s), and the underlying SSNs change their topographical structure as a function of the timescale; while the corresponding SSN is simple at the short timescale (0.033-0.1 s), the SSN at the longer timescales (0.1 s to ˜3 s) becomes rather complex in order to capture multiscale nonstationary kinetics emerging at longer timescales. It is also found that visiting the unbound form of the EGFR-Grb2 system approximately resets all information of history or memory of the process.

Properties of the Magnitude Terms of Orthogonal Scaling Functions.

PubMed

Tay, Peter C; Havlicek, Joseph P; Acton, Scott T; Hossack, John A

2010-09-01

The spectrum of the convolution of two continuous functions can be determined as the continuous Fourier transform of the cross-correlation function. The same can be said about the spectrum of the convolution of two infinite discrete sequences, which can be determined as the discrete time Fourier transform of the cross-correlation function of the two sequences. In current digital signal processing, the spectrum of the contiuous Fourier transform and the discrete time Fourier transform are approximately determined by numerical integration or by densely taking the discrete Fourier transform. It has been shown that all three transforms share many analogous properties. In this paper we will show another useful property of determining the spectrum terms of the convolution of two finite length sequences by determining the discrete Fourier transform of the modified cross-correlation function. In addition, two properties of the magnitude terms of orthogonal wavelet scaling functions are developed. These properties are used as constraints for an exhaustive search to determine an robust lower bound on conjoint localization of orthogonal scaling functions.

Brain without mind: Computer simulation of neural networks with modifiable neuronal interactions

NASA Astrophysics Data System (ADS)

Clark, John W.; Rafelski, Johann; Winston, Jeffrey V.

1985-07-01

Aspects of brain function are examined in terms of a nonlinear dynamical system of highly interconnected neuron-like binary decision elements. The model neurons operate synchronously in discrete time, according to deterministic or probabilistic equations of motion. Plasticity of the nervous system, which underlies such cognitive collective phenomena as adaptive development, learning, and memory, is represented by temporal modification of interneuronal connection strengths depending on momentary or recent neural activity. A formal basis is presented for the construction of local plasticity algorithms, or connection-modification routines, spanning a large class. To build an intuitive understanding of the behavior of discrete-time network models, extensive computer simulations have been carried out (a) for nets with fixed, quasirandom connectivity and (b) for nets with connections that evolve under one or another choice of plasticity algorithm. From the former experiments, insights are gained concerning the spontaneous emergence of order in the form of cyclic modes of neuronal activity. In the course of the latter experiments, a simple plasticity routine (“brainwashing,” or “anti-learning”) was identified which, applied to nets with initially quasirandom connectivity, creates model networks which provide more felicitous starting points for computer experiments on the engramming of content-addressable memories and on learning more generally. The potential relevance of this algorithm to developmental neurobiology and to sleep states is discussed. The model considered is at the same time a synthesis of earlier synchronous neural-network models and an elaboration upon them; accordingly, the present article offers both a focused review of the dynamical properties of such systems and a selection of new findings derived from computer simulation.

Random walkers with extreme value memory: modelling the peak-end rule

NASA Astrophysics Data System (ADS)

Harris, Rosemary J.

2015-05-01

Motivated by the psychological literature on the ‘peak-end rule’ for remembered experience, we perform an analysis within a random walk framework of a discrete choice model where agents’ future choices depend on the peak memory of their past experiences. In particular, we use this approach to investigate whether increased noise/disruption always leads to more switching between decisions. Here extreme value theory illuminates different classes of dynamics indicating that the long-time behaviour is dependent on the scale used for reflection; this could have implications, for example, in questionnaire design.

Interaction of solitons with a string of coupled quantum dots

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

Kumar, Vijendra, E-mail: vsmedphysics@gmail.com; Swami, O. P., E-mail: omg1789@gmail.com; Nagar, A. K., E-mail: ajaya.nagar@gmail.com

2016-05-06

In this paper, we develop a theory for discrete solitons interaction with a string of coupled quantum dots in view of the local field effects. Discrete nonlinear Schrodinger (DNLS) equations are used to describe the dynamics of the string. Numerical calculations are carried out and results are analyzed with the help of matlab software. With the help of numerical solutions we demonstrate that in the quantum dots string, Rabi oscillations (RO) are self trapped into stable bright Rabi solitons. The Rabi oscillations in different types of nanostructures have potential applications to the elements of quantum logic and quantum memory.

Design and performance of a large vocabulary discrete word recognition system. Volume 2: Appendixes. [flow charts and users manual

NASA Technical Reports Server (NTRS)

1973-01-01

The users manual for the word recognition computer program contains flow charts of the logical diagram, the memory map for templates, the speech analyzer card arrangement, minicomputer input/output routines, and assembly language program listings.

45 CFR 2400.63 - Excluded graduate study.

Code of Federal Regulations, 2010 CFR

2010-10-01

... arts in public affairs or public administration. The Foundation may at its discretion, upon request of... 45 Public Welfare 4 2010-10-01 2010-10-01 false Excluded graduate study. 2400.63 Section 2400.63 Public Welfare Regulations Relating to Public Welfare (Continued) JAMES MADISON MEMORIAL FELLOWSHIP...

Discrete cosine and sine transforms generalized to honeycomb lattice

NASA Astrophysics Data System (ADS)

Hrivnák, Jiří; Motlochová, Lenka

2018-06-01

The discrete cosine and sine transforms are generalized to a triangular fragment of the honeycomb lattice. The honeycomb point sets are constructed by subtracting the root lattice from the weight lattice points of the crystallographic root system A2. The two-variable orbit functions of the Weyl group of A2, discretized simultaneously on the weight and root lattices, induce a novel parametric family of extended Weyl orbit functions. The periodicity and von Neumann and Dirichlet boundary properties of the extended Weyl orbit functions are detailed. Three types of discrete complex Fourier-Weyl transforms and real-valued Hartley-Weyl transforms are described. Unitary transform matrices and interpolating behavior of the discrete transforms are exemplified. Consequences of the developed discrete transforms for transversal eigenvibrations of the mechanical graphene model are discussed.

Final report for''FOSPACK''

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

Ruge, J W; Dean, D

2000-11-20

The goal of this subcontract was to modify the FOSPACK code, developed by John Ruge, to call the BoomerAMG solver developed at LLNL through the HYPRE interface. FOSPACK is a package developed for the automatic discretization and solution of First-Order System Least-Squares (FOSLS) formulations of 2D partial differential equations (c.f [3-9]). FOSPACK takes a user-specified mesh (which can be an unstructured combination of triangular and quadrilateral elements) and specification of the first-order system, and produces the discretizations needed for solution. Generally, all specifications are contained in data files, so no re-compilation is necessary when changing domains, mesh sizes, problems, etc.more » Much of the work in FOSPACK has gone into an interpreter that allows for simple, intuitive specification of the equations. The interpreter reads the equations, processes them, and stores them as instruction lists needed to apply the operators involved to finite element basis functions, allowing assembly of the discrete system. Quite complex equations may be specified, including variable coefficients, user defined functions, and vector notation. The first-order systems may be nonlinear, with linearizations either performed automatically, or specified in a convenient way by the user. The program also includes global/local refinement capability. FOSLS formulations are very well suited for solution by algebraic multigrid (AMG) (c.f. [10-13]). The original version uses a version of algebraic multigrid written by John Ruge in FORTRAN 77, and modified somewhat for use with FOSPACK. BoomerAMG, a version of AMG developed at CASC, has a number of advantages over the FORTRAN version, including dynamic memory allocation and parallel capability. This project was to benefit both FRSC and CASC, giving FOSPACK the advantages of BoomerAMG, while giving CASC a tool for testing FOSLS as a discretization method for problems of interest there. The major parts of this work were implementation and testing of the HYPRE package on our computers, writing a C wrapper/driver for the FOSPACK code, and modifying the wrapper to call BoomerAMG through the HYPRE interface.« less

Mapping common aphasia assessments to underlying cognitive processes and their neural substrates

PubMed Central

Lacey, Elizabeth H.; Skipper-Kallal, LM; Xing, S; Fama, ME; Turkeltaub, PE

2017-01-01

Background Understanding the relationships between clinical tests, the processes they measure, and the brain networks underlying them, is critical in order for clinicians to move beyond aphasia syndrome classification toward specification of individual language process impairments. Objective To understand the cognitive, language, and neuroanatomical factors underlying scores of commonly used aphasia tests. Methods 25 behavioral tests were administered to a group of 38 chronic left hemisphere stroke survivors and a high resolution MRI was obtained. Test scores were entered into a principal components analysis to extract the latent variables (factors) measured by the tests. Multivariate lesion-symptom mapping was used to localize lesions associated with the factor scores. Results The principal components analysis yielded four dissociable factors, which we labeled Word Finding/Fluency, Comprehension, Phonology/Working Memory Capacity, and Executive Function. While many tests loaded onto the factors in predictable ways, some relied heavily on factors not commonly associated with the tests. Lesion symptom mapping demonstrated discrete brain structures associated with each factor, including frontal, temporal, and parietal areas extending beyond the classical language network. Specific functions mapped onto brain anatomy largely in correspondence with modern neural models of language processing. Conclusions An extensive clinical aphasia assessment identifies four independent language functions, relying on discrete parts of the left middle cerebral artery territory. A better understanding of the processes underlying cognitive tests and the link between lesion and behavior may lead to improved aphasia diagnosis, and may yield treatments better targeted to an individual’s specific pattern of deficits and preserved abilities. PMID:28135902

Episodic reinstatement in the medial temporal lobe.

PubMed

Staresina, Bernhard P; Henson, Richard N A; Kriegeskorte, Nikolaus; Alink, Arjen

2012-12-12

The essence of episodic memory is our ability to reexperience past events in great detail, even in the absence of external stimulus cues. Does the phenomenological reinstatement of past experiences go along with reinstating unique neural representations in the brain? And if so, how is this accomplished by the medial temporal lobe (MTL), a brain region intimately linked to episodic memory? Computational models suggest that such reinstatement (also termed "pattern completion") in cortical regions is mediated by the hippocampus, a key region of the MTL. Although recent functional magnetic resonance imaging studies demonstrated reinstatement of coarse item properties like stimulus category or task context across different brain regions, it has not yet been shown whether reinstatement can be observed at the level of individual, discrete events-arguably the defining feature of episodic memory-nor whether MTL structures like the hippocampus support this "true episodic" reinstatement. Here we show that neural activity patterns for unique word-scene combinations encountered during encoding are reinstated in human parahippocampal cortex (PhC) during retrieval. Critically, this reinstatement occurs when word-scene combinations are successfully recollected (even though the original scene is not visually presented) and does not encompass other stimulus domains (such as word-color associations). Finally, the degree of PhC reinstatement across retrieval events correlated with hippocampal activity, consistent with a role of the hippocampus in coordinating pattern completion in cortical regions.

Multiprocessing MCNP on an IBN RS/6000 cluster

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

McKinney, G.W.; West, J.T.

1993-01-01

The advent of high-performance computer systems has brought to maturity programming concepts like vectorization, multiprocessing, and multitasking. While there are many schools of thought as to the most significant factor in obtaining order-of-magnitude increases in performance, such speedup can only be achieved by integrating the computer system and application code. Vectorization leads to faster manipulation of arrays by overlapping instruction CPU cycles. Discrete ordinates codes, which require the solving of large matrices, have proved to be major benefactors of vectorization. Monte Carlo transport, on the other hand, typically contains numerous logic statements and requires extensive redevelopment to benefit from vectorization.more » Multiprocessing and multitasking provide additional CPU cycles via multiple processors. Such systems are generally designed with either common memory access (multitasking) or distributed memory access. In both cases, theoretical speedup, as a function of the number of processors P and the fraction f of task time that multiprocesses, can be formulated using Amdahl's law: S(f, P) =1/(1-f+f/P). However, for most applications, this theoretical limit cannot be achieved because of additional terms (e.g., multitasking overhead, memory overlap, etc.) that are not included in Amdahl's law. Monte Carlo transport is a natural candidate for multiprocessing because the particle tracks are generally independent, and the precision of the result increases as the square Foot of the number of particles tracked.« less

Linear discrete systems with memory: a generalization of the Langmuir model

NASA Astrophysics Data System (ADS)

Băleanu, Dumitru; Nigmatullin, Raoul R.

2013-10-01

In this manuscript we analyzed a general solution of the linear nonlocal Langmuir model within time scale calculus. Several generalizations of the Langmuir model are presented together with their exact corresponding solutions. The physical meaning of the proposed models are investigated and their corresponding geometries are reported.

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

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

The medial prefrontal cortex and memory of cue location in the rat.

PubMed

Rawson, Tim; O'Kane, Michael; Talk, Andrew

2010-01-01

We developed a single-trial cue-location memory task in which rats experienced an auditory cue while exploring an environment. They then recalled and avoided the sound origination point after the cue was paired with shock in a separate context. Subjects with medial prefrontal cortical (mPFC) lesions made no such avoidance response, but both lesioned and control subjects avoided the cue itself when presented at test. A follow up assessment revealed no spatial learning impairment in either group. These findings suggest that the rodent mPFC is required for incidental learning or recollection of the location at which a discrete cue occurred, but is not required for cue recognition or for allocentric spatial memory. Copyright 2009 Elsevier Inc. All rights reserved.

Nanopatterned ferroelectrics for ultrahigh density rad-hard nonvolatile memories.

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

Brennecka, Geoffrey L.; Stevens, Jeffrey; Scrymgeour, David

2010-09-01

Radiation hard nonvolatile random access memory (NVRAM) is a crucial component for DOE and DOD surveillance and defense applications. NVRAMs based upon ferroelectric materials (also known as FERAMs) are proven to work in radiation-rich environments and inherently require less power than many other NVRAM technologies. However, fabrication and integration challenges have led to state-of-the-art FERAMs still being fabricated using a 130nm process while competing phase-change memory (PRAM) has been demonstrated with a 20nm process. Use of block copolymer lithography is a promising approach to patterning at the sub-32nm scale, but is currently limited to self-assembly directly on Si or SiO{submore » 2} layers. Successful integration of ferroelectrics with discrete and addressable features of {approx}15-20nm would represent a 100-fold improvement in areal memory density and would enable more highly integrated electronic devices required for systems advances. Towards this end, we have developed a technique that allows us to carry out block copolymer self-assembly directly on a huge variety of different materials and have investigated the fabrication, integration, and characterization of electroceramic materials - primarily focused on solution-derived ferroelectrics - with discrete features of {approx}20nm and below. Significant challenges remain before such techniques will be capable of fabricating fully integrated NVRAM devices, but the tools developed for this effort are already finding broader use. This report introduces the nanopatterned NVRAM device concept as a mechanism for motivating the subsequent studies, but the bulk of the document will focus on the platform and technology development.« less

The effects of AMPA receptor blockade in the prelimbic cortex on systemic and ventral tegmental area opiate reward sensitivity.

PubMed

De Jaeger, Xavier; Bishop, Stephanie F; Ahmad, Tasha; Lyons, Danika; Ng, Garye Ami; Laviolette, Steven R

2013-02-01

The medial prefrontal cortex (mPFC) is a key neural region involved in opiate-related reward memory processing. AMPA receptor transmission in the mPFC modulates opiate-related reward memory processing, and chronic opiate exposure is associated with alterations in intra-mPFC AMPA receptor function. The objectives of this study were to examine how pharmacological blockade of AMPA receptor transmission in the prelimbic (PLC) division of the mPFC may modulate opiate reward memory acquisition and whether opiate exposure state may modulate the functional role of intra-PLC AMPA receptor transmission during opiate reward learning. Using an unbiased conditioned place preference (CPP) procedure in rats, we performed discrete, bilateral intra-PLC microinfusions of the AMPA receptor antagonist, 6,7-dinitroquinoxaline-2,3-dione, prior to behavioral morphine CPP conditioning, using sub-reward threshold conditioning doses of either systemic (0.05 mg/kg; i.p.) or intra-ventral tegmental area (VTA) morphine (250 ng/0.5 μl). We show that, in both opiate-naïve and opiate-dependent states, intra-PLC blockade of AMPA receptor transmission, but not the infralimbic cortex, increases the behavioral reward magnitude of systemic or intra-VTA morphine. This effect is dependent on dopamine (DA)ergic signaling because pre-administration of cis-(Z)-flupenthixol-dihydrochloride (α-flu), a broad-spectrum dopamine receptor antagonist, blocked the morphine-reward potentiating effects of AMPA receptor blockade. These findings suggest a critical role for intra-PLC AMPA receptor transmission in the processing of opiate reward signaling. Furthermore, blockade of AMPA transmission specifically within the PLC is capable of switching opiate reward processing to a DA-dependent reward system, independently of previous opiate exposure history.

FOURTH SEMINAR TO THE MEMORY OF D.N. KLYSHKO: Algebraic solution of the synthesis problem for coded sequences

NASA Astrophysics Data System (ADS)

Leukhin, Anatolii N.

2005-08-01

The algebraic solution of a 'complex' problem of synthesis of phase-coded (PC) sequences with the zero level of side lobes of the cyclic autocorrelation function (ACF) is proposed. It is shown that the solution of the synthesis problem is connected with the existence of difference sets for a given code dimension. The problem of estimating the number of possible code combinations for a given code dimension is solved. It is pointed out that the problem of synthesis of PC sequences is related to the fundamental problems of discrete mathematics and, first of all, to a number of combinatorial problems, which can be solved, as the number factorisation problem, by algebraic methods by using the theory of Galois fields and groups.

Michael Jackson, Bin Laden and I: functions of positive and negative, public and private flashbulb memories.

PubMed

Demiray, Burcu; Freund, Alexandra M

2015-01-01

This study examined the perceived psychosocial functions of flashbulb memories: It compared positive and negative public flashbulb memories (positive: Bin Laden's death, negative: Michael Jackson's death) with private ones (positive: pregnancy, negative: death of a loved one). A sample of n = 389 young and n = 176 middle-aged adults answered canonical category questions used to identify flashbulb memories and rated the personal significance, the psychological temporal distance, and the functions of each memory (i.e., self-continuity, social-boding, directive functions). Hierarchical regressions showed that, in general, private memories were rated more functional than public memories. Positive and negative private memories were comparable in self-continuity and directionality, but the positive private memory more strongly served social functions. In line with the positivity bias in autobiographical memory, positive flashbulb memories felt psychologically closer than negative ones. Finally, middle-aged adults rated their memories as less functional regarding self-continuity and social-bonding than young adults. Results are discussed regarding the tripartite model of autobiographical memory functions.

Efficient genetic algorithms using discretization scheduling.

PubMed

McLay, Laura A; Goldberg, David E

2005-01-01

In many applications of genetic algorithms, there is a tradeoff between speed and accuracy in fitness evaluations when evaluations use numerical methods with varying discretization. In these types of applications, the cost and accuracy vary from discretization errors when implicit or explicit quadrature is used to estimate the function evaluations. This paper examines discretization scheduling, or how to vary the discretization within the genetic algorithm in order to use the least amount of computation time for a solution of a desired quality. The effectiveness of discretization scheduling can be determined by comparing its computation time to the computation time of a GA using a constant discretization. There are three ingredients for the discretization scheduling: population sizing, estimated time for each function evaluation and predicted convergence time analysis. Idealized one- and two-dimensional experiments and an inverse groundwater application illustrate the computational savings to be achieved from using discretization scheduling.

Electrophysiological basis for the ability of olanzapine to improve verbal memory and functional outcome in patients with schizophrenia: a LORETA analysis of P300.

PubMed

Higuchi, Yuko; Sumiyoshi, Tomiki; Kawasaki, Yasuhiro; Matsui, Mie; Arai, Hirofumi; Kurachi, Masayoshi

2008-04-01

Abnormality of P300 waveforms of event-related potentials (ERPs) has been suggested to represent an aspect of the pathophysiology of schizophrenia. Previous work points to the contribution of altered neural function in discrete brain regions in the left hemisphere to psychotic symptoms and cognitive deficits of schizophrenia. In this study, we sought to determine: 1) if patients with schizophrenia elicit a decreased P300 current source density in brain areas, such as the superior temporal gyrus (STG); 2) if decreased P300 generator density in the left STG is recovered by treatment with the most widely-used antipsychotic drug olanzapine; and 3) if the recovery of P300 source density is associated with improvements of cognitive and functional status. P300 in response to an auditory oddball task, as well as verbal learning memory, psychopathology, and quality of life were evaluated in 16 right-handed patients with schizophrenia before and after treatment with olanzapine for 6 months. ERP data were also obtained from 16 right-handed age and gender-matched normal volunteers. Low resolution electromagnetic tomography (LORETA) analysis was used to obtain current density images of P300. Patients with schizophrenia showed significantly smaller LORETA values in several brain regions in the left side, particularly STG, middle frontal gyrus, and precentral gyrus, compared with control subjects. Six-month treatment with olanzapine significantly increased P300 source density only in the left STG. Positive symptoms, negative symptoms, verbal learning memory, and quality of life were also improved during treatment. Significant correlations were found between the increase in LORETA values of left STG vs. improvements of negative symptoms, as measured by Scale for the Assessment of the Negative Symptoms, and verbal learning memory, as measured by the Japanese Verbal Learning Test. Improvement of quality of life, as evaluated by the Quality of Life Scale, were significantly associated with an increase in LORETA values of middle frontal gyrus, and tended to correlate with that of precentral gyrus. The results of this study suggest that changes in cortical activity, as measured by ERPs, are responsible for the ability of some antipsychotic drugs to improve cognition and functional outcome in patients with schizophrenia.

Event segmentation improves event memory up to one month later.

PubMed

Flores, Shaney; Bailey, Heather R; Eisenberg, Michelle L; Zacks, Jeffrey M

2017-08-01

When people observe everyday activity, they spontaneously parse it into discrete meaningful events. Individuals who segment activity in a more normative fashion show better subsequent memory for the events. If segmenting events effectively leads to better memory, does asking people to attend to segmentation improve subsequent memory? To answer this question, participants viewed movies of naturalistic activity with instructions to remember the activity for a later test, and in some conditions additionally pressed a button to segment the movies into meaningful events or performed a control condition that required button-pressing but not attending to segmentation. In 5 experiments, memory for the movies was assessed at intervals ranging from immediately following viewing to 1 month later. Performing the event segmentation task led to superior memory at delays ranging from 10 min to 1 month. Further, individual differences in segmentation ability predicted individual differences in memory performance for up to a month following encoding. This study provides the first evidence that manipulating event segmentation affects memory over long delays and that individual differences in event segmentation are related to differences in memory over long delays. These effects suggest that attending to how an activity breaks down into meaningful events contributes to memory formation. Instructing people to more effectively segment events may serve as a potential intervention to alleviate everyday memory complaints in aging and clinical populations. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Remembering Complex Objects in Visual Working Memory: Do Capacity Limits Restrict Objects or Features?

PubMed Central

Hardman, Kyle; Cowan, Nelson

2014-01-01

Visual working memory stores stimuli from our environment as representations that can be accessed by high-level control processes. This study addresses a longstanding debate in the literature about whether storage limits in visual working memory include a limit to the complexity of discrete items. We examined the issue with a number of change-detection experiments that used complex stimuli which possessed multiple features per stimulus item. We manipulated the number of relevant features of the stimulus objects in order to vary feature load. In all of our experiments, we found that increased feature load led to a reduction in change-detection accuracy. However, we found that feature load alone could not account for the results, but that a consideration of the number of relevant objects was also required. This study supports capacity limits for both feature and object storage in visual working memory. PMID:25089739

Superior memory efficiency of quantum devices for the simulation of continuous-time stochastic processes

NASA Astrophysics Data System (ADS)

Elliott, Thomas J.; Gu, Mile

2018-03-01

Continuous-time stochastic processes pervade everyday experience, and the simulation of models of these processes is of great utility. Classical models of systems operating in continuous-time must typically track an unbounded amount of information about past behaviour, even for relatively simple models, enforcing limits on precision due to the finite memory of the machine. However, quantum machines can require less information about the past than even their optimal classical counterparts to simulate the future of discrete-time processes, and we demonstrate that this advantage extends to the continuous-time regime. Moreover, we show that this reduction in the memory requirement can be unboundedly large, allowing for arbitrary precision even with a finite quantum memory. We provide a systematic method for finding superior quantum constructions, and a protocol for analogue simulation of continuous-time renewal processes with a quantum machine.

Effect of the image resolution on the statistical descriptors of heterogeneous media.

PubMed

Ledesma-Alonso, René; Barbosa, Romeli; Ortegón, Jaime

2018-02-01

The characterization and reconstruction of heterogeneous materials, such as porous media and electrode materials, involve the application of image processing methods to data acquired by scanning electron microscopy or other microscopy techniques. Among them, binarization and decimation are critical in order to compute the correlation functions that characterize the microstructure of the above-mentioned materials. In this study, we present a theoretical analysis of the effects of the image-size reduction, due to the progressive and sequential decimation of the original image. Three different decimation procedures (random, bilinear, and bicubic) were implemented and their consequences on the discrete correlation functions (two-point, line-path, and pore-size distribution) and the coarseness (derived from the local volume fraction) are reported and analyzed. The chosen statistical descriptors (correlation functions and coarseness) are typically employed to characterize and reconstruct heterogeneous materials. A normalization for each of the correlation functions has been performed. When the loss of statistical information has not been significant for a decimated image, its normalized correlation function is forecast by the trend of the original image (reference function). In contrast, when the decimated image does not hold statistical evidence of the original one, the normalized correlation function diverts from the reference function. Moreover, the equally weighted sum of the average of the squared difference, between the discrete correlation functions of the decimated images and the reference functions, leads to a definition of an overall error. During the first stages of the gradual decimation, the error remains relatively small and independent of the decimation procedure. Above a threshold defined by the correlation length of the reference function, the error becomes a function of the number of decimation steps. At this stage, some statistical information is lost and the error becomes dependent on the decimation procedure. These results may help us to restrict the amount of information that one can afford to lose during a decimation process, in order to reduce the computational and memory cost, when one aims to diminish the time consumed by a characterization or reconstruction technique, yet maintaining the statistical quality of the digitized sample.

Effect of the image resolution on the statistical descriptors of heterogeneous media

NASA Astrophysics Data System (ADS)

Ledesma-Alonso, René; Barbosa, Romeli; Ortegón, Jaime

2018-02-01

The characterization and reconstruction of heterogeneous materials, such as porous media and electrode materials, involve the application of image processing methods to data acquired by scanning electron microscopy or other microscopy techniques. Among them, binarization and decimation are critical in order to compute the correlation functions that characterize the microstructure of the above-mentioned materials. In this study, we present a theoretical analysis of the effects of the image-size reduction, due to the progressive and sequential decimation of the original image. Three different decimation procedures (random, bilinear, and bicubic) were implemented and their consequences on the discrete correlation functions (two-point, line-path, and pore-size distribution) and the coarseness (derived from the local volume fraction) are reported and analyzed. The chosen statistical descriptors (correlation functions and coarseness) are typically employed to characterize and reconstruct heterogeneous materials. A normalization for each of the correlation functions has been performed. When the loss of statistical information has not been significant for a decimated image, its normalized correlation function is forecast by the trend of the original image (reference function). In contrast, when the decimated image does not hold statistical evidence of the original one, the normalized correlation function diverts from the reference function. Moreover, the equally weighted sum of the average of the squared difference, between the discrete correlation functions of the decimated images and the reference functions, leads to a definition of an overall error. During the first stages of the gradual decimation, the error remains relatively small and independent of the decimation procedure. Above a threshold defined by the correlation length of the reference function, the error becomes a function of the number of decimation steps. At this stage, some statistical information is lost and the error becomes dependent on the decimation procedure. These results may help us to restrict the amount of information that one can afford to lose during a decimation process, in order to reduce the computational and memory cost, when one aims to diminish the time consumed by a characterization or reconstruction technique, yet maintaining the statistical quality of the digitized sample.

106-17 Telemetry Standards Recorder and Reproducer Command and Control Chapter 6

DTIC Science & Technology

2017-07-01

6-35 6.3 MIL-STD-1553 Remote Terminal Command and Control ..................................... 6-36 6.4 Discrete Command and...6-6 Figure 6-9. Required Discrete Control Functions...6-36 Figure 6-10. Discrete Control and Indicator Functional Diagram .......................................... 6-37 Telemetry Standards

3D frequency-domain finite-difference modeling of acoustic wave propagation

NASA Astrophysics Data System (ADS)

Operto, S.; Virieux, J.

2006-12-01

We present a 3D frequency-domain finite-difference method for acoustic wave propagation modeling. This method is developed as a tool to perform 3D frequency-domain full-waveform inversion of wide-angle seismic data. For wide-angle data, frequency-domain full-waveform inversion can be applied only to few discrete frequencies to develop reliable velocity model. Frequency-domain finite-difference (FD) modeling of wave propagation requires resolution of a huge sparse system of linear equations. If this system can be solved with a direct method, solutions for multiple sources can be computed efficiently once the underlying matrix has been factorized. The drawback of the direct method is the memory requirement resulting from the fill-in of the matrix during factorization. We assess in this study whether representative problems can be addressed in 3D geometry with such approach. We start from the velocity-stress formulation of the 3D acoustic wave equation. The spatial derivatives are discretized with second-order accurate staggered-grid stencil on different coordinate systems such that the axis span over as many directions as possible. Once the discrete equations were developed on each coordinate system, the particle velocity fields are eliminated from the first-order hyperbolic system (following the so-called parsimonious staggered-grid method) leading to second-order elliptic wave equations in pressure. The second-order wave equations discretized on each coordinate system are combined linearly to mitigate the numerical anisotropy. Secondly, grid dispersion is minimized by replacing the mass term at the collocation point by its weighted averaging over all the grid points of the stencil. Use of second-order accurate staggered- grid stencil allows to reduce the bandwidth of the matrix to be factorized. The final stencil incorporates 27 points. Absorbing conditions are PML. The system is solved using the parallel direct solver MUMPS developed for distributed-memory computers. The MUMPS solver is based on a multifrontal method for LU factorization. We used the METIS algorithm to perform re-ordering of the matrix coefficients before factorization. Four grid points per minimum wavelength is used for discretization. We applied our algorithm to the 3D SEG/EAGE synthetic onshore OVERTHRUST model of dimensions 20 x 20 x 4.65 km. The velocities range between 2 and 6 km/s. We performed the simulations using 192 processors with 2 Gbytes of RAM memory per processor. We performed simulations for the 5 Hz, 7 Hz and 10 Hz frequencies in some fractions of the OVERTHRUST model. The grid interval was 100 m, 75 m and 50 m respectively. The grid dimensions were 207x207x53, 275x218x71 and 409x109x102 respectively corresponding to 100, 80 and 25 percents of the model respectively. The time for factorization is 20 mn, 108 mn and 163 mn respectively. The time for resolution was 3.8, 9.3 and 10.3 s per source. The total memory used during factorization is 143, 384 and 449 Gbytes respectively. One can note the huge memory requirement for factorization and the efficiency of the direct method to compute solutions for a large number of sources. This highlights the respective drawback and merit of the frequency-domain approach with respect to the time- domain counterpart. These results show that 3D acoustic frequency-domain wave propagation modeling can be performed at low frequencies using direct solver on large clusters of Pcs. This forward modeling algorithm may be used in the future as a tool to image the first kilometers of the crust by frequency-domain full-waveform inversion. For larger problems, we will use the out-of-core memory during factorization that has been implemented by the authors of MUMPS.

[Short-term memory characteristics of vibration intensity tactile perception on human wrist].

PubMed

Hao, Fei; Chen, Li-Juan; Lu, Wei; Song, Ai-Guo

2014-12-25

In this study, a recall experiment and a recognition experiment were designed to assess the human wrist's short-term memory characteristics of tactile perception on vibration intensity, by using a novel homemade vibrotactile display device based on the spatiotemporal combination vibration of multiple micro vibration motors as a test device. Based on the obtained experimental data, the short-term memory span, recognition accuracy and reaction time of vibration intensity were analyzed. From the experimental results, some important conclusions can be made: (1) The average short-term memory span of tactile perception on vibration intensity is 3 ± 1 items; (2) The greater difference between two adjacent discrete intensities of vibrotactile stimulation is defined, the better average short-term memory span human wrist gets; (3) There is an obvious difference of the average short-term memory span on vibration intensity between the male and female; (4) The mechanism of information extraction in short-term memory of vibrotactile display is to traverse the scanning process by comparison; (5) The recognition accuracy and reaction time performance of vibrotactile display compares unfavourably with that of visual and auditory. The results from this study are important for designing vibrotactile display coding scheme.

Path statistics, memory, and coarse-graining of continuous-time random walks on networks

PubMed Central

Kion-Crosby, Willow; Morozov, Alexandre V.

2015-01-01

Continuous-time random walks (CTRWs) on discrete state spaces, ranging from regular lattices to complex networks, are ubiquitous across physics, chemistry, and biology. Models with coarse-grained states (for example, those employed in studies of molecular kinetics) or spatial disorder can give rise to memory and non-exponential distributions of waiting times and first-passage statistics. However, existing methods for analyzing CTRWs on complex energy landscapes do not address these effects. Here we use statistical mechanics of the nonequilibrium path ensemble to characterize first-passage CTRWs on networks with arbitrary connectivity, energy landscape, and waiting time distributions. Our approach can be applied to calculating higher moments (beyond the mean) of path length, time, and action, as well as statistics of any conservative or non-conservative force along a path. For homogeneous networks, we derive exact relations between length and time moments, quantifying the validity of approximating a continuous-time process with its discrete-time projection. For more general models, we obtain recursion relations, reminiscent of transfer matrix and exact enumeration techniques, to efficiently calculate path statistics numerically. We have implemented our algorithm in PathMAN (Path Matrix Algorithm for Networks), a Python script that users can apply to their model of choice. We demonstrate the algorithm on a few representative examples which underscore the importance of non-exponential distributions, memory, and coarse-graining in CTRWs. PMID:26646868

Can we improve the clinical assessment of working memory? An evaluation of the Wechsler Adult Intelligence Scale-Third Edition using a working memory criterion construct.

PubMed

Hill, B D; Elliott, Emily M; Shelton, Jill T; Pella, Russell D; O'Jile, Judith R; Gouvier, W Drew

2010-03-01

Working memory is the cognitive ability to hold a discrete amount of information in mind in an accessible state for utilization in mental tasks. This cognitive ability is impaired in many clinical populations typically assessed by clinical neuropsychologists. Recently, there have been a number of theoretical shifts in the way that working memory is conceptualized and assessed in the experimental literature. This study sought to determine to what extent the Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) Working Memory Index (WMI) measures the construct studied in the cognitive working memory literature, whether an improved WMI could be derived from the subtests that comprise the WAIS-III, and what percentage of variance in individual WAIS-III subtests is explained by working memory. It was hypothesized that subtests beyond those currently used to form the WAIS-III WMI would be able to account for a greater percentage of variance in a working memory criterion construct than the current WMI. Multiple regression analyses (n = 180) revealed that the best predictor model of subtests for assessing working memory was composed of the Digit Span, Letter-Number Sequencing, Matrix Reasoning, and Vocabulary. The Arithmetic subtest was not a significant contributor to the model. These results are discussed in the context of how they relate to Unsworth and Engle's (2006, 2007) new conceptualization of working memory mechanisms.

Electrophysiological Repetition Effects in Persons with Mild Cognitive Impairment depend upon Working Memory Demand.

PubMed

Broster, Lucas S; Jenkins, Shonna L; Holmes, Sarah D; Edwards, Matthew G; Jicha, Gregory A; Jiang, Yang

2018-05-07

Forms of implicit memory, including repetition effects, are preserved relative to explicit memory in clinical Alzheimer's disease. Consequently, cognitive interventions for persons with Alzheimer's disease have been developed that leverage this fact. However, despite the clinical robustness of behavioral repetition effects, altered neural mechanisms of repetition effects are studied as biomarkers of both clinical Alzheimer's disease and pre-morbid Alzheimer's changes in the brain. We hypothesized that the clinical preservation of behavioral repetition effects results in part from concurrent operation of discrete memory systems. We developed two experiments that included probes of emotional repetition effects differing in that one included an embedded working memory task. We found that neural repetition effects manifested in patients with amnestic mild cognitive impairment, the earliest form of clinical Alzheimer's disease, during emotional working memory tasks, but they did not manifest during the task that lacked the embedded working memory manipulation. Specifically, the working memory task evoked neural repetition effects in the P600 time-window, but the same neural mechanism was only minimally implicated in the task without a working memory component. We also found that group differences in behavioral repetition effects were smaller in the experiment with a working memory task. We suggest that cross-domain cognitive challenge can expose "defunct" neural capabilities of individuals with amnestic mild cognitive impairment. Copyright © 2018. Published by Elsevier Ltd.

Effects of Discrete Emotions on Young Children's Suggestibility

ERIC Educational Resources Information Center

Levine, Linda J.; Burgess, Stewart L.; Laney, Cara

2008-01-01

Two experiments investigated the effects of sadness, anger, and happiness on 4- to 6-year-old children's memory and suggestibility concerning story events. In Experiment 1, children were presented with 3 interactive stories on a video monitor. The stories included protagonists who wanted to give the child a prize. After each story, the child…

Multi-objective flexible job-shop scheduling problem using modified discrete particle swarm optimization.

PubMed

Huang, Song; Tian, Na; Wang, Yan; Ji, Zhicheng

2016-01-01

Taking resource allocation into account, flexible job shop problem (FJSP) is a class of complex scheduling problem in manufacturing system. In order to utilize the machine resources rationally, multi-objective particle swarm optimization (MOPSO) integrating with variable neighborhood search is introduced to address FJSP efficiently. Firstly, the assignment rules (AL) and dispatching rules (DR) are provided to initialize the population. And then special discrete operators are designed to produce new individuals and earliest completion machine (ECM) is adopted in the disturbance operator to escape the optima. Secondly, personal-best archives (cognitive memories) and global-best archive (social memory), which are updated by the predefined non-dominated archive update strategy, are simultaneously designed to preserve non-dominated individuals and select personal-best positions and the global-best position. Finally, three neighborhoods are provided to search the neighborhoods of global-best archive for enhancing local search ability. The proposed algorithm is evaluated by using Kacem instances and Brdata instances, and a comparison with other approaches shows the effectiveness of the proposed algorithm for FJSP.

Differential Entropy Preserves Variational Information of Near-Infrared Spectroscopy Time Series Associated With Working Memory.

PubMed

Keshmiri, Soheil; Sumioka, Hidenubo; Yamazaki, Ryuji; Ishiguro, Hiroshi

2018-01-01

Neuroscience research shows a growing interest in the application of Near-Infrared Spectroscopy (NIRS) in analysis and decoding of the brain activity of human subjects. Given the correlation that is observed between the Blood Oxygen Dependent Level (BOLD) responses that are exhibited by the time series data of functional Magnetic Resonance Imaging (fMRI) and the hemoglobin oxy/deoxy-genation that is captured by NIRS, linear models play a central role in these applications. This, in turn, results in adaptation of the feature extraction strategies that are well-suited for discretization of data that exhibit a high degree of linearity, namely, slope and the mean as well as their combination, to summarize the informational contents of the NIRS time series. In this article, we demonstrate that these features are inefficient in capturing the variational information of NIRS data, limiting the reliability and the adequacy of the conclusion on their results. Alternatively, we propose the linear estimate of differential entropy of these time series as a natural representation of such information. We provide evidence for our claim through comparative analysis of the application of these features on NIRS data pertinent to several working memory tasks as well as naturalistic conversational stimuli.

Tunable-Porosity Membranes From Discrete Nanoparticles

PubMed Central

Marchetti, Patrizia; Mechelhoff, Martin; Livingston, Andrew G.

2015-01-01

Thin film composite membranes were prepared through a facile single-step wire-wound rod coating procedure in which internally crosslinked poly(styrene-co-butadiene) polymer nanoparticles self-assembled to form a thin film on a hydrophilic ultrafiltration support. This nanoparticle film provided a defect-free separation layer 130–150 nm thick, which was highly permeable and able to withstand aggressive pH conditions beyond the range of available commercial membranes. The nanoparticles were found to coalesce to form a rubbery film when heated above their glass transition temperature (Tg). The retention properties of the novel membrane were strongly affected by charge repulsion, due to the negative charge of the hydroxyl functionalized nanoparticles. Porosity was tuned by annealing the membranes at different temperatures, below and above the nanoparticle Tg. This enabled fabrication of membranes with varying performance. Nanofiltration properties were achieved with a molecular weight cut-off below 500 g mol−1 and a low fouling tendency. Interestingly, after annealing above Tg, memory of the interstitial spaces between the nanoparticles persisted. This memory led to significant water permeance, in marked contrast to the almost impermeable films cast from a solution of the same polymer. PMID:26626565

Electrical Stimulation Modulates High γ Activity and Human Memory Performance

PubMed Central

Berry, Brent M.; Miller, Laura R.; Khadjevand, Fatemeh; Ezzyat, Youssef; Wanda, Paul; Sperling, Michael R.; Lega, Bradley; Stead, S. Matt

2018-01-01

Direct electrical stimulation of the brain has emerged as a powerful treatment for multiple neurological diseases, and as a potential technique to enhance human cognition. Despite its application in a range of brain disorders, it remains unclear how stimulation of discrete brain areas affects memory performance and the underlying electrophysiological activities. Here, we investigated the effect of direct electrical stimulation in four brain regions known to support declarative memory: hippocampus (HP), parahippocampal region (PH) neocortex, prefrontal cortex (PF), and lateral temporal cortex (TC). Intracranial EEG recordings with stimulation were collected from 22 patients during performance of verbal memory tasks. We found that high γ (62–118 Hz) activity induced by word presentation was modulated by electrical stimulation. This modulatory effect was greatest for trials with “poor” memory encoding. The high γ modulation correlated with the behavioral effect of stimulation in a given brain region: it was negative, i.e., the induced high γ activity was decreased, in the regions where stimulation decreased memory performance, and positive in the lateral TC where memory enhancement was observed. Our results suggest that the effect of electrical stimulation on high γ activity induced by word presentation may be a useful biomarker for mapping memory networks and guiding therapeutic brain stimulation. PMID:29404403

Exponential stability preservation in semi-discretisations of BAM networks with nonlinear impulses

NASA Astrophysics Data System (ADS)

Mohamad, Sannay; Gopalsamy, K.

2009-01-01

This paper demonstrates the reliability of a discrete-time analogue in preserving the exponential convergence of a bidirectional associative memory (BAM) network that is subject to nonlinear impulses. The analogue derived from a semi-discretisation technique with the value of the time-step fixed is treated as a discrete-time dynamical system while its exponential convergence towards an equilibrium state is studied. Thereby, a family of sufficiency conditions governing the network parameters and the impulse magnitude and frequency is obtained for the convergence. As special cases, one can obtain from our results, those corresponding to the non-impulsive discrete-time BAM networks and also those corresponding to continuous-time (impulsive and non-impulsive) systems. A relation between the Lyapunov exponent of the non-impulsive system and that of the impulsive system involving the size of the impulses and the inter-impulse intervals is obtained.

Emotion perception, but not affect perception, is impaired with semantic memory loss.

PubMed

Lindquist, Kristen A; Gendron, Maria; Barrett, Lisa Feldman; Dickerson, Bradford C

2014-04-01

For decades, psychologists and neuroscientists have hypothesized that the ability to perceive emotions on others' faces is inborn, prelinguistic, and universal. Concept knowledge about emotion has been assumed to be epiphenomenal to emotion perception. In this article, we report findings from 3 patients with semantic dementia that cannot be explained by this "basic emotion" view. These patients, who have substantial deficits in semantic processing abilities, spontaneously perceived pleasant and unpleasant expressions on faces, but not discrete emotions such as anger, disgust, fear, or sadness, even in a task that did not require the use of emotion words. Our findings support the hypothesis that discrete emotion concept knowledge helps transform perceptions of affect (positively or negatively valenced facial expressions) into perceptions of discrete emotions such as anger, disgust, fear, and sadness. These findings have important consequences for understanding the processes supporting emotion perception.

Emotion perception, but not affect perception, is impaired with semantic memory loss

PubMed Central

Lindquist, Kristen A.; Gendron, Maria; Feldman Barrett, Lisa; Dickerson, Bradford C.

2014-01-01

For decades, psychologists and neuroscientists have hypothesized that the ability to perceive emotions on others’ faces is inborn, pre-linguistic, and universal. Concept knowledge about emotion has been assumed to be epiphenomenal to emotion perception. In this paper, we report findings from three patients with semantic dementia that cannot be explained by this “basic emotion” view. These patients, who have substantial deficits in semantic processing abilities, spontaneously perceived pleasant and unpleasant expressions on faces, but not discrete emotions such as anger, disgust, fear, or sadness, even in a task that did not require the use of emotion words. Our findings support the hypothesis that discrete emotion concept knowledge helps transform perceptions of affect (positively or negatively valenced facial expressions) into perceptions of discrete emotions such as anger, disgust, fear and sadness. These findings have important consequences for understanding the processes supporting emotion perception. PMID:24512242

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

PubMed

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

2013-01-01

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

Numerical model of a single nanocrystal devoted to the study of disordered nanocrystal floating gates of new flash memories

NASA Astrophysics Data System (ADS)

Leroy, Yann; Armeanu, Dumitru; Cordan, Anne-Sophie

2011-05-01

The improvement of our model concerning a single nanocrystal that belongs to a nanocrystal floating gate of a flash memory is presented. In order to extend the gate voltage range applicability of the model, the 3D continuum of states of either metallic or semiconducting electrodes is discretized into 2D subbands. Such an approach gives precise information about the mechanisms behind the charging or release processes of the nanocrystal. Then, the self-energy and screening effects of an electron within the nanocrystal are evaluated and introduced in the model. This enables a better determination of the operating point of the nanocrystal memory. The impact of those improvements on the charging or release time of the nanocrystal is discussed.

VLSI 'smart' I/O module development

NASA Astrophysics Data System (ADS)

Kirk, Dan

The developmental history, design, and operation of the MIL-STD-1553A/B discrete and serial module (DSM) for the U.S. Navy AN/AYK-14(V) avionics computer are described and illustrated with diagrams. The ongoing preplanned product improvement for the AN/AYK-14(V) includes five dual-redundant MIL-STD-1553 channels based on DSMs. The DSM is a front-end processor for transferring data to and from a common memory, sharing memory with a host processor to provide improved 'smart' input/output performance. Each DSM comprises three hardware sections: three VLSI-6000 semicustomized CMOS arrays, memory units to support the arrays, and buffers and resynchronization circuits. The DSM hardware module design, VLSI-6000 design tools, controlware and test software, and checkout procedures (using a hardware simulator) are characterized in detail.

Knowledge of memory functions in European and Asian American adults and children: the relation to autobiographical memory.

PubMed

Wang, Qi; Koh, Jessie Bee Kim; Song, Qingfang; Hou, Yubo

2015-01-01

This study investigated explicit knowledge of autobiographical memory functions using a newly developed questionnaire. European and Asian American adults (N = 57) and school-aged children (N = 68) indicated their agreement with 13 statements about why people think about and share memories pertaining to four broad functions-self, social, directive and emotion regulation. Children were interviewed for personal memories concurrently with the memory function knowledge assessment and again 3 months later. It was found that adults agreed to the self, social and directive purposes of memory to a greater extent than did children, whereas European American children agreed to the emotion regulation purposes of memory to a greater extent than did European American adults. Furthermore, European American children endorsed more self and emotion regulation functions than did Asian American children, whereas Asian American adults endorsed more directive functions than did European American adults. Children's endorsement of memory functions, particularly social functions, was associated with more detailed and personally meaningful memories. These findings are informative for the understanding of developmental and cultural influences on memory function knowledge and of the relation of such knowledge to autobiographical memory development.

Computation of scattering matrix elements of large and complex shaped absorbing particles with multilevel fast multipole algorithm

NASA Astrophysics Data System (ADS)

Wu, Yueqian; Yang, Minglin; Sheng, Xinqing; Ren, Kuan Fang

2015-05-01

Light scattering properties of absorbing particles, such as the mineral dusts, attract a wide attention due to its importance in geophysical and environment researches. Due to the absorbing effect, light scattering properties of particles with absorption differ from those without absorption. Simple shaped absorbing particles such as spheres and spheroids have been well studied with different methods but little work on large complex shaped particles has been reported. In this paper, the surface Integral Equation (SIE) with Multilevel Fast Multipole Algorithm (MLFMA) is applied to study scattering properties of large non-spherical absorbing particles. SIEs are carefully discretized with piecewise linear basis functions on triangle patches to model whole surface of the particle, hence computation resource needs increase much more slowly with the particle size parameter than the volume discretized methods. To improve further its capability, MLFMA is well parallelized with Message Passing Interface (MPI) on distributed memory computer platform. Without loss of generality, we choose the computation of scattering matrix elements of absorbing dust particles as an example. The comparison of the scattering matrix elements computed by our method and the discrete dipole approximation method (DDA) for an ellipsoid dust particle shows that the precision of our method is very good. The scattering matrix elements of large ellipsoid dusts with different aspect ratios and size parameters are computed. To show the capability of the presented algorithm for complex shaped particles, scattering by asymmetry Chebyshev particle with size parameter larger than 600 of complex refractive index m = 1.555 + 0.004 i and different orientations are studied.

Longitudinal Study of a Novel Performance-based Measure of Daily Function

DTIC Science & Technology

2015-04-01

measures of cognition (e.g., episodic memory , semantic memory , executive function, speed). We found that patients with MCI had compromises in...UPSA, as well as measures of cognition (e.g., episodic memory , semantic memory , executive function, speed). We found that patients with MCI had... memory , semantic memory , executive function, speed). We found that patients with MCI had compromises in everyday functional competence and that the

Structural correlates of subjective and objective memory performance in multiple sclerosis.

PubMed

Pardini, Matteo; Bergamino, Maurizio; Bommarito, Giulia; Bonzano, Laura; Luigi Mancardi, Gian; Roccatagliata, Luca

2014-04-01

Subjective and objective memory deficits represent a frequent and ill-understood aspect of multiple sclerosis (MS), and a significant cause of disability and quality of life reduction. The aim of the study is to verify the role of hippocampal and temporal associative fibers' damage in MS-related memory complaints. To reach this aim, 25 patients with low disability relapsing-remitting MS and 19 healthy controls were included in the study. All subjects underwent 3D T1 structural imaging and Diffusion Tensor Imaging. Additionally, MS patients underwent neuropsychological evaluation of objective (Selective Reminding Test and Spatial Recall Test) and of subjective (Perceived Deficit Questionnaire, Retrospective and Prospective Memory Subscales) memory deficits. Normalized hippocampal volume (NHV) and mean Fractional Anisotropy (FA) for the uncinate fasciculus (UF) and for the ventral division of the cingulum bundle (VCB) were calculated for all subjects. We showed that, compared to controls, MS subjects presented with reduced right NHV and with reduced mean FA bilaterally in the UF and the VCB. In the MS group, verbal memory scores correlated with left NHV, spatial memory scores correlated with right NHV, while perceived retrospective and prospective memory deficits correlated with left VCB and left UF mean FA respectively. Our data confirm an early involvement of memory-related brain structures in MS patients. Our data suggest that verbal and nonverbal memory as well as perceived retrospective and prospective memory deficits are related to alterations of discrete anatomical structures in the low-disability phase of MS. Copyright © 2013 Wiley Periodicals, Inc.

Exact Analytical Solutions for Elastodynamic Impact

DTIC Science & Technology

2015-11-30

corroborated by derivation of exact discrete solutions from recursive equations for the impact problems. 15. SUBJECT TERMS One-dimensional impact; Elastic...wave propagation; Laplace transform; Floor function; Discrete solutions 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18...impact Elastic wave propagation Laplace transform Floor function Discrete solutionsWe consider the one-dimensional impact problem in which a semi

An Optimized Multicolor Point-Implicit Solver for Unstructured Grid Applications on Graphics Processing Units

NASA Technical Reports Server (NTRS)

Zubair, Mohammad; Nielsen, Eric; Luitjens, Justin; Hammond, Dana

2016-01-01

In the field of computational fluid dynamics, the Navier-Stokes equations are often solved using an unstructuredgrid approach to accommodate geometric complexity. Implicit solution methodologies for such spatial discretizations generally require frequent solution of large tightly-coupled systems of block-sparse linear equations. The multicolor point-implicit solver used in the current work typically requires a significant fraction of the overall application run time. In this work, an efficient implementation of the solver for graphics processing units is proposed. Several factors present unique challenges to achieving an efficient implementation in this environment. These include the variable amount of parallelism available in different kernel calls, indirect memory access patterns, low arithmetic intensity, and the requirement to support variable block sizes. In this work, the solver is reformulated to use standard sparse and dense Basic Linear Algebra Subprograms (BLAS) functions. However, numerical experiments show that the performance of the BLAS functions available in existing CUDA libraries is suboptimal for matrices representative of those encountered in actual simulations. Instead, optimized versions of these functions are developed. Depending on block size, the new implementations show performance gains of up to 7x over the existing CUDA library functions.

Testing episodic memory in animals: a new approach.

PubMed

Griffiths, D P; Clayton, N S

2001-08-01

Episodic memory involves the encoding and storage of memories concerned with unique personal experiences and their subsequent recall, and it has long been the subject of intensive investigation in humans. According to Tulving's classical definition, episodic memory "receives and stores information about temporally dated episodes or events and temporal-spatial relations among these events." Thus, episodic memory provides information about the 'what' and 'when' of events ('temporally dated experiences') and about 'where' they happened ('temporal-spatial relations'). The storage and subsequent recall of this episodic information was thought to be beyond the memory capabilities of nonhuman animals. Although there are many laboratory procedures for investigating memory for discrete past episodes, until recently there were no previous studies that fully satisfied the criteria of Tulving's definition: they can all be explained in much simpler terms than episodic memory. However, current studies of memory for cache sites in food-storing jays provide an ethologically valid model for testing episodic-like memory in animals, thereby bridging the gap between human and animal studies memory. There is now a pressing need to adapt these experimental tests of episodic memory for other animals. Given the potential power of transgenic and knock-out procedures for investigating the genetic and molecular bases of learning and memory in laboratory rodents, not to mention the wealth of knowledge about the neuroanatomy and neurophysiology of the rodent hippocampus (a brain area heavily implicated in episodic memory), an obvious next step is to develop a rodent model of episodic-like memory based on the food-storing bird paradigm. The development of a rodent model system could make an important contribution to our understanding of the neural, molecular, and behavioral mechanisms of mammalian episodic memory.

A hierarchical preconditioner for the electric field integral equation on unstructured meshes based on primal and dual Haar bases

NASA Astrophysics Data System (ADS)

Adrian, S. B.; Andriulli, F. P.; Eibert, T. F.

2017-02-01

A new hierarchical basis preconditioner for the electric field integral equation (EFIE) operator is introduced. In contrast to existing hierarchical basis preconditioners, it works on arbitrary meshes and preconditions both the vector and the scalar potential within the EFIE operator. This is obtained by taking into account that the vector and the scalar potential discretized with loop-star basis functions are related to the hypersingular and the single layer operator (i.e., the well known integral operators from acoustics). For the single layer operator discretized with piecewise constant functions, a hierarchical preconditioner can easily be constructed. Thus the strategy we propose in this work for preconditioning the EFIE is the transformation of the scalar and the vector potential into operators equivalent to the single layer operator and to its inverse. More specifically, when the scalar potential is discretized with star functions as source and testing functions, the resulting matrix is a single layer operator discretized with piecewise constant functions and multiplied left and right with two additional graph Laplacian matrices. By inverting these graph Laplacian matrices, the discretized single layer operator is obtained, which can be preconditioned with the hierarchical basis. Dually, when the vector potential is discretized with loop functions, the resulting matrix can be interpreted as a hypersingular operator discretized with piecewise linear functions. By leveraging on a scalar Calderón identity, we can interpret this operator as spectrally equivalent to the inverse single layer operator. Then we use a linear-in-complexity, closed-form inverse of the dual hierarchical basis to precondition the hypersingular operator. The numerical results show the effectiveness of the proposed preconditioner and the practical impact of theoretical developments in real case scenarios.

Staphylococcus aureus infection of mice expands a population of memory γδ T cells that are protective against subsequent infection

PubMed Central

Murphy, Alison G.; O’Keeffe, Kate M.; Lalor, Stephen J.; Maher, Belinda M.; Mills, Kingston H. G.; McLoughlin, Rachel M.

2014-01-01

The development of vaccines against S. aureus has consistently failed in clinical trials, likely due to inefficient induction of cellular immunity. T cell-derived IL-17 is one of the few known correlates of anti-staphyloccoal immunity, conferring protection against S. aureus infections through its ability to promote phagocytic cell effector functions. A comprehensive understanding of the discrete T cell subsets critical for site-specific IL-17-mediated bacterial clearance will therefore be necessary to inform the development of vaccines that efficiently target cellular immunity. In this study, we have identified a population of CD44+CD27− memory γδ T cells, expanded upon infection of C57BL/6 mice with S. aureus, which produce high levels of IL-17 and mediate enhanced bacterial clearance upon re-infection with the bacterium. These cells are comprised largely of the Vγ4+ subset and accumulate at the site of infection subsequent to an initial Vγ1.1+ and Vγ2+ T cell response. Moreover, these Vγ4+ T cells are retained in the peritoneum and draining mediastinal lymph nodes for a prolonged period following bacterial clearance. In contrast to its critical requirement for γδ T cell activation during the primary infection, IL-1 signalling was dispensable for activation and expansion of memory γδ T cells upon re-exposure to S. aureus. Our findings demonstrate that a γδ T cell memory response can be induced upon exposure to S. aureus, in a fashion analogous to that associated with classical αβ T cells, and suggest that induction of IL-17-expressing γδ T cells may be an important property of a protective vaccine against S. aureus. PMID:24623128

Deletion of the Mouse Homolog of CACNA1C Disrupts Discrete Forms of Hippocampal-Dependent Memory and Neurogenesis within the Dentate Gyrus.

PubMed

Temme, Stephanie J; Bell, Ryan Z; Fisher, Grace L; Murphy, Geoffrey G

2016-01-01

L-type voltage-gated calcium channels (LVGCCs) have been implicated in various forms of learning, memory, and synaptic plasticity. Within the hippocampus, the LVGCC subtype, Ca V 1.2 is prominently expressed throughout the dentate gyrus. Despite the apparent high levels of Ca V 1.2 expression in the dentate gyrus, the role of Ca V 1.2 in hippocampal- and dentate gyrus-associated forms of learning remain unknown. To address this question, we examined alternate forms of hippocampal-dependent associative and spatial memory in mice lacking the mouse ortholog of CACNA1C ( Cacna1c ), which encodes Ca V 1.2, with dentate gyrus function implicated in difficult forms of each task. We found that while the deletion of Ca V 1.2 did not impair the acquisition of fear of a conditioned context, mice lacking Ca V 1.2 exhibited deficits in the ability to discriminate between two contexts, one in which the mice were conditioned and one in which they were not. Similarly, Ca V 1.2 knock-out mice exhibited normal acquisition and recall of the location of the hidden platform in a standard Morris water maze, but were unable to form a memory of the platform location when the task was made more difficult by restricting the number of available spatial cues. Within the dentate gyrus, pan-neuronal deletion of Ca V 1.2 resulted in decreased cell proliferation and the numbers of doublecortin-positive adult-born neurons, implicating Ca V 1.2 in adult neurogenesis. These results suggest that Ca V 1.2 is important for dentate gyrus-associated tasks and may mediate these forms of learning via a role in adult neurogenesis and cell proliferation within the dentate gyrus.

Combined Cognitive Training vs. Memory Strategy Training in Healthy Older Adults.

PubMed

Li, Bing; Zhu, Xinyi; Hou, Jianhua; Chen, Tingji; Wang, Pengyun; Li, Juan

2016-01-01

As mnemonic utilization deficit in older adults associates with age-related decline in executive function, we hypothesized that memory strategy training combined with executive function training might induce larger training effect in memory and broader training effects in non-memory outcomes than pure memory training. The present study compared the effects of combined cognitive training (executive function training plus memory strategy training) to pure memory strategy training. Forty healthy older adults were randomly assigned to a combined cognitive training group or a memory strategy training group. A control group receiving no training was also included. Combined cognitive training group received 16 sessions of training (eight sessions of executive function training followed by eight sessions of memory strategy training). Memory training group received 16 sessions of memory strategy training. The results partly supported our hypothesis in that indeed improved performance on executive function was only found in combined training group, whereas memory performance increased less in combined training compared to memory strategy group. Results suggest that combined cognitive training may be less efficient than pure memory training in memory outcomes, though the influences from insufficient training time and less closeness between trained executive function and working memory could not be excluded; however it has broader training effects in non-memory outcomes. www.chictr.org.cn, identifier ChiCTR-OON-16007793.

Discrete-Trial Functional Analysis and Functional Communication Training with Three Individuals with Autism and Severe Problem Behavior

ERIC Educational Resources Information Center

Schmidt, Jonathan D.; Drasgow, Erik; Halle, James W.; Martin, Christian A.; Bliss, Sacha A.

2014-01-01

Discrete-trial functional analysis (DTFA) is an experimental method for determining the variables maintaining problem behavior in the context of natural routines. Functional communication training (FCT) is an effective method for replacing problem behavior, once identified, with a functionally equivalent response. We implemented these procedures…

CRAVE: a database, middleware and visualization system for phenotype ontologies.

PubMed

Gkoutos, Georgios V; Green, Eain C J; Greenaway, Simon; Blake, Andrew; Mallon, Ann-Marie; Hancock, John M

2005-04-01

A major challenge in modern biology is to link genome sequence information to organismal function. In many organisms this is being done by characterizing phenotypes resulting from mutations. Efficiently expressing phenotypic information requires combinatorial use of ontologies. However tools are not currently available to visualize combinations of ontologies. Here we describe CRAVE (Concept Relation Assay Value Explorer), a package allowing storage, active updating and visualization of multiple ontologies. CRAVE is a web-accessible JAVA application that accesses an underlying MySQL database of ontologies via a JAVA persistent middleware layer (Chameleon). This maps the database tables into discrete JAVA classes and creates memory resident, interlinked objects corresponding to the ontology data. These JAVA objects are accessed via calls through the middleware's application programming interface. CRAVE allows simultaneous display and linking of multiple ontologies and searching using Boolean and advanced searches.

Enhancing effects of chronic lithium on memory in the rat.

PubMed

Tsaltas, Eleftheria; Kontis, Dimitrios; Boulougouris, Vasileios; Papakosta, Vasiliki-Maria; Giannou, Haralambos; Poulopoulou, Cornelia; Soldatos, Constantine

2007-02-12

In spite of recent enrichment of neurochemical and behavioural data establishing a neuroprotective role for lithium, its primary effects on cognitive functioning remain ambiguous. This study examines chronic lithium effects on spatial working memory and long-term retention. In three discrete experiments, rats subjected to 30 daily intraperitoneal injections (2mmol/kg) of lithium (lithium groups: serum lithium=0.5+/-0.4mEq/l, 12h post-injection) or saline (controls) were trained in 0-s delay T-maze alternation and then tested in 30-, 45- and 60-s delay alternation (Experiments 1, 2, 3, respectively). Animals from Experiment 1 were further tested in one-trial step-through passive avoidance under mild shock parameters (0.5mA, 1s). Retention was assessed 6h later. Daily lithium or saline injections continued throughout behavioural testing. Lithium animals were indistinguishable from controls during 0-delay alternation baseline (Experiments 1-3, accuracy>88%) but showed significantly higher accuracy than controls at 30- and 45-s delays (93% versus 85% and 92% versus 82%, Experiments 1 and 2, respectively). At 60-s delay (Experiment 3) this beneficial effect of lithium was no longer apparent (lithium and control accuracy=78%). In Experiment 4, the shock used did not support 6-h passive avoidance retention in controls, whereas lithium animals showed significant step-through latency increases. Chronic lithium enhanced spatial working memory and promoted long-term retention of a weak aversive contingency. The results suggest that lithium may have potential as a cognitive enhancer.

Unstructured Adaptive (UA) NAS Parallel Benchmark. Version 1.0

NASA Technical Reports Server (NTRS)

Feng, Huiyu; VanderWijngaart, Rob; Biswas, Rupak; Mavriplis, Catherine

2004-01-01

We present a complete specification of a new benchmark for measuring the performance of modern computer systems when solving scientific problems featuring irregular, dynamic memory accesses. It complements the existing NAS Parallel Benchmark suite. The benchmark involves the solution of a stylized heat transfer problem in a cubic domain, discretized on an adaptively refined, unstructured mesh.

Distinguishing Discrete and Gradient Category Structure in Language: Insights from Verb-Particle Constructions

ERIC Educational Resources Information Center

Brehm, Laurel; Goldrick, Matthew

2017-01-01

The current work uses memory errors to examine the mental representation of verb-particle constructions (VPCs; e.g., "make up" the story, "cut up the meat"). Some evidence suggests that VPCs are represented by a cline in which the relationship between the VPC and its component elements ranges from highly transparent ("cut…

Context Fear Learning Specifically Activates Distinct Populations of Neurons in Amygdala and Hypothalamus

ERIC Educational Resources Information Center

Trogrlic, Lidia; Wilson, Yvette M.; Newman, Andrew G.; Murphy, Mark

2011-01-01

The identity and distribution of neurons that are involved in any learning or memory event is not known. In previous studies, we identified a discrete population of neurons in the lateral amygdala that show learning-specific activation of a c-"fos"-regulated transgene following context fear conditioning. Here, we have extended these studies to…

An Efficient Means of Adaptive Refinement Within Systems of Overset Grids

NASA Technical Reports Server (NTRS)

Meakin, Robert L.

1996-01-01

An efficient means of adaptive refinement within systems of overset grids is presented. Problem domains are segregated into near-body and off-body fields. Near-body fields are discretized via overlapping body-fitted grids that extend only a short distance from body surfaces. Off-body fields are discretized via systems of overlapping uniform Cartesian grids of varying levels of refinement. a novel off-body grid generation and management scheme provides the mechanism for carrying out adaptive refinement of off-body flow dynamics and solid body motion. The scheme allows for very efficient use of memory resources, and flow solvers and domain connectivity routines that can exploit the structure inherent to uniform Cartesian grids.

Bifurcation and chaos of a new discrete fractional-order logistic map

NASA Astrophysics Data System (ADS)

Ji, YuanDong; Lai, Li; Zhong, SuChuan; Zhang, Lu

2018-04-01

The fractional-order discrete maps with chaotic behaviors based on the theory of ;fractional difference; are proposed in recent years. In this paper, instead of using fractional difference, a new fractionalized logistic map is proposed based on the numerical algorithm of fractional differentiation definition. The bifurcation diagrams of this map with various differential orders are given by numerical simulation. The simulation results show that the fractional-order logistic map derived in this manner holds rich dynamical behaviors because of its memory effect. In addition, new types of behaviors of bifurcation and chaos are found, which are different from those of the integer-order and the previous fractional-order logistic maps.

Adaptive Wavelet Modeling of Geophysical Data

NASA Astrophysics Data System (ADS)

Plattner, A.; Maurer, H.; Dahmen, W.; Vorloeper, J.

2009-12-01

Despite the ever-increasing power of modern computers, realistic modeling of complex three-dimensional Earth models is still a challenging task and requires substantial computing resources. The overwhelming majority of current geophysical modeling approaches includes either finite difference or non-adaptive finite element algorithms, and variants thereof. These numerical methods usually require the subsurface to be discretized with a fine mesh to accurately capture the behavior of the physical fields. However, this may result in excessive memory consumption and computing times. A common feature of most of these algorithms is that the modeled data discretizations are independent of the model complexity, which may be wasteful when there are only minor to moderate spatial variations in the subsurface parameters. Recent developments in the theory of adaptive numerical solvers have the potential to overcome this problem. Here, we consider an adaptive wavelet based approach that is applicable to a large scope of problems, also including nonlinear problems. To the best of our knowledge such algorithms have not yet been applied in geophysics. Adaptive wavelet algorithms offer several attractive features: (i) for a given subsurface model, they allow the forward modeling domain to be discretized with a quasi minimal number of degrees of freedom, (ii) sparsity of the associated system matrices is guaranteed, which makes the algorithm memory efficient, and (iii) the modeling accuracy scales linearly with computing time. We have implemented the adaptive wavelet algorithm for solving three-dimensional geoelectric problems. To test its performance, numerical experiments were conducted with a series of conductivity models exhibiting varying degrees of structural complexity. Results were compared with a non-adaptive finite element algorithm, which incorporates an unstructured mesh to best fit subsurface boundaries. Such algorithms represent the current state-of-the-art in geoelectrical modeling. An analysis of the numerical accuracy as a function of the number of degrees of freedom revealed that the adaptive wavelet algorithm outperforms the finite element solver for simple and moderately complex models, whereas the results become comparable for models with spatially highly variable electrical conductivities. The linear dependency of the modeling error and the computing time proved to be model-independent. This feature will allow very efficient computations using large-scale models as soon as our experimental code is optimized in terms of its implementation.

Determining A Purely Symbolic Transfer Function from Symbol Streams: Theory and Algorithms

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

Griffin, Christopher H

Transfer function modeling is a \\emph{standard technique} in classical Linear Time Invariant and Statistical Process Control. The work of Box and Jenkins was seminal in developing methods for identifying parameters associated with classicalmore » $(r,s,k)$$ transfer functions. Discrete event systems are often \\emph{used} for modeling hybrid control structures and high-level decision problems. \\emph{Examples include} discrete time, discrete strategy repeated games. For these games, a \\emph{discrete transfer function in the form of} an accurate hidden Markov model of input-output relations \\emph{could be used to derive optimal response strategies.} In this paper, we develop an algorithm \\emph{for} creating probabilistic \\textit{Mealy machines} that act as transfer function models for discrete event dynamic systems (DEDS). Our models are defined by three parameters, $$(l_1, l_2, k)$ just as the Box-Jenkins transfer function models. Here $$l_1$$ is the maximal input history lengths to consider, $$l_2$$ is the maximal output history lengths to consider and $k$ is the response lag. Using related results, We show that our Mealy machine transfer functions are optimal in the sense that they maximize the mutual information between the current known state of the DEDS and the next observed input/output pair.« less

Combined Cognitive Training vs. Memory Strategy Training in Healthy Older Adults

PubMed Central

Li, Bing; Zhu, Xinyi; Hou, Jianhua; Chen, Tingji; Wang, Pengyun; Li, Juan

2016-01-01

As mnemonic utilization deficit in older adults associates with age-related decline in executive function, we hypothesized that memory strategy training combined with executive function training might induce larger training effect in memory and broader training effects in non-memory outcomes than pure memory training. The present study compared the effects of combined cognitive training (executive function training plus memory strategy training) to pure memory strategy training. Forty healthy older adults were randomly assigned to a combined cognitive training group or a memory strategy training group. A control group receiving no training was also included. Combined cognitive training group received 16 sessions of training (eight sessions of executive function training followed by eight sessions of memory strategy training). Memory training group received 16 sessions of memory strategy training. The results partly supported our hypothesis in that indeed improved performance on executive function was only found in combined training group, whereas memory performance increased less in combined training compared to memory strategy group. Results suggest that combined cognitive training may be less efficient than pure memory training in memory outcomes, though the influences from insufficient training time and less closeness between trained executive function and working memory could not be excluded; however it has broader training effects in non-memory outcomes. Clinical Trial Registration: www.chictr.org.cn, identifier ChiCTR-OON-16007793. PMID:27375521

Principles of Discrete Time Mechanics

NASA Astrophysics Data System (ADS)

Jaroszkiewicz, George

2014-04-01

1. Introduction; 2. The physics of discreteness; 3. The road to calculus; 4. Temporal discretization; 5. Discrete time dynamics architecture; 6. Some models; 7. Classical cellular automata; 8. The action sum; 9. Worked examples; 10. Lee's approach to discrete time mechanics; 11. Elliptic billiards; 12. The construction of system functions; 13. The classical discrete time oscillator; 14. Type 2 temporal discretization; 15. Intermission; 16. Discrete time quantum mechanics; 17. The quantized discrete time oscillator; 18. Path integrals; 19. Quantum encoding; 20. Discrete time classical field equations; 21. The discrete time Schrodinger equation; 22. The discrete time Klein-Gordon equation; 23. The discrete time Dirac equation; 24. Discrete time Maxwell's equations; 25. The discrete time Skyrme model; 26. Discrete time quantum field theory; 27. Interacting discrete time scalar fields; 28. Space, time and gravitation; 29. Causality and observation; 30. Concluding remarks; Appendix A. Coherent states; Appendix B. The time-dependent oscillator; Appendix C. Quaternions; Appendix D. Quantum registers; References; Index.

A two-factor theory for concussion assessment using ImPACT: memory and speed.

PubMed

Schatz, Philip; Maerlender, Arthur

2013-12-01

We present the initial validation of a two-factor structure of Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) using ImPACT composite scores and document the reliability and validity of this factor structure. Factor analyses were conducted for baseline (N = 21,537) and post-concussion (N = 560) data, yielding "Memory" (Verbal and Visual) and "Speed" (Visual Motor Speed and Reaction Time) Factors; inclusion of Total Symptom Scores resulted in a third discrete factor. Speed and Memory z-scores were calculated, and test-retest reliability (using intra-class correlation coefficients) at 1 month (0.88/0.81), 1 year (0.85/0.75), and 2 years (0.76/0.74) were higher than published data using Composite scores. Speed and Memory scores yielded 89% sensitivity and 70% specificity, which was higher than composites (80%/62%) and comparable with subscales (91%/69%). This emergent two-factor structure has improved test-retest reliability with no loss of sensitivity/specificity and may improve understanding and interpretability of ImPACT test results.

Remembering complex objects in visual working memory: do capacity limits restrict objects or features?

PubMed

Hardman, Kyle O; Cowan, Nelson

2015-03-01

Visual working memory stores stimuli from our environment as representations that can be accessed by high-level control processes. This study addresses a longstanding debate in the literature about whether storage limits in visual working memory include a limit to the complexity of discrete items. We examined the issue with a number of change-detection experiments that used complex stimuli that possessed multiple features per stimulus item. We manipulated the number of relevant features of the stimulus objects in order to vary feature load. In all of our experiments, we found that increased feature load led to a reduction in change-detection accuracy. However, we found that feature load alone could not account for the results but that a consideration of the number of relevant objects was also required. This study supports capacity limits for both feature and object storage in visual working memory. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Space-Bounded Church-Turing Thesis and Computational Tractability of Closed Systems.

PubMed

Braverman, Mark; Schneider, Jonathan; Rojas, Cristóbal

2015-08-28

We report a new limitation on the ability of physical systems to perform computation-one that is based on generalizing the notion of memory, or storage space, available to the system to perform the computation. Roughly, we define memory as the maximal amount of information that the evolving system can carry from one instant to the next. We show that memory is a limiting factor in computation even in lieu of any time limitations on the evolving system-such as when considering its equilibrium regime. We call this limitation the space-bounded Church-Turing thesis (SBCT). The SBCT is supported by a simulation assertion (SA), which states that predicting the long-term behavior of bounded-memory systems is computationally tractable. In particular, one corollary of SA is an explicit bound on the computational hardness of the long-term behavior of a discrete-time finite-dimensional dynamical system that is affected by noise. We prove such a bound explicitly.

Scaling of seismic memory with earthquake size

NASA Astrophysics Data System (ADS)

Zheng, Zeyu; Yamasaki, Kazuko; Tenenbaum, Joel; Podobnik, Boris; Tamura, Yoshiyasu; Stanley, H. Eugene

2012-07-01

It has been observed that discrete earthquake events possess memory, i.e., that events occurring in a particular location are dependent on the history of that location. We conduct an analysis to see whether continuous real-time data also display a similar memory and, if so, whether such autocorrelations depend on the size of earthquakes within close spatiotemporal proximity. We analyze the seismic wave form database recorded by 64 stations in Japan, including the 2011 “Great East Japan Earthquake,” one of the five most powerful earthquakes ever recorded, which resulted in a tsunami and devastating nuclear accidents. We explore the question of seismic memory through use of mean conditional intervals and detrended fluctuation analysis (DFA). We find that the wave form sign series show power-law anticorrelations while the interval series show power-law correlations. We find size dependence in earthquake autocorrelations: as the earthquake size increases, both of these correlation behaviors strengthen. We also find that the DFA scaling exponent α has no dependence on the earthquake hypocenter depth or epicentral distance.

Space-Bounded Church-Turing Thesis and Computational Tractability of Closed Systems

NASA Astrophysics Data System (ADS)

Braverman, Mark; Schneider, Jonathan; Rojas, Cristóbal

2015-08-01

We report a new limitation on the ability of physical systems to perform computation—one that is based on generalizing the notion of memory, or storage space, available to the system to perform the computation. Roughly, we define memory as the maximal amount of information that the evolving system can carry from one instant to the next. We show that memory is a limiting factor in computation even in lieu of any time limitations on the evolving system—such as when considering its equilibrium regime. We call this limitation the space-bounded Church-Turing thesis (SBCT). The SBCT is supported by a simulation assertion (SA), which states that predicting the long-term behavior of bounded-memory systems is computationally tractable. In particular, one corollary of SA is an explicit bound on the computational hardness of the long-term behavior of a discrete-time finite-dimensional dynamical system that is affected by noise. We prove such a bound explicitly.

Graph-cut based discrete-valued image reconstruction.

PubMed

Tuysuzoglu, Ahmet; Karl, W Clem; Stojanovic, Ivana; Castañòn, David; Ünlü, M Selim

2015-05-01

Efficient graph-cut methods have been used with great success for labeling and denoising problems occurring in computer vision. Unfortunately, the presence of linear image mappings has prevented the use of these techniques in most discrete-amplitude image reconstruction problems. In this paper, we develop a graph-cut based framework for the direct solution of discrete amplitude linear image reconstruction problems cast as regularized energy function minimizations. We first analyze the structure of discrete linear inverse problem cost functions to show that the obstacle to the application of graph-cut methods to their solution is the variable mixing caused by the presence of the linear sensing operator. We then propose to use a surrogate energy functional that overcomes the challenges imposed by the sensing operator yet can be utilized efficiently in existing graph-cut frameworks. We use this surrogate energy functional to devise a monotonic iterative algorithm for the solution of discrete valued inverse problems. We first provide experiments using local convolutional operators and show the robustness of the proposed technique to noise and stability to changes in regularization parameter. Then we focus on nonlocal, tomographic examples where we consider limited-angle data problems. We compare our technique with state-of-the-art discrete and continuous image reconstruction techniques. Experiments show that the proposed method outperforms state-of-the-art techniques in challenging scenarios involving discrete valued unknowns.

Performance Prediction Toolkit

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

Chennupati, Gopinath; Santhi, Nanadakishore; Eidenbenz, Stephen

The Performance Prediction Toolkit (PPT), is a scalable co-design tool that contains the hardware and middle-ware models, which accept proxy applications as input in runtime prediction. PPT relies on Simian, a parallel discrete event simulation engine in Python or Lua, that uses the process concept, where each computing unit (host, node, core) is a Simian entity. Processes perform their task through message exchanges to remain active, sleep, wake-up, begin and end. The PPT hardware model of a compute core (such as a Haswell core) consists of a set of parameters, such as clock speed, memory hierarchy levels, their respective sizes,more » cache-lines, access times for different cache levels, average cycle counts of ALU operations, etc. These parameters are ideally read off a spec sheet or are learned using regression models learned from hardware counters (PAPI) data. The compute core model offers an API to the software model, a function called time_compute(), which takes as input a tasklist. A tasklist is an unordered set of ALU, and other CPU-type operations (in particular virtual memory loads and stores). The PPT application model mimics the loop structure of the application and replaces the computational kernels with a call to the hardware model's time_compute() function giving tasklists as input that model the compute kernel. A PPT application model thus consists of tasklists representing kernels and the high-er level loop structure that we like to think of as pseudo code. The key challenge for the hardware model's time_compute-function is to translate virtual memory accesses into actual cache hierarchy level hits and misses.PPT also contains another CPU core level hardware model, Analytical Memory Model (AMM). The AMM solves this challenge soundly, where our previous alternatives explicitly include the L1,L2,L3 hit-rates as inputs to the tasklists. Explicit hit-rates inevitably only reflect the application modeler's best guess, perhaps informed by a few small test problems using hardware counters; also, hard-coded hit-rates make the hardware model insensitive to changes in cache sizes. Alternatively, we use reuse distance distributions in the tasklists. In general, reuse profiles require the application modeler to run a very expensive trace analysis on the real code that realistically can be done at best for small examples.« less

Multiple Types of Memory and Everyday Functional Assessment in Older Adults

PubMed Central

Beaver, Jenna

2017-01-01

Abstract Objective Current proxy measures for assessing everyday functioning (e.g., questionnaires, performance-based measures, and direct observation) show discrepancies in their rating of functional status. The present study investigated the relationship between multiple proxy measures of functional status and content memory (i.e., memory for information), temporal order memory, and prospective memory in an older adult sample. Method A total of 197 community-dwelling older adults who did (n = 45) or did not meet (n = 152) criteria for mild cognitive impairment (MCI), completed six different assessments of functional status (two questionnaires, two performance-based tasks, and two direct observation tasks) as well as experimental measures of content memory, prospective memory, and temporal order memory. Results After controlling for demographics and content memory, the temporal order and prospective memory measures explained a significant amount of variance in all proxy functional status measures. When all variables were entered into the regression analyses, content memory and prospective memory were found to be significant predictors of all measures of functional status, whereas temporal order memory was a significant predictor for the questionnaire and direct observation measures, but not performance-based measures. Conclusion The results suggest that direct observation and questionnaire measures may be able to capture components of everyday functioning that require context and temporal sequencing abilities, such as multi-tasking, that are not as well captured in many current laboratory performance-based measures of functional status. Future research should aim to inform the development and use of maximally effective and valid proxy measures of functional ability. PMID:28334170

Cortical Neural Computation by Discrete Results Hypothesis

PubMed Central

Castejon, Carlos; Nuñez, Angel

2016-01-01

One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called “Discrete Results” (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of “Discrete Results” is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel “Discrete Results” concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast-spiking (FS) interneuron may be a key element in our hypothesis providing the basis for this computation. PMID:27807408

Cortical Neural Computation by Discrete Results Hypothesis.

PubMed

Castejon, Carlos; Nuñez, Angel

2016-01-01

One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called "Discrete Results" (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of "Discrete Results" is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel "Discrete Results" concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast-spiking (FS) interneuron may be a key element in our hypothesis providing the basis for this computation.

Development of a discrete gas-kinetic scheme for simulation of two-dimensional viscous incompressible and compressible flows.

PubMed

Yang, L M; Shu, C; Wang, Y

2016-03-01

In this work, a discrete gas-kinetic scheme (DGKS) is presented for simulation of two-dimensional viscous incompressible and compressible flows. This scheme is developed from the circular function-based GKS, which was recently proposed by Shu and his co-workers [L. M. Yang, C. Shu, and J. Wu, J. Comput. Phys. 274, 611 (2014)]. For the circular function-based GKS, the integrals for conservation forms of moments in the infinity domain for the Maxwellian function-based GKS are simplified to those integrals along the circle. As a result, the explicit formulations of conservative variables and fluxes are derived. However, these explicit formulations of circular function-based GKS for viscous flows are still complicated, which may not be easy for the application by new users. By using certain discrete points to represent the circle in the phase velocity space, the complicated formulations can be replaced by a simple solution process. The basic requirement is that the conservation forms of moments for the circular function-based GKS can be accurately satisfied by weighted summation of distribution functions at discrete points. In this work, it is shown that integral quadrature by four discrete points on the circle, which forms the D2Q4 discrete velocity model, can exactly match the integrals. Numerical results showed that the present scheme can provide accurate numerical results for incompressible and compressible viscous flows with roughly the same computational cost as that needed by the Roe scheme.

Birth weight interacts with a functional variant of the oxytocin receptor gene (OXTR) to predict executive functioning in children.

PubMed

Wade, Mark; Prime, Heather; Hoffmann, Thomas J; Schmidt, Louis A; O'Connor, Thomas G; Jenkins, Jennifer M

2018-02-01

Genetic variation in the oxytocin receptor gene (OXTR) is associated with several psychiatric conditions characterized by deficits in executive functioning (EF). A specific OXTR variant, rs2254298, has previously been associated with brain functioning in regions implicated in EF. Moreover, birth weight variation across the entire range is associated with individual differences in cortical structure and function that underlie EF. This is the first study to examine the main and interactive effect between rs2254298 and birth weight on EF in children. The sample consisted of 310 children from an ongoing longitudinal study. EF was measured at age 4.5 using observational tasks indexing working memory, cognitive flexibility, and inhibitory control. A family-based design that controlled for population admixture, stratification, and nongenomic confounds was employed. A significant genetic association between rs2254298 and EF was observed, with more copies of the major allele (G) associated with higher EF. There was also a significant interaction between rs2254298 and birth weight, such that more copies of the major allele in combination with higher birth weight predicted better EF. Findings suggest that OXTR may be associated with discrete neurocognitive abilities in childhood, and these effects may be modulated by intrauterine conditions related to fetal growth and development.

Relations between the functions of autobiographical memory and psychological wellbeing.

PubMed

Waters, Theodore E A

2014-01-01

Researchers have proposed that autobiographical memory serves three basic functions in everyday life: self-definition, social connection, and directing behaviour (e.g., Bluck, Alea, Habermas, & Rubin, 2005). However, no research has examined relations between the functions of autobiographical memory and healthy functioning (i.e., psychological wellbeing). The present research examined the relations between the self, social, and directive functions of autobiographical memory and three factors of psychological wellbeing in single and recurring autobiographical memories. A total of 103 undergraduate students were recruited and provided ratings of each function for four autobiographical memories (two single, two recurring events). Results found that individuals who use their autobiographical memories to serve self, social, and directive functions reported higher levels of Purpose and Communion and Positive Relationships, and that these relations differ slightly by event type.

The partition function of the Bures ensemble as the τ-function of BKP and DKP hierarchies: continuous and discrete

NASA Astrophysics Data System (ADS)

Hu, Xing-Biao; Li, Shi-Hao

2017-07-01

The relationship between matrix integrals and integrable systems was revealed more than 20 years ago. As is known, matrix integrals over a Gaussian ensemble used in random matrix theory could act as the τ-function of several hierarchies of integrable systems. In this article, we will show that the time-dependent partition function of the Bures ensemble, whose measure has many interesting geometric properties, could act as the τ-function of BKP and DKP hierarchies. In addition, if discrete time variables are introduced, then this partition function could act as the τ-function of discrete BKP and DKP hierarchies. In particular, there are some links between the partition function of the Bures ensemble and Toda-type equations.

Study of the Gray Scale, Polychromatic, Distortion Invariant Neural Networks Using the Ipa Model.

NASA Astrophysics Data System (ADS)

Uang, Chii-Maw

Research in the optical neural network field is primarily motivated by the fact that humans recognize objects better than the conventional digital computers and the massively parallel inherent nature of optics. This research represents a continuous effort during the past several years in the exploitation of using neurocomputing for pattern recognition. Based on the interpattern association (IPA) model and Hamming net model, many new systems and applications are introduced. A gray level discrete associative memory that is based on object decomposition/composition is proposed for recognizing gray-level patterns. This technique extends the processing ability from the binary mode to gray-level mode, and thus the information capacity is increased. Two polychromatic optical neural networks using color liquid crystal television (LCTV) panels for color pattern recognition are introduced. By introducing a color encoding technique in conjunction with the interpattern associative algorithm, a color associative memory was realized. Based on the color decomposition and composition technique, a color exemplar-based Hamming net was built for color image classification. A shift-invariant neural network is presented through use of the translation invariant property of the modulus of the Fourier transformation and the hetero-associative interpattern association (IPA) memory. To extract the main features, a quadrantal sampling method is used to sampled data and then replace the training patterns. Using the concept of hetero-associative memory to recall the distorted object. A shift and rotation invariant neural network using an interpattern hetero-association (IHA) model is presented. To preserve the shift and rotation invariant properties, a set of binarized-encoded circular harmonic expansion (CHE) functions at the Fourier domain is used as the training set. We use the shift and symmetric properties of the modulus of the Fourier spectrum to avoid the problem of centering the CHE functions. Almost all neural networks have the positive and negative weights, which increases the difficulty of optical implementation. A method to construct a unipolar IPA IWM is discussed. By searching the redundant interconnection links, an effective way that removes all negative links is discussed.

Multiple Types of Memory and Everyday Functional Assessment in Older Adults.

PubMed

Beaver, Jenna; Schmitter-Edgecombe, Maureen

2017-06-01

Current proxy measures for assessing everyday functioning (e.g., questionnaires, performance-based measures, and direct observation) show discrepancies in their rating of functional status. The present study investigated the relationship between multiple proxy measures of functional status and content memory (i.e., memory for information), temporal order memory, and prospective memory in an older adult sample. A total of 197 community-dwelling older adults who did (n = 45) or did not meet (n = 152) criteria for mild cognitive impairment (MCI), completed six different assessments of functional status (two questionnaires, two performance-based tasks, and two direct observation tasks) as well as experimental measures of content memory, prospective memory, and temporal order memory. After controlling for demographics and content memory, the temporal order and prospective memory measures explained a significant amount of variance in all proxy functional status measures. When all variables were entered into the regression analyses, content memory and prospective memory were found to be significant predictors of all measures of functional status, whereas temporal order memory was a significant predictor for the questionnaire and direct observation measures, but not performance-based measures. The results suggest that direct observation and questionnaire measures may be able to capture components of everyday functioning that require context and temporal sequencing abilities, such as multi-tasking, that are not as well captured in many current laboratory performance-based measures of functional status. Future research should aim to inform the development and use of maximally effective and valid proxy measures of functional ability. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Autobiographical Memory Functioning among Abused, Neglected, and Nonmaltreated Children: The Overgeneral Memory Effect

ERIC Educational Resources Information Center

Valentino, Kristin; Toth, Sheree L.; Cicchetti, Dante

2009-01-01

Background: This investigation addresses whether there are differences in the form and content of autobiographical memory recall as a function of maltreatment, and examines the roles of self-system functioning and psychopathology in autobiographical memory processes. Methods: Autobiographical memory for positive and negative nontraumatic events…

A new paper and pencil task reveals adult false belief reasoning bias.

PubMed

Coburn, Patricia I; Bernstein, Daniel M; Begeer, Sander

2015-09-01

Theory of mind (ToM) is the ability to take other people's perspective by inferring their mental state. Most 6-year olds pass the change-of-location false belief task that is commonly used to assess ToM. However, the change-of-location task is not suitable for individuals over 5 years of age, due to its discrete response options. In two experiments, we used a paper and pencil version of a modified change-of-location task (the Real Object Sandbox task) to assess false belief reasoning continuously rather than discretely in adults. Participants heard nine change-of-location scenarios and answered a critical question after each. The memory control questions only required the participant to remember the object's original location, whereas the false belief questions required participants to take the perspective of the protagonist. Participants were more accurate on memory trials than trials requiring perspective taking, and performance on paper and pencil trials correlated with corresponding trials on the Real Object Sandbox task. The Paper and Pencil Sandbox task is a convenient continuous measure of ToM that could be administered to a wide range of age groups.

Using Stocking or Harvesting to Reverse Period-Doubling Bifurcations in Discrete Population Models

Treesearch

James F. Selgrade

1998-01-01

This study considers a general class of 2-dimensional, discrete population models where each per capita transition function (fitness) depends on a linear combination of the densities of the interacting populations. The fitness functions are either monotone decreasing functions (pioneer fitnesses) or one-humped functions (climax fitnesses). Four sets of necessary...

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.

On pseudo-spectral time discretizations in summation-by-parts form

NASA Astrophysics Data System (ADS)

Ruggiu, Andrea A.; Nordström, Jan

2018-05-01

Fully-implicit discrete formulations in summation-by-parts form for initial-boundary value problems must be invertible in order to provide well functioning procedures. We prove that, under mild assumptions, pseudo-spectral collocation methods for the time derivative lead to invertible discrete systems when energy-stable spatial discretizations are used.

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis.

PubMed

Sakhanenko, Nikita A; Kunert-Graf, James; Galas, David J

2017-12-01

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. We present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discrete variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis-that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. We illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.

Schroedinger's Wave Structure of Matter (WSM)

NASA Astrophysics Data System (ADS)

Wolff, Milo; Haselhurst, Geoff

2009-10-01

The puzzling electron is due to the belief that it is a discrete particle. Einstein deduced this structure was impossible since Nature does not allow the discrete particle. Clifford (1876) rejected discrete matter and suggested structures in `space'. Schroedinger, (1937) also eliminated discrete particles writing: What we observe as material bodies and forces are nothing but shapes and variations in the structure of space. Particles are just schaumkommen (appearances). He rejected wave-particle duality. Schroedinger's concept was developed by Milo Wolff and Geoff Haselhurst (SpaceAndMotion.com) using the Scalar Wave Equation to find spherical wave solutions in a 3D quantum space. This WSM, the origin of all the Natural Laws, contains all the electron's properties including the Schroedinger Equation. The origin of Newton's Law F=ma is no longer a puzzle; It originates from Mach's principle of inertia (1883) that depends on the space medium and the WSM. Carver Mead (1999) at CalTech used the WSM to design Intel micro-chips correcting errors of Maxwell's magnetic Equations. Applications of the WSM also describe matter at molecular dimensions: alloys, catalysts, biology and medicine, molecular computers and memories. See ``Schroedinger's Universe'' - at Amazon.com

Schroedinger's Wave Structure of Matter (WSM)

NASA Astrophysics Data System (ADS)

Wolff, Milo

2009-05-01

The puzzling electron is due to the belief that it is a discrete particle. Einstein deduced this structure impossible since Nature does not match the discrete particle. Clifford (1876) rejected discrete matter and suggested structures in `space'. Schroedinger, (1937) also eliminated discrete particles writing: What we observe as material bodies and forces are nothing but shapes and variations in the structure of space. Particles are just schaumkommen (appearances). He rejected wave-particle duality. Schroedinger's concept was developed by Milo Wolff and Geoff Haselhurst (http://www.SpaceAndMotion.com) using the Scalar Wave Equation to find spherical wave solutions in a 3D quantum space. This WSM is the origin of all the Natural Laws; thus it contains all the electron's properties including the Schroedinger Equation. The origin of Newton's Law F=ma is no longer a puzzle; it is shown to originate from Mach's principle of inertia (1883) that depends on the space medium. Carver Mead (1999) applied the WSM to design Intel micro-chips correcting errors of Maxwell's magnetic Equations. Applications of the WSM describe matter at molecular dimensions: alloys, catalysts, the mechanisms of biology and medicine, molecular computers and memories. See http://www.amazon.com/Schro at Amazon.com.

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks.

PubMed

Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

2016-07-14

Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle's position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption.

Solving the Fluid Pressure Poisson Equation Using Multigrid-Evaluation and Improvements.

PubMed

Dick, Christian; Rogowsky, Marcus; Westermann, Rudiger

2016-11-01

In many numerical simulations of fluids governed by the incompressible Navier-Stokes equations, the pressure Poisson equation needs to be solved to enforce mass conservation. Multigrid solvers show excellent convergence in simple scenarios, yet they can converge slowly in domains where physically separated regions are combined at coarser scales. Moreover, existing multigrid solvers are tailored to specific discretizations of the pressure Poisson equation, and they cannot easily be adapted to other discretizations. In this paper we analyze the convergence properties of existing multigrid solvers for the pressure Poisson equation in different simulation domains, and we show how to further improve the multigrid convergence rate by using a graph-based extension to determine the coarse grid hierarchy. The proposed multigrid solver is generic in that it can be applied to different kinds of discretizations of the pressure Poisson equation, by using solely the specification of the simulation domain and pre-assembled computational stencils. We analyze the proposed solver in combination with finite difference and finite volume discretizations of the pressure Poisson equation. Our evaluations show that, despite the common assumption, multigrid schemes can exploit their potential even in the most complicated simulation scenarios, yet this behavior is obtained at the price of higher memory consumption.

The role of executive functioning in memory performance in pediatric focal epilepsy

PubMed Central

Sepeta, Leigh N.; Casaletto, Kaitlin Blackstone; Terwilliger, Virginia; Facella-Ervolini, Joy; Sady, Maegan; Mayo, Jessica; Gaillard, William D.; Berl, Madison M.

2016-01-01

Objective Learning and memory are essential for academic success and everyday functioning, but the pattern of memory skills and its relationship to executive functioning in children with focal epilepsy is not fully delineated. We address a gap in the literature by examining the relationship between memory and executive functioning in a pediatric focal epilepsy population. Methods Seventy children with focal epilepsy and 70 typically developing children matched on age, intellectual functioning, and gender underwent neuropsychological assessment, including measures of intelligence (WASI/DAS), as well as visual (CMS Dot Locations) and verbal episodic memory (WRAML Story Memory and CVLT-C). Executive functioning was measured directly (WISC-IV Digit Span Backward; CELF-IV Recalling Sentences) and by parent report (Behavior Rating Inventory of Executive Function (BRIEF)). Results Children with focal epilepsy had lower delayed free recall scores than controls across visual and verbal memory tasks (p = 0.02; partial η2 = .12). In contrast, recognition memory performance was similar for patients and controls (p = 0.36; partial η2 = .03). Children with focal epilepsy demonstrated difficulties in working memory (p = 0.02; partial η2 = .08) and planning/organization (p = 0.02) compared to controls. Working memory predicted 9–19% of the variance in delayed free recall for verbal and visual memory; organization predicted 9–10% of the variance in verbal memory. Patients with both left and right focal epilepsy demonstrated more difficulty on verbal versus visual tasks (p = 0.002). Memory performance did not differ by location of seizure foci (temporal vs. extra-temporal, frontal vs. extra-frontal). Significance Children with focal epilepsy demonstrated memory ability within age-level expectations, but delayed free recall was inefficient compared to typically developing controls. Memory difficulties were not related to general cognitive impairment or seizure localization. Executive functioning accounted for significant variance in memory performance, suggesting that poor executive control negatively influences memory retrieval. PMID:28111742

Stochastic modeling and simulation of reaction-diffusion system with Hill function dynamics.

PubMed

Chen, Minghan; Li, Fei; Wang, Shuo; Cao, Young

2017-03-14

Stochastic simulation of reaction-diffusion systems presents great challenges for spatiotemporal biological modeling and simulation. One widely used framework for stochastic simulation of reaction-diffusion systems is reaction diffusion master equation (RDME). Previous studies have discovered that for the RDME, when discretization size approaches zero, reaction time for bimolecular reactions in high dimensional domains tends to infinity. In this paper, we demonstrate that in the 1D domain, highly nonlinear reaction dynamics given by Hill function may also have dramatic change when discretization size is smaller than a critical value. Moreover, we discuss methods to avoid this problem: smoothing over space, fixed length smoothing over space and a hybrid method. Our analysis reveals that the switch-like Hill dynamics reduces to a linear function of discretization size when the discretization size is small enough. The three proposed methods could correctly (under certain precision) simulate Hill function dynamics in the microscopic RDME system.

Episodic memory and executive functioning in currently depressed patients compared to healthy controls.

PubMed

Pauls, Franz; Petermann, Franz; Lepach, Anja Christina

2015-01-01

At present, little is still known about the link between depression, memory and executive functioning. This study examined whether there are memory-related impairments in depressed patients and whether the size of such deficits depends on the age group and on specific types of cognitive measures. Memory performances of 215 clinically depressed patients were compared to the data of a matched control sample. Regression analyses were performed to determine the extent to which executive dysfunctions contributed to episodic memory impairments. When compared with healthy controls, significantly lower episodic memory and executive functioning performances were found for depressed patients of all age groups. Effect sizes appeared to vary across different memory and executive functioning measures. The extent to which executive dysfunctions could explain episodic memory impairments varied depending on the type of measure examined. These findings emphasise the need to consider memory-related functioning of depressed patients in the context of therapeutic treatments.

Memory effects in nanoparticle dynamics and transport

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

An interface for the direct coupling of small liquid samples to AMS

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

Ognibene, T. J.; Thomas, A. T.; Daley, P. F.

We describe the moving wire interface attached to the 1-MV AMS system at LLNL’s Center for Accelerator Mass Spectrometry for the analysis of nonvolatile liquid samples as either discrete drops or from the direct output of biochemical separatory instrumentation, such as high-performance liquid chromatography (HPLC). Discrete samples containing at least a few 10 s of nanograms of carbon and as little as 50 zmol 14C can be measured with a 3–5% precision in a few minutes. The dynamic range of our system spans approximately 3 orders in magnitude. Sample to sample memory is minimized by the use of fresh targetsmore » for each discrete sample or by minimizing the amount of carbon present in a peak generated by an HPLC containing a significant amount of 14C. As a result, liquid sample AMS provides a new technology to expand our biomedical AMS program by enabling the capability to measure low-level biochemicals in extremely small samples that would otherwise be inaccessible.« less

An interface for the direct coupling of small liquid samples to AMS

DOE PAGES

Ognibene, T. J.; Thomas, A. T.; Daley, P. F.; ...

2015-05-28

We describe the moving wire interface attached to the 1-MV AMS system at LLNL’s Center for Accelerator Mass Spectrometry for the analysis of nonvolatile liquid samples as either discrete drops or from the direct output of biochemical separatory instrumentation, such as high-performance liquid chromatography (HPLC). Discrete samples containing at least a few 10 s of nanograms of carbon and as little as 50 zmol 14C can be measured with a 3–5% precision in a few minutes. The dynamic range of our system spans approximately 3 orders in magnitude. Sample to sample memory is minimized by the use of fresh targetsmore » for each discrete sample or by minimizing the amount of carbon present in a peak generated by an HPLC containing a significant amount of 14C. As a result, liquid sample AMS provides a new technology to expand our biomedical AMS program by enabling the capability to measure low-level biochemicals in extremely small samples that would otherwise be inaccessible.« less

Does the greater involvement of executive control in memory with age act as a compensatory mechanism?

PubMed

Bouazzaoui, Badiâa; Angel, Lucie; Fay, Séverine; Taconnat, Laurence; Charlotte, Froger; Isingrini, Michel

2014-03-01

Recent behavioural and imaging data have shown that memory functioning seems to rely more on executive functions and on the prefrontal cortex (PFC) in older than in young adults. Using a behavioural approach, our objective was to confirm the hypothesis that young and older adults present different patterns of correlation between episodic memory performance and executive functioning. We report three studies comparing the correlations of young and older adults in a broad range of episodic memory and executive function tasks. The results indicated that memory and executive performance were consistently and significantly correlated in older but not in younger adults. Regression analyses confirmed that age-related differences in episodic memory performance could be explained by individual differences in executive functioning. The results are consistent with the view that memory functioning in aging is accompanied by a shift from automatic to controlled forms of processing. They also generalise the executive hypothesis of episodic memory aging and are in line with the idea that executive functions act as a compensatory mechanism against age-related memory decline.

The Influence of Fluid Intelligence, Executive Functions and Premorbid Intelligence on Memory in Frontal Patients.

PubMed

Chan, Edgar; MacPherson, Sarah E; Bozzali, Marco; Shallice, Tim; Cipolotti, Lisa

2018-01-01

Objective: It is commonly thought that memory deficits in frontal patients are a result of impairments in executive functions which impact upon storage and retrieval processes. Yet, few studies have specifically examined the relationship between memory performance and executive functions in frontal patients. Furthermore, the contribution of more general cognitive processes such as fluid intelligence and demographic factors such as age, education, and premorbid intelligence has not been considered. Method: Our study examined the relationship between recall and recognition memory and performance on measures of fluid intelligence, executive functions and premorbid intelligence in 39 frontal patients and 46 healthy controls. Results: Recall memory impairments in frontal patients were strongly correlated with fluid intelligence, executive functions and premorbid intelligence. These factors were all found to be independent predictors of recall performance, with fluid intelligence being the strongest predictor. In contrast, recognition memory impairments were not related to any of these factors. Furthermore, age and education were not significantly correlated with either recall or recognition memory measures. Conclusion: Our findings show that recall memory in frontal patients was related to fluid intelligence, executive functions and premorbid intelligence. In contrast, recognition memory was not. These findings suggest that recall and recognition memory deficits following frontal injury arise from separable cognitive factors. Recognition memory tests may be more useful when assessing memory functions in frontal patients.

The Influence of Fluid Intelligence, Executive Functions and Premorbid Intelligence on Memory in Frontal Patients

PubMed Central

Chan, Edgar; MacPherson, Sarah E.; Bozzali, Marco; Shallice, Tim; Cipolotti, Lisa

2018-01-01

Objective: It is commonly thought that memory deficits in frontal patients are a result of impairments in executive functions which impact upon storage and retrieval processes. Yet, few studies have specifically examined the relationship between memory performance and executive functions in frontal patients. Furthermore, the contribution of more general cognitive processes such as fluid intelligence and demographic factors such as age, education, and premorbid intelligence has not been considered. Method: Our study examined the relationship between recall and recognition memory and performance on measures of fluid intelligence, executive functions and premorbid intelligence in 39 frontal patients and 46 healthy controls. Results: Recall memory impairments in frontal patients were strongly correlated with fluid intelligence, executive functions and premorbid intelligence. These factors were all found to be independent predictors of recall performance, with fluid intelligence being the strongest predictor. In contrast, recognition memory impairments were not related to any of these factors. Furthermore, age and education were not significantly correlated with either recall or recognition memory measures. Conclusion: Our findings show that recall memory in frontal patients was related to fluid intelligence, executive functions and premorbid intelligence. In contrast, recognition memory was not. These findings suggest that recall and recognition memory deficits following frontal injury arise from separable cognitive factors. Recognition memory tests may be more useful when assessing memory functions in frontal patients. PMID:29937746

Self-consistent field theory simulations of polymers on arbitrary domains

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

Ouaknin, Gaddiel, E-mail: gaddielouaknin@umail.ucsb.edu; Laachi, Nabil; Delaney, Kris

2016-12-15

We introduce a framework for simulating the mesoscale self-assembly of block copolymers in arbitrary confined geometries subject to Neumann boundary conditions. We employ a hybrid finite difference/volume approach to discretize the mean-field equations on an irregular domain represented implicitly by a level-set function. The numerical treatment of the Neumann boundary conditions is sharp, i.e. it avoids an artificial smearing in the irregular domain boundary. This strategy enables the study of self-assembly in confined domains and enables the computation of physically meaningful quantities at the domain interface. In addition, we employ adaptive grids encoded with Quad-/Oc-trees in parallel to automatically refinemore » the grid where the statistical fields vary rapidly as well as at the boundary of the confined domain. This approach results in a significant reduction in the number of degrees of freedom and makes the simulations in arbitrary domains using effective boundary conditions computationally efficient in terms of both speed and memory requirement. Finally, in the case of regular periodic domains, where pseudo-spectral approaches are superior to finite differences in terms of CPU time and accuracy, we use the adaptive strategy to store chain propagators, reducing the memory footprint without loss of accuracy in computed physical observables.« less

Multiprocessing MCNP on an IBM RS/6000 cluster

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

McKinney, G.W.; West, J.T.

1993-01-01

The advent of high-performance computer systems has brought to maturity programming concepts like vectorization, multiprocessing, and multitasking. While there are many schools of thought as to the most significant factor in obtaining order-of-magnitude increases in performance, such speedup can only be achieved by integrating the computer system and application code. Vectorization leads to faster manipulation of arrays by overlapping instruction CPU cycles. Discrete ordinates codes, which require the solving of large matrices, have proved to be major benefactors of vectorization. Monte Carlo transport, on the other hand, typically contains numerous logic statements and requires extensive redevelopment to benefit from vectorization.more » Multiprocessing and multitasking provide additional CPU cycles via multiple processors. Such systems are generally designed with either common memory access (multitasking) or distributed memory access. In both cases, theoretical speedup, as a function of the number of processors (P) and the fraction of task time that multiprocesses (f), can be formulated using Amdahl's Law S ((f,P) = 1 f + f/P). However, for most applications this theoretical limit cannot be achieved, due to additional terms not included in Amdahl's Law. Monte Carlo transport is a natural candidate for multiprocessing, since the particle tracks are generally independent and the precision of the result increases as the square root of the number of particles tracked.« less

Differential Entropy Preserves Variational Information of Near-Infrared Spectroscopy Time Series Associated With Working Memory

PubMed Central

Keshmiri, Soheil; Sumioka, Hidenubo; Yamazaki, Ryuji; Ishiguro, Hiroshi

2018-01-01

Neuroscience research shows a growing interest in the application of Near-Infrared Spectroscopy (NIRS) in analysis and decoding of the brain activity of human subjects. Given the correlation that is observed between the Blood Oxygen Dependent Level (BOLD) responses that are exhibited by the time series data of functional Magnetic Resonance Imaging (fMRI) and the hemoglobin oxy/deoxy-genation that is captured by NIRS, linear models play a central role in these applications. This, in turn, results in adaptation of the feature extraction strategies that are well-suited for discretization of data that exhibit a high degree of linearity, namely, slope and the mean as well as their combination, to summarize the informational contents of the NIRS time series. In this article, we demonstrate that these features are inefficient in capturing the variational information of NIRS data, limiting the reliability and the adequacy of the conclusion on their results. Alternatively, we propose the linear estimate of differential entropy of these time series as a natural representation of such information. We provide evidence for our claim through comparative analysis of the application of these features on NIRS data pertinent to several working memory tasks as well as naturalistic conversational stimuli. PMID:29922144

Advanced Age Dissociates Dual Functions of the Perirhinal Cortex

PubMed Central

Burke, Sara N.; Maurer, Andrew P.; Nematollahi, Saman; Uprety, Ajay; Wallace, Jenelle L.

2014-01-01

The perirhinal cortex (PRC) is proposed to both represent high-order sensory information and maintain those representations across delays. These cognitive processes are required for recognition memory, which declines during normal aging. Whether or not advanced age affects the ability of PRC principal cells to support these dual roles, however, is not known. The current experiment recorded PRC neurons as young and aged rats traversed a track. When objects were placed on the track, a subset of the neurons became active at discrete locations adjacent to objects. Importantly, the aged rats had a lower proportion of neurons that were activated by objects. Once PRC activity patterns in the presence of objects were established, however, both age groups maintained these representations across delays up to 2 h. These data support the hypothesis that age-associated deficits in stimulus recognition arise from impairments in high-order stimulus representation rather than difficulty in sustaining stable activity patterns over time. PMID:24403147

Advanced age dissociates dual functions of the perirhinal cortex.

PubMed

Burke, Sara N; Maurer, Andrew P; Nematollahi, Saman; Uprety, Ajay; Wallace, Jenelle L; Barnes, Carol A

2014-01-08

The perirhinal cortex (PRC) is proposed to both represent high-order sensory information and maintain those representations across delays. These cognitive processes are required for recognition memory, which declines during normal aging. Whether or not advanced age affects the ability of PRC principal cells to support these dual roles, however, is not known. The current experiment recorded PRC neurons as young and aged rats traversed a track. When objects were placed on the track, a subset of the neurons became active at discrete locations adjacent to objects. Importantly, the aged rats had a lower proportion of neurons that were activated by objects. Once PRC activity patterns in the presence of objects were established, however, both age groups maintained these representations across delays up to 2 h. These data support the hypothesis that age-associated deficits in stimulus recognition arise from impairments in high-order stimulus representation rather than difficulty in sustaining stable activity patterns over time.

Image analysis for microelectronic retinal prosthesis.

PubMed

Hallum, L E; Cloherty, S L; Lovell, N H

2008-01-01

By way of extracellular, stimulating electrodes, a microelectronic retinal prosthesis aims to render discrete, luminous spots-so-called phosphenes-in the visual field, thereby providing a phosphene image (PI) as a rudimentary remediation of profound blindness. As part thereof, a digital camera, or some other photosensitive array, captures frames, frames are analyzed, and phosphenes are actuated accordingly by way of modulated charge injections. Here, we present a method that allows the assessment of image analysis schemes for integration with a prosthetic device, that is, the means of converting the captured image (high resolution) to modulated charge injections (low resolution). We use the mutual-information function to quantify the amount of information conveyed to the PI observer (device implantee), while accounting for the statistics of visual stimuli. We demonstrate an effective scheme involving overlapping, Gaussian kernels, and discuss extensions of the method to account for shortterm visual memory in observers, and their perceptual errors of omission and commission.

Fourier-Accelerated Nodal Solvers (FANS) for homogenization problems

NASA Astrophysics Data System (ADS)

Leuschner, Matthias; Fritzen, Felix

2017-11-01

Fourier-based homogenization schemes are useful to analyze heterogeneous microstructures represented by 2D or 3D image data. These iterative schemes involve discrete periodic convolutions with global ansatz functions (mostly fundamental solutions). The convolutions are efficiently computed using the fast Fourier transform. FANS operates on nodal variables on regular grids and converges to finite element solutions. Compared to established Fourier-based methods, the number of convolutions is reduced by FANS. Additionally, fast iterations are possible by assembling the stiffness matrix. Due to the related memory requirement, the method is best suited for medium-sized problems. A comparative study involving established Fourier-based homogenization schemes is conducted for a thermal benchmark problem with a closed-form solution. Detailed technical and algorithmic descriptions are given for all methods considered in the comparison. Furthermore, many numerical examples focusing on convergence properties for both thermal and mechanical problems, including also plasticity, are presented.

Functional expansion representations of artificial neural networks

NASA Technical Reports Server (NTRS)

Gray, W. Steven

1992-01-01

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

Multilevel Green's function interpolation method for scattering from composite metallic and dielectric objects.

PubMed

Shi, Yan; Wang, Hao Gang; Li, Long; Chan, Chi Hou

2008-10-01

A multilevel Green's function interpolation method based on two kinds of multilevel partitioning schemes--the quasi-2D and the hybrid partitioning scheme--is proposed for analyzing electromagnetic scattering from objects comprising both conducting and dielectric parts. The problem is formulated using the surface integral equation for homogeneous dielectric and conducting bodies. A quasi-2D multilevel partitioning scheme is devised to improve the efficiency of the Green's function interpolation. In contrast to previous multilevel partitioning schemes, noncubic groups are introduced to discretize the whole EM structure in this quasi-2D multilevel partitioning scheme. Based on the detailed analysis of the dimension of the group in this partitioning scheme, a hybrid quasi-2D/3D multilevel partitioning scheme is proposed to effectively handle objects with fine local structures. Selection criteria for some key parameters relating to the interpolation technique are given. The proposed algorithm is ideal for the solution of problems involving objects such as missiles, microstrip antenna arrays, photonic bandgap structures, etc. Numerical examples are presented to show that CPU time is between O(N) and O(N log N) while the computer memory requirement is O(N).

Joint image and motion reconstruction for PET using a B-spline motion model.

PubMed

Blume, Moritz; Navab, Nassir; Rafecas, Magdalena

2012-12-21

We present a novel joint image and motion reconstruction method for PET. The method is based on gated data and reconstructs an image together with a motion function. The motion function can be used to transform the reconstructed image to any of the input gates. All available events (from all gates) are used in the reconstruction. The presented method uses a B-spline motion model, together with a novel motion regularization procedure that does not need a regularization parameter (which is usually extremely difficult to adjust). Several image and motion grid levels are used in order to reduce the reconstruction time. In a simulation study, the presented method is compared to a recently proposed joint reconstruction method. While the presented method provides comparable reconstruction quality, it is much easier to use since no regularization parameter has to be chosen. Furthermore, since the B-spline discretization of the motion function depends on fewer parameters than a displacement field, the presented method is considerably faster and consumes less memory than its counterpart. The method is also applied to clinical data, for which a novel purely data-driven gating approach is presented.

The role of executive functioning in memory performance in pediatric focal epilepsy.

PubMed

Sepeta, Leigh N; Casaletto, Kaitlin Blackstone; Terwilliger, Virginia; Facella-Ervolini, Joy; Sady, Maegan; Mayo, Jessica; Gaillard, William D; Berl, Madison M

2017-02-01

Learning and memory are essential for academic success and everyday functioning, but the pattern of memory skills and its relationship to executive functioning in children with focal epilepsy is not fully delineated. We address a gap in the literature by examining the relationship between memory and executive functioning in a pediatric focal epilepsy population. Seventy children with focal epilepsy and 70 typically developing children matched on age, intellectual functioning, and gender underwent neuropsychological assessment, including measures of intelligence (Wechsler Abbreviated Scale of Intelligence [WASI]/Differential Ability Scales [DAS]), as well as visual Children's Memory Scale (CMS Dot Locations) and verbal episodic memory (Wide Range Assessment of Memory and Learning [WRAML] Story Memory and California Verbal Learning Test for Children [CVLT-C]). Executive functioning was measured directly (WISC-IV Digit Span Backward; Clinical Evaluation of Language Fundamentals, Fourth Edition (CELF-IV) Recalling Sentences) and by parent report (Behavior Rating Inventory of Executive Function [BRIEF]). Children with focal epilepsy had lower delayed free-recall scores than controls across visual and verbal memory tasks (p = 0.02; partial η 2 = 0.12). In contrast, recognition memory performance was similar for patients and controls (p = 0.36; partial η 2 = 0.03). Children with focal epilepsy demonstrated difficulties in working memory (p = 0.02; partial η 2 = 0.08) and planning/organization (p = 0.02) compared to controls. Working memory predicted 9-19% of the variance in delayed free recall for verbal and visual memory; organization predicted 9-10% of the variance in verbal memory. Patients with both left and right focal epilepsy demonstrated more difficulty on verbal versus visual tasks (p = 0.002). Memory performance did not differ by location of seizure foci (temporal vs. extratemporal, frontal vs. extrafrontal). Children with focal epilepsy demonstrated memory ability within age-level expectations, but delayed free recall was inefficient compared to typically developing controls. Memory difficulties were not related to general cognitive impairment or seizure localization. Executive functioning accounted for significant variance in memory performance, suggesting that poor executive control negatively influences memory retrieval. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Fortran programs for the time-dependent Gross-Pitaevskii equation in a fully anisotropic trap

NASA Astrophysics Data System (ADS)

Muruganandam, P.; Adhikari, S. K.

2009-10-01

Here we develop simple numerical algorithms for both stationary and non-stationary solutions of the time-dependent Gross-Pitaevskii (GP) equation describing the properties of Bose-Einstein condensates at ultra low temperatures. In particular, we consider algorithms involving real- and imaginary-time propagation based on a split-step Crank-Nicolson method. In a one-space-variable form of the GP equation we consider the one-dimensional, two-dimensional circularly-symmetric, and the three-dimensional spherically-symmetric harmonic-oscillator traps. In the two-space-variable form we consider the GP equation in two-dimensional anisotropic and three-dimensional axially-symmetric traps. The fully-anisotropic three-dimensional GP equation is also considered. Numerical results for the chemical potential and root-mean-square size of stationary states are reported using imaginary-time propagation programs for all the cases and compared with previously obtained results. Also presented are numerical results of non-stationary oscillation for different trap symmetries using real-time propagation programs. A set of convenient working codes developed in Fortran 77 are also provided for all these cases (twelve programs in all). In the case of two or three space variables, Fortran 90/95 versions provide some simplification over the Fortran 77 programs, and these programs are also included (six programs in all). Program summaryProgram title: (i) imagetime1d, (ii) imagetime2d, (iii) imagetime3d, (iv) imagetimecir, (v) imagetimesph, (vi) imagetimeaxial, (vii) realtime1d, (viii) realtime2d, (ix) realtime3d, (x) realtimecir, (xi) realtimesph, (xii) realtimeaxial Catalogue identifier: AEDU_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEDU_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 122 907 No. of bytes in distributed program, including test data, etc.: 609 662 Distribution format: tar.gz Programming language: FORTRAN 77 and Fortran 90/95 Computer: PC Operating system: Linux, Unix RAM: 1 GByte (i, iv, v), 2 GByte (ii, vi, vii, x, xi), 4 GByte (iii, viii, xii), 8 GByte (ix) Classification: 2.9, 4.3, 4.12 Nature of problem: These programs are designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in one-, two- or three-space dimensions with a harmonic, circularly-symmetric, spherically-symmetric, axially-symmetric or anisotropic trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Solution method: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation, in either imaginary or real time, over small time steps. The method yields the solution of stationary and/or non-stationary problems. Additional comments: This package consists of 12 programs, see "Program title", above. FORTRAN77 versions are provided for each of the 12 and, in addition, Fortran 90/95 versions are included for ii, iii, vi, viii, ix, xii. For the particular purpose of each program please see the below. Running time: Minutes on a medium PC (i, iv, v, vii, x, xi), a few hours on a medium PC (ii, vi, viii, xii), days on a medium PC (iii, ix). Program summary (1)Title of program: imagtime1d.F Title of electronic file: imagtime1d.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 1 GByte Programming language used: Fortran 77 Typical running time: Minutes on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in one-space dimension with a harmonic trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in imaginary time over small time steps. The method yields the solution of stationary problems. Program summary (2)Title of program: imagtimecir.F Title of electronic file: imagtimecir.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 1 GByte Programming language used: Fortran 77 Typical running time: Minutes on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in two-space dimensions with a circularly-symmetric trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in imaginary time over small time steps. The method yields the solution of stationary problems. Program summary (3)Title of program: imagtimesph.F Title of electronic file: imagtimesph.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 1 GByte Programming language used: Fortran 77 Typical running time: Minutes on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in three-space dimensions with a spherically-symmetric trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in imaginary time over small time steps. The method yields the solution of stationary problems. Program summary (4)Title of program: realtime1d.F Title of electronic file: realtime1d.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 2 GByte Programming language used: Fortran 77 Typical running time: Minutes on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in one-space dimension with a harmonic trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in real time over small time steps. The method yields the solution of stationary and non-stationary problems. Program summary (5)Title of program: realtimecir.F Title of electronic file: realtimecir.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 2 GByte Programming language used: Fortran 77 Typical running time: Minutes on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in two-space dimensions with a circularly-symmetric trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in real time over small time steps. The method yields the solution of stationary and non-stationary problems. Program summary (6)Title of program: realtimesph.F Title of electronic file: realtimesph.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 2 GByte Programming language used: Fortran 77 Typical running time: Minutes on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in three-space dimensions with a spherically-symmetric trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in real time over small time steps. The method yields the solution of stationary and non-stationary problems. Program summary (7)Title of programs: imagtimeaxial.F and imagtimeaxial.f90 Title of electronic file: imagtimeaxial.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 2 GByte Programming language used: Fortran 77 and Fortran 90 Typical running time: Few hours on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in three-space dimensions with an axially-symmetric trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in imaginary time over small time steps. The method yields the solution of stationary problems. Program summary (8)Title of program: imagtime2d.F and imagtime2d.f90 Title of electronic file: imagtime2d.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 2 GByte Programming language used: Fortran 77 and Fortran 90 Typical running time: Few hours on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in two-space dimensions with an anisotropic trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in imaginary time over small time steps. The method yields the solution of stationary problems. Program summary (9)Title of program: realtimeaxial.F and realtimeaxial.f90 Title of electronic file: realtimeaxial.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 4 GByte Programming language used: Fortran 77 and Fortran 90 Typical running time Hours on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in three-space dimensions with an axially-symmetric trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in real time over small time steps. The method yields the solution of stationary and non-stationary problems. Program summary (10)Title of program: realtime2d.F and realtime2d.f90 Title of electronic file: realtime2d.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 4 GByte Programming language used: Fortran 77 and Fortran 90 Typical running time: Hours on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in two-space dimensions with an anisotropic trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in real time over small time steps. The method yields the solution of stationary and non-stationary problems. Program summary (11)Title of program: imagtime3d.F and imagtime3d.f90 Title of electronic file: imagtime3d.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 4 GByte Programming language used: Fortran 77 and Fortran 90 Typical running time: Few days on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in three-space dimensions with an anisotropic trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in imaginary time over small time steps. The method yields the solution of stationary problems. Program summary (12)Title of program: realtime3d.F and realtime3d.f90 Title of electronic file: realtime3d.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum Ram Memory: 8 GByte Programming language used: Fortran 77 and Fortran 90 Typical running time: Days on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in three-space dimensions with an anisotropic trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in real time over small time steps. The method yields the solution of stationary and non-stationary problems.

Novel structures for Discrete Hartley Transform based on first-order moments

NASA Astrophysics Data System (ADS)

Xiong, Jun; Zheng, Wenjuan; Wang, Hao; Liu, Jianguo

2018-03-01

Discrete Hartley Transform (DHT) is an important tool in digital signal processing. In the present paper, the DHT is firstly transformed into the first-order moments-based form, then a new fast algorithm is proposed to calculate the first-order moments without multiplication. Based on the algorithm theory, the corresponding hardware architecture for DHT is proposed, which only contains shift operations and additions with no need for multipliers and large memory. To verify the availability and effectiveness, the proposed design is implemented with hardware description language and synthesized by Synopsys Design Compiler with 0.18-μm SMIC library. A series of experiments have proved that the proposed architecture has better performance in terms of the product of the hardware consumption and computation time.

Memory and long-range correlations in chess games

NASA Astrophysics Data System (ADS)

Schaigorodsky, Ana L.; Perotti, Juan I.; Billoni, Orlando V.

2014-01-01

In this paper we report the existence of long-range memory in the opening moves of a chronologically ordered set of chess games using an extensive chess database. We used two mapping rules to build discrete time series and analyzed them using two methods for detecting long-range correlations; rescaled range analysis and detrended fluctuation analysis. We found that long-range memory is related to the level of the players. When the database is filtered according to player levels we found differences in the persistence of the different subsets. For high level players, correlations are stronger at long time scales; whereas in intermediate and low level players they reach the maximum value at shorter time scales. This can be interpreted as a signature of the different strategies used by players with different levels of expertise. These results are robust against the assignation rules and the method employed in the analysis of the time series.

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.

A Design of Finite Memory Residual Generation Filter for Sensor Fault Detection

NASA Astrophysics Data System (ADS)

Kim, Pyung Soo

2017-04-01

In the current paper, a residual generation filter with finite memory structure is proposed for sensor fault detection. The proposed finite memory residual generation filter provides the residual by real-time filtering of fault vector using only the most recent finite measurements and inputs on the window. It is shown that the residual given by the proposed residual generation filter provides the exact fault for noisefree systems. The proposed residual generation filter is specified to the digital filter structure for the amenability to hardware implementation. Finally, to illustrate the capability of the proposed residual generation filter, extensive simulations are performed for the discretized DC motor system with two types of sensor faults, incipient soft bias-type fault and abrupt bias-type fault. In particular, according to diverse noise levels and windows lengths, meaningful simulation results are given for the abrupt bias-type fault.

Inflated speedups in parallel simulations via malloc()

NASA Technical Reports Server (NTRS)

Nicol, David M.

1990-01-01

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

Stabilisation of discrete-time polynomial fuzzy systems via a polynomial lyapunov approach

NASA Astrophysics Data System (ADS)

Nasiri, Alireza; Nguang, Sing Kiong; Swain, Akshya; Almakhles, Dhafer

2018-02-01

This paper deals with the problem of designing a controller for a class of discrete-time nonlinear systems which is represented by discrete-time polynomial fuzzy model. Most of the existing control design methods for discrete-time fuzzy polynomial systems cannot guarantee their Lyapunov function to be a radially unbounded polynomial function, hence the global stability cannot be assured. The proposed control design in this paper guarantees a radially unbounded polynomial Lyapunov functions which ensures global stability. In the proposed design, state feedback structure is considered and non-convexity problem is solved by incorporating an integrator into the controller. Sufficient conditions of stability are derived in terms of polynomial matrix inequalities which are solved via SOSTOOLS in MATLAB. A numerical example is presented to illustrate the effectiveness of the proposed controller.

77 FR 18687 - Guidance Regarding Deduction and Capitalization of Expenditures Related to Tangible Property...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-28

... 20. * * * The plumbing fixtures in all the restrooms perform a discrete and critical function in the... fixtures in the hotel building perform a discrete and critical function in the operation of the plumbing...

Memory Hazard Functions: A Vehicle for Theory Development and Test

ERIC Educational Resources Information Center

Chechile, Richard A.

2006-01-01

A framework is developed to rigorously test an entire class of memory retention functions by examining hazard properties. Evidence is provided that the memory hazard function is not monotonically decreasing. Yet most of the proposals for retention functions, which have emerged from the psychological literature, imply that memory hazard is…

Quantum circuit dynamics via path integrals: Is there a classical action for discrete-time paths?

NASA Astrophysics Data System (ADS)

Penney, Mark D.; Enshan Koh, Dax; Spekkens, Robert W.

2017-07-01

It is straightforward to compute the transition amplitudes of a quantum circuit using the sum-over-paths methodology when the gates in the circuit are balanced, where a balanced gate is one for which all non-zero transition amplitudes are of equal magnitude. Here we consider the question of whether, for such circuits, the relative phases of different discrete-time paths through the configuration space can be defined in terms of a classical action, as they are for continuous-time paths. We show how to do so for certain kinds of quantum circuits, namely, Clifford circuits where the elementary systems are continuous-variable systems or discrete systems of odd-prime dimension. These types of circuit are distinguished by having phase-space representations that serve to define their classical counterparts. For discrete systems, the phase-space coordinates are also discrete variables. We show that for each gate in the generating set, one can associate a symplectomorphism on the phase-space and to each of these one can associate a generating function, defined on two copies of the configuration space. For discrete systems, the latter association is achieved using tools from algebraic geometry. Finally, we show that if the action functional for a discrete-time path through a sequence of gates is defined using the sum of the corresponding generating functions, then it yields the correct relative phases for the path-sum expression. These results are likely to be relevant for quantizing physical theories where time is fundamentally discrete, characterizing the classical limit of discrete-time quantum dynamics, and proving complexity results for quantum circuits.

Infant differential behavioral responding to discrete emotions.

PubMed

Walle, Eric A; Reschke, Peter J; Camras, Linda A; Campos, Joseph J

2017-10-01

Emotional communication regulates the behaviors of social partners. Research on individuals' responding to others' emotions typically compares responses to a single negative emotion compared with responses to a neutral or positive emotion. Furthermore, coding of such responses routinely measure surface level features of the behavior (e.g., approach vs. avoidance) rather than its underlying function (e.g., the goal of the approach or avoidant behavior). This investigation examined infants' responding to others' emotional displays across 5 discrete emotions: joy, sadness, fear, anger, and disgust. Specifically, 16-, 19-, and 24-month-old infants observed an adult communicate a discrete emotion toward a stimulus during a naturalistic interaction. Infants' responses were coded to capture the function of their behaviors (e.g., exploration, prosocial behavior, and security seeking). The results revealed a number of instances indicating that infants use different functional behaviors in response to discrete emotions. Differences in behaviors across emotions were clearest in the 24-month-old infants, though younger infants also demonstrated some differential use of behaviors in response to discrete emotions. This is the first comprehensive study to identify differences in how infants respond with goal-directed behaviors to discrete emotions. Additionally, the inclusion of a function-based coding scheme and interpersonal paradigms may be informative for future emotion research with children and adults. Possible developmental accounts for the observed behaviors and the benefits of coding techniques emphasizing the function of social behavior over their form are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Executive Functions and Working Memory Behaviours in Children with a Poor Working Memory

ERIC Educational Resources Information Center

St. Clair-Thompson, Helen L.

2011-01-01

Previous research has suggested that working memory difficulties play an integral role in children's underachievement at school. However, working memory is just one of several executive functions. The extent to which problems in working memory extend to other executive functions is not well understood. In the current study 38 children with a poor…

Supervisory Control of Discrete Event Systems Modeled by Mealy Automata with Nondeterministic Output Functions

NASA Astrophysics Data System (ADS)

Ushio, Toshimitsu; Takai, Shigemasa

Supervisory control is a general framework of logical control of discrete event systems. A supervisor assigns a set of control-disabled controllable events based on observed events so that the controlled discrete event system generates specified languages. In conventional supervisory control, it is assumed that observed events are determined by internal events deterministically. But, this assumption does not hold in a discrete event system with sensor errors and a mobile system, where each observed event depends on not only an internal event but also a state just before the occurrence of the internal event. In this paper, we model such a discrete event system by a Mealy automaton with a nondeterministic output function. We introduce two kinds of supervisors: one assigns each control action based on a permissive policy and the other based on an anti-permissive one. We show necessary and sufficient conditions for the existence of each supervisor. Moreover, we discuss the relationship between the supervisors in the case that the output function is determinisitic.

Longitudinal Study of a Novel, Performance-based Measure of Daily Function

DTIC Science & Technology

2016-06-01

have functional impairments, and healthy age matched controls on the UPSA, as well as measures of cognition (e.g., episodic memory , semantic memory ...controls on the UPSA, as well as measures of cognition (e.g., episodic memory , semantic memory , executive function, speed). We found that patients with...diagnosis have functional impairments, and healthy age matched controls on the UPSA, as well as measures of cognition (e.g., episodic memory , semantic

Studies of Implicit Prototype Extraction In Patients with Mild Cognitive Impairment and Early Alzheimer’s Disease

PubMed Central

Nosofsky, Robert M.; Denton, Stephen E.; Zaki, Safa R.; Murphy-Knudsen, Anne F.; Unverzagt, Frederick W.

2013-01-01

Studies of incidental category learning support the hypothesis of an implicit prototype-extraction system which is distinct from explicit memory (Smith, 2008). In those studies, patients with explicit-memory impairments due to damage to the medial-temporal lobe performed normally in implicit categorization tasks (Bozoki, Grossman, & Smith, 2006; Knowlton & Squire, 1993). However, alternative interpretations are that: i) even people with impairments to a single memory system have sufficient resources to succeed on the particular categorization tasks that have been tested (Nosofsky & Zaki, 1998; Zaki & Nosofsky, 2001); and ii) working memory can be used at time of test to learn the categories (Palmeri & Flanery, 1999). In the present experiments, patients with amnestic mild cognitive impairment or early Alzheimer’s disease were tested in prototype-extraction tasks to examine these possibilities. In a categorization task involving discrete-feature stimuli, the majority of subjects relied on memories for exceedingly few features, even when the task structure strongly encouraged reliance on broad-based prototypes. In a dot-pattern categorization task, even the memory-impaired patients were able to use working memory at time of test to extract the category structure (at least for the stimulus set used in past work). We argue that the results weaken the past case made in favor of a separate system of implicit-prototype extraction. PMID:22746953

The influence of context boundaries on memory for the sequential order of events.

PubMed

DuBrow, Sarah; Davachi, Lila

2013-11-01

Episodic memory allows people to reexperience the past by recovering the sequences of events that characterize those prior experiences. Although experience is continuous, people are able to selectively retrieve and reexperience more discrete episodes from their past, raising the possibility that some elements become tightly related to each other in memory, whereas others do not. The current series of experiments was designed to ask how shifts in context during an experience influence how people remember the past. Specifically, we asked how context shifts influence the ability to remember the relative order of past events, a hallmark of episodic memory. We found that memory for the order of events was enhanced within, rather than across, context shifts, or boundaries (Experiment 1). Next, we showed that this relative enhancement in order memory was eliminated when across-item associative processing was disrupted (Experiment 2), suggesting that context shifts have a selective effect on sequential binding. Finally, we provide evidence that the act of making order memory judgments involves the reactivation of representations that bridged the tested items (Experiment 3). Together, these data suggest that boundaries may serve to parse continuous experience into sequences of contextually related events and that this organization facilitates remembering the temporal order of events that share the same context. PsycINFO Database Record (c) 2013 APA, all rights reserved.

An essential memory trace found.

PubMed

Thompson, Richard F

2013-10-01

I argue here that we have succeeded in localizing an essential memory trace for a basic form of associative learning and memory--classical conditioning of discrete responses learned with an aversive stimulus--to the anterior interpositus nucleus of the cerebellum. We first identified the entire essential circuit, using eyelid conditioning as the model system, and used reversible inactivation, during training, of critical structures and pathways to localize definitively the essential memory trace. In recognition of the 30th anniversary of Behavioral Neuroscience, I highlight 1 paper (Tracy, Thompson, Krupa, & Thompson, 1998) that was particularly significant for the progress of this research program. In this review, I present definitive evidence that the essential memory trace for eyelid conditioning is localized to the cerebellum and to no other part of the essential circuit, using electrical stimulation of the pontine nuclei-mossy fibers projecting to the cerebellum as the conditional stimulus (CS; it proved to be a supernormal stimulus resulting in much faster learning than with any peripheral CS) and using an electrical stimulus to the output of the cerebellum as a test, which did not change. Pontine patterns of projection to the cerebellum were confirmed with retrograde labeling techniques. 2013 APA, all rights reserved

A Radiation-Tolerant, Low-Power Non-Volatile Memory Based on Silicon Nanocrystal Quantum Dots

NASA Technical Reports Server (NTRS)

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

2001-01-01

Nanocrystal nonvolatile floating-gate memories are a good candidate for space applications - initial results suggest they are fast, more reliable and consume less power than conventional floating gate memories. In the nanocrystal based NVM device, charge is not stored on a continuous polysilicon layer (so-called floating gate), but instead on a layer of discrete nanocrystals. Charge injection and storage in dense arrays of silicon nanocrystals in SiO2 is a critical aspect of the performance of potential nanocrystal flash memory structures. The ultimate goal for this class of devices is few- or single-electron storage in a small number of nanocrystal elements. In addition, the nanocrystal layer fabrication technique should be simple, 8-inch wafer compatible and well controlled in program/erase threshold voltage swing was seen during 100,000 program and erase cycles. Additional near-term goals for this project include extensive testing for radiation hardness and the development of artificial layered tunnel barrier heterostructures which have the potential for large speed enhancements for read/write of nanocrystal memory elements, compared with conventional flash devices. Additional information is contained in the original extended abstract.

Competition with and without priority control: linking rivalry to attention through winner-take-all networks with memory

PubMed Central

Marx, Svenja; Gruenhage, Gina; Walper, Daniel; Rutishauser, Ueli; Einhäuser, Wolfgang

2015-01-01

Competition is ubiquitous in perception. For example, items in the visual field compete for processing resources, and attention controls their priority (biased competition). The inevitable ambiguity in the interpretation of sensory signals yields another form of competition: distinct perceptual interpretations compete for access to awareness. Rivalry, where two equally likely percepts compete for dominance, explicates the latter form of competition. Building upon the similarity between attention and rivalry, we propose to model rivalry by a generic competitive circuit that is widely used in the attention literature—a winner-take-all (WTA) network. Specifically, we show that a network of two coupled WTA circuits replicates three common hallmarks of rivalry: the distribution of dominance durations, their dependence on input strength (“Levelt's propositions”), and the effects of stimulus removal (blanking). This model introduces a form of memory by forming discrete states and explains experimental data better than competitive models of rivalry without memory. This result supports the crucial role of memory in rivalry specifically and in competitive processes in general. Our approach unifies the seemingly distinct phenomena of rivalry, memory, and attention in a single model with competition as the common underlying principle. PMID:25581077

Regulation of Cognitive Processes through Perceived Self-Efficacy.

ERIC Educational Resources Information Center

Bandura, Albert

1989-01-01

Addresses issues concerning the extension of self-efficacy theory to memory functioning. Issues include perceived memory capabilities, memory self-appraisal, personal control over memory functioning, preservation of a favorable sense of memory self-efficacy, and strategies for generalizing the impact of training in memory skills. (RJC)

Memory reorganization following anterior temporal lobe resection: a longitudinal functional MRI study

PubMed Central

Bonelli, Silvia B.; Thompson, Pamela J.; Yogarajah, Mahinda; Powell, Robert H. W.; Samson, Rebecca S.; McEvoy, Andrew W.; Symms, Mark R.; Koepp, Matthias J.

2013-01-01

Anterior temporal lobe resection controls seizures in 50–60% of patients with intractable temporal lobe epilepsy but may impair memory function, typically verbal memory following left, and visual memory following right anterior temporal lobe resection. Functional reorganization can occur within the ipsilateral and contralateral hemispheres. We investigated the reorganization of memory function in patients with temporal lobe epilepsy before and after left or right anterior temporal lobe resection and the efficiency of postoperative memory networks. We studied 46 patients with unilateral medial temporal lobe epilepsy (25/26 left hippocampal sclerosis, 16/20 right hippocampal sclerosis) before and after anterior temporal lobe resection on a 3 T General Electric magnetic resonance imaging scanner. All subjects had neuropsychological testing and performed a functional magnetic resonance imaging memory encoding paradigm for words, pictures and faces, testing verbal and visual memory in a single scanning session, preoperatively and again 4 months after surgery. Event-related analysis revealed that patients with left temporal lobe epilepsy had greater activation in the left posterior medial temporal lobe when successfully encoding words postoperatively than preoperatively. Greater pre- than postoperative activation in the ipsilateral posterior medial temporal lobe for encoding words correlated with better verbal memory outcome after left anterior temporal lobe resection. In contrast, greater postoperative than preoperative activation in the ipsilateral posterior medial temporal lobe correlated with worse postoperative verbal memory performance. These postoperative effects were not observed for visual memory function after right anterior temporal lobe resection. Our findings provide evidence for effective preoperative reorganization of verbal memory function to the ipsilateral posterior medial temporal lobe due to the underlying disease, suggesting that it is the capacity of the posterior remnant of the ipsilateral hippocampus rather than the functional reserve of the contralateral hippocampus that is important for maintaining verbal memory function after anterior temporal lobe resection. Early postoperative reorganization to ipsilateral posterior or contralateral medial temporal lobe structures does not underpin better performance. Additionally our results suggest that visual memory function in right temporal lobe epilepsy is affected differently by right anterior temporal lobe resection than verbal memory in left temporal lobe epilepsy. PMID:23715092

Modelling the effects of Prairie wetlands on streamflow

NASA Astrophysics Data System (ADS)

Shook, K.; Pomeroy, J. W.

2015-12-01

Recent research has demonstrated that the contributing areas of Prairie streams dominated by depressional (wetland) storage demonstrate hysteresis with respect to catchment water storage. As such contributing fractions can vary over time from a very small percentage of catchment area to the entire catchment during floods. However, catchments display complex memories of past storage states and their contributing fractions cannot be modelled accurately by any single-valued function. The Cold Regions Hydrological Modelling platform, CRHM, which is capable of modelling all of the hydrological processes of cold regions using a hydrological response unit discretization of the catchment, was used to further investigate dynamical contributing area response to hydrological processes. Contributing fraction in CRHM is also controlled by the episodic nature of runoff generation in this cold, sub-humid environment where runoff is dominated by snowmelt over frozen soils, snowdrifts define the contributing fraction in late spring, unfrozen soils have high water holding capacity and baseflow from sub-surface flow does not exist. CRHM was improved by adding a conceptual model of individual Prairie depression fill and spill runoff generation that displays hysteresis in the storage - contributing fraction relationship and memory of storage state. The contributing area estimated by CRHM shows strong sensitivity to hydrological inputs, storage and the threshold runoff rate chosen. The response of the contributing area to inputs from various runoff generating processes from snowmelt to rain-on-snow to rainfall with differing degrees of spatial variation was investigated as was the importance of the memory of storage states on streamflow generation. The importance of selecting hydrologically and ecologically meaningful runoff thresholds in estimating contributing area is emphasized.

Accurate artificial boundary conditions for the semi-discretized linear Schrödinger and heat equations on rectangular domains

NASA Astrophysics Data System (ADS)

Ji, Songsong; Yang, Yibo; Pang, Gang; Antoine, Xavier

2018-01-01

The aim of this paper is to design some accurate artificial boundary conditions for the semi-discretized linear Schrödinger and heat equations in rectangular domains. The Laplace transform in time and discrete Fourier transform in space are applied to get Green's functions of the semi-discretized equations in unbounded domains with single-source. An algorithm is given to compute these Green's functions accurately through some recurrence relations. Furthermore, the finite-difference method is used to discretize the reduced problem with accurate boundary conditions. Numerical simulations are presented to illustrate the accuracy of our method in the case of the linear Schrödinger and heat equations. It is shown that the reflection at the corners is correctly eliminated.

Obesity and episodic memory function.

PubMed

Loprinzi, Paul D; Frith, Emily

2018-04-17

Obesity-related lifestyle factors, such as physical activity behavior and dietary intake, have been shown to be associated with episodic memory function. From animal work, there is considerable biological plausibility linking obesity with worse memory function. There are no published systematic reviews evaluating the effects of obesity on episodic memory function among humans, and examining whether physical activity and diet influences this obesity-memory link. Thus, the purpose of this systematic review was to evaluate the totality of research examining whether obesity is associated with episodic memory function, and whether physical activity and dietary behavior confounds this relationship. A review approach was employed, using PubMed, PsychInfo, and Sports Discus databases. Fourteen studies met our criteria. Among these 14 reviewed studies, eight were cross-sectional, four were prospective, and two employed a randomized controlled experimental design. Twelve of the 14 studies did not take into consideration dietary behavior in their analysis, and similarly, nine of the 14 studies did not take into consideration participant physical activity behavior. Among the 14 studies, ten found an inverse association of weight status on memory function, but for one of these studies, this association was attenuated after controlling for physical activity. Among the 14 evaluated studies, four did not find a direct effect of weight status on memory. Among the four null studies, one, however, found an indirect effect of BMI on episodic memory and another found a moderation effect of BMI and age on memory function. It appears that obesity may be associated with worse memory function, with the underlying mechanisms discussed herein. At this point, it is uncertain whether adiposity, itself, is influencing memory changes, or rather, whether adiposity-related lifestyle behaviors (e.g., physical inactivity and diet) are driving the obesity-memory relationship.

[Nostalgia and the functions of autobiographical memory].

PubMed

Wolf, T

2014-11-01

Current research on autobiographical memory distinguishes between a self function, a directive function, and a social function of autobiographical memory. From a lifespan perspective, the use of autobiographical memory for these functions is expected to decrease with age. The present study extended these functions by the function of nostalgia: Often triggered by negative emotions, remembering personal and positive experiences might, among others, enhance positive effects. This emotion-regulating function is expected to become more important in old age. In the present study 273 adults (aged between 19 and 90 years) completed the Thinking About Life Experiences Questionnaire (TALE) as well as 11 newly developed items to assess the nostalgia function. Exploratory and confirmatory factor analyses supported a four-factor model reflecting the presumed self, directive, social, and nostalgia functions of autobiographical memory. The results showed a decrease in the use of autobiographical memory for self, directive and social functions with increasing age, whereas the nostalgia function followed a U-shaped pattern.

An integrative and functional framework for the study of animal emotion and mood

PubMed Central

Mendl, Michael; Burman, Oliver H. P.; Paul, Elizabeth S.

2010-01-01

A better understanding of animal emotion is an important goal in disciplines ranging from neuroscience to animal welfare science. The conscious experience of emotion cannot be assessed directly, but neural, behavioural and physiological indicators of emotion can be measured. Researchers have used these measures to characterize how animals respond to situations assumed to induce discrete emotional states (e.g. fear). While advancing our understanding of specific emotions, this discrete emotion approach lacks an overarching framework that can incorporate and integrate the wide range of possible emotional states. Dimensional approaches that conceptualize emotions in terms of universal core affective characteristics (e.g. valence (positivity versus negativity) and arousal) can provide such a framework. Here, we bring together discrete and dimensional approaches to: (i) offer a structure for integrating different discrete emotions that provides a functional perspective on the adaptive value of emotional states, (ii) suggest how long-term mood states arise from short-term discrete emotions, how they also influence these discrete emotions through a bi-directional relationship and how they may function to guide decision-making, and (iii) generate novel hypothesis-driven measures of animal emotion and mood. PMID:20685706

An integrative and functional framework for the study of animal emotion and mood.

PubMed

Mendl, Michael; Burman, Oliver H P; Paul, Elizabeth S

2010-10-07

A better understanding of animal emotion is an important goal in disciplines ranging from neuroscience to animal welfare science. The conscious experience of emotion cannot be assessed directly, but neural, behavioural and physiological indicators of emotion can be measured. Researchers have used these measures to characterize how animals respond to situations assumed to induce discrete emotional states (e.g. fear). While advancing our understanding of specific emotions, this discrete emotion approach lacks an overarching framework that can incorporate and integrate the wide range of possible emotional states. Dimensional approaches that conceptualize emotions in terms of universal core affective characteristics (e.g. valence (positivity versus negativity) and arousal) can provide such a framework. Here, we bring together discrete and dimensional approaches to: (i) offer a structure for integrating different discrete emotions that provides a functional perspective on the adaptive value of emotional states, (ii) suggest how long-term mood states arise from short-term discrete emotions, how they also influence these discrete emotions through a bi-directional relationship and how they may function to guide decision-making, and (iii) generate novel hypothesis-driven measures of animal emotion and mood.

A model of the human in a cognitive prediction task.

NASA Technical Reports Server (NTRS)

Rouse, W. B.

1973-01-01

The human decision maker's behavior when predicting future states of discrete linear dynamic systems driven by zero-mean Gaussian processes is modeled. The task is on a slow enough time scale that physiological constraints are insignificant compared with cognitive limitations. The model is basically a linear regression system identifier with a limited memory and noisy observations. Experimental data are presented and compared to the model.

Chronic Treatment with Haloperidol Induces Deficits in Working Memory and Feedback Effects of Interval Timing

ERIC Educational Resources Information Center

Lustig, C.; Meck, W.H.

2005-01-01

Normal participants (n=5) having no experience with antipsychotic drugs and medicated participants (n=5) with clinical experience with chronic low doses of haloperidol (3-10mg/day for 2-4 months) in the treatment of neuroses were evaluated for the effects of inter-trial interval (ITI) feedback on a discrete-trials peak-interval timing procedure.…

Generation of optimal artificial neural networks using a pattern search algorithm: application to approximation of chemical systems.

PubMed

Ihme, Matthias; Marsden, Alison L; Pitsch, Heinz

2008-02-01

A pattern search optimization method is applied to the generation of optimal artificial neural networks (ANNs). Optimization is performed using a mixed variable extension to the generalized pattern search method. This method offers the advantage that categorical variables, such as neural transfer functions and nodal connectivities, can be used as parameters in optimization. When used together with a surrogate, the resulting algorithm is highly efficient for expensive objective functions. Results demonstrate the effectiveness of this method in optimizing an ANN for the number of neurons, the type of transfer function, and the connectivity among neurons. The optimization method is applied to a chemistry approximation of practical relevance. In this application, temperature and a chemical source term are approximated as functions of two independent parameters using optimal ANNs. Comparison of the performance of optimal ANNs with conventional tabulation methods demonstrates equivalent accuracy by considerable savings in memory storage. The architecture of the optimal ANN for the approximation of the chemical source term consists of a fully connected feedforward network having four nonlinear hidden layers and 117 synaptic weights. An equivalent representation of the chemical source term using tabulation techniques would require a 500 x 500 grid point discretization of the parameter space.

Functions of autobiographical memory in Taiwanese and American emerging adults.

PubMed

Liao, Hsiao-Wen; Bluck, Susan; Alea, Nicole; Cheng, Ching-Ling

2016-01-01

The study addresses cultural and person-level factors contributing to emerging adult's use of memory to serve adaptive functions. The focus is on three functions: self-continuity, social-bonding and directing-behaviour. Taiwanese (N = 85, 52 women) and American (N = 95, 51 women) emerging adults completed the Thinking about Life Experiences scale, and measures of trait personality, self-concept clarity and future time perspective. Findings show that individuals from both cultures use memory to serve these three functions, but Taiwanese individuals use memory more frequently than Americans to maintain self-continuity. Culture also interacted with person-level factors: in Taiwan, but not America, memory is more frequently used to create self-continuity in individuals high in conscientiousness. Across cultures, having lower self-concept clarity was related to greater use of memory to create self-continuity. Findings are discussed in terms of how memory serves functions in context and specific aspects of the Taiwanese and American cultural context that may predict the functional use of memory in emerging adulthood.

Universal scaling function in discrete time asymmetric exclusion processes

NASA Astrophysics Data System (ADS)

Chia, Nicholas; Bundschuh, Ralf

2005-03-01

In the universality class of the one dimensional Kardar-Parisi-Zhang surface growth, Derrida and Lebowitz conjectured the universality of not only the scaling exponents, but of an entire scaling function. Since Derrida and Lebowitz' original publication this universality has been verified for a variety of continuous time systems in the KPZ universality class. We study the Derrida-Lebowitz scaling function for multi-particle versions of the discrete time Asymmetric Exclusion Process. We find that in this discrete time system the Derrida-Lebowitz scaling function not only properly characterizes the large system size limit, but even accurately describes surprisingly small systems. These results have immediate applications in searching biological sequence databases.

Memory functioning in children with reading disabilities and/or attention deficit/hyperactivity disorder: a clinical investigation of their working memory and long-term memory functioning.

PubMed

Kibby, Michelle Y; Cohen, Morris J

2008-11-01

We examined memory functioning in children with reading disabilities (RD), Attention deficit/hyperactivity disorder (ADHD), and RD/ADHD using a clinic sample with a clinical instrument: the Children's Memory Scale, enhancing its generalizability. Participants included 23 children with RD, 30 with ADHD, 30 with RD/ADHD, and 30 controls. Children with RD presented with reduced verbal short-term memory (STM) but intact visual STM, central executive (CE), and long-term memory (LTM) functioning. Their deficit in STM appeared specific to tasks requiring phonetic coding of material. Children with ADHD displayed intact CE and LTM functioning but reduced visual-spatial STM, especially when off stimulant medication. Children with RD/ADHD had deficits consistent with both disorders.

A Review of Discrete Element Method (DEM) Particle Shapes and Size Distributions for Lunar Soil

NASA Technical Reports Server (NTRS)

Lane, John E.; Metzger, Philip T.; Wilkinson, R. Allen

2010-01-01

As part of ongoing efforts to develop models of lunar soil mechanics, this report reviews two topics that are important to discrete element method (DEM) modeling the behavior of soils (such as lunar soils): (1) methods of modeling particle shapes and (2) analytical representations of particle size distribution. The choice of particle shape complexity is driven primarily by opposing tradeoffs with total number of particles, computer memory, and total simulation computer processing time. The choice is also dependent on available DEM software capabilities. For example, PFC2D/PFC3D and EDEM support clustering of spheres; MIMES incorporates superquadric particle shapes; and BLOKS3D provides polyhedra shapes. Most commercial and custom DEM software supports some type of complex particle shape beyond the standard sphere. Convex polyhedra, clusters of spheres and single parametric particle shapes such as the ellipsoid, polyellipsoid, and superquadric, are all motivated by the desire to introduce asymmetry into the particle shape, as well as edges and corners, in order to better simulate actual granular particle shapes and behavior. An empirical particle size distribution (PSD) formula is shown to fit desert sand data from Bagnold. Particle size data of JSC-1a obtained from a fine particle analyzer at the NASA Kennedy Space Center is also fitted to a similar empirical PSD function.

A study of discrete control signal fault conditions in the shuttle DPS

NASA Technical Reports Server (NTRS)

Reddi, S. S.; Retter, C. T.

1976-01-01

An analysis of the effects of discrete failures on the data processing subsystem is presented. A functional description of each discrete together with a list of software modules that use this discrete are included. A qualitative description of the consequences that may ensue due to discrete failures is given followed by a probabilistic reliability analysis of the data processing subsystem. Based on the investigation conducted, recommendations were made to improve the reliability of the subsystem.

Memory formation during anaesthesia: plausibility of a neurophysiological basis

PubMed Central

Veselis, R. A.

2015-01-01

As opposed to conscious, personally relevant (explicit) memories that we can recall at will, implicit (unconscious) memories are prototypical of ‘hidden’ memory; memories that exist, but that we do not know we possess. Nevertheless, our behaviour can be affected by these memories; in fact, these memories allow us to function in an ever-changing world. It is still unclear from behavioural studies whether similar memories can be formed during anaesthesia. Thus, a relevant question is whether implicit memory formation is a realistic possibility during anaesthesia, considering the underlying neurophysiology. A different conceptualization of memory taxonomy is presented, the serial parallel independent model of Tulving, which focuses on dynamic information processing with interactions among different memory systems rather than static classification of different types of memories. The neurophysiological basis for subliminal information processing is considered in the context of brain function as embodied in network interactions. Function of sensory cortices and thalamic activity during anaesthesia are reviewed. The role of sensory and perisensory cortices, in particular the auditory cortex, in support of memory function is discussed. Although improbable, with the current knowledge of neurophysiology one cannot rule out the possibility of memory formation during anaesthesia. PMID:25735711

Mnemonic function in small vessel disease and associations with white matter tract microstructure.

PubMed

Metoki, Athanasia; Brookes, Rebecca L; Zeestraten, Eva; Lawrence, Andrew J; Morris, Robin G; Barrick, Thomas R; Markus, Hugh S; Charlton, Rebecca A

2017-09-01

Cerebral small vessel disease (SVD) is associated with deficits in working memory, with a relative sparing of long-term memory; function may be influenced by white matter microstructure. Working and long-term memory were examined in 106 patients with SVD and 35 healthy controls. Microstructure was measured in the uncinate fasciculi and cingula. Working memory was more impaired than long-term memory in SVD, but both abilities were reduced compared to controls. Regression analyses found that having SVD explained the variance in memory functions, with additional variance explained by the cingula (working memory) and uncinate (long-term memory). Performance can be explained in terms of integrity loss in specific white matter tract associated with mnemonic functions. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Effects of aging on functional connectivity of the amygdala for subsequent memory of negative pictures: a network analysis of functional magnetic resonance imaging data.

PubMed

St Jacques, Peggy L; Dolcos, Florin; Cabeza, Roberto

2009-01-01

Aging is associated with preserved enhancement of emotional memory, as well as with age-related reductions in memory for negative stimuli, but the neural networks underlying such alterations are not clear. We used a subsequent-memory paradigm to identify brain activity predicting enhanced emotional memory in young and older adults. Activity in the amygdala predicted enhanced emotional memory, with subsequent-memory activity greater for negative stimuli than for neutral stimuli, across age groups, a finding consistent with an overall enhancement of emotional memory. However, older adults recruited greater activity in anterior regions and less activity in posterior regions in general for negative stimuli that were subsequently remembered. Functional connectivity of the amygdala with the rest of the brain was consistent with age-related reductions in memory for negative stimuli: Older adults showed decreased functional connectivity between the amygdala and the hippocampus, but increased functional connectivity between the amygdala and dorsolateral prefrontal cortices. These findings suggest that age-related differences in the enhancement of emotional memory might reflect decreased connectivity between the amygdala and typical subsequent-memory regions, as well as the engagement of regulatory processes that inhibit emotional responses.

A fast, high-endurance and scalable non-volatile memory device made from asymmetric Ta2O5-x/TaO2-x bilayer structures

NASA Astrophysics Data System (ADS)

Lee, Myoung-Jae; Lee, Chang Bum; Lee, Dongsoo; Lee, Seung Ryul; Chang, Man; Hur, Ji Hyun; Kim, Young-Bae; Kim, Chang-Jung; Seo, David H.; Seo, Sunae; Chung, U.-In; Yoo, In-Kyeong; Kim, Kinam

2011-08-01

Numerous candidates attempting to replace Si-based flash memory have failed for a variety of reasons over the years. Oxide-based resistance memory and the related memristor have succeeded in surpassing the specifications for a number of device requirements. However, a material or device structure that satisfies high-density, switching-speed, endurance, retention and most importantly power-consumption criteria has yet to be announced. In this work we demonstrate a TaOx-based asymmetric passive switching device with which we were able to localize resistance switching and satisfy all aforementioned requirements. In particular, the reduction of switching current drastically reduces power consumption and results in extreme cycling endurances of over 1012. Along with the 10 ns switching times, this allows for possible applications to the working-memory space as well. Furthermore, by combining two such devices each with an intrinsic Schottky barrier we eliminate any need for a discrete transistor or diode in solving issues of stray leakage current paths in high-density crossbar arrays.

Essentialist thinking predicts decrements in children's memory for racially ambiguous faces.

PubMed

Gaither, Sarah E; Schultz, Jennifer R; Pauker, Kristin; Sommers, Samuel R; Maddox, Keith B; Ambady, Nalini

2014-02-01

Past research shows that adults often display poor memory for racially ambiguous and racial outgroup faces, with both face types remembered worse than own-race faces. In the present study, the authors examined whether children also show this pattern of results. They also examined whether emerging essentialist thinking about race predicts children's memory for faces. Seventy-four White children (ages 4-9 years) completed a face-memory task comprising White, Black, and racially ambiguous Black-White faces. Essentialist thinking about race was also assessed (i.e., thinking of race as immutable and biologically based). White children who used essentialist thinking showed the same bias as White adults: They remembered White faces significantly better than they remembered ambiguous and Black faces. However, children who did not use essentialist thinking remembered both White and racially ambiguous faces significantly better than they remembered Black faces. This finding suggests a specific shift in racial thinking wherein the boundaries between racial groups become more discrete, highlighting the importance of how race is conceptualized in judgments of racially ambiguous individuals.

Acceleration of discrete stochastic biochemical simulation using GPGPU.

PubMed

Sumiyoshi, Kei; Hirata, Kazuki; Hiroi, Noriko; Funahashi, Akira

2015-01-01

For systems made up of a small number of molecules, such as a biochemical network in a single cell, a simulation requires a stochastic approach, instead of a deterministic approach. The stochastic simulation algorithm (SSA) simulates the stochastic behavior of a spatially homogeneous system. Since stochastic approaches produce different results each time they are used, multiple runs are required in order to obtain statistical results; this results in a large computational cost. We have implemented a parallel method for using SSA to simulate a stochastic model; the method uses a graphics processing unit (GPU), which enables multiple realizations at the same time, and thus reduces the computational time and cost. During the simulation, for the purpose of analysis, each time course is recorded at each time step. A straightforward implementation of this method on a GPU is about 16 times faster than a sequential simulation on a CPU with hybrid parallelization; each of the multiple simulations is run simultaneously, and the computational tasks within each simulation are parallelized. We also implemented an improvement to the memory access and reduced the memory footprint, in order to optimize the computations on the GPU. We also implemented an asynchronous data transfer scheme to accelerate the time course recording function. To analyze the acceleration of our implementation on various sizes of model, we performed SSA simulations on different model sizes and compared these computation times to those for sequential simulations with a CPU. When used with the improved time course recording function, our method was shown to accelerate the SSA simulation by a factor of up to 130.

Acceleration of discrete stochastic biochemical simulation using GPGPU

PubMed Central

Sumiyoshi, Kei; Hirata, Kazuki; Hiroi, Noriko; Funahashi, Akira

2015-01-01

For systems made up of a small number of molecules, such as a biochemical network in a single cell, a simulation requires a stochastic approach, instead of a deterministic approach. The stochastic simulation algorithm (SSA) simulates the stochastic behavior of a spatially homogeneous system. Since stochastic approaches produce different results each time they are used, multiple runs are required in order to obtain statistical results; this results in a large computational cost. We have implemented a parallel method for using SSA to simulate a stochastic model; the method uses a graphics processing unit (GPU), which enables multiple realizations at the same time, and thus reduces the computational time and cost. During the simulation, for the purpose of analysis, each time course is recorded at each time step. A straightforward implementation of this method on a GPU is about 16 times faster than a sequential simulation on a CPU with hybrid parallelization; each of the multiple simulations is run simultaneously, and the computational tasks within each simulation are parallelized. We also implemented an improvement to the memory access and reduced the memory footprint, in order to optimize the computations on the GPU. We also implemented an asynchronous data transfer scheme to accelerate the time course recording function. To analyze the acceleration of our implementation on various sizes of model, we performed SSA simulations on different model sizes and compared these computation times to those for sequential simulations with a CPU. When used with the improved time course recording function, our method was shown to accelerate the SSA simulation by a factor of up to 130. PMID:25762936

Functional Relationships for Investigating Cognitive Processes

PubMed Central

Wright, Anthony A.

2013-01-01

Functional relationships (from systematic manipulation of critical variables) are advocated for revealing fundamental processes of (comparative) cognition—through examples from my work in psychophysics, learning, and memory. Functional relationships for pigeon wavelength (hue) discrimination revealed best discrimination at the spectral points of hue transition for pigeons—a correspondence (i.e., functional relationship) similar to that for humans. Functional relationships for learning revealed: Item-specific or relational learning in matching to sample as a function of the pigeons’ sample-response requirement, and same/different abstract-concept learning as a function of the training set size for rhesus monkeys, capuchin monkeys, and pigeons. Functional relationships for visual memory revealed serial position functions (a 1st order functional relationship) that changed systematically with retention delay (a 2nd order relationship) for pigeons, capuchin monkeys, rhesus monkeys, and humans. Functional relationships for rhesus-monkey auditory memory also revealed systematic changes in serial position functions with delay, but these changes were opposite to those for visual memory. Functional relationships for proactive interference revealed interference that varied as a function of a ratio of delay times. Functional relationships for change detection memory revealed (qualitative) similarities and (quantitative) differences in human and monkey visual short term memory as a function of the number of memory items. It is concluded that these findings were made possible by varying critical variables over a substantial portion of the manipulable range to generate functions and derive relationships. PMID:23174335

Generalized hydrodynamic correlations and fractional memory functions

NASA Astrophysics Data System (ADS)

Rodríguez, Rosalio F.; Fujioka, Jorge

2015-12-01

A fractional generalized hydrodynamic (GH) model of the longitudinal velocity fluctuations correlation, and its associated memory function, for a complex fluid is analyzed. The adiabatic elimination of fast variables introduces memory effects in the transport equations, and the dynamic of the fluctuations is described by a generalized Langevin equation with long-range noise correlations. These features motivate the introduction of Caputo time fractional derivatives and allows us to calculate analytic expressions for the fractional longitudinal velocity correlation function and its associated memory function. Our analysis eliminates a spurious constant term in the non-fractional memory function found in the non-fractional description. It also produces a significantly slower power-law decay of the memory function in the GH regime that reduces to the well-known exponential decay in the non-fractional Navier-Stokes limit.

Segmentation of discrete vector fields.

PubMed

Li, Hongyu; Chen, Wenbin; Shen, I-Fan

2006-01-01

In this paper, we propose an approach for 2D discrete vector field segmentation based on the Green function and normalized cut. The method is inspired by discrete Hodge Decomposition such that a discrete vector field can be broken down into three simpler components, namely, curl-free, divergence-free, and harmonic components. We show that the Green Function Method (GFM) can be used to approximate the curl-free and the divergence-free components to achieve our goal of the vector field segmentation. The final segmentation curves that represent the boundaries of the influence region of singularities are obtained from the optimal vector field segmentations. These curves are composed of piecewise smooth contours or streamlines. Our method is applicable to both linear and nonlinear discrete vector fields. Experiments show that the segmentations obtained using our approach essentially agree with human perceptual judgement.

Mechanisms underlying the production of false memories for famous people's names in aging and Alzheimer's disease.

PubMed

Plancher, Gaën; Guyard, Anne; Nicolas, Serge; Piolino, Pascale

2009-10-01

It is well known that the occurrence of false memories increases with aging, but the results remain inconsistent concerning Alzheimer's disease (AD). Moreover, the mechanisms underlying the production of false memories are still unclear. Using an experimental episodic memory test with material based on the names of famous people in a procedure derived from the DRM paradigm [Roediger, H. L., III, & McDermott, K. B. (1995). Creating false memories: Remembering words not presented in lists. Journal of Experimental Psychology: Learning, Memory & Cognition, 21, 803-814], we examined correct and false recall and recognition in 30 young adults, 40 healthy older adults, and 30 patients with AD. Moreover, we evaluated the relationships between false memory performance, correct episodic memory performance, and a set of neuropsychological assessments evaluating the semantic memory and executive functions. The results clearly indicated that correct recall and recognition performance decreased with the subjects' age, but it decreased even more with AD. In addition, semantically related false recalls and false recognitions increased with age but not with dementia. On the contrary, non-semantically related false recalls and false recognitions increased with AD. Finally, the regression analyses showed that executive functions mediated related false memories and episodic memory mediated related and unrelated false memories in aging. Moreover, executive functions predicted related and unrelated false memories in AD, and episodic and semantic memory predicted semantically related and unrelated false memories in AD. In conclusion, the results obtained are consistent with the current constructive models of memory suggesting that false memory creation depends on different cognitive functions and, consequently, that the impairments of these functions influence the production of false memories.

Cerebral localization, then and now.

PubMed

Marshall, John C; Fink, Gereon R

2003-11-01

We review some of the progress made in understanding the nature of functional specialization in the human brain, beginning with the anatomical claim that all mental faculties have their own distinct material substrate in different regions of the brain and the psychological claim that each mental faculty is characterized by the content domain with which it deals. This conceptual framework led behavioral neurologists to show how discrete brain lesions provoked different types of language, praxic, gnostic, spatial, and memory disorders. The simplest way of interpreting these anatomoclinical associations was to conjecture that the normal function (now impaired by brain damage) was localized within that lesioned region. It was also realized that cognitive impairments could arise from lesions that spared the functional centers themselves but disconnected them from other centers. Nonetheless, many neuroscientists remained skeptical of the entire paradigm. Accordingly, in the late 19th century functional localization began to be studied in the intact human brain by such techniques as measuring the temperature of different brain regions when different cognitive tasks were performed. During the 20th century these crude techniques gave way to positron emission tomography, functional magnetic resonance imaging, and magnetoencephalography. The relatively precise spatial and temporal resolution of modern methods now raises a crucial question: Do the functional localizations obtained by the anatomoclinical method converge with those implied by the functional neuroimaging of cognition in healthy volunteers? We then conclude with some recent suggestions that functional specialization is not such a fixed property of brain regions as previously supposed.

The effect of two types of memory training on subjective and objective memory performance in healthy individuals aged 55 years and older: a randomized controlled trial.

PubMed

Valentijn, Susanne A M; van Hooren, Susan A H; Bosma, Hans; Touw, Dory M; Jolles, Jelle; van Boxtel, Martin P J; Ponds, Rudolf W H M

2005-04-01

The objective of the study was to examine the effectiveness of two types of memory training (collective and individual), compared to control (waiting list), on memory performance. Participants were 139 community-dwelling older individuals recruited through media advertisements asking for people with subjective memory complaints to participate in a study. Data were collected at baseline, and at 1 week and 4 months after the intervention. Training efficacy was assessed using measures of subjective and objective memory performance. After the intervention, participants in the collective training group reported more stability in memory functioning and had fewer feelings of anxiety and stress about memory functioning. In addition, positive effects were found on objective memory functioning. Compared with the other two groups, the collective training group participants had an improved recall of a previously learned word list. Compared to controls, participants in the individual training group reported fewer feelings of anxiety and stress in relation to memory functioning.

Decomposing the relationship between cognitive functioning and self-referent memory beliefs in older adulthood: What’s memory got to do with it?

PubMed Central

Payne, Brennan R.; Gross, Alden L.; Hill, Patrick L.; Parisi, Jeanine M.; Rebok, George W.; Stine-Morrow, Elizabeth A. L.

2018-01-01

With advancing age, episodic memory performance shows marked declines along with concurrent reports of lower subjective memory beliefs. Given that normative age-related declines in episodic memory co-occur with declines in other cognitive domains, we examined the relationship between memory beliefs and multiple domains of cognitive functioning. Confirmatory bi-factor structural equation models were used to parse the shared and independent variance among factors representing episodic memory, psychomotor speed, and executive reasoning in one large cohort study (Senior Odyssey, N = 462), and replicated using another large cohort of healthy older adults (ACTIVE, N = 2,802). Accounting for a general fluid cognitive functioning factor (comprised of the shared variance among measures of episodic memory, speed, and reasoning) attenuated the relationship between objective memory performance and subjective memory beliefs in both samples. Moreover, the general cognitive functioning factor was the strongest predictor of memory beliefs in both samples. These findings are consistent with the notion that dispositional memory beliefs may reflect perceptions of cognition more broadly. This may be one reason why memory beliefs have broad predictive validity for interventions that target fluid cognitive ability. PMID:27685541

Decomposing the relationship between cognitive functioning and self-referent memory beliefs in older adulthood: what's memory got to do with it?

PubMed

Payne, Brennan R; Gross, Alden L; Hill, Patrick L; Parisi, Jeanine M; Rebok, George W; Stine-Morrow, Elizabeth A L

2017-07-01

With advancing age, episodic memory performance shows marked declines along with concurrent reports of lower subjective memory beliefs. Given that normative age-related declines in episodic memory co-occur with declines in other cognitive domains, we examined the relationship between memory beliefs and multiple domains of cognitive functioning. Confirmatory bi-factor structural equation models were used to parse the shared and independent variance among factors representing episodic memory, psychomotor speed, and executive reasoning in one large cohort study (Senior Odyssey, N = 462), and replicated using another large cohort of healthy older adults (ACTIVE, N = 2802). Accounting for a general fluid cognitive functioning factor (comprised of the shared variance among measures of episodic memory, speed, and reasoning) attenuated the relationship between objective memory performance and subjective memory beliefs in both samples. Moreover, the general cognitive functioning factor was the strongest predictor of memory beliefs in both samples. These findings are consistent with the notion that dispositional memory beliefs may reflect perceptions of cognition more broadly. This may be one reason why memory beliefs have broad predictive validity for interventions that target fluid cognitive ability.

The Packing Property

DTIC Science & Technology

2000-11-01

Discrete Math . 115, 141-152. [7] Edmonds J., Giles R. (1977) A Min-Max relation for submodular functions on graphs, Annals of Discrete Math . 1, 185...projective planes, handwritten man- uscript, published: (1990) Polyhedral Combinatorics (W. Cook, P.D. Seymour eds.), DIMACS Series in Discrete Math . and...Theoretical Computer Science 1, 101-105. [11] Lovasz L. (1972) Normal hypergraphs and the perfect graph conjecture, Discrete Math . 2, 253-267. [12

The extended trajectory of hippocampal development: implications for early memory development and disorder

PubMed Central

Gómez, Rebecca L.; Edgin, Jamie O.

2015-01-01

Hippocampus has an extended developmental trajectory, with refinements occurring in the trisynaptic circuit until adolescence. While structural change should suggest a protracted course in behavior, some studies find evidence of precocious hippocampal development in the first postnatal year and continuity in memory processes beyond. However, a number of memory functions, including binding and relational inference, can be cortically supported. Evidence from the animal literature suggests that tasks often associated with hippocampus (Visual Paired Comparison, binding of a visuomotor response) can be mediated by structures external to hippocampus. Thus, a complete examination of memory development will have to rule out cortex as a source of early memory competency. We propose that early memory must show properties associated with full function of the trisynaptic circuit to reflect “adult-like” memory function, mainly 1) rapid encoding of contextual details of overlapping patterns, and 2) retention of these details over sleep-dependent delays. A wealth of evidence suggests that these functions are not apparent until 18–24 months, with behavioral discontinuities reflecting shifts in the neural structures subserving memory beginning approximately at this point in development. We discuss the implications of these observations for theories of memory and for identifying and measuring memory function in populations with typical and atypical hippocampal function. PMID:26437910

The Profile of Memory Function in Children With Autism

PubMed Central

Williams, Diane L.; Goldstein, Gerald; Minshew, Nancy J.

2007-01-01

A clinical memory test was administered to 38 high-functioning children with autism and 38 individually matched normal controls, 8–16 years of age. The resulting profile of memory abilities in the children with autism was characterized by relatively poor memory for complex visual and verbal information and spatial working memory with relatively intact associative learning ability, verbal working memory, and recognition memory. A stepwise discriminant function analysis of the subtests found that the Finger Windows subtest, a measure of spatial working memory, discriminated most accurately between the autism and normal control groups. A principal components analysis indicated that the factor structure of the subtests differed substantially between the children with autism and controls, suggesting differing organizations of memory ability. PMID:16460219

Autobiographical memory functioning among abused, neglected, and nonmaltreated children: the overgeneral memory effect.

PubMed

Valentino, Kristin; Toth, Sheree L; Cicchetti, Dante

2009-08-01

This investigation addresses whether there are differences in the form and content of autobiographical memory recall as a function of maltreatment, and examines the roles of self-system functioning and psychopathology in autobiographical memory processes. Autobiographical memory for positive and negative nontraumatic events was evaluated among abused, neglected, and nonmaltreated school-aged children. Abused children's memories were more overgeneral and contained more negative self-representations than did those of the nonmaltreated children. Negative self-representations and depression were significantly related to overgeneral memory, but did not mediate the relation between abuse and overgeneral memory. The meaning of these findings for models of memory and for the development of overgenerality is emphasized. Moreover, the clinical implications of the current research are discussed.

Miniature wireless recording and stimulation system for rodent behavioural testing

NASA Astrophysics Data System (ADS)

Pinnell, R. C.; Dempster, J.; Pratt, J.

2015-12-01

Objective. Elucidation of neural activity underpinning rodent behaviour has traditionally been hampered by the use of tethered systems and human involvement. Furthermore the combination of deep-brain stimulation (DBS) and various neural recording modalities can lead to complex and time-consuming laboratory setups. For studies of this type, novel tools are required to drive forward this research. Approach. A miniature wireless system weighing 8.5 g (including battery) was developed for rodent use that combined multichannel DBS and local-field potential (LFP) recordings. Its performance was verified in a working memory task that involved 4-channel fronto-hippocampal LFP recording and bilateral constant-current fimbria-fornix DBS. The system was synchronised with video-tracking for extraction of LFP at discrete task phases, and DBS was activated intermittently at discrete phases of the task. Main results. In addition to having a fast set-up time, the system could reliably transmit continuous LFP at over 8 hours across 3-5 m distances. During the working memory task, LFP pertaining to discrete task phases was extracted and compared with well-known neural correlates of active exploratory behaviour in rodents. DBS could be wirelessly activated/deactivated at any part of the experiment during EEG recording and transmission, allowing for a seamless integration of this modality. Significance. The wireless system combines a small size with a level of robustness and versatility that can greatly simplify rodent behavioural experiments involving EEG recording and DBS. Designed for versatility and simplicity, the small size and low-cost of the system and its receiver allow for enhanced portability, fast experimental setup times, and pave the way for integration with more complex behaviour.

System and method for memory allocation in a multiclass memory system

DOEpatents

Loh, Gabriel; Meswani, Mitesh; Ignatowski, Michael; Nutter, Mark

2016-06-28

A system for memory allocation in a multiclass memory system includes a processor coupleable to a plurality of memories sharing a unified memory address space, and a library store to store a library of software functions. The processor identifies a type of a data structure in response to a memory allocation function call to the library for allocating memory to the data structure. Using the library, the processor allocates portions of the data structure among multiple memories of the multiclass memory system based on the type of the data structure.

Functional connectivity pattern during rest within the episodic memory network in association with episodic memory performance in bipolar disorder.

PubMed

Oertel-Knöchel, Viola; Reinke, Britta; Matura, Silke; Prvulovic, David; Linden, David E J; van de Ven, Vincent

2015-02-28

In this study, we sought to examine the intrinsic functional organization of the episodic memory network during rest in bipolar disorder (BD). The previous work suggests that deficits in intrinsic functional connectivity may account for impaired memory performance. We hypothesized that regions involved in episodic memory processing would reveal aberrant functional connectivity in patients with bipolar disorder. We examined 21 patients with BD and 21 healthy matched controls who underwent functional magnetic resonance imaging (fMRI) during a resting condition. We did a seed-based functional connectivity analysis (SBA), using the regions of the episodic memory network that showed a significantly different activation pattern during task-related fMRI as seeds. The functional connectivity scores (FC) were further correlated with episodic memory task performance. Our results revealed decreased FC scores within frontal areas and between frontal and temporal/hippocampal/limbic regions in BD patients in comparison with controls. We observed higher FC in BD patients compared with controls between frontal and limbic regions. The decrease in fronto-frontal functional connectivity in BD patients showed a significant positive association with episodic memory performance. The association between task-independent dysfunctional frontal-limbic FC and episodic memory performance may be relevant for current pathophysiological models of the disease. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Discrete linear canonical transforms based on dilated Hermite functions.

PubMed

Pei, Soo-Chang; Lai, Yun-Chiu

2011-08-01

Linear canonical transform (LCT) is very useful and powerful in signal processing and optics. In this paper, discrete LCT (DLCT) is proposed to approximate LCT by utilizing the discrete dilated Hermite functions. The Wigner distribution function is also used to investigate DLCT performances in the time-frequency domain. Compared with the existing digital computation of LCT, our proposed DLCT possess additivity and reversibility properties with no oversampling involved. In addition, the length of input/output signals will not be changed before and after the DLCT transformations, which is consistent with the time-frequency area-preserving nature of LCT; meanwhile, the proposed DLCT has very good approximation of continuous LCT.

Discrete shaped strain sensors for intelligent structures

NASA Technical Reports Server (NTRS)

Andersson, Mark S.; Crawley, Edward F.

1992-01-01

Design of discrete, highly distributed sensor systems for intelligent structures has been studied. Data obtained indicate that discrete strain-averaging sensors satisfy the functional requirements for distributed sensing of intelligent structures. Bartlett and Gauss-Hanning sensors, in particular, provide good wavenumber characteristics while meeting the functional requirements. They are characterized by good rolloff rates and positive Fourier transforms for all wavenumbers. For the numerical integration schemes, Simpson's rule is considered to be very simple to implement and consistently provides accurate results for five sensors or more. It is shown that a sensor system that satisfies the functional requirements can be applied to a structure that supports mode shapes with purely sinusoidal curvature.

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.

Estimation and Application of Ecological Memory Functions in Time and Space

NASA Astrophysics Data System (ADS)

Itter, M.; Finley, A. O.; Dawson, A.

2017-12-01

A common goal in quantitative ecology is the estimation or prediction of ecological processes as a function of explanatory variables (or covariates). Frequently, the ecological process of interest and associated covariates vary in time, space, or both. Theory indicates many ecological processes exhibit memory to local, past conditions. Despite such theoretical understanding, few methods exist to integrate observations from the recent past or within a local neighborhood as drivers of these processes. We build upon recent methodological advances in ecology and spatial statistics to develop a Bayesian hierarchical framework to estimate so-called ecological memory functions; that is, weight-generating functions that specify the relative importance of local, past covariate observations to ecological processes. Memory functions are estimated using a set of basis functions in time and/or space, allowing for flexible ecological memory based on a reduced set of parameters. Ecological memory functions are entirely data driven under the Bayesian hierarchical framework—no a priori assumptions are made regarding functional forms. Memory function uncertainty follows directly from posterior distributions for model parameters allowing for tractable propagation of error to predictions of ecological processes. We apply the model framework to simulated spatio-temporal datasets generated using memory functions of varying complexity. The framework is also applied to estimate the ecological memory of annual boreal forest growth to local, past water availability. Consistent with ecological understanding of boreal forest growth dynamics, memory to past water availability peaks in the year previous to growth and slowly decays to zero in five to eight years. The Bayesian hierarchical framework has applicability to a broad range of ecosystems and processes allowing for increased understanding of ecosystem responses to local and past conditions and improved prediction of ecological processes.

The cost of misremembering: Inferring the loss function in visual working memory.

PubMed

Sims, Chris R

2015-03-04

Visual working memory (VWM) is a highly limited storage system. A basic consequence of this fact is that visual memories cannot perfectly encode or represent the veridical structure of the world. However, in natural tasks, some memory errors might be more costly than others. This raises the intriguing possibility that the nature of memory error reflects the costs of committing different kinds of errors. Many existing theories assume that visual memories are noise-corrupted versions of afferent perceptual signals. However, this additive noise assumption oversimplifies the problem. Implicit in the behavioral phenomena of visual working memory is the concept of a loss function: a mathematical entity that describes the relative cost to the organism of making different types of memory errors. An optimally efficient memory system is one that minimizes the expected loss according to a particular loss function, while subject to a constraint on memory capacity. This paper describes a novel theoretical framework for characterizing visual working memory in terms of its implicit loss function. Using inverse decision theory, the empirical loss function is estimated from the results of a standard delayed recall visual memory experiment. These results are compared to the predicted behavior of a visual working memory system that is optimally efficient for a previously identified natural task, gaze correction following saccadic error. Finally, the approach is compared to alternative models of visual working memory, and shown to offer a superior account of the empirical data across a range of experimental datasets. © 2015 ARVO.

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

Linear diffusion-wave channel routing using a discrete Hayami convolution method

Treesearch

Li Wang; Joan Q. Wu; William J. Elliot; Fritz R. Feidler; Sergey Lapin

2014-01-01

The convolution of an input with a response function has been widely used in hydrology as a means to solve various problems analytically. Due to the high computation demand in solving the functions using numerical integration, it is often advantageous to use the discrete convolution instead of the integration of the continuous functions. This approach greatly reduces...

The effect of hippocampal function, volume and connectivity on posterior cingulate cortex functioning during episodic memory fMRI in mild cognitive impairment.

PubMed

Papma, Janne M; Smits, Marion; de Groot, Marius; Mattace Raso, Francesco U; van der Lugt, Aad; Vrooman, Henri A; Niessen, Wiro J; Koudstaal, Peter J; van Swieten, John C; van der Veen, Frederik M; Prins, Niels D

2017-09-01

Diminished function of the posterior cingulate cortex (PCC) is a typical finding in early Alzheimer's disease (AD). It is hypothesized that in early stage AD, PCC functioning relates to or reflects hippocampal dysfunction or atrophy. The aim of this study was to examine the relationship between hippocampus function, volume and structural connectivity, and PCC activation during an episodic memory task-related fMRI study in mild cognitive impairment (MCI). MCI patients (n = 27) underwent episodic memory task-related fMRI, 3D-T1w MRI, 2D T2-FLAIR MRI and diffusion tensor imaging. Stepwise linear regression analysis was performed to examine the relationship between PCC activation and hippocampal activation, hippocampal volume and diffusion measures within the cingulum along the hippocampus. We found a significant relationship between PCC and hippocampus activation during successful episodic memory encoding and correct recognition in MCI patients. We found no relationship between the PCC and structural hippocampal predictors. Our results indicate a relationship between PCC and hippocampus activation during episodic memory engagement in MCI. This may suggest that during episodic memory, functional network deterioration is the most important predictor of PCC functioning in MCI. • PCC functioning during episodic memory relates to hippocampal functioning in MCI. • PCC functioning during episodic memory does not relate to hippocampal structure in MCI. • Functional network changes are an important predictor of PCC functioning in MCI.

The Relation of Finite Element and Finite Difference Methods

NASA Technical Reports Server (NTRS)

Vinokur, M.

1976-01-01

Finite element and finite difference methods are examined in order to bring out their relationship. It is shown that both methods use two types of discrete representations of continuous functions. They differ in that finite difference methods emphasize the discretization of independent variable, while finite element methods emphasize the discretization of dependent variable (referred to as functional approximations). An important point is that finite element methods use global piecewise functional approximations, while finite difference methods normally use local functional approximations. A general conclusion is that finite element methods are best designed to handle complex boundaries, while finite difference methods are superior for complex equations. It is also shown that finite volume difference methods possess many of the advantages attributed to finite element methods.

Computational complexity of Boolean functions

NASA Astrophysics Data System (ADS)

Korshunov, Aleksei D.

2012-02-01

Boolean functions are among the fundamental objects of discrete mathematics, especially in those of its subdisciplines which fall under mathematical logic and mathematical cybernetics. The language of Boolean functions is convenient for describing the operation of many discrete systems such as contact networks, Boolean circuits, branching programs, and some others. An important parameter of discrete systems of this kind is their complexity. This characteristic has been actively investigated starting from Shannon's works. There is a large body of scientific literature presenting many fundamental results. The purpose of this survey is to give an account of the main results over the last sixty years related to the complexity of computation (realization) of Boolean functions by contact networks, Boolean circuits, and Boolean circuits without branching. Bibliography: 165 titles.

Activation of Gαq Signaling Enhances Memory Consolidation and Slows Cognitive Decline.

PubMed

Arey, Rachel N; Stein, Geneva M; Kaletsky, Rachel; Kauffman, Amanda; Murphy, Coleen T

2018-05-02

Perhaps the most devastating decline with age is the loss of memory. Therefore, identifying mechanisms to restore memory function with age is critical. Using C. elegans associative learning and memory assays, we identified a gain-of-function G αq signaling pathway mutant that forms a long-term (cAMP response element binding protein [CREB]-dependent) memory following one conditioned stimulus-unconditioned stimulus (CS-US) pairing, which usually requires seven CS-US pairings. Increased CREB activity in AIM interneurons reduces the threshold for memory consolidation through transcription of a set of previously identified "long-term memory" genes. Enhanced G αq signaling in the AWC sensory neuron is both necessary and sufficient for improved memory and increased AIM CREB activity, and activation of G αq specifically in aged animals rescues the ability to form memory. Activation of G αq in AWC sensory neurons non-cell autonomously induces consolidation after one CS-US pairing, enabling both cognitive function maintenance with age and restoration of memory function in animals with impaired memory performance without decreased longevity. Copyright © 2018 Elsevier Inc. All rights reserved.

The effect of bupropion XL and escitalopram on memory and functional outcomes in adults with major depressive disorder: results from a randomized controlled trial.

PubMed

Soczynska, Joanna K; Ravindran, Lakshmi N; Styra, Rima; McIntyre, Roger S; Cyriac, Anna; Manierka, Marena S; Kennedy, Sidney H

2014-12-15

Decrements in cognitive function are a common feature of Major Depressive Disorder (MDD), and whether distinct classes of antidepressants differentially affect memory in these individuals has not been sufficiently evaluated. In this study we sought to determine the effect of escitalopram and bupropion XL on memory and psychosocial function. Forty-one individuals (18-50 years) with MDD were enrolled in an 8-week, double-blind, double-dummy, randomized controlled comparative trial of bupropion XL and escitalopram. Thirty-six participants completed pre and post memory assessments. Verbal, non-verbal and working memory were evaluated with a comprehensive neuropsychological battery. Psychosocial function was assessed with the Sheehan Disability Scale and Endicott Work Productivity Scale. Escitalopram and bupropion XL significantly improved immediate as well as delayed verbal and nonverbal memory, global function (all p≤0.001), and work productivity (p=0.045), with no significant between-group differences. Improvement in immediate verbal memory exerted a direct influence on improvement in global function (p=0.006). Treatment with either escitalopram or bupropion XL was associated with improvement in memory and psychosocial function in adults with MDD. Copyright © 2014. Published by Elsevier Ireland Ltd.

Fast non-overlapping Schwarz domain decomposition methods for solving the neutron diffusion equation

NASA Astrophysics Data System (ADS)

Jamelot, Erell; Ciarlet, Patrick

2013-05-01

Studying numerically the steady state of a nuclear core reactor is expensive, in terms of memory storage and computational time. In order to address both requirements, one can use a domain decomposition method, implemented on a parallel computer. We present here such a method for the mixed neutron diffusion equations, discretized with Raviart-Thomas-Nédélec finite elements. This method is based on the Schwarz iterative algorithm with Robin interface conditions to handle communications. We analyse this method from the continuous point of view to the discrete point of view, and we give some numerical results in a realistic highly heterogeneous 3D configuration. Computations are carried out with the MINOS solver of the APOLLO3® neutronics code. APOLLO3 is a registered trademark in France.

Memory formation during anaesthesia: plausibility of a neurophysiological basis.

PubMed

Veselis, R A

2015-07-01

As opposed to conscious, personally relevant (explicit) memories that we can recall at will, implicit (unconscious) memories are prototypical of 'hidden' memory; memories that exist, but that we do not know we possess. Nevertheless, our behaviour can be affected by these memories; in fact, these memories allow us to function in an ever-changing world. It is still unclear from behavioural studies whether similar memories can be formed during anaesthesia. Thus, a relevant question is whether implicit memory formation is a realistic possibility during anaesthesia, considering the underlying neurophysiology. A different conceptualization of memory taxonomy is presented, the serial parallel independent model of Tulving, which focuses on dynamic information processing with interactions among different memory systems rather than static classification of different types of memories. The neurophysiological basis for subliminal information processing is considered in the context of brain function as embodied in network interactions. Function of sensory cortices and thalamic activity during anaesthesia are reviewed. The role of sensory and perisensory cortices, in particular the auditory cortex, in support of memory function is discussed. Although improbable, with the current knowledge of neurophysiology one cannot rule out the possibility of memory formation during anaesthesia. © The Author 2015. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Discrete-state phasor neural networks

NASA Astrophysics Data System (ADS)

Noest, André J.

1988-08-01

An associative memory network with local variables assuming one of q equidistant positions on the unit circle (q-state phasors) is introduced, and its recall behavior is solved exactly for any q when the interactions are sparse and asymmetric. Such models can describe natural or artifical networks of (neuro-)biological, chemical, or electronic limit-cycle oscillators with q-fold instead of circular symmetry, or similar optical computing devices using a phase-encoded data representation.

A Protein Synthesis and Nitric Oxide-Dependent Presynaptic Enhancement in Persistent Forms of Long-Term Potentiation

ERIC Educational Resources Information Center

Johnstone, Victoria P. A.; Raymond, Clarke R.

2011-01-01

Long-term potentiation (LTP) is an important process underlying learning and memory in the brain. At CA3-CA1 synapses in the hippocampus, three discrete forms of LTP (LTP1, 2, and 3) can be differentiated on the basis of maintenance and induction mechanisms. However, the relative roles of pre- and post-synaptic expression mechanisms in LTP1, 2,…

Discrete Fluctuations in Memory Erasure without Energy Cost

NASA Astrophysics Data System (ADS)

Croucher, Toshio; Bedkihal, Salil; Vaccaro, Joan A.

2017-02-01

According to Landauer's principle, erasing one bit of information incurs a minimum energy cost. Recently, Vaccaro and Barnett (VB) explored information erasure within the context of generalized Gibbs ensembles and demonstrated that for energy-degenerate spin reservoirs the cost of erasure can be solely in terms of a minimum amount of spin angular momentum and no energy. As opposed to the Landauer case, the cost of erasure in this case is associated with an intrinsically discrete degree of freedom. Here we study the discrete fluctuations in this cost and the probability of violation of the VB bound. We also obtain a Jarzynski-like equality for the VB erasure protocol. We find that the fluctuations below the VB bound are exponentially suppressed at a far greater rate and more tightly than for an equivalent Jarzynski expression for VB erasure. We expose a trade-off between the size of the fluctuations and the cost of erasure. We find that the discrete nature of the fluctuations is pronounced in the regime where reservoir spins are maximally polarized. We also state the first laws of thermodynamics corresponding to the conservation of spin angular momentum for this particular erasure protocol. Our work will be important for novel heat engines based on information erasure schemes that do not incur an energy cost.

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks

PubMed Central

Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

2016-01-01

Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle’s position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption. PMID:27428971

Pose Invariant Face Recognition Based on Hybrid Dominant Frequency Features

NASA Astrophysics Data System (ADS)

Wijaya, I. Gede Pasek Suta; Uchimura, Keiichi; Hu, Zhencheng

Face recognition is one of the most active research areas in pattern recognition, not only because the face is a human biometric characteristics of human being but also because there are many potential applications of the face recognition which range from human-computer interactions to authentication, security, and surveillance. This paper presents an approach to pose invariant human face image recognition. The proposed scheme is based on the analysis of discrete cosine transforms (DCT) and discrete wavelet transforms (DWT) of face images. From both the DCT and DWT domain coefficients, which describe the facial information, we build compact and meaningful features vector, using simple statistical measures and quantization. This feature vector is called as the hybrid dominant frequency features. Then, we apply a combination of the L2 and Lq metric to classify the hybrid dominant frequency features to a person's class. The aim of the proposed system is to overcome the high memory space requirement, the high computational load, and the retraining problems of previous methods. The proposed system is tested using several face databases and the experimental results are compared to a well-known Eigenface method. The proposed method shows good performance, robustness, stability, and accuracy without requiring geometrical normalization. Furthermore, the purposed method has low computational cost, requires little memory space, and can overcome retraining problem.

Further evidence that similar principles govern recall from episodic and semantic memory: the Canadian prime ministerial serial position function.

PubMed

Neath, Ian; Saint-Aubin, Jean

2011-06-01

The serial position function, with its characteristic primacy and recency effects, is one of the most ubiquitous findings in episodic memory tasks. In contrast, there are only two demonstrations of such functions in tasks thought to tap semantic memory. Here, we provide a third demonstration, showing that free recall of the prime ministers of Canada also results in a serial position function. Scale Independent Memory, Perception, and Learning (SIMPLE), a local distinctiveness model of memory that was designed to account for serial position effects in episodic memory, fit the data. According to SIMPLE, serial position functions observed in episodic and semantic memory all reflect the relative distinctiveness principle: items will be well remembered to the extent that they are more distinct than competing items at the time of retrieval. (PsycINFO Database Record (c) 2011 APA, all rights reserved).

The effect of functional hearing loss and age on long- and short-term visuospatial memory: evidence from the UK biobank resource.

PubMed

Rönnberg, Jerker; Hygge, Staffan; Keidser, Gitte; Rudner, Mary

2014-01-01

The UK Biobank offers cross-sectional epidemiological data collected on >500,000 individuals in the UK between 40 and 70 years of age. Using the UK Biobank data, the aim of this study was to investigate the effects of functional hearing loss and hearing aid usage on visuospatial memory function. This selection of variables resulted in a sub-sample of 138,098 participants after discarding extreme values. A digit triplets functional hearing test was used to divide the participants into three groups: poor, insufficient and normal hearers. We found negative relationships between functional hearing loss and both visuospatial working memory (i.e., a card pair matching task) and visuospatial, episodic long-term memory (i.e., a prospective memory task), with the strongest association for episodic long-term memory. The use of hearing aids showed a small positive effect for working memory performance for the poor hearers, but did not have any influence on episodic long-term memory. Age also showed strong main effects for both memory tasks and interacted with gender and education for the long-term memory task. Broader theoretical implications based on a memory systems approach will be discussed and compared to theoretical alternatives.

Neuro-Cognitive Intervention for Working Memory: Preliminary Results and Future Directions.

PubMed

Bree, Kathleen D; Beljan, Paul

2016-01-01

Definitions of working memory identify it as a function of the executive function system in which an individual maintains two or more pieces of information in mind and uses that information simultaneously for some purpose. In academics, working memory is necessary for a variety of functions, including attending to the information one's teacher presents and then using that information simultaneously for problem solving. Research indicates difficulties with working memory are observed in children with mathematics learning disorder (MLD) and reading disorders (RD). To improve working memory and other executive function difficulties, and as an alternative to medication treatments for attention and executive function disorders, the Motor Cognition(2)® (MC(2)®)program was developed. Preliminary research on this program indicates statistically significant improvements in working memory, mathematics, and nonsense word decoding for reading. Further research on the MC(2)® program and its impact on working memory, as well as other areas of executive functioning, is warranted.

Temporal lobe surgery in childhood and neuroanatomical predictors of long-term declarative memory outcome

PubMed Central

Skirrow, Caroline; Cross, J. Helen; Harrison, Sue; Cormack, Francesca; Harkness, William; Coleman, Rosie; Meierotto, Ellen; Gaiottino, Johanna; Vargha-Khadem, Faraneh

2015-01-01

The temporal lobes play a prominent role in declarative memory function, including episodic memory (memory for events) and semantic memory (memory for facts and concepts). Surgical resection for medication-resistant and well-localized temporal lobe epilepsy has good prognosis for seizure freedom, but is linked to memory difficulties in adults, especially when the removal is on the left side. Children may benefit most from surgery, because brain plasticity may facilitate post-surgical reorganization, and seizure cessation may promote cognitive development. However, the long-term impact of this intervention in children is not known. We examined memory function in 53 children (25 males, 28 females) who were evaluated for epilepsy surgery: 42 underwent unilateral temporal lobe resections (25 left, 17 right, mean age at surgery 13.8 years), 11 were treated only pharmacologically. Average follow-up was 9 years (range 5–15). Post-surgical change in visual and verbal episodic memory, and semantic memory at follow-up were examined. Pre- and post-surgical T1-weighted MRI brain scans were analysed to extract hippocampal and resection volumes, and evaluate post-surgical temporal lobe integrity. Language lateralization indices were derived from functional magnetic resonance imaging. There were no significant pre- to postoperative decrements in memory associated with surgery. In contrast, gains in verbal episodic memory were seen after right temporal lobe surgery, and visual episodic memory improved after left temporal lobe surgery, indicating a functional release in the unoperated temporal lobe after seizure reduction or cessation. Pre- to post-surgical change in memory function was not associated with any indices of brain structure derived from MRI. However, better verbal memory at follow-up was linked to greater post-surgical residual hippocampal volumes, most robustly in left surgical participants. Better semantic memory at follow-up was associated with smaller resection volumes and greater temporal pole integrity after left temporal surgery. Results were independent of post-surgical intellectual function and language lateralization. Our findings indicate post-surgical, hemisphere-dependent material-specific improvement in memory functions in the intact temporal lobe. However, outcome was linked to the anatomical integrity of the temporal lobe memory system, indicating that compensatory mechanisms are constrained by the amount of tissue which remains in the operated temporal lobe. Careful tailoring of resections for children undergoing epilepsy surgery may enhance long-term memory outcome. PMID:25392199

Episodic memory retrieval, parietal cortex, and the default mode network: functional and topographic analyses.

PubMed

Sestieri, Carlo; Corbetta, Maurizio; Romani, Gian Luca; Shulman, Gordon L

2011-03-23

The default mode network (DMN) is often considered a functionally homogeneous system that is broadly associated with internally directed cognition (e.g., episodic memory, theory of mind, self-evaluation). However, few studies have examined how this network interacts with other networks during putative "default" processes such as episodic memory retrieval. Using functional magnetic resonance imaging, we investigated the topography and response profile of human parietal regions inside and outside the DMN, independently defined using task-evoked deactivations and resting-state functional connectivity, during episodic memory retrieval. Memory retrieval activated posterior nodes of the DMN, particularly the angular gyrus, but also more anterior and dorsal parietal regions that were anatomically separate from the DMN. The two sets of parietal regions showed different resting-state functional connectivity and response profiles. During memory retrieval, responses in DMN regions peaked sooner than non-DMN regions, which in turn showed responses that were sustained until a final memory judgment was reached. Moreover, a parahippocampal region that showed strong resting-state connectivity with parietal DMN regions also exhibited a pattern of task-evoked activity similar to that exhibited by DMN regions. These results suggest that DMN parietal regions directly supported memory retrieval, whereas non-DMN parietal regions were more involved in postretrieval processes such as memory-based decision making. Finally, a robust functional dissociation within the DMN was observed. Whereas angular gyrus and posterior cingulate/precuneus were significantly activated during memory retrieval, an anterior DMN node in medial prefrontal cortex was strongly deactivated. This latter finding demonstrates functional heterogeneity rather than homogeneity within the DMN during episodic memory retrieval.

Oscillatory lower body negative pressure impairs working memory task-related functional hyperemia in healthy volunteers.

PubMed

Merchant, Sana; Medow, Marvin S; Visintainer, Paul; Terilli, Courtney; Stewart, Julian M

2017-04-01

Neurovascular coupling (NVC) describes the link between an increase in task-related neural activity and increased cerebral blood flow denoted "functional hyperemia." We previously showed induced cerebral blood flow oscillations suppressed functional hyperemia; conversely functional hyperemia also suppressed cerebral blood flow oscillations. We used lower body negative pressure (OLBNP) oscillations to force oscillations in middle cerebral artery cerebral blood flow velocity (CBFv). Here, we used N-back testing, an intellectual memory challenge as a neural activation task, to test the hypothesis that OLBNP-induced oscillatory cerebral blood flow can reduce functional hyperemia and NVC produced by a working memory task and can interfere with working memory. We used OLBNP (-30 mmHg) at 0.03, 0.05, and 0.10 Hz and measured spectral power of CBFv at all frequencies. Neither OLBNP nor N-back, alone or combined, affected hemodynamic parameters. 2-Back power and OLBNP individually were compared with 2-back power during OLBNP. 2-Back alone produced a narrow band increase in oscillatory arterial pressure (OAP) and oscillatory cerebral blood flow power centered at 0.0083 Hz. Functional hyperemia in response to 2-back was reduced to near baseline and 2-back memory performance was decreased by 0.03-, 0.05-, and 0.10-Hz OLBNP. OLBNP alone produced increased oscillatory power at frequencies of oscillation not suppressed by added 2-back. However, 2-back preceding OLBNP suppressed OLBNP power. OLBNP-driven oscillatory CBFv blunts NVC and memory performance, while memory task reciprocally interfered with forced CBFv oscillations. This shows that induced cerebral blood flow oscillations suppress functional hyperemia and functional hyperemia suppresses cerebral blood flow oscillations. NEW & NOTEWORTHY We show that induced cerebral blood flow oscillations suppress functional hyperemia produced by a working memory task as well as memory task performance. We conclude that oscillatory cerebral blood flow produces causal reductions of memory task neurovascular coupling and memory task performance. Reductions of functional hyperemia are constrained by autoregulation. Copyright © 2017 the American Physiological Society.

Nonmonotonic Aging and Memory in a Frictional Interface

NASA Astrophysics Data System (ADS)

Dillavou, Sam; Rubinstein, Shmuel M.

2018-06-01

We measure the static frictional resistance and the real area of contact between two solid blocks subjected to a normal load. We show that following a two-step change in the normal load the system exhibits nonmonotonic aging and memory effects, two hallmarks of glassy dynamics. These dynamics are strongly influenced by the discrete geometry of the frictional interface, characterized by the attachment and detachment of unique microcontacts. The results are in good agreement with a theoretical model we propose that incorporates this geometry into the framework recently used to describe Kovacs-like relaxation in glasses as well as thermal disordered systems. These results indicate that a frictional interface is a glassy system and strengthen the notion that nonmonotonic relaxation behavior is generic in such systems.

Practical Unitary Simulator for Non-Markovian Complex Processes

NASA Astrophysics Data System (ADS)

Binder, Felix C.; Thompson, Jayne; Gu, Mile

2018-06-01

Stochastic processes are as ubiquitous throughout the quantitative sciences as they are notorious for being difficult to simulate and predict. In this Letter, we propose a unitary quantum simulator for discrete-time stochastic processes which requires less internal memory than any classical analogue throughout the simulation. The simulator's internal memory requirements equal those of the best previous quantum models. However, in contrast to previous models, it only requires a (small) finite-dimensional Hilbert space. Moreover, since the simulator operates unitarily throughout, it avoids any unnecessary information loss. We provide a stepwise construction for simulators for a large class of stochastic processes hence directly opening the possibility for experimental implementations with current platforms for quantum computation. The results are illustrated for an example process.

Fast and Accurate Learning When Making Discrete Numerical Estimates.

PubMed

Sanborn, Adam N; Beierholm, Ulrik R

2016-04-01

Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates.

Fast and Accurate Learning When Making Discrete Numerical Estimates

PubMed Central

Sanborn, Adam N.; Beierholm, Ulrik R.

2016-01-01

Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates. PMID:27070155

Effects of Attention and Levels of Processing on Explicit and Implicit Memory Function with Interesting and Uninteresting Tasks in University Students

NASA Astrophysics Data System (ADS)

Mahdavian, Alireza; Kormi-Nouri, Reza

This study aims to investigate the effect of attention and levels of processing on memory function and recalling words in two situations when students are interested in the subject and when they are not. This is an experimental study of 160 students conducted individually using a computer software. Results reveal focused attention, interest in the subject and deep processing caused the explicit memory to be at its highest level of functionality. On the contrary, shallow processing, divided attention and lack of interest in the subject plunged memory function into its lowest levels. Variables have different effects on attention, explicit and implicit memory. That is, interesting tasks with focused attention and deep processing have the highest effect on explicit memory in order. Also, interesting tasks, focused attention, respectively affect implicit memory. But level of processing does not affect implicit memory significantly.

Three-dimensional geoelectric modelling with optimal work/accuracy rate using an adaptive wavelet algorithm

NASA Astrophysics Data System (ADS)

Plattner, A.; Maurer, H. R.; Vorloeper, J.; Dahmen, W.

2010-08-01

Despite the ever-increasing power of modern computers, realistic modelling of complex 3-D earth models is still a challenging task and requires substantial computing resources. The overwhelming majority of current geophysical modelling approaches includes either finite difference or non-adaptive finite element algorithms and variants thereof. These numerical methods usually require the subsurface to be discretized with a fine mesh to accurately capture the behaviour of the physical fields. However, this may result in excessive memory consumption and computing times. A common feature of most of these algorithms is that the modelled data discretizations are independent of the model complexity, which may be wasteful when there are only minor to moderate spatial variations in the subsurface parameters. Recent developments in the theory of adaptive numerical solvers have the potential to overcome this problem. Here, we consider an adaptive wavelet-based approach that is applicable to a large range of problems, also including nonlinear problems. In comparison with earlier applications of adaptive solvers to geophysical problems we employ here a new adaptive scheme whose core ingredients arose from a rigorous analysis of the overall asymptotically optimal computational complexity, including in particular, an optimal work/accuracy rate. Our adaptive wavelet algorithm offers several attractive features: (i) for a given subsurface model, it allows the forward modelling domain to be discretized with a quasi minimal number of degrees of freedom, (ii) sparsity of the associated system matrices is guaranteed, which makes the algorithm memory efficient and (iii) the modelling accuracy scales linearly with computing time. We have implemented the adaptive wavelet algorithm for solving 3-D geoelectric problems. To test its performance, numerical experiments were conducted with a series of conductivity models exhibiting varying degrees of structural complexity. Results were compared with a non-adaptive finite element algorithm, which incorporates an unstructured mesh to best-fitting subsurface boundaries. Such algorithms represent the current state-of-the-art in geoelectric modelling. An analysis of the numerical accuracy as a function of the number of degrees of freedom revealed that the adaptive wavelet algorithm outperforms the finite element solver for simple and moderately complex models, whereas the results become comparable for models with high spatial variability of electrical conductivities. The linear dependence of the modelling error and the computing time proved to be model-independent. This feature will allow very efficient computations using large-scale models as soon as our experimental code is optimized in terms of its implementation.

Autobiographical memory functioning among abused, neglected, and nonmaltreated children: The overgeneral memory effect

PubMed Central

Valentino, Kristin; Toth, Sheree L.; Cicchetti, Dante

2012-01-01

Background This investigation addresses whether there are differences in the form and content of autobiographical memory recall as a function of maltreatment, and examines the roles of self-system functioning and psychopathology in autobiographical memory processes. Methods Autobiographical memory for positive and negative nontraumatic events was evaluated among abused, neglected, and nonmaltreated school-aged children. Results Abused children’s memories were more overgeneral and contained more negative self-representations than did those of the nonmaltreated children. Negative self-representations and depression were significantly related to overgeneral memory, but did not mediate the relation between abuse and overgeneral memory. Conclusions The meaning of these findings for models of memory and for the development of overgenerality is emphasized. Moreover, the clinical implications of the current research are discussed. PMID:19490313

Does widowhood affect memory performance of older persons?

PubMed

Aartsen, Marja J; Van Tilburg, Theo; Smits, Carolien H M; Comijs, Hannie C; Knipscheer, Kees C P M

2005-02-01

The loss of a spouse has been found to have a negative effect on physical and mental health and leads to increased mortality. Whether conjugal bereavement also affects memory functioning has largely been unexamined. The present study investigates the effect of widowhood on memory functioning in older persons. The sample consisted of 474 married women and 690 married men aged 60-85 years in 1992, followed up in 1995 and 1998. During the study 135 (28%) of the women and 69 (10%) of the men lost their spouse. Linear regression analysis was used to examine whether widowed men and women differed from those who had not been widowed in rate of memory change over 6 years. Cross-domain latent-change models were subsequently used to evaluate the extent to which changes in memory are related to changes in other domains of functioning that may be affected by widowhood. Older adults who lost a spouse during follow-up showed a greater decline in memory over 6 years than those who remained married. A higher level of depressive symptoms at baseline was related to lower levels of memory functioning and a greater decline. Memory decline was unrelated to changes in depressive symptoms and physical health. Loss of the spouse is related to a greater decline in memory in older adults. The absence of an association with physical functioning and the weak association with mental functioning suggest that losing a spouse has an independent effect on memory functioning.

Acute exercise enhances the consolidation of fear extinction memory and reduces conditioned fear relapse in a sex-dependent manner.

PubMed

Bouchet, Courtney A; Lloyd, Brian A; Loetz, Esteban C; Farmer, Caroline E; Ostrovskyy, Mykola; Haddad, Natalie; Foright, Rebecca M; Greenwood, Benjamin N

2017-08-01

Fear extinction-based exposure therapy is the most common behavioral therapy for anxiety and trauma-related disorders, but fear extinction memories are labile and fear tends to return even after successful extinction. The relapse of fear contributes to the poor long-term efficacy of exposure therapy. A single session of voluntary exercise can enhance the acquisition and consolidation of fear extinction in male rats, but the effects of exercise on relapse of fear after extinction are not well understood. Here, we characterized the effects of 2 h of voluntary exercise during the consolidation phase of contextual or auditory fear extinction learning on long-term fear extinction memory and renewal in adult, male and female, Long-Evans rats. Results indicate that exercise enhances consolidation of fear extinction memory and reduces fear relapse after extinction in a sex-dependent manner. These data suggest that brief bouts of exercise could be used as an augmentation strategy for exposure therapy, even in previously sedentary subjects. Fear memories of discrete cues, rather than of contextual ones, may be most susceptible to exercise-augmented extinction, especially in males. Additionally, exercise seems to have the biggest impact on fear relapse phenomena, even if fear extinction memories themselves are only minimally enhanced. © 2017 Bouchet et al.; Published by Cold Spring Harbor Laboratory Press.

Improved charge trapping properties by embedded graphene oxide quantum-dots for flash memory application

NASA Astrophysics Data System (ADS)

Jia, Xinlei; Yan, Xiaobing; Wang, Hong; Yang, Tao; Zhou, Zhenyu; Zhao, Jianhui

2018-06-01

In this work, we have investigated two kinds of charge trapping memory devices with Pd/Al2O3/ZnO/SiO2/p-Si and Pd/Al2O3/ZnO/graphene oxide quantum-dots (GOQDs)/ZnO/SiO2/p-Si structure. Compared with the single ZnO sample, the memory window of the ZnO-GOQDs-ZnO sample reaches a larger value (more than doubled) of 2.7 V under the sweeping gate voltage ± 7 V, indicating a better charge storage capability and the significant charge trapping effects by embedding the GOQDs trapping layer. The ZnO-GOQDs-ZnO devices have better date retention properties with the high and low capacitances loss of ˜ 1.1 and ˜ 6.9%, respectively, as well as planar density of the trapped charges of 1.48 × 1012 cm- 2. It is proposed that the GOQDs play an important role in the outstanding memory characteristics due to the deep quantum potential wells and the discrete distribution of the GOQDs. The long date retention time might have resulted from the high potential barrier which suppressed both the back tunneling and the leakage current. Intercalating GOQDs in the memory device is a promising method to realize large memory window, low-power consumption and excellent retention properties.

Current Density and Continuity in Discretized Models

ERIC Educational Resources Information Center

Boykin, Timothy B.; Luisier, Mathieu; Klimeck, Gerhard

2010-01-01

Discrete approaches have long been used in numerical modelling of physical systems in both research and teaching. Discrete versions of the Schrodinger equation employing either one or several basis functions per mesh point are often used by senior undergraduates and beginning graduate students in computational physics projects. In studying…

Discrete-to-continuous transition in quantum phase estimation

NASA Astrophysics Data System (ADS)

Rządkowski, Wojciech; Demkowicz-Dobrzański, Rafał

2017-09-01

We analyze the problem of quantum phase estimation in which the set of allowed phases forms a discrete N -element subset of the whole [0 ,2 π ] interval, φn=2 π n /N , n =0 ,⋯,N -1 , and study the discrete-to-continuous transition N →∞ for various cost functions as well as the mutual information. We also analyze the relation between the problems of phase discrimination and estimation by considering a step cost function of a given width σ around the true estimated value. We show that in general a direct application of the theory of covariant measurements for a discrete subgroup of the U(1 ) group leads to suboptimal strategies due to an implicit requirement of estimating only the phases that appear in the prior distribution. We develop the theory of subcovariant measurements to remedy this situation and demonstrate truly optimal estimation strategies when performing a transition from discrete to continuous phase estimation.

Implementation of quantum and classical discrete fractional Fourier transforms.

PubMed

Weimann, Steffen; Perez-Leija, Armando; Lebugle, Maxime; Keil, Robert; Tichy, Malte; Gräfe, Markus; Heilmann, René; Nolte, Stefan; Moya-Cessa, Hector; Weihs, Gregor; Christodoulides, Demetrios N; Szameit, Alexander

2016-03-23

Fourier transforms, integer and fractional, are ubiquitous mathematical tools in basic and applied science. Certainly, since the ordinary Fourier transform is merely a particular case of a continuous set of fractional Fourier domains, every property and application of the ordinary Fourier transform becomes a special case of the fractional Fourier transform. Despite the great practical importance of the discrete Fourier transform, implementation of fractional orders of the corresponding discrete operation has been elusive. Here we report classical and quantum optical realizations of the discrete fractional Fourier transform. In the context of classical optics, we implement discrete fractional Fourier transforms of exemplary wave functions and experimentally demonstrate the shift theorem. Moreover, we apply this approach in the quantum realm to Fourier transform separable and path-entangled biphoton wave functions. The proposed approach is versatile and could find applications in various fields where Fourier transforms are essential tools.

Efficient Construction of Discrete Adjoint Operators on Unstructured Grids by Using Complex Variables

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.; Kleb, William L.

2005-01-01

A methodology is developed and implemented to mitigate the lengthy software development cycle typically associated with constructing a discrete adjoint solver for aerodynamic simulations. The approach is based on a complex-variable formulation that enables straightforward differentiation of complicated real-valued functions. An automated scripting process is used to create the complex-variable form of the set of discrete equations. An efficient method for assembling the residual and cost function linearizations is developed. The accuracy of the implementation is verified through comparisons with a discrete direct method as well as a previously developed handcoded discrete adjoint approach. Comparisons are also shown for a large-scale configuration to establish the computational efficiency of the present scheme. To ultimately demonstrate the power of the approach, the implementation is extended to high temperature gas flows in chemical nonequilibrium. Finally, several fruitful research and development avenues enabled by the current work are suggested.

Efficient Construction of Discrete Adjoint Operators on Unstructured Grids Using Complex Variables

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.; Kleb, William L.

2005-01-01

A methodology is developed and implemented to mitigate the lengthy software development cycle typically associated with constructing a discrete adjoint solver for aerodynamic simulations. The approach is based on a complex-variable formulation that enables straightforward differentiation of complicated real-valued functions. An automated scripting process is used to create the complex-variable form of the set of discrete equations. An efficient method for assembling the residual and cost function linearizations is developed. The accuracy of the implementation is verified through comparisons with a discrete direct method as well as a previously developed handcoded discrete adjoint approach. Comparisons are also shown for a large-scale configuration to establish the computational efficiency of the present scheme. To ultimately demonstrate the power of the approach, the implementation is extended to high temperature gas flows in chemical nonequilibrium. Finally, several fruitful research and development avenues enabled by the current work are suggested.

Implementation of quantum and classical discrete fractional Fourier transforms

PubMed Central

Weimann, Steffen; Perez-Leija, Armando; Lebugle, Maxime; Keil, Robert; Tichy, Malte; Gräfe, Markus; Heilmann, René; Nolte, Stefan; Moya-Cessa, Hector; Weihs, Gregor; Christodoulides, Demetrios N.; Szameit, Alexander

2016-01-01

Fourier transforms, integer and fractional, are ubiquitous mathematical tools in basic and applied science. Certainly, since the ordinary Fourier transform is merely a particular case of a continuous set of fractional Fourier domains, every property and application of the ordinary Fourier transform becomes a special case of the fractional Fourier transform. Despite the great practical importance of the discrete Fourier transform, implementation of fractional orders of the corresponding discrete operation has been elusive. Here we report classical and quantum optical realizations of the discrete fractional Fourier transform. In the context of classical optics, we implement discrete fractional Fourier transforms of exemplary wave functions and experimentally demonstrate the shift theorem. Moreover, we apply this approach in the quantum realm to Fourier transform separable and path-entangled biphoton wave functions. The proposed approach is versatile and could find applications in various fields where Fourier transforms are essential tools. PMID:27006089

Cholinergic modulation of the hippocampal region and memory function.

PubMed

Haam, Juhee; Yakel, Jerrel L

2017-08-01

Acetylcholine (ACh) plays an important role in memory function and has been implicated in aging-related dementia, in which the impairment of hippocampus-dependent learning strongly manifests. Cholinergic neurons densely innervate the hippocampus, mediating the formation of episodic as well as semantic memory. Here, we will review recent findings on acetylcholine's modulation of memory function, with a particular focus on hippocampus-dependent learning, and the circuits involved. In addition, we will discuss the complexity of ACh actions in memory function to better understand the physiological role of ACh in memory. This is an article for the special issue XVth International Symposium on Cholinergic Mechanisms. © 2017 International Society for Neurochemistry.

Sliding mode control-based linear functional observers for discrete-time stochastic systems

NASA Astrophysics Data System (ADS)

Singh, Satnesh; Janardhanan, Sivaramakrishnan

2017-11-01

Sliding mode control (SMC) is one of the most popular techniques to stabilise linear discrete-time stochastic systems. However, application of SMC becomes difficult when the system states are not available for feedback. This paper presents a new approach to design a SMC-based functional observer for discrete-time stochastic systems. The functional observer is based on the Kronecker product approach. Existence conditions and stability analysis of the proposed observer are given. The control input is estimated by a novel linear functional observer. This approach leads to a non-switching type of control, thereby eliminating the fundamental cause of chatter. Furthermore, the functional observer is designed in such a way that the effect of process and measurement noise is minimised. Simulation example is given to illustrate and validate the proposed design method.

Disrupting Jagged1-Notch signaling impairs spatial memory formation in adult mice.

PubMed

Sargin, Derya; Botly, Leigh C P; Higgs, Gemma; Marsolais, Alexander; Frankland, Paul W; Egan, Sean E; Josselyn, Sheena A

2013-07-01

It is well-known that Notch signaling plays a critical role in brain development and growing evidence implicates this signaling pathway in adult synaptic plasticity and memory formation. The Notch1 receptor is activated by two subclasses of ligands, Delta-like (including Dll1 and Dll4) and Jagged (including Jag1 and Jag2). Ligand-induced Notch1 receptor signaling is modulated by a family of Fringe proteins, including Lunatic fringe (Lfng). Although Dll1, Jag1 and Lfng are critical regulators of Notch signaling, their relative contribution to memory formation in the adult brain is unknown. To investigate the roles of these important components of Notch signaling in memory formation, we examined spatial and fear memory formation in adult mice with reduced expression of Dll1, Jag1, Lfng and Dll1 plus Lfng. We also examined motor activity, anxiety-like behavior and sensorimotor gating using the acoustic startle response in these mice. Of the lines of mutant mice tested, we found that only mice with reduced Jag1 expression (mice heterozygous for a null mutation in Jag1, Jag1(+/-)) showed a selective impairment in spatial memory formation. Importantly, all other behavior including open field activity, conditioned fear memory (both context and discrete cue), acoustic startle response and prepulse inhibition, was normal in this line of mice. These results provide the first in vivo evidence that Jag1-Notch signaling is critical for memory formation in the adult brain. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

The extended trajectory of hippocampal development: Implications for early memory development and disorder.

PubMed

Gómez, Rebecca L; Edgin, Jamie O

2016-04-01

Hippocampus has an extended developmental trajectory, with refinements occurring in the trisynaptic circuit until adolescence. While structural change should suggest a protracted course in behavior, some studies find evidence of precocious hippocampal development in the first postnatal year and continuity in memory processes beyond. However, a number of memory functions, including binding and relational inference, can be cortically supported. Evidence from the animal literature suggests that tasks often associated with hippocampus (visual paired comparison, binding of a visuomotor response) can be mediated by structures external to hippocampus. Thus, a complete examination of memory development will have to rule out cortex as a source of early memory competency. We propose that early memory must show properties associated with full function of the trisynaptic circuit to reflect "adult-like" memory function, mainly (1) rapid encoding of contextual details of overlapping patterns, and (2) retention of these details over sleep-dependent delays. A wealth of evidence suggests that these functions are not apparent until 18-24 months, with behavioral discontinuities reflecting shifts in the neural structures subserving memory beginning approximately at this point in development. We discuss the implications of these observations for theories of memory and for identifying and measuring memory function in populations with typical and atypical hippocampal function. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Longitudinal Associations of Subjective Memory with Memory Performance and Depressive Symptoms: Between-Person and Within-Person Perspectives

PubMed Central

Hülür, Gizem; Hertzog, Christopher; Pearman, Ann; Ram, Nilam; Gerstorf, Denis

2015-01-01

Clinical diagnostic criteria for memory loss in adults typically assume that subjective memory ratings accurately reflect compromised memory functioning. Research has documented small positive between-person associations between subjective memory and memory performance in older adults. Less is known, however, about whether within-person fluctuations in subjective memory covary with within-person variance in memory performance and depressive symptoms. The present study applied multilevel models of change to nine waves of data from 27,395 participants of the Health and Retirement Study (HRS; mean age at baseline = 63.78; SD = 10.30; 58% women) to examine whether subjective memory is associated with both between-person differences and within-person variability in memory performance and depressive symptoms and explored the moderating role of known correlates (age, gender, education, and functional limitations). Results revealed that across persons, level of subjective memory indeed covaried with level of memory performance and depressive symptoms, with small-to-moderate between-person standardized effect sizes (0.19 for memory performance and 0.21 for depressive symptoms). Within individuals, occasions when participants scored higher than usual on a test of episodic memory or reported fewer-than-average depressive symptoms generated above-average subjective memory. At the within-person level, subjective memory ratings became more sensitive to within-person alterations in memory performance over time and those suffering from functional limitations were more sensitive to within-person alterations in memory performance and depressive symptoms. We take our results to suggest that within-person changes in subjective memory in part reflect monitoring flux in one’s own memory functioning, but are also influenced by flux in depressive symptoms. PMID:25244464

Medial prefrontal functional connectivity--relation to memory self-appraisal accuracy in older adults with and without memory disorders.

PubMed

Ries, Michele L; McLaren, Donald G; Bendlin, Barbara B; Guofanxu; Rowley, Howard A; Birn, Rasmus; Kastman, Erik K; Sager, Mark A; Asthana, Sanjay; Johnson, Sterling C

2012-04-01

It is tentatively estimated that 25% of people with early Alzheimer's disease (AD) show impaired awareness of disease-related changes in their own cognition. Research examining both normative self-awareness and altered awareness resulting from brain disease or injury points to the central role of the medial prefrontal cortex (MPFC) in generating accurate self-appraisals. The current project builds on this work - examining changes in MPFC functional connectivity that correspond to impaired self-appraisal accuracy early in the AD time course. Our behavioral focus was self-appraisal accuracy for everyday memory function, and this was measured using the Memory Function Scale of the Memory Awareness Rating Scale - an instrument psychometrically validated for this purpose. Using regression analysis of data from people with healthy memory (n=12) and people with impaired memory due to amnestic mild cognitive impairment or early AD (n=12), we tested the hypothesis that altered MPFC functional connectivity - particularly with other cortical midline structures and dorsolateral prefrontal cortex - explains variation in memory self-appraisal accuracy. We spatially constrained (i.e., explicitly masked) our regression analyses to those regions that work in conjunction with the MPFC to evoke self-appraisals in a normative group. This empirically derived explicit mask was generated from the result of a psychophysiological interaction analysis of fMRI self-appraisal task data in a separate, large group of cognitively healthy individuals. Results of our primary analysis (i.e., the regression of memory self-appraisal accuracy on MPFC functional connectivity) were generally consistent with our hypothesis: people who were less accurate in making memory self-appraisals showed attenuated functional connectivity between the MPFC seed region and proximal areas within the MPFC (including subgenual anterior cingulate cortex), bilateral dorsolateral prefrontal cortex, bilateral caudate, and left posterior hippocampus. Contrary to our expectations, MPFC functional connectivity with the posterior cingulate was not significantly related to accuracy of memory self-appraisals. Results reported here corroborate findings of variable memory self-appraisal accuracy during the earliest emergence of AD symptoms and reveal alterations in MPFC functional connectivity that correspond to impaired memory self-appraisal. Copyright © 2012 Elsevier Ltd. All rights reserved.

Discrete ellipsoidal statistical BGK model and Burnett equations

NASA Astrophysics Data System (ADS)

Zhang, Yu-Dong; Xu, Ai-Guo; Zhang, Guang-Cai; Chen, Zhi-Hua; Wang, Pei

2018-06-01

A new discrete Boltzmann model, the discrete ellipsoidal statistical Bhatnagar-Gross-Krook (ESBGK) model, is proposed to simulate nonequilibrium compressible flows. Compared with the original discrete BGK model, the discrete ES-BGK has a flexible Prandtl number. For the discrete ES-BGK model in the Burnett level, two kinds of discrete velocity model are introduced and the relations between nonequilibrium quantities and the viscous stress and heat flux in the Burnett level are established. The model is verified via four benchmark tests. In addition, a new idea is introduced to recover the actual distribution function through the macroscopic quantities and their space derivatives. The recovery scheme works not only for discrete Boltzmann simulation but also for hydrodynamic ones, for example, those based on the Navier-Stokes or the Burnett equations.

A Domain-Specific Language for Discrete Mathematics

NASA Astrophysics Data System (ADS)

Jha, Rohit; Samuel, Alfy; Pawar, Ashmee; Kiruthika, M.

2013-05-01

This paper discusses a Domain Specific Language (DSL) that has been developed to enable implementation of concepts of discrete mathematics. A library of data types and functions provides functionality which is frequently required by users. Covering the areas of Mathematical Logic, Set Theory, Functions, Graph Theory, Number Theory, Linear Algebra and Combinatorics, the language's syntax is close to the actual notation used in the specific fields.

Autobiographical memory functions in young Japanese men and women.

PubMed

Maki, Yoichi; Kawasaki, Yayoi; Demiray, Burcu; Janssen, Steve M J

2015-01-01

The present study examined whether the three major functions of autobiographical memory observed in Western societies (i.e., directing-behaviour, social-bonding and self-continuity) also exist in an East Asian society. Two self-report measures were used to assess the autobiographical memory functions of Japanese men and women. Japanese young adults (N = 451, ages 17-28 years) first completed the original Thinking About Life Experiences (TALE) Questionnaire. They subsequently received three TALE items that represented memory functions and attempted to recall a specific instance of memory recall for each item. Confirmatory factor analyses on the TALE showed that the three functions were replicated in the current sample. However, Japanese participants reported lower levels of all three functions than American participants in a previous study. We also explored whether there was an effect of gender in this Japanese sample. Women reported higher levels of the self-continuity and social-bonding functions than men. Finally, participants recalled more specific instances of memory recall for the TALE items that had received higher ratings on the TALE, suggesting that the findings on the first measure were supported by the second measure. Results are discussed in relation to the functional approach to autobiographical memory in a cross-cultural context.

Reduced Hippocampal Functional Connectivity During Episodic Memory Retrieval in Autism

PubMed Central

Cooper, Rose A.; Richter, Franziska R.; Bays, Paul M.; Plaisted-Grant, Kate C.; Baron-Cohen, Simon

2017-01-01

Abstract Increasing recent research has sought to understand the recollection impairments experienced by individuals with autism spectrum disorder (ASD). Here, we tested whether these memory deficits reflect a reduction in the probability of retrieval success or in the precision of memory representations. We also used functional magnetic resonance imaging (fMRI) to study the neural mechanisms underlying memory encoding and retrieval in ASD, focusing particularly on the functional connectivity of core episodic memory networks. Adults with ASD and typical control participants completed a memory task that involved studying visual displays and subsequently using a continuous dial to recreate their appearance. The ASD group exhibited reduced retrieval success, but there was no evidence of a difference in retrieval precision. fMRI data revealed similar patterns of brain activity and functional connectivity during memory encoding in the 2 groups, though encoding-related lateral frontal activity predicted subsequent retrieval success only in the control group. During memory retrieval, the ASD group exhibited attenuated lateral frontal activity and substantially reduced hippocampal connectivity, particularly between hippocampus and regions of the fronto-parietal control network. These findings demonstrate notable differences in brain function during episodic memory retrieval in ASD and highlight the importance of functional connectivity to understanding recollection-related retrieval deficits in this population. PMID:28057726

Aerobic exercise increases hippocampal volume and improves memory in multiple sclerosis: preliminary findings.

PubMed

Leavitt, V M; Cirnigliaro, C; Cohen, A; Farag, A; Brooks, M; Wecht, J M; Wylie, G R; Chiaravalloti, N D; DeLuca, J; Sumowski, J F

2014-01-01

Multiple sclerosis leads to prominent hippocampal atrophy, which is linked to memory deficits. Indeed, 50% of multiple sclerosis patients suffer memory impairment, with negative consequences for quality of life. There are currently no effective memory treatments for multiple sclerosis either pharmacological or behavioral. Aerobic exercise improves memory and promotes hippocampal neurogenesis in nonhuman animals. Here, we investigate the benefits of aerobic exercise in memory-impaired multiple sclerosis patients. Pilot data were collected from two ambulatory, memory-impaired multiple sclerosis participants randomized to non-aerobic (stretching) and aerobic (stationary cycling) conditions. The following baseline/follow-up measurements were taken: high-resolution MRI (neuroanatomical volumes), fMRI (functional connectivity), and memory assessment. Intervention was 30-minute sessions 3 times per week for 3 months. Aerobic exercise resulted in 16.5% increase in hippocampal volume and 53.7% increase in memory, as well as increased hippocampal resting-state functional connectivity. Improvements were specific, with no comparable changes in overall cerebral gray matter (+2.4%), non-hippocampal deep gray matter structures (thalamus, caudate: -4.0%), or in non-memory cognitive functioning (executive functions, processing speed, working memory: changes ranged from -11% to +4%). Non-aerobic exercise resulted in relatively no change in hippocampal volume (2.8%) or memory (0.0%), and no changes in hippocampal functional connectivity. This is the first evidence for aerobic exercise to increase hippocampal volume and connectivity and improve memory in multiple sclerosis. Aerobic exercise represents a cost-effective, widely available, natural, and self-administered treatment with no adverse side effects that may be the first effective memory treatment for multiple sclerosis patients.

Concurrent Tumor Segmentation and Registration with Uncertainty-based Sparse non-Uniform Graphs

PubMed Central

Parisot, Sarah; Wells, William; Chemouny, Stéphane; Duffau, Hugues; Paragios, Nikos

2014-01-01

In this paper, we present a graph-based concurrent brain tumor segmentation and atlas to diseased patient registration framework. Both segmentation and registration problems are modeled using a unified pairwise discrete Markov Random Field model on a sparse grid superimposed to the image domain. Segmentation is addressed based on pattern classification techniques, while registration is performed by maximizing the similarity between volumes and is modular with respect to the matching criterion. The two problems are coupled by relaxing the registration term in the tumor area, corresponding to areas of high classification score and high dissimilarity between volumes. In order to overcome the main shortcomings of discrete approaches regarding appropriate sampling of the solution space as well as important memory requirements, content driven samplings of the discrete displacement set and the sparse grid are considered, based on the local segmentation and registration uncertainties recovered by the min marginal energies. State of the art results on a substantial low-grade glioma database demonstrate the potential of our method, while our proposed approach shows maintained performance and strongly reduced complexity of the model. PMID:24717540

Increased Hippocampus–Medial Prefrontal Cortex Resting-State Functional Connectivity and Memory Function after Tai Chi Chuan Practice in Elder Adults

PubMed Central

Tao, Jing; Liu, Jiao; Egorova, Natalia; Chen, Xiangli; Sun, Sharon; Xue, Xiehua; Huang, Jia; Zheng, Guohua; Wang, Qin; Chen, Lidian; Kong, Jian

2016-01-01

Previous studies provide evidence that aging is associated with the decline of memory function and alterations in the hippocampal (HPC) function, including functional connectivity to the medial prefrontal cortex (mPFC). In this study, we investigated if longitudinal (12-week) Tai Chi Chuan and Baduanjin practice can improve memory function and modulate HPC resting-state functional connectivity (rs-FC). Memory function measurements and resting-state functional magnetic resonance imaging (rs-fMRI) were applied at the beginning and the end of the experiment. The results showed that (1) the memory quotient (MQ) measured by the Wechsler Memory Scale-Chinese Revision significantly increased after Tai Chi Chuan and Baduanjin practice as compared with the control group, and no significant difference was observed in MQ between the Tai Chi Chuan and Baduanjin groups; (2) rs-FC between the bilateral hippocampus and mPFC significantly increased in the Tai Chi Chuan group compared to the control group (also in the Baduanjin group compared to the control group, albeit at a lower threshold), and no significant difference between the Tai Chi Chuan and Baduanjin groups was observed; (3) rs-FC increases between the bilateral hippocampus and mPFC were significantly associated with corresponding memory function improvement across all subjects. Similar results were observed using the left or right hippocampus as seeds. Our results suggest that both Tai Chi Chuan and Baduanjin may be effective exercises to prevent memory decline during aging. PMID:26909038

Increased Hippocampus-Medial Prefrontal Cortex Resting-State Functional Connectivity and Memory Function after Tai Chi Chuan Practice in Elder Adults.

PubMed

Tao, Jing; Liu, Jiao; Egorova, Natalia; Chen, Xiangli; Sun, Sharon; Xue, Xiehua; Huang, Jia; Zheng, Guohua; Wang, Qin; Chen, Lidian; Kong, Jian

2016-01-01

Previous studies provide evidence that aging is associated with the decline of memory function and alterations in the hippocampal (HPC) function, including functional connectivity to the medial prefrontal cortex (mPFC). In this study, we investigated if longitudinal (12-week) Tai Chi Chuan and Baduanjin practice can improve memory function and modulate HPC resting-state functional connectivity (rs-FC). Memory function measurements and resting-state functional magnetic resonance imaging (rs-fMRI) were applied at the beginning and the end of the experiment. The results showed that (1) the memory quotient (MQ) measured by the Wechsler Memory Scale-Chinese Revision significantly increased after Tai Chi Chuan and Baduanjin practice as compared with the control group, and no significant difference was observed in MQ between the Tai Chi Chuan and Baduanjin groups; (2) rs-FC between the bilateral hippocampus and mPFC significantly increased in the Tai Chi Chuan group compared to the control group (also in the Baduanjin group compared to the control group, albeit at a lower threshold), and no significant difference between the Tai Chi Chuan and Baduanjin groups was observed; (3) rs-FC increases between the bilateral hippocampus and mPFC were significantly associated with corresponding memory function improvement across all subjects. Similar results were observed using the left or right hippocampus as seeds. Our results suggest that both Tai Chi Chuan and Baduanjin may be effective exercises to prevent memory decline during aging.

Hybrid Discrete-Continuous Markov Decision Processes

NASA Technical Reports Server (NTRS)

Feng, Zhengzhu; Dearden, Richard; Meuleau, Nicholas; Washington, Rich

2003-01-01

This paper proposes a Markov decision process (MDP) model that features both discrete and continuous state variables. We extend previous work by Boyan and Littman on the mono-dimensional time-dependent MDP to multiple dimensions. We present the principle of lazy discretization, and piecewise constant and linear approximations of the model. Having to deal with several continuous dimensions raises several new problems that require new solutions. In the (piecewise) linear case, we use techniques from partially- observable MDPs (POMDPS) to represent value functions as sets of linear functions attached to different partitions of the state space.

Role of serial order in the impact of talker variability on short-term memory: testing a perceptual organization-based account.

PubMed

Hughes, Robert W; Marsh, John E; Jones, Dylan M

2011-11-01

In two experiments, we examined the impact of the degree of match between sequential auditory perceptual organization processes and the demands of a short-term memory task (memory for order vs. item information). When a spoken sequence of digits was presented so as to promote its perceptual partitioning into two distinct streams by conveying it in alternating female (F) and male (M) voices (FMFMFMFM)--thereby disturbing the perception of true temporal order--recall of item order was greatly impaired (as compared to recall of item identity). Moreover, an order error type consistent with the formation of voice-based streams was committed more quickly in the alternating-voice condition (Exp. 1). In contrast, when the perceptual organization of the sequence mapped well onto an optimal two-group serial rehearsal strategy--by presenting the two voices in discrete clusters (FFFFMMMM)--order, but not item, recall was enhanced (Exp. 2). The results are consistent with the view that the degree of compatibility between perceptual and deliberate sequencing processes is a key determinant of serial short-term memory performance. Alternative accounts of talker variability effects in short-term memory, based on the concept of a dedicated phonological short-term store and a capacity-limited focus of attention, are also reviewed.

Face format at encoding affects the other-race effect in face memory.

PubMed

Zhao, Mintao; Hayward, William G; Bülthoff, Isabelle

2014-08-07

Memory of own-race faces is generally better than memory of other-races faces. This other-race effect (ORE) in face memory has been attributed to differences in contact, holistic processing, and motivation to individuate faces. Since most studies demonstrate the ORE with participants learning and recognizing static, single-view faces, it remains unclear whether the ORE can be generalized to different face learning conditions. Using an old/new recognition task, we tested whether face format at encoding modulates the ORE. The results showed a significant ORE when participants learned static, single-view faces (Experiment 1). In contrast, the ORE disappeared when participants learned rigidly moving faces (Experiment 2). Moreover, learning faces displayed from four discrete views produced the same results as learning rigidly moving faces (Experiment 3). Contact with other-race faces was correlated with the magnitude of the ORE. Nonetheless, the absence of the ORE in Experiments 2 and 3 cannot be readily explained by either more frequent contact with other-race faces or stronger motivation to individuate them. These results demonstrate that the ORE is sensitive to face format at encoding, supporting the hypothesis that relative involvement of holistic and featural processing at encoding mediates the ORE observed in face memory. © 2014 ARVO.

The discrete adjoint method for parameter identification in multibody system dynamics.

PubMed

Lauß, Thomas; Oberpeilsteiner, Stefan; Steiner, Wolfgang; Nachbagauer, Karin

2018-01-01

The adjoint method is an elegant approach for the computation of the gradient of a cost function to identify a set of parameters. An additional set of differential equations has to be solved to compute the adjoint variables, which are further used for the gradient computation. However, the accuracy of the numerical solution of the adjoint differential equation has a great impact on the gradient. Hence, an alternative approach is the discrete adjoint method , where the adjoint differential equations are replaced by algebraic equations. Therefore, a finite difference scheme is constructed for the adjoint system directly from the numerical time integration method. The method provides the exact gradient of the discretized cost function subjected to the discretized equations of motion.

Height growth of solutions and a discrete Painlevé equation

NASA Astrophysics Data System (ADS)

Al-Ghassani, A.; Halburd, R. G.

2015-07-01

Consider the discrete equation where the right side is of degree two in yn and where the coefficients an, bn and cn are rational functions of n with rational coefficients. Suppose that there is a solution such that for all sufficiently large n, y_n\\in{Q} and the height of yn dominates the height of the coefficient functions an, bn and cn. We show that if the logarithmic height of yn grows no faster than a power of n then either the equation is a well known discrete Painlevé equation dPII or its autonomous version or yn is also an admissible solution of a discrete Riccati equation. This provides further evidence that slow height growth is a good detector of integrability.

Essays in financial economics and econometrics

NASA Astrophysics Data System (ADS)

La Spada, Gabriele

Chapter 1 (my job market paper) asks the following question: Do asset managers reach for yield because of competitive pressures in a low rate environment? I propose a tournament model of money market funds (MMFs) to study this issue. I show that funds with different costs of default respond differently to changes in interest rates, and that it is important to distinguish the role of risk-free rates from that of risk premia. An increase in the risk premium leads funds with lower default costs to increase risk-taking, while funds with higher default costs reduce risk-taking. Without changes in the premium, low risk-free rates reduce risk-taking. My empirical analysis shows that these predictions are consistent with the risk-taking of MMFs during the 2006--2008 period. Chapter 2, co-authored with Fabrizio Lillo and published in Studies in Nonlinear Dynamics and Econometrics (2014), studies the effect of round-off error (or discretization) on stationary Gaussian long-memory process. For large lags, the autocovariance is rescaled by a factor smaller than one, and we compute this factor exactly. Hence, the discretized process has the same Hurst exponent as the underlying one. We show that in presence of round-off error, two common estimators of the Hurst exponent, the local Whittle (LW) estimator and the detrended fluctuation analysis (DFA), are severely negatively biased in finite samples. We derive conditions for consistency and asymptotic normality of the LW estimator applied to discretized processes and compute the asymptotic properties of the DFA for generic long-memory processes that encompass discretized processes. Chapter 3, co-authored with Fabrizio Lillo, studies the effect of round-off error on integrated Gaussian processes with possibly correlated increments. We derive the variance and kurtosis of the realized increment process in the limit of both "small" and "large" round-off errors, and its autocovariance for large lags. We propose novel estimators for the variance and lag-one autocorrelation of the underlying, unobserved increment process. We also show that for fractionally integrated processes, the realized increments have the same Hurst exponent as the underlying ones, but the LW estimator applied to the realized series is severely negatively biased in medium-sized samples.

Bidirectional Frontoparietal Oscillatory Systems Support Working Memory.

PubMed

Johnson, Elizabeth L; Dewar, Callum D; Solbakk, Anne-Kristin; Endestad, Tor; Meling, Torstein R; Knight, Robert T

2017-06-19

The ability to represent and select information in working memory provides the neurobiological infrastructure for human cognition. For 80 years, dominant views of working memory have focused on the key role of prefrontal cortex (PFC) [1-8]. However, more recent work has implicated posterior cortical regions [9-12], suggesting that PFC engagement during working memory is dependent on the degree of executive demand. We provide evidence from neurological patients with discrete PFC damage that challenges the dominant models attributing working memory to PFC-dependent systems. We show that neural oscillations, which provide a mechanism for PFC to communicate with posterior cortical regions [13], independently subserve communications both to and from PFC-uncovering parallel oscillatory mechanisms for working memory. Fourteen PFC patients and 20 healthy, age-matched controls performed a working memory task where they encoded, maintained, and actively processed information about pairs of common shapes. In controls, the electroencephalogram (EEG) exhibited oscillatory activity in the low-theta range over PFC and directional connectivity from PFC to parieto-occipital regions commensurate with executive processing demands. Concurrent alpha-beta oscillations were observed over parieto-occipital regions, with directional connectivity from parieto-occipital regions to PFC, regardless of processing demands. Accuracy, PFC low-theta activity, and PFC → parieto-occipital connectivity were attenuated in patients, revealing a PFC-independent, alpha-beta system. The PFC patients still demonstrated task proficiency, which indicates that the posterior alpha-beta system provides sufficient resources for working memory. Taken together, our findings reveal neurologically dissociable PFC and parieto-occipital systems and suggest that parallel, bidirectional oscillatory systems form the basis of working memory. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Parvalbumin interneurons constrain the size of the lateral amygdala engram.

PubMed

Morrison, Dano J; Rashid, Asim J; Yiu, Adelaide P; Yan, Chen; Frankland, Paul W; Josselyn, Sheena A

2016-11-01

Memories are thought to be represented by discrete physiological changes in the brain, collectively referred to as an engram, that allow patterns of activity present during learning to be reactivated in the future. During the formation of a conditioned fear memory, a subset of principal (excitatory) neurons in the lateral amygdala (LA) are allocated to a neuronal ensemble that encodes an association between an initially neutral stimulus and a threatening aversive stimulus. Previous experimental and computational work suggests that this subset consists of only a small proportion of all LA neurons, and that this proportion remains constant across different memories. Here we examine the mechanisms that contribute to the stability of the size of the LA component of an engram supporting a fear memory. Visualizing expression of the activity-dependent gene Arc following memory retrieval to identify neurons allocated to an engram, we first show that the overall size of the LA engram remains constant across conditions of different memory strength. That is, the strength of a memory was not correlated with the number of LA neurons allocated to the engram supporting that memory. We then examine potential mechanisms constraining the size of the LA engram by expressing inhibitory DREADDS (designer receptors exclusively activated by designer drugs) in parvalbumin-positive (PV + ) interneurons of the amygdala. We find that silencing PV + neurons during conditioning increases the size of the engram, especially in the dorsal subnucleus of the LA. These results confirm predictions from modeling studies regarding the role of inhibition in shaping the size of neuronal memory ensembles and provide additional support for the idea that neurons in the LA are sparsely allocated to the engram based on relative neuronal excitability. Copyright © 2016 Elsevier Inc. All rights reserved.

The Role of Sex in Memory Function: Considerations and Recommendations in the Context of Exercise.

PubMed

Loprinzi, Paul D; Frith, Emily

2018-05-31

There is evidence to suggest that biological sex plays a critical role in memory function, with sex differentially influencing memory type. In this review, we detail the current evidence evaluating sex-specific effects on various memory types. We also discuss potential mechanisms that explain these sex-specific effects, which include sex differences in neuroanatomy, neurochemical differences, biological differences, and cognitive and affect-related differences. Central to this review, we also highlight that, despite the established sex differences in memory, there is little work directly comparing whether males and females have a differential exercise-induced effect on memory function. As discussed herein, such a differential effect is plausible given the clear sex-specific effects on memory, exercise response, and molecular mediators of memory. We emphasize that future work should be carefully powered to detect sex differences. Future research should also examine these potential exercise-related sex-specific effects for various memory types and exercise intensities and modalities. This will help enhance our understanding of whether sex indeed moderates the effects of exercise and memory function, and as such, will improve our understanding of whether sex-specific, memory-enhancing interventions should be developed, implemented, and evaluated.

Autonomous learning by simple dynamical systems with a discrete-time formulation

NASA Astrophysics Data System (ADS)

Bilen, Agustín M.; Kaluza, Pablo

2017-05-01

We present a discrete-time formulation for the autonomous learning conjecture. The main feature of this formulation is the possibility to apply the autonomous learning scheme to systems in which the errors with respect to target functions are not well-defined for all times. This restriction for the evaluation of functionality is a typical feature in systems that need a finite time interval to process a unit piece of information. We illustrate its application on an artificial neural network with feed-forward architecture for classification and a phase oscillator system with synchronization properties. The main characteristics of the discrete-time formulation are shown by constructing these systems with predefined functions.

Bifurcations in a discrete time model composed of Beverton-Holt function and Ricker function.

PubMed

Shang, Jin; Li, Bingtuan; Barnard, Michael R

2015-05-01

We provide rigorous analysis for a discrete-time model composed of the Ricker function and Beverton-Holt function. This model was proposed by Lewis and Li [Bull. Math. Biol. 74 (2012) 2383-2402] in the study of a population in which reproduction occurs at a discrete instant of time whereas death and competition take place continuously during the season. We show analytically that there exists a period-doubling bifurcation curve in the model. The bifurcation curve divides the parameter space into the region of stability and the region of instability. We demonstrate through numerical bifurcation diagrams that the regions of periodic cycles are intermixed with the regions of chaos. We also study the global stability of the model. Copyright © 2015 Elsevier Inc. All rights reserved.

The role of the thalamus and hippocampus in episodic memory performance in patients with multiple sclerosis.

PubMed

Koenig, Katherine A; Rao, Stephen M; Lowe, Mark J; Lin, Jian; Sakaie, Ken E; Stone, Lael; Bermel, Robert A; Trapp, Bruce D; Phillips, Micheal D

2018-03-01

Episodic memory loss is one of the most common cognitive symptoms in patients with multiple sclerosis (MS), but the pathophysiology of this symptom remains unclear. Both the hippocampus and thalamus have been implicated in episodic memory and show regional atrophy in patients with MS. In this work, we used functional magnetic resonance imaging (fMRI) during a verbal episodic memory task, lesion load, and volumetric measures of the hippocampus and thalamus to assess the relative contributions to verbal and visual-spatial episodic memory. Functional activation, lesion load, and volumetric measures from 32 patients with MS and 16 healthy controls were used in a predictive analysis of episodic memory function. After adjusting for disease duration, immediate recall performance on a visual-spatial episodic memory task was significantly predicted by hippocampal volume ( p < 0.003). Delayed recall on the same task was significantly predicted by volume of the left thalamus ( p < 0.003). For both memory measures, functional activation of the thalamus during encoding was more predictive than that of volume measures ( p < 0.002). Our results suggest that functional activation may be useful as a predictive measure of episodic memory loss in patients with MS.

Autobiographical memory functions of nostalgia in comparison to rumination and counterfactual thinking: similarity and uniqueness.

PubMed

Cheung, Wing-Yee; Wildschut, Tim; Sedikides, Constantine

2018-02-01

We compared and contrasted nostalgia with rumination and counterfactual thinking in terms of their autobiographical memory functions. Specifically, we assessed individual differences in nostalgia, rumination, and counterfactual thinking, which we then linked to self-reported functions or uses of autobiographical memory (Self-Regard, Boredom Reduction, Death Preparation, Intimacy Maintenance, Conversation, Teach/Inform, and Bitterness Revival). We tested which memory functions are shared and which are uniquely linked to nostalgia. The commonality among nostalgia, rumination, and counterfactual thinking resides in their shared positive associations with all memory functions: individuals who evinced a stronger propensity towards past-oriented thought (as manifested in nostalgia, rumination, and counterfactual thinking) reported greater overall recruitment of memories in the service of present functioning. The uniqueness of nostalgia resides in its comparatively strong positive associations with Intimacy Maintenance, Teach/Inform, and Self-Regard and weak association with Bitterness Revival. In all, nostalgia possesses a more positive functional signature than do rumination and counterfactual thinking.

Memory-focused interventions for people with cognitive disorders: A systematic review and meta-analysis of randomized controlled studies.

PubMed

Yang, Hui-Ling; Chan, Pi-Tuan; Chang, Pi-Chen; Chiu, Huei-Ling; Sheen Hsiao, Shu-Tai; Chu, Hsin; Chou, Kuei-Ru

2018-02-01

A better understanding of people with cognitive disorders improves performance on memory tasks through memory-focused interventions are needed. The purpose of this study was to assess the effect of memoryfocused interventions on cognitive disorders through a meta-analysis. Systematic review and meta-analysis. The online electronic databases PubMed, the Cochrane Library, Ovid-Medline, CINHAL, PsycINFO, Ageline, and Embase (up to May 2017) were used in this study. No language restriction was applied to the search. Objective memory (learning and memory function, immediate recall, delayed recall, and recognition) was the primary indicator and subjective memory performance, global cognitive function, and depression were the secondary indicators. The Hedges' g of change, subgroup analyses, and meta-regression were analyzed on the basis of the characteristics of people with cognitive disorders. A total of 27 studies (2177 participants, mean age=75.80) reporting RCTs were included in the meta-analysis. The results indicated a medium-to-large effect of memory-focused interventions on learning and memory function (Hedges' g=0.62) and subjective memory performance (Hedges' g=0.67), a small-to-medium effect on delayed recall and depression, and a small effect on immediate recall and global cognitive function (all p<0.05) compared with the control. Subgroup analysis and meta-regression indicated that the effects on learning and memory function were more profound in the format of memory training, individual training, shorter treatment duration, and more than eight treatment sessions, and the effect size indicated the MMSE score was the most crucial indicator (β=-0.06, p=0.04). This is first comprehensive meta-analysis of special memory domains in people with cognitive disorders. The results revealed that memory-focused interventions effectively improved memory-related performance in people with cognitive disorders. An appropriately designed intervention can effectively improve memory function, reduce disability progression, and improve mood state in people with cognitive disorders. Additional randomized controlled trials including measures of recognition, global cognitive function, and depression should be conducted and analyzed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Intelligence or years of education: which is better correlated with memory function in normal elderly Japanese subjects?

PubMed

Murayama, Norio; Iseki, Eizo; Tagaya, Hirokuni; Ota, Kazumi; Kasanuki, Koji; Fujishiro, Hiroshige; Arai, Heii; Sato, Kiyoshi

2013-03-01

We compared differences in intelligence and memory function between normal elderly Japanese subjects with more years of education and those with fewer years of education. We also investigated clinical and neuropsychological factors that are strongly correlated with memory function. There were 118 normal elderly subjects who underwent the Mini-Mental State Examination, Wechsler Adult Intelligence Scale, 3rd edition (WAIS-III), and Wechsler Memory Scale Revised. Subjects with at least 13 years of education were categorized as the H group, and those with 12 years of education or less were categorized as the L group. Age and Mini-Mental State Examination scores were not significantly different between the two groups. On the WAIS-III, there were significant differences between the two groups in Verbal IQ and Full Scale IQ. On the Wechsler Memory Scale Revised, there were significant differences between the two groups in Visual Memory, General Memory, and Delayed Recall. Correlation coefficients between memory function and the other factors demonstrated significant but weak correlations between years of education and General Memory (R = 0.22) and between years of education and Delayed Recall (R = 0.20). Strong correlations were found between Verbal IQ and Verbal Memory (R = 0.45), between Verbal IQ and General Memory (R = 0.49), between Full Scale IQ and General Memory (R = 0.50) and between Full Scale IQ and Delayed Recall (R = 0.48). In normal elderly Japanese subjects, years of education weakly correlated with memory function while Verbal IQ, Full Scale IQ and Verbal Comprehension on WAIS-III had stronger correlations with memory function. Verbal IQ and Verbal Comprehension on WAIS-III were found to be insusceptible to the cognitive decline characteristic of Alzheimer's disease or amnestic mild cognitive impairment. Therefore, verbal intelligence, as measured by Verbal IQ and Verbal Comprehension, may be the most useful factor for inferring premorbid memory function in Alzheimer's disease or amnestic mild cognitive impairment patients. © 2013 The Authors. Psychogeriatrics © 2013 Japanese Psychogeriatric Society.

A simplified computational memory model from information processing.

PubMed

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

2016-11-23

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

Functional brain imaging in 14 patients with dissociative amnesia reveals right inferolateral prefrontal hypometabolism.

PubMed

Brand, Matthias; Eggers, Carsten; Reinhold, Nadine; Fujiwara, Esther; Kessler, Josef; Heiss, Wolf-Dieter; Markowitsch, Hans J

2009-10-30

Dissociative amnesia is a condition usually characterized by severely impaired retrograde memory functioning in the absence of structural brain damage. Recent case studies nevertheless found functional brain changes in patients suffering from autobiographical-episodic memory loss in the cause of dissociative amnesia. Functional changes were demonstrated in both resting state and memory retrieval conditions. In addition, some but not all cases also showed other neuropsychological impairments beyond retrograde memory deficits. However, there is no group study available that examined potential functional brain abnormalities and accompanying neuropsychological deteriorations in larger samples of patients with dissociative retrograde amnesia. We report functional imaging and neuropsychological data acquired in 14 patients with dissociative amnesia following stressful or traumatic events. All patients suffered from autobiographical memory loss. In addition, approximately half of the patients had deficits in anterograde memory and executive functioning. Accompanying functional brain changes were measured by [18F]fluorodeoxyglucose positron emission tomography (FDG-PET). Regional glucose utilization of the patients was compared with that of 19 healthy subjects, matched for age and gender. We found significantly decreased glucose utilization in the right inferolateral prefrontal cortex in the patients. Hypometabolism in this brain region, known to be involved in retrieval of autobiographical memories and self-referential processing, may be a functional brain correlate of dissociative amnesia.

Nonautonomous discrete bright soliton solutions and interaction management for the Ablowitz-Ladik equation.

PubMed

Yu, Fajun

2015-03-01

We present the nonautonomous discrete bright soliton solutions and their interactions in the discrete Ablowitz-Ladik (DAL) equation with variable coefficients, which possesses complicated wave propagation in time and differs from the usual bright soliton waves. The differential-difference similarity transformation allows us to relate the discrete bright soliton solutions of the inhomogeneous DAL equation to the solutions of the homogeneous DAL equation. Propagation and interaction behaviors of the nonautonomous discrete solitons are analyzed through the one- and two-soliton solutions. We study the discrete snaking behaviors, parabolic behaviors, and interaction behaviors of the discrete solitons. In addition, the interaction management with free functions and dynamic behaviors of these solutions is investigated analytically, which have certain applications in electrical and optical systems.

(Putative) Sex differences in neuroimmune modulation of memory

PubMed Central

Tronson, Natalie C.; Collette, Katie M.

2016-01-01

The neuroimmune system is significantly sexually dimorphic, with sex differences evident in the number and activation states of microglia, in the activation of astrocytes, and in cytokine release and function. Neuroimmune cells and signaling are now recognized as critical for many neural functions throughout the lifespan, including synaptic plasticity and memory function. Here we address the question of how cytokines, astrocytes, and microglia contribute to memory, and specifically how neuroimmune modulation of memory differentially affects males and females. Understanding sex differences in both normal memory processes and dysregulation of memory in psychiatric and neurological disorders is critical for developing treatment and preventive strategies for memory disorders that are effective for both men and women. PMID:27870428

Working Memory in Children With Neurocognitive Effects From Sickle Cell Disease: Contributions of the Central Executive and Processing Speed

PubMed Central

Smith, Kelsey E.; Schatz, Jeffrey

2017-01-01

Children with sickle cell disease (SCD) are at risk for working memory deficits due to multiple disease processes. We assessed working memory abilities and related functions in 32 school-age children with SCD and 85 matched comparison children using Baddeley’s working memory model as a framework. Children with SCD performed worse than controls for working memory, central executive function, and processing/rehearsal speed. Central executive function was found to mediate the relationship between SCD status and working memory, but processing speed did not. Cognitive remediation strategies that focus on central executive processes may be important for remediating working memory deficits in SCD. PMID:27759435

Effector functions of memory CTLs can be affected by signals received during reactivation.

PubMed

Lv, Yingjun; Mattson, Elliot; Bhadurihauck, Anjuli; Garcia, Karla; Li, Lei; Xiao, Zhengguo

2017-08-01

Memory cytotoxic T lymphocytes (CTLs) are able to provide protections to the host against repeated insults from intracellular pathogens. However, it has not been completely understood how the effector functions of memory CTLs are induced upon antigen challenge, which is directly related to the efficacy of their protection. Third signal cytokines, such as IL-12 and type I interferon, have been suggested to be involved in the protective function of memory CTLs, but direct evidence is warranted. In this report, we found that memory CTLs need to be reactivated to exert effector functions. Infusion of a large population of quiescent memory CTLs did not lead to cancer control in tumor-bearing mice, whereas infusion of a reactivated memory CTL population did. This reactivation of memory CTLs requires cytokines such as IL-12 in addition to antigen but was less dependent upon costimulation and IL-2 compared to naive CTLs. Memory CTLs responded more quickly and with greater strength than their naive counterparts upon stimulation, which is associated with higher upregulation of important transcription factors such as T-bet and phosphorylated STAT4. In addition, memory CTLs underwent less expansion than naive CTLs upon pathogen challenge. In conclusion, effector functions of established memory CTLs may be affected by certain cytokines such as IL-12 and type I IFN. Thus, a pathogen's ability to induce cytokines could contribute to the efficacy of protection of an established memory CTL population.

Serotonin is critical for rewarded olfactory short-term memory in Drosophila.

PubMed

Sitaraman, Divya; LaFerriere, Holly; Birman, Serge; Zars, Troy

2012-06-01

The biogenic amines dopamine, octopamine, and serotonin are critical in establishing normal memories. A common view for the amines in insect memory performance has emerged in which dopamine and octopamine are largely responsible for aversive and appetitive memories. Examination of the function of serotonin begins to challenge the notion of one amine type per memory because altering serotonin function also reduces aversive olfactory memory and place memory levels. Could the function of serotonin be restricted to the aversive domain, suggesting a more specific dopamine/serotonin system interaction? The function of the serotonergic system in appetitive olfactory memory was examined. By targeting the tetanus toxin light chain (TNT) and the human inwardly rectifying potassium channel (Kir2.1) to the serotonin neurons with two different GAL4 driver combinations, the serotonergic system was inhibited. Additional use of the GAL80(ts1) system to control expression of transgenes to the adult stage of the life cycle addressed a potential developmental role of serotonin in appetitive memory. Reduction in appetitive olfactory memory performance in flies with these transgenic manipulations, without altering control behaviors, showed that the serotonergic system is also required for normal appetitive memory. Thus, serotonin appears to have a more general role in Drosophila memory, and implies an interaction with both the dopaminergic and octopaminergic systems.

Relation of Physical Activity to Memory Functioning in Older Adults: The Memory Workout Program.

ERIC Educational Resources Information Center

Rebok, George W.; Plude, Dana J.

2001-01-01

The Memory Workout, a CD-ROM program designed to help older adults increase changes in physical and cognitive activity influencing memory, was tested with 24 subjects. Results revealed a significant relationship between exercise time, exercise efficacy, and cognitive function, as well as interest in improving memory and physical activity.…

The Regulation of Cytokine Networks in Hippocampal CA1 Differentiates Extinction from Those Required for the Maintenance of Contextual Fear Memory after Recall

PubMed Central

Scholz, Birger; Doidge, Amie N.; Barnes, Philip; Hall, Jeremy; Wilkinson, Lawrence S.; Thomas, Kerrie L.

2016-01-01

We investigated the distinctiveness of gene regulatory networks in CA1 associated with the extinction of contextual fear memory (CFM) after recall using Affymetrix GeneChip Rat Genome 230 2.0 Arrays. These data were compared to previously published retrieval and reconsolidation-attributed, and consolidation datasets. A stringent dual normalization and pareto-scaled orthogonal partial least-square discriminant multivariate analysis together with a jack-knifing-based cross-validation approach was used on all datasets to reduce false positives. Consolidation, retrieval and extinction were correlated with distinct patterns of gene expression 2 hours later. Extinction-related gene expression was most distinct from the profile accompanying consolidation. A highly specific feature was the discrete regulation of neuroimmunological gene expression associated with retrieval and extinction. Immunity–associated genes of the tyrosine kinase receptor TGFβ and PDGF, and TNF families’ characterized extinction. Cytokines and proinflammatory interleukins of the IL-1 and IL-6 families were enriched with the no-extinction retrieval condition. We used comparative genomics to predict transcription factor binding sites in proximal promoter regions of the retrieval-regulated genes. Retrieval that does not lead to extinction was associated with NF-κB-mediated gene expression. We confirmed differential NF-κBp65 expression, and activity in all of a representative sample of our candidate genes in the no-extinction condition. The differential regulation of cytokine networks after the acquisition and retrieval of CFM identifies the important contribution that neuroimmune signalling plays in normal hippocampal function. Further, targeting cytokine signalling upon retrieval offers a therapeutic strategy to promote extinction mechanisms in human disorders characterised by dysregulation of associative memory. PMID:27224427

Towards representation of a perceptual color manifold using associative memory for color constancy.

PubMed

Seow, Ming-Jung; Asari, Vijayan K

2009-01-01

In this paper, we propose the concept of a manifold of color perception through empirical observation that the center-surround properties of images in a perceptually similar environment define a manifold in the high dimensional space. Such a manifold representation can be learned using a novel recurrent neural network based learning algorithm. Unlike the conventional recurrent neural network model in which the memory is stored in an attractive fixed point at discrete locations in the state space, the dynamics of the proposed learning algorithm represent memory as a nonlinear line of attraction. The region of convergence around the nonlinear line is defined by the statistical characteristics of the training data. This learned manifold can then be used as a basis for color correction of the images having different color perception to the learned color perception. Experimental results show that the proposed recurrent neural network learning algorithm is capable of color balance the lighting variations in images captured in different environments successfully.

Adaptive Fading Memory H∞ Filter Design for Compensation of Delayed Components in Self Powered Flux Detectors

NASA Astrophysics Data System (ADS)

Tamboli, Prakash Kumar; Duttagupta, Siddhartha P.; Roy, Kallol

2015-08-01

The paper deals with dynamic compensation of delayed Self Powered Flux Detectors (SPFDs) using discrete time H∞ filtering method for improving the response of SPFDs with significant delayed components such as Platinum and Vanadium SPFD. We also present a comparative study between the Linear Matrix Inequality (LMI) based H∞ filtering and Algebraic Riccati Equation (ARE) based Kalman filtering methods with respect to their delay compensation capabilities. Finally an improved recursive H∞ filter based on the adaptive fading memory technique is proposed which provides an improved performance over existing methods. The existing delay compensation algorithms do not account for the rate of change in the signal for determining the filter gain and therefore add significant noise during the delay compensation process. The proposed adaptive fading memory H∞ filter minimizes the overall noise very effectively at the same time keeps the response time at minimum values. The recursive algorithm is easy to implement in real time as compared to the LMI (or ARE) based solutions.

Non-thermalization in trapped atomic ion spin chains

NASA Astrophysics Data System (ADS)

Hess, P. W.; Becker, P.; Kaplan, H. B.; Kyprianidis, A.; Lee, A. C.; Neyenhuis, B.; Pagano, G.; Richerme, P.; Senko, C.; Smith, J.; Tan, W. L.; Zhang, J.; Monroe, C.

2017-10-01

Linear arrays of trapped and laser-cooled atomic ions are a versatile platform for studying strongly interacting many-body quantum systems. Effective spins are encoded in long-lived electronic levels of each ion and made to interact through laser-mediated optical dipole forces. The advantages of experiments with cold trapped ions, including high spatio-temporal resolution, decoupling from the external environment and control over the system Hamiltonian, are used to measure quantum effects not always accessible in natural condensed matter samples. In this review, we highlight recent work using trapped ions to explore a variety of non-ergodic phenomena in long-range interacting spin models, effects that are heralded by the memory of out-of-equilibrium initial conditions. We observe long-lived memory in static magnetizations for quenched many-body localization and prethermalization, while memory is preserved in the periodic oscillations of a driven discrete time crystal state. This article is part of the themed issue 'Breakdown of ergodicity in quantum systems: from solids to synthetic matter'.

Non-thermalization in trapped atomic ion spin chains.

PubMed

Hess, P W; Becker, P; Kaplan, H B; Kyprianidis, A; Lee, A C; Neyenhuis, B; Pagano, G; Richerme, P; Senko, C; Smith, J; Tan, W L; Zhang, J; Monroe, C

2017-12-13

Linear arrays of trapped and laser-cooled atomic ions are a versatile platform for studying strongly interacting many-body quantum systems. Effective spins are encoded in long-lived electronic levels of each ion and made to interact through laser-mediated optical dipole forces. The advantages of experiments with cold trapped ions, including high spatio-temporal resolution, decoupling from the external environment and control over the system Hamiltonian, are used to measure quantum effects not always accessible in natural condensed matter samples. In this review, we highlight recent work using trapped ions to explore a variety of non-ergodic phenomena in long-range interacting spin models, effects that are heralded by the memory of out-of-equilibrium initial conditions. We observe long-lived memory in static magnetizations for quenched many-body localization and prethermalization, while memory is preserved in the periodic oscillations of a driven discrete time crystal state.This article is part of the themed issue 'Breakdown of ergodicity in quantum systems: from solids to synthetic matter'. © 2017 The Author(s).

Pushing Memory Bandwidth Limitations Through Efficient Implementations of Block-Krylov Space Solvers on GPUs

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

Clark, M. A.; Strelchenko, Alexei; Vaquero, Alejandro

Lattice quantum chromodynamics simulations in nuclear physics have benefited from a tremendous number of algorithmic advances such as multigrid and eigenvector deflation. These improve the time to solution but do not alleviate the intrinsic memory-bandwidth constraints of the matrix-vector operation dominating iterative solvers. Batching this operation for multiple vectors and exploiting cache and register blocking can yield a super-linear speed up. Block-Krylov solvers can naturally take advantage of such batched matrix-vector operations, further reducing the iterations to solution by sharing the Krylov space between solves. However, practical implementations typically suffer from the quadratic scaling in the number of vector-vector operations.more » Using the QUDA library, we present an implementation of a block-CG solver on NVIDIA GPUs which reduces the memory-bandwidth complexity of vector-vector operations from quadratic to linear. We present results for the HISQ discretization, showing a 5x speedup compared to highly-optimized independent Krylov solves on NVIDIA's SaturnV cluster.« less

Distributed state-space generation of discrete-state stochastic models

NASA Technical Reports Server (NTRS)

Ciardo, Gianfranco; Gluckman, Joshua; Nicol, David

1995-01-01

High-level formalisms such as stochastic Petri nets can be used to model complex systems. Analysis of logical and numerical properties of these models of ten requires the generation and storage of the entire underlying state space. This imposes practical limitations on the types of systems which can be modeled. Because of the vast amount of memory consumed, we investigate distributed algorithms for the generation of state space graphs. The distributed construction allows us to take advantage of the combined memory readily available on a network of workstations. The key technical problem is to find effective methods for on-the-fly partitioning, so that the state space is evenly distributed among processors. In this paper we report on the implementation of a distributed state-space generator that may be linked to a number of existing system modeling tools. We discuss partitioning strategies in the context of Petri net models, and report on performance observed on a network of workstations, as well as on a distributed memory multi-computer.

Discovering Event Structure in Continuous Narrative Perception and Memory.

PubMed

Baldassano, Christopher; Chen, Janice; Zadbood, Asieh; Pillow, Jonathan W; Hasson, Uri; Norman, Kenneth A

2017-08-02

During realistic, continuous perception, humans automatically segment experiences into discrete events. Using a novel model of cortical event dynamics, we investigate how cortical structures generate event representations during narrative perception and how these events are stored to and retrieved from memory. Our data-driven approach allows us to detect event boundaries as shifts between stable patterns of brain activity without relying on stimulus annotations and reveals a nested hierarchy from short events in sensory regions to long events in high-order areas (including angular gyrus and posterior medial cortex), which represent abstract, multimodal situation models. High-order event boundaries are coupled to increases in hippocampal activity, which predict pattern reinstatement during later free recall. These areas also show evidence of anticipatory reinstatement as subjects listen to a familiar narrative. Based on these results, we propose that brain activity is naturally structured into nested events, which form the basis of long-term memory representations. Copyright © 2017 Elsevier Inc. All rights reserved.

The importance of individual frequencies of endogenous brain oscillations for auditory cognition - A short review.

PubMed

Baltus, Alina; Herrmann, Christoph Siegfried

2016-06-01

Oscillatory EEG activity in the human brain with frequencies in the gamma range (approx. 30-80Hz) is known to be relevant for a large number of cognitive processes. Interestingly, each subject reveals an individual frequency of the auditory gamma-band response (GBR) that coincides with the peak in the auditory steady state response (ASSR). A common resonance frequency of auditory cortex seems to underlie both the individual frequency of the GBR and the peak of the ASSR. This review sheds light on the functional role of oscillatory gamma activity for auditory processing. For successful processing, the auditory system has to track changes in auditory input over time and store information about past events in memory which allows the construction of auditory objects. Recent findings support the idea of gamma oscillations being involved in the partitioning of auditory input into discrete samples to facilitate higher order processing. We review experiments that seem to suggest that inter-individual differences in the resonance frequency are behaviorally relevant for gap detection and speech processing. A possible application of these resonance frequencies for brain computer interfaces is illustrated with regard to optimized individual presentation rates for auditory input to correspond with endogenous oscillatory activity. This article is part of a Special Issue entitled SI: Auditory working memory. Copyright © 2015 Elsevier B.V. All rights reserved.

Multiprocessing MCNP on an IBM RS/6000 cluster

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

McKinney, G.W.; West, J.T.

1993-03-01

The advent of high-performance computer systems has brought to maturity programming concepts like vectorization, multiprocessing, and multitasking. While there are many schools of thought as to the most significant factor in obtaining order-of-magnitude increases in performance, such speedup can only be achieved by integrating the computer system and application code. Vectorization leads to faster manipulation of arrays by overlapping instruction CPU cycles. Discrete ordinates codes, which require the solving of large matrices, have proved to be major benefactors of vectorization. Monte Carlo transport, on the other hand, typically contains numerous logic statements and requires extensive redevelopment to benefit from vectorization.more » Multiprocessing and multitasking provide additional CPU cycles via multiple processors. Such systems are generally designed with either common memory access (multitasking) or distributed memory access. In both cases, theoretical speedup, as a function of the number of processors (P) and the fraction of task time that multiprocesses (f), can be formulated using Amdahl`s Law S ((f,P) = 1 f + f/P). However, for most applications this theoretical limit cannot be achieved, due to additional terms not included in Amdahl`s Law. Monte Carlo transport is a natural candidate for multiprocessing, since the particle tracks are generally independent and the precision of the result increases as the square root of the number of particles tracked.« less

Age is no barrier: predictors of academic success in older learners

NASA Astrophysics Data System (ADS)

Imlach, Abbie-Rose; Ward, David D.; Stuart, Kimberley E.; Summers, Mathew J.; Valenzuela, Michael J.; King, Anna E.; Saunders, Nichole L.; Summers, Jeffrey; Srikanth, Velandai K.; Robinson, Andrew; Vickers, James C.

2017-11-01

Although predictors of academic success have been identified in young adults, such predictors are unlikely to translate directly to an older student population, where such information is scarce. The current study aimed to examine cognitive, psychosocial, lifetime, and genetic predictors of university-level academic performance in older adults (50-79 years old). Participants were mostly female (71%) and had a greater than high school education level (M = 14.06 years, SD = 2.76), on average. Two multiple linear regression analyses were conducted. The first examined all potential predictors of grade point average (GPA) in the subset of participants who had volunteered samples for genetic analysis (N = 181). Significant predictors of GPA were then re-examined in a second multiple linear regression using the full sample (N = 329). Our data show that the cognitive domains of episodic memory and language processing, in conjunction with midlife engagement in cognitively stimulating activities, have a role in predicting academic performance as measured by GPA in the first year of study. In contrast, it was determined that age, IQ, gender, working memory, psychosocial factors, and common brain gene polymorphisms linked to brain function, plasticity and degeneration (APOE, BDNF, COMT, KIBRA, SERT) did not influence academic performance. These findings demonstrate that ageing does not impede academic achievement, and that discrete cognitive skills as well as lifetime engagement in cognitively stimulating activities can promote academic success in older adults.

Teach Children with Autism with the Discrete-Trial Approach.

ERIC Educational Resources Information Center

Din, Feng S.; McLaughlin, Donna

This paper discusses the outcomes of a study that investigated whether applying the discrete-trial approach is effective in teaching children with autism to learn functional and pre-academic skills. Participants were four young children with autism (ages 3-4) attending a preschool special education program of an urban public school. Discrete-trial…

Discrete-continuous variable structural synthesis using dual methods

NASA Technical Reports Server (NTRS)

Schmit, L. A.; Fleury, C.

1980-01-01

Approximation concepts and dual methods are extended to solve structural synthesis problems involving a mix of discrete and continuous sizing type of design variables. Pure discrete and pure continuous variable problems can be handled as special cases. The basic mathematical programming statement of the structural synthesis problem is converted into a sequence of explicit approximate primal problems of separable form. These problems are solved by constructing continuous explicit dual functions, which are maximized subject to simple nonnegativity constraints on the dual variables. A newly devised gradient projection type of algorithm called DUAL 1, which includes special features for handling dual function gradient discontinuities that arise from the discrete primal variables, is used to find the solution of each dual problem. Computational implementation is accomplished by incorporating the DUAL 1 algorithm into the ACCESS 3 program as a new optimizer option. The power of the method set forth is demonstrated by presenting numerical results for several example problems, including a pure discrete variable treatment of a metallic swept wing and a mixed discrete-continuous variable solution for a thin delta wing with fiber composite skins.

Functional classification of memory CD8(+) T cells by CX3CR1 expression.

PubMed

Böttcher, Jan P; Beyer, Marc; Meissner, Felix; Abdullah, Zeinab; Sander, Jil; Höchst, Bastian; Eickhoff, Sarah; Rieckmann, Jan C; Russo, Caroline; Bauer, Tanja; Flecken, Tobias; Giesen, Dominik; Engel, Daniel; Jung, Steffen; Busch, Dirk H; Protzer, Ulrike; Thimme, Robert; Mann, Matthias; Kurts, Christian; Schultze, Joachim L; Kastenmüller, Wolfgang; Knolle, Percy A

2015-09-25

Localization of memory CD8(+) T cells to lymphoid or peripheral tissues is believed to correlate with proliferative capacity or effector function. Here we demonstrate that the fractalkine-receptor/CX3CR1 distinguishes memory CD8(+) T cells with cytotoxic effector function from those with proliferative capacity, independent of tissue-homing properties. CX3CR1-based transcriptome and proteome-profiling defines a core signature of memory CD8(+) T cells with effector function. We find CD62L(hi)CX3CR1(+) memory T cells that reside within lymph nodes. This population shows distinct migration patterns and positioning in proximity to pathogen entry sites. Virus-specific CX3CR1(+) memory CD8(+) T cells are scarce during chronic infection in humans and mice but increase when infection is controlled spontaneously or by therapeutic intervention. This CX3CR1-based functional classification will help to resolve the principles of protective CD8(+) T-cell memory.

Hippocampal-targeted Theta-burst Stimulation Enhances Associative Memory Formation.

PubMed

Tambini, Arielle; Nee, Derek Evan; D'Esposito, Mark

2018-06-19

The hippocampus plays a critical role in episodic memory, among other cognitive functions. However, few tools exist to causally manipulate hippocampal function in healthy human participants. Recent work has targeted hippocampal-cortical networks by performing TMS to a region interconnected with the hippocampus, posterior inferior parietal cortex (pIPC). Such hippocampal-targeted TMS enhances associative memory and influences hippocampal functional connectivity. However, it is currently unknown which stages of mnemonic processing (encoding or retrieval) are affected by hippocampal-targeted TMS. Here, we examined whether hippocampal-targeted TMS influences the initial encoding of associations (vs. items) into memory. To selectively influence encoding and not retrieval, we performed continuous theta-burst TMS before participants encoded object-location associations and assessed memory after the direct effect of stimulation dissipated. Relative to control TMS and baseline memory, pIPC TMS enhanced associative memory success and confidence. Item memory was unaffected, demonstrating a selective influence on associative versus item memory. The strength of hippocampal-pIPC functional connectivity predicted TMS-related memory benefits, which was mediated by parahippocampal and retrosplenial cortices. Our findings indicate that hippocampal-targeted TMS can specifically modulate the encoding of new associations into memory without directly influencing retrieval processes and suggest that the ability to influence associative memory may be related to the fidelity of hippocampal TMS targeting. Our results support the notion that pIPC TMS may serve as a potential tool for manipulating hippocampal function in healthy participants. Nonetheless, future work combining hippocampal-targeted continuous theta-burst TMS with neuroimaging is needed to better understand the neural basis of TMS-induced memory changes.

Pathways to functional outcomes following a first episode of psychosis: The roles of premorbid adjustment, verbal memory and symptom remission.

PubMed

Jordan, Gerald; Veru, Franz; Lepage, Martin; Joober, Ridha; Malla, Ashok; Iyer, Srividya N

2017-12-01

Most studies have investigated either the singular or relative contributions of premorbid adjustment, verbal memory and symptom remission to functional outcomes in first-episode psychosis. Fewer studies have examined the pathways of these factors in impacting functioning. Our study addresses this gap. The objective was to determine whether the relationship between premorbid adjustment and functional outcomes was mediated by verbal memory and symptom remission. A total of 334 first-episode psychosis participants (aged 14-35 years) were assessed on premorbid adjustment, verbal memory upon entry, and positive and negative symptom remission and functioning at multiple time points over a 2-year follow-up. Mediation analyses showed that over the first year, the relationship between premorbid adjustment and functioning was mediated by verbal memory and positive symptom remission (β = -0.18; 95% confidence interval = [-0.51, -0.04]), as well as by verbal memory and negative symptom remission (β = -0.41; 95% confidence interval = [-1.11, -1.03]). Over 2 years, the relationship between premorbid adjustment and functioning was mediated by verbal memory and only negative symptom remission (β = -0.38; 95% confidence interval = [-1.46, -0.02]). Comparatively less malleable factors (premorbid adjustment and verbal memory) may contribute to functional outcomes through more malleable factors (symptoms). Promoting remission may be an important parsimonious means to achieving better functional outcomes.

Episodic memory retrieval, parietal cortex, and the Default Mode Network: functional and topographic analyses

PubMed Central

Sestieri, Carlo; Corbetta, Maurizio; Romani, Gian Luca; Shulman, Gordon L.

2011-01-01

The default mode network (DMN) is often considered a functionally homogeneous system that is broadly associated with internally directed cognition (e.g. episodic memory, theory of mind, self-evaluation). However, few studies have examined how this network interacts with other networks during putative “default” processes such as episodic memory retrieval. Using fMRI, we investigated the topography and response profile of human parietal regions inside and outside the DMN, independently defined using task-evoked deactivations and resting state functional connectivity, during episodic memory retrieval. Memory retrieval activated posterior nodes of the DMN, particularly the angular gyrus, but also more anterior and dorsal parietal regions that were anatomically separate from the DMN. The two sets of parietal regions showed different resting-state functional connectivity and response profiles. During memory retrieval, responses in DMN regions peaked sooner than non-DMN regions, which in turn showed responses that were sustained until a final memory judgment was reached. Moreover, a parahippocampal region that showed strong resting-state connectivity with parietal DMN regions also exhibited a pattern of task-evoked activity similar to that exhibited by DMN regions. These results suggest that DMN parietal regions directly supported memory retrieval, whereas non-DMN parietal regions were more involved in post-retrieval processes such as memory-based decision making. Finally, a robust functional dissociation within the DMN was observed. While angular gyrus and posterior cingulate/precuneus were significantly activated during memory retrieval, an anterior DMN node in medial prefrontal cortex was strongly deactivated. This latter finding demonstrates functional heterogeneity rather than homogeneity within the DMN during episodic memory retrieval. PMID:21430142

A Brief Measure for Assessing Patient Perceptions of Cognitive Side Effects After Electroconvulsive Therapy: The Subjective Assessment of Memory Impairment.

PubMed

Kumar, Divya Rani; Han, Hank Ke; Tiller, John; Loo, Colleen K; Martin, Donel M

2016-12-01

Directly inquiring about patient experiences of memory problems after ECT may alert clinicians to the existence of treatment side effects and provide an impression of their intrusiveness. In this study, we examined use of a novel and brief patient-reported measure to assess perceptions of memory side effects and their functional consequences before and after an acute ECT treatment course. These outcomes were compared with objective cognitive and subjective quality of life measures. Data for 75 patients who were prescribed an acute course of ECT were analyzed. Subjective and objective measures were assessed before ECT (pretreatment) and at posttreatment. Patient perceptions were assessed using the Subjective Assessment of Memory Impairment, which consists of two items: The Memory Problems item, and The Impact of Cognitive Adverse Events item. Objective cognitive outcomes were assessed using the Montreal Cognitive Assessment. Quality of life was assessed using the Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form. Patient perceptions of their memory problems did not change across the ECT course, and their functional impact were considered less intrusive after ECT. Greater functional impact of memory impairment was related to poorer quality of life at posttreatment, but not at pretreatment. Subjectively rated cognitive functioning was not associated with objective cognitive outcomes. The Subjective Assessment of Memory Impairment is a brief tool for measuring patient-rated memory function. Overall, patients did not report any change in subjective memory problems after ECT. Although perceptions of functional memory impairment and quality of life were related after ECT, there was no association with objectively assessed cognitive outcomes.

Are there reliable changes in memory and executive functions after cognitive behavioural therapy in patients with obsessive-compulsive disorder?

PubMed

Vandborg, Sanne Kjær; Hartmann, Tue Borst; Bennedsen, Birgit Egedal; Pedersen, Anders Degn; Thomsen, Per Hove

2015-01-01

Patients with obsessive-compulsive disorder (OCD) have impaired memory and executive functions, but it is unclear whether these functions improve after cognitive behavioural therapy (CBT) of OCD symptoms. The primary aim of this study was to investigate whether memory and executive functions change after CBT in patients with OCD. We assessed 39 patients with OCD before and after CBT with neuropsychological tests of memory and executive functions. To correct for practice effects, 39 healthy controls (HCs) were assessed at two parallel time intervals with the neuropsychological tests. There were no changes in memory and executive functions after CBT in patients with OCD when results were corrected for practice effects. Patients performed worse on a test of visuospatial memory and organisational skills (Rey complex figure test [RCFT]) compared to HCs both before and after CBT (ps = .002-.036). The finding of persistent poor RCFT performances indicates that patients with OCD have impaired visuospatial memory and organisational skills that may be trait-related rather than state-dependent. These impairments may need to be considered in treatment. Our findings underline the importance of correcting for practice effects when investigating changes in cognitive functions.

Delay-dependent dynamical analysis of complex-valued memristive neural networks: Continuous-time and discrete-time cases.

PubMed

Wang, Jinling; Jiang, Haijun; Ma, Tianlong; Hu, Cheng

2018-05-01

This paper considers the delay-dependent stability of memristive complex-valued neural networks (MCVNNs). A novel linear mapping function is presented to transform the complex-valued system into the real-valued system. Under such mapping function, both continuous-time and discrete-time MCVNNs are analyzed in this paper. Firstly, when activation functions are continuous but not Lipschitz continuous, an extended matrix inequality is proved to ensure the stability of continuous-time MCVNNs. Furthermore, if activation functions are discontinuous, a discontinuous adaptive controller is designed to acquire its stability by applying Lyapunov-Krasovskii functionals. Secondly, compared with techniques in continuous-time MCVNNs, the Halanay-type inequality and comparison principle are firstly used to exploit the dynamical behaviors of discrete-time MCVNNs. Finally, the effectiveness of theoretical results is illustrated through numerical examples. Copyright © 2018 Elsevier Ltd. All rights reserved.

The effect of anticipation and the specificity of sex differences for amygdala and hippocampus function in emotional memory.

PubMed

Mackiewicz, Kristen L; Sarinopoulos, Issidoros; Cleven, Krystal L; Nitschke, Jack B

2006-09-19

Prior research has shown memory is enhanced for emotional events. Key brain areas involved in emotional memory are the amygdala and hippocampus, which are also recruited during aversion and its anticipation. This study investigated whether anticipatory processes signaling an upcoming aversive event contribute to emotional memory. In an event-related functional MRI paradigm, 40 healthy participants viewed aversive and neutral pictures preceded by predictive warning cues. Participants completed a surprise recognition task directly after functional MRI scanning or 2 weeks later. In anticipation of aversive pictures, bilateral dorsal amygdala and anterior hippocampus activations were associated with better immediate recognition memory. Similar associations with memory were observed for activation of those areas in response to aversive pictures. Anticipatory activation predicted immediate memory over and above these associations for picture viewing. Bilateral ventral amygdala activations in response to aversive pictures predicted delayed memory only. We found that previously reported sex differences of memory associations with left amygdala for women and with right amygdala for men were confined to the ventral amygdala during picture viewing and delayed memory. Results support an established animal model elucidating the functional neuroanatomy of the amygdala and hippocampus in emotional memory, highlight the importance of anticipatory processes in such memory for aversive events, and extend neuroanatomical evidence of sex differences for emotional memory.

Discrete Gust Model for Launch Vehicle Assessments

NASA Technical Reports Server (NTRS)

Leahy, Frank B.

2008-01-01

Analysis of spacecraft vehicle responses to atmospheric wind gusts during flight is important in the establishment of vehicle design structural requirements and operational capability. Typically, wind gust models can be either a spectral type determined by a random process having a wide range of wavelengths, or a discrete type having a single gust of predetermined magnitude and shape. Classical discrete models used by NASA during the Apollo and Space Shuttle Programs included a 9 m/sec quasi-square-wave gust with variable wavelength from 60 to 300 m. A later study derived discrete gust from a military specification (MIL-SPEC) document that used a "1-cosine" shape. The MIL-SPEC document contains a curve of non-dimensional gust magnitude as a function of non-dimensional gust half-wavelength based on the Dryden spectral model, but fails to list the equation necessary to reproduce the curve. Therefore, previous studies could only estimate a value of gust magnitude from the curve, or attempt to fit a function to it. This paper presents the development of the MIL-SPEC curve, and provides the necessary information to calculate discrete gust magnitudes as a function of both gust half-wavelength and the desired probability level of exceeding a specified gust magnitude.

Adaptive NN controller design for a class of nonlinear MIMO discrete-time systems.

PubMed

Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip

2015-05-01

An adaptive neural network tracking control is studied for a class of multiple-input multiple-output (MIMO) nonlinear systems. The studied systems are in discrete-time form and the discretized dead-zone inputs are considered. In addition, the studied MIMO systems are composed of N subsystems, and each subsystem contains unknown functions and external disturbance. Due to the complicated framework of the discrete-time systems, the existence of the dead zone and the noncausal problem in discrete-time, it brings about difficulties for controlling such a class of systems. To overcome the noncausal problem, by defining the coordinate transformations, the studied systems are transformed into a special form, which is suitable for the backstepping design. The radial basis functions NNs are utilized to approximate the unknown functions of the systems. The adaptation laws and the controllers are designed based on the transformed systems. By using the Lyapunov method, it is proved that the closed-loop system is stable in the sense that the semiglobally uniformly ultimately bounded of all the signals and the tracking errors converge to a bounded compact set. The simulation examples and the comparisons with previous approaches are provided to illustrate the effectiveness of the proposed control algorithm.

Functional MR imaging or Wada test: which is the better predictor of individual postoperative memory outcome?

PubMed

Dupont, Sophie; Duron, Emmanuelle; Samson, Séverine; Denos, Marisa; Volle, Emmanuelle; Delmaire, Christine; Navarro, Vincent; Chiras, Jacques; Lehéricy, Stéphane; Samson, Yves; Baulac, Michel

2010-04-01

To retrospectively determine whether blood oxygen level-dependent functional magnetic resonance (MR) imaging can aid prediction of postoperative memory changes in epileptic patients after temporal lobe surgery. This study was approved by the local ethics committee, and informed consent was obtained from all patients. Data were analyzed from 25 patients (12 women, 13 men; age range, 19-52 years) with refractory epilepsy in whom temporal lobe surgery was performed after they underwent preoperative functional MR imaging, the Wada test, and neuropsychological testing. The functional MR imaging protocol included three different memory tasks (24-hour delayed recognition, encoding, and immediate recognition). Individual activations were measured in medial temporal lobe (MTL) regions of both hemispheres. The prognostic accuracy of functional MR imaging for prediction of postoperative memory changes was compared with the accuracy of the Wada test and preoperative neuropsychological testing by using a backward multiple regression analysis. An equation that was based on left functional MR imaging MTL activation during delayed recognition, side of the epileptic focus, and preoperative global verbal memory score was used to correctly predict worsening of verbal memory in 90% of patients. The right functional MR imaging MTL activation did not substantially correlate with the nonverbal memory outcome, which was only predicted by using the preoperative nonverbal global score. Wada test data were not good predictors of changes in either verbal or nonverbal memory. Findings suggest that functional MR imaging activation during a delayed-recognition task is a better predictor of individual postoperative verbal memory outcome than is the Wada test. RSNA, 2010

Vertical discretization with finite elements for a global hydrostatic model on the cubed sphere

NASA Astrophysics Data System (ADS)

Yi, Tae-Hyeong; Park, Ja-Rin

2017-06-01

A formulation of Galerkin finite element with basis-spline functions on a hybrid sigma-pressure coordinate is presented to discretize the vertical terms of global Eulerian hydrostatic equations employed in a numerical weather prediction system, which is horizontally discretized with high-order spectral elements on a cubed sphere grid. This replaces the vertical discretization of conventional central finite difference that is first-order accurate in non-uniform grids and causes numerical instability in advection-dominant flows. Therefore, a model remains in the framework of Galerkin finite elements for both the horizontal and vertical spatial terms. The basis-spline functions, obtained from the de-Boor algorithm, are employed to derive both the vertical derivative and integral operators, since Eulerian advection terms are involved. These operators are used to discretize the vertical terms of the prognostic and diagnostic equations. To verify the vertical discretization schemes and compare their performance, various two- and three-dimensional idealized cases and a hindcast case with full physics are performed in terms of accuracy and stability. It was shown that the vertical finite element with the cubic basis-spline function is more accurate and stable than that of the vertical finite difference, as indicated by faster residual convergence, fewer statistical errors, and reduction in computational mode. This leads to the general conclusion that the overall performance of a global hydrostatic model might be significantly improved with the vertical finite element.