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Sample records for human memory network

  1. A computational predictor of human episodic memory based on a theta phase precession network.

    Directory of Open Access Journals (Sweden)

    Naoyuki Sato

    Full Text Available In the rodent hippocampus, a phase precession phenomena of place cell firing with the local field potential (LFP theta is called "theta phase precession" and is considered to contribute to memory formation with spike time dependent plasticity (STDP. On the other hand, in the primate hippocampus, the existence of theta phase precession is unclear. Our computational studies have demonstrated that theta phase precession dynamics could contribute to primate-hippocampal dependent memory formation, such as object-place association memory. In this paper, we evaluate human theta phase precession by using a theory-experiment combined analysis. Human memory recall of object-place associations was analyzed by an individual hippocampal network simulated by theta phase precession dynamics of human eye movement and EEG data during memory encoding. It was found that the computational recall of the resultant network is significantly correlated with human memory recall performance, while other computational predictors without theta phase precession are not significantly correlated with subsequent memory recall. Moreover the correlation is larger than the correlation between human recall and traditional experimental predictors. These results indicate that theta phase precession dynamics are necessary for the better prediction of human recall performance with eye movement and EEG data. In this analysis, theta phase precession dynamics appear useful for the extraction of memory-dependent components from the spatio-temporal pattern of eye movement and EEG data as an associative network. Theta phase precession may be a common neural dynamic between rodents and humans for the formation of environmental memories.

  2. Cognitive Memory Network

    CERN Document Server

    James, Alex Pappachen; 10.1049/el.2010.0279

    2012-01-01

    A resistive memory network that has no crossover wiring is proposed to overcome the hardware limitations to size and functional complexity that is associated with conventional analogue neural networks. The proposed memory network is based on simple network cells that are arranged in a hierarchical modular architecture. Cognitive functionality of this network is demonstrated by an example of character recognition. The network is trained by an evolutionary process to completely recognise characters deformed by random noise, rotation, scaling and shifting

  3. Continuous Timescale Long-Short Term Memory Neural Network for Human Intent Understanding

    Directory of Open Access Journals (Sweden)

    Zhibin Yu

    2017-08-01

    Full Text Available Understanding of human intention by observing a series of human actions has been a challenging task. In order to do so, we need to analyze longer sequences of human actions related with intentions and extract the context from the dynamic features. The multiple timescales recurrent neural network (MTRNN model, which is believed to be a kind of solution, is a useful tool for recording and regenerating a continuous signal for dynamic tasks. However, the conventional MTRNN suffers from the vanishing gradient problem which renders it impossible to be used for longer sequence understanding. To address this problem, we propose a new model named Continuous Timescale Long-Short Term Memory (CTLSTM in which we inherit the multiple timescales concept into the Long-Short Term Memory (LSTM recurrent neural network (RNN that addresses the vanishing gradient problem. We design an additional recurrent connection in the LSTM cell outputs to produce a time-delay in order to capture the slow context. Our experiments show that the proposed model exhibits better context modeling ability and captures the dynamic features on multiple large dataset classification tasks. The results illustrate that the multiple timescales concept enhances the ability of our model to handle longer sequences related with human intentions and hence proving to be more suitable for complex tasks, such as intention recognition.

  4. A balanced memory network.

    Directory of Open Access Journals (Sweden)

    Yasser Roudi

    2007-09-01

    Full Text Available A fundamental problem in neuroscience is understanding how working memory--the ability to store information at intermediate timescales, like tens of seconds--is implemented in realistic neuronal networks. The most likely candidate mechanism is the attractor network, and a great deal of effort has gone toward investigating it theoretically. Yet, despite almost a quarter century of intense work, attractor networks are not fully understood. In particular, there are still two unanswered questions. First, how is it that attractor networks exhibit irregular firing, as is observed experimentally during working memory tasks? And second, how many memories can be stored under biologically realistic conditions? Here we answer both questions by studying an attractor neural network in which inhibition and excitation balance each other. Using mean-field analysis, we derive a three-variable description of attractor networks. From this description it follows that irregular firing can exist only if the number of neurons involved in a memory is large. The same mean-field analysis also shows that the number of memories that can be stored in a network scales with the number of excitatory connections, a result that has been suggested for simple models but never shown for realistic ones. Both of these predictions are verified using simulations with large networks of spiking neurons.

  5. Audiovisual classification of vocal outbursts in human conversation using long-short-term memory networks

    NARCIS (Netherlands)

    Eyben, Florian; Petridis, Stavros; Schuller, Björn; Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja

    2011-01-01

    We investigate classification of non-linguistic vocalisations with a novel audiovisual approach and Long Short-Term Memory (LSTM) Recurrent Neural Networks as highly successful dynamic sequence classifiers. As database of evaluation serves this year's Paralinguistic Challenge's Audiovisual Interest

  6. Networks with Memory

    CERN Document Server

    Rosvall, Martin; Lancichinetti, Andrea; West, Jevin D; Lambiotte, Renaud

    2013-01-01

    It is a paradigm to capture the spread of information and disease with random flow on networks. However, this conventional approach ignores an important feature of the dynamics: where flow moves to depends on where it comes from. That is, memory matters. We analyze multi-step pathways from different systems and show that ignoring memory has profound consequences for community detection and ranking as well as for epidemic spreading. Specifically, memoryless dynamics on networks understate the effect of communities and exaggerate the effect of highly connected nodes. Including memory reveals actual travel patterns in air traffic, ranking that favors specialized journals in scientific communication, and diseases that spread more slowly and persist longer in hospitals.

  7. Human memory search

    NARCIS (Netherlands)

    Davelaar, E.J.; Raaijmakers, J.G.W.; Hills, T.T.; Robbins, T.W.; Todd, P.M.

    2012-01-01

    The importance of understanding human memory search is hard to exaggerate: we build and live our lives based on what whe remember. This chapter explores the characteristics of memory search, with special emphasis on the use of retrieval cues. We introduce the dependent measures that are obtained

  8. Human Memory: The Basics

    Science.gov (United States)

    Martinez, Michael E.

    2010-01-01

    The human mind has two types of memory: short-term and long-term. In all types of learning, it is best to use that structure rather than to fight against it. One way to do that is to ensure that learners can fit new information into patterns that can be stored in and more easily retrieved from long-term memory.

  9. Human Memory: The Basics

    Science.gov (United States)

    Martinez, Michael E.

    2010-01-01

    The human mind has two types of memory: short-term and long-term. In all types of learning, it is best to use that structure rather than to fight against it. One way to do that is to ensure that learners can fit new information into patterns that can be stored in and more easily retrieved from long-term memory.

  10. Human Learning and Memory

    Science.gov (United States)

    Lieberman, David A.

    2012-01-01

    This innovative textbook is the first to integrate learning and memory, behaviour, and cognition. It focuses on fascinating human research in both memory and learning (while also bringing in important animal studies) and brings the reader up to date with the latest developments in the subject. Students are encouraged to think critically: key…

  11. Human learning and memory.

    Science.gov (United States)

    Johnson, M K; Hasher, L

    1987-01-01

    There have been several notable recent trends in the area of learning and memory. Problems with the episodic/semantic distinction have become more apparent, and new efforts have been made (exemplar models, distributed-memory models) to represent general knowledge without assuming a separate semantic system. Less emphasis is being placed on stable, prestored prototypes and more emphasis on a flexible memory system that provides the basis for a multitude of categories or frames of reference, derived on the spot as tasks demand. There is increasing acceptance of the idea that mental models are constructed and stored in memory in addition to, rather than instead of, memorial representations that are more closely tied to perceptions. This gives rise to questions concerning the conditions that permit inferences to be drawn and mental models to be constructed, and to questions concerning the similarities and differences in the nature of the representations in memory of perceived and generated information and in their functions. There has also been a swing from interest in deliberate strategies to interest in automatic, unconscious (even mechanistic!) processes, reflecting an appreciation that certain situations (e.g. recognition, frequency judgements, savings in indirect tasks, aspects of skill acquisition, etc) seem not to depend much on the products of strategic, effortful or reflective processes. There is a lively interest in relations among memory measures and attempts to characterize memory representations and/or processes that could give rise to dissociations among measures. Whether the pattern of results reflects the operation of functional subsystems of memory and, if so, what the "modules" are is far from clear. This issue has been fueled by work with amnesics and has contributed to a revival of interaction between researchers studying learning and memory in humans and those studying learning and memory in animals. Thus, neuroscience rivals computer science as a

  12. [Alzheimer's disease and human memory].

    Science.gov (United States)

    Eustache, F; Giffard, B; Rauchs, G; Chételat, G; Piolino, P; Desgranges, B

    2006-10-01

    Memory disorders observed in Alzheimer's disease gave rise, from the eighties, to a detailed analysis into the framework of cognitive neuropsychology which aimed at describing the deficits of very specific processes. Beyond their clinical interest, these studies contributed to the modelisation of human memory thanks to the characterization of different memory systems and their relationships. The first part of this paper gives an overview of the memory deficits in Alzheimer's disease and insists on particular cognitive phenomena. Hence, several examples are developed in the domains of semantic memory (such as hyperpriming and hypopriming effects) and autobiographical memory. Recent results highlight the existence of severe autobiographical amnesia observed in all neurodegenerative diseases, though with contrasting profiles: Ribot's gradient in Alzheimer's disease (showing that remote memories are better preserved than recent ones), reverse gradient in semantic dementia and no clear gradient in the frontal variant of frontotemporal dementia. The second part of this article presents advances in cognitive neuroscience searching to disclose the cerebral substrates of these cognitive deficits in Alzheimer's disease. The studies using functional imaging techniques are the most informative regarding this problematic. While showing the dysfunctions of an extended network, they emphasize the selectivity of cerebral damages that are at the root of very specific cognitive dysfunctions, coming close in that way to the conceptions of cognitive neuropsychology. These neuroimaging studies unravel the existence of compensatory mechanisms, which until recently were clearly missing in the literature on neurodegenerative diseases. These different researches lead to a wide conception of human memory, not just limited to simple instrumental processes (encoding, storage, retrieval), but necessarily covering models of identity and continuity of the subject, which interact in a dynamic way

  13. Context-Dependent Human Extinction Memory Is Mediated by a Ventromedial Prefrontal and Hippocampal Network

    OpenAIRE

    Kalisch, R; Korenfeld, E; Stephan, K.E.; Weiskopf, N.; Seymour, B; Dolan, R.J.

    2006-01-01

    In fear extinction, an animal learns that a conditioned stimulus (CS) no longer predicts a noxious stimulus [unconditioned stimulus (UCS)] to which it had previously been associated, leading to inhibition of the conditioned response (CR). Extinction creates a new CS-noUCS memory trace, competing with the initial fear (CS-UCS) memory. Recall of extinction memory and, hence, CR inhibition at later CS encounters is facilitated by contextual stimuli present during extinction training. In line wit...

  14. Memory Stacking in Hierarchical Networks.

    Science.gov (United States)

    Westö, Johan; May, Patrick J C; Tiitinen, Hannu

    2016-02-01

    Robust representations of sounds with a complex spectrotemporal structure are thought to emerge in hierarchically organized auditory cortex, but the computational advantage of this hierarchy remains unknown. Here, we used computational models to study how such hierarchical structures affect temporal binding in neural networks. We equipped individual units in different types of feedforward networks with local memory mechanisms storing recent inputs and observed how this affected the ability of the networks to process stimuli context dependently. Our findings illustrate that these local memories stack up in hierarchical structures and hence allow network units to exhibit selectivity to spectral sequences longer than the time spans of the local memories. We also illustrate that short-term synaptic plasticity is a potential local memory mechanism within the auditory cortex, and we show that it can bring robustness to context dependence against variation in the temporal rate of stimuli, while introducing nonlinearities to response profiles that are not well captured by standard linear spectrotemporal receptive field models. The results therefore indicate that short-term synaptic plasticity might provide hierarchically structured auditory cortex with computational capabilities important for robust representations of spectrotemporal patterns.

  15. A parietal memory network revealed by multiple MRI methods.

    Science.gov (United States)

    Gilmore, Adrian W; Nelson, Steven M; McDermott, Kathleen B

    2015-09-01

    The manner by which the human brain learns and recognizes stimuli is a matter of ongoing investigation. Through examination of meta-analyses of task-based functional MRI and resting state functional connectivity MRI, we identified a novel network strongly related to learning and memory. Activity within this network at encoding predicts subsequent item memory, and at retrieval differs for recognized and unrecognized items. The direction of activity flips as a function of recent history: from deactivation for novel stimuli to activation for stimuli that are familiar due to recent exposure. We term this network the 'parietal memory network' (PMN) to reflect its broad involvement in human memory processing. We provide a preliminary framework for understanding the key functional properties of the network. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Memory Chain in a Chaotic Autoassociative Neural Network

    Institute of Scientific and Technical Information of China (English)

    FAN Hong; WANG Zhi-jie; ZHANG Jue

    2005-01-01

    Memory chain is observed in a chaotic autoassociative neural network. The network recalls first stored pattern from a fragment of a memory, stays at this pattern for a while, transits to the second stored pattern that overlaps with the first recalled pattern.Then it stays at the second recalled pattern for a while, transits to the third stored pattern that overlaps with the second recalled pattern, and so on. Thus a memory chain is generated. The memory chain ends with the pattern that overlaps no other stored patten. This phenomenon is similar to the way of recalling process of human beings in some respects.

  17. Associative memory in phasing neuron networks

    Energy Technology Data Exchange (ETDEWEB)

    Nair, Niketh S [ORNL; Bochove, Erik J. [United States Air Force Research Laboratory, Kirtland Air Force Base; Braiman, Yehuda [ORNL

    2014-01-01

    We studied pattern formation in a network of coupled Hindmarsh-Rose model neurons and introduced a new model for associative memory retrieval using networks of Kuramoto oscillators. Hindmarsh-Rose Neural Networks can exhibit a rich set of collective dynamics that can be controlled by their connectivity. Specifically, we showed an instance of Hebb's rule where spiking was correlated with network topology. Based on this, we presented a simple model of associative memory in coupled phase oscillators.

  18. Properties of a memory network in psychology

    Science.gov (United States)

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

    2007-12-01

    We have previously described neurotic psychopathology and psychoanalytic working-through by an associative memory mechanism, based on a neural network model, where memory was modelled by a Boltzmann machine (BM). Since brain neural topology is selectively structured, we simulated known microscopic mechanisms that control synaptic properties, showing that the network self-organizes to a hierarchical, clustered structure. Here, we show some statistical mechanical properties of the complex networks which result from this self-organization. They indicate that a generalization of the BM may be necessary to model memory.

  19. Multi-Valued Associative Memory Neural Network

    Institute of Scientific and Technical Information of China (English)

    修春波; 刘向东; 张宇河

    2003-01-01

    A novel learning method for multi-valued associative memory network is introduced, which is based on Hebb rule, but utilizes more information. According to the current probe vector, the connection weights matrix could be chosen dynamically. Double-valued and multi-valued associative memory are all realized in our simulation experiment. The experimental results show that the method could enhance the associative success rate.

  20. Persistent memories in transient networks

    OpenAIRE

    Babichev, Andrey; Dabaghian, Yuri

    2016-01-01

    Spatial awareness in mammals is based on an internalized representation of the environment, encoded by large networks of spiking neurons. While such representations can last for a long time, the underlying neuronal network is transient: neuronal cells die every day, synaptic connections appear and disappear, the networks constantly change their architecture due to various forms of synaptic and structural plasticity. How can a network with a dynamic architecture encode a stable map of space? W...

  1. Copolymer Networks From Oligo(ε-caprolactone) and n-Butyl Acrylate Enable a Reversible Bidirectional Shape-Memory Effect at Human Body Temperature.

    Science.gov (United States)

    Saatchi, Mersa; Behl, Marc; Nöchel, Ulrich; Lendlein, Andreas

    2015-05-01

    Exploiting the tremendous potential of the recently discovered reversible bidirectional shape-memory effect (rbSME) for biomedical applications requires switching temperatures in the physiological range. The recent strategy is based on the reduction of the melting temperature range (ΔT m ) of the actuating oligo(ε-caprolactone) (OCL) domains in copolymer networks from OCL and n-butyl acrylate (BA), where the reversible effect can be adjusted to the human body temperature. In addition, it is investigated whether an rbSME in the temperature range close or even above Tm,offset (end of the melting transition) can be obtained. Two series of networks having mixtures of OCLs reveal broad ΔTm s from 2 °C to 50 °C and from -10 °C to 37 °C, respectively. In cyclic, thermomechanical experiments the rbSME can be tailored to display pronounced actuation in a temperature interval between 20 °C and 37 °C. In this way, the application spectrum of the rbSME can be extended to biomedical applications.

  2. Cognitive Control Network Contributions to Memory-Guided Visual Attention.

    Science.gov (United States)

    Rosen, Maya L; Stern, Chantal E; Michalka, Samantha W; Devaney, Kathryn J; Somers, David C

    2016-05-01

    Visual attentional capacity is severely limited, but humans excel in familiar visual contexts, in part because long-term memories guide efficient deployment of attention. To investigate the neural substrates that support memory-guided visual attention, we performed a set of functional MRI experiments that contrast long-term, memory-guided visuospatial attention with stimulus-guided visuospatial attention in a change detection task. Whereas the dorsal attention network was activated for both forms of attention, the cognitive control network(CCN) was preferentially activated during memory-guided attention. Three posterior nodes in the CCN, posterior precuneus, posterior callosal sulcus/mid-cingulate, and lateral intraparietal sulcus exhibited the greatest specificity for memory-guided attention. These 3 regions exhibit functional connectivity at rest, and we propose that they form a subnetwork within the broader CCN. Based on the task activation patterns, we conclude that the nodes of this subnetwork are preferentially recruited for long-term memory guidance of visuospatial attention.

  3. Memory and betweenness preference in temporal networks induced from time series

    Science.gov (United States)

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

    2017-02-01

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

  4. Memory, neurodynamics, and human relationships.

    Science.gov (United States)

    Grigsby, Jim; Stevens, David

    2002-01-01

    In this article we discuss the implications of the functional organization and dynamics of the brain for understanding human relationships. In particular, we focus on the brain's multiple memory systems and the various roles they play in organizing the interactions of people as they come to know one another. The distinction between the relatively independent declarative, procedural, and emotional learning systems is especially significant in this regard, as the former mediates what we know about one another, the second mediates what we do with one another, and the third affects behavior by altering our emotional state. Knowledge of the functioning of these dissociable memory systems provides a novel perspective on relationships--both ordinary social relationships and those that develop in psychotherapy--and further illuminates psychotherapeutic transference and countertransference phenomena. We begin with a review of the neural basis of these processes, then turn our attention to the interpersonal level of analysis.

  5. Intensive Working Memory Training Produces Functional Changes in Large-scale Frontoparietal Networks.

    Science.gov (United States)

    Thompson, Todd W; Waskom, Michael L; Gabrieli, John D E

    2016-04-01

    Working memory is central to human cognition, and intensive cognitive training has been shown to expand working memory capacity in a given domain. It remains unknown, however, how the neural systems that support working memory are altered through intensive training to enable the expansion of working memory capacity. We used fMRI to measure plasticity in activations associated with complex working memory before and after 20 days of training. Healthy young adults were randomly assigned to train on either a dual n-back working memory task or a demanding visuospatial attention task. Training resulted in substantial and task-specific expansion of dual n-back abilities accompanied by changes in the relationship between working memory load and activation. Training differentially affected activations in two large-scale frontoparietal networks thought to underlie working memory: the executive control network and the dorsal attention network. Activations in both networks linearly scaled with working memory load before training, but training dissociated the role of the two networks and eliminated this relationship in the executive control network. Load-dependent functional connectivity both within and between these two networks increased following training, and the magnitudes of increased connectivity were positively correlated with improvements in task performance. These results provide insight into the adaptive neural systems that underlie large gains in working memory capacity through training.

  6. On Memory Capacity of the Probabilistic Logic Neuron Network

    Institute of Scientific and Technical Information of China (English)

    1993-01-01

    In this paper,the memory capacity of Probabilistic Logic Neuron(PLN) network is discussed.We obtain two main results:(1)the method for constructing a PLN network with a given memory capacity;(2)the relationship between the memory capacity and the size of a PLN network.We show that the memory capacity of a PLN network depends on not only the number of input ports of its element but also the number of elements themselves.The results provide a new method for designing a PLN network.

  7. The hippocampus: hub of brain network communication for memory.

    NARCIS (Netherlands)

    F.P. Battaglia; K. Benchenane; A. Sirota; C.M.A. Pennartz; S.I. Wiener

    2011-01-01

    A complex brain network, centered on the hippocampus, supports episodic memories throughout their lifetimes. Classically, upon memory encoding during active behavior, hippocampal activity is dominated by theta oscillations (6-10Hz). During inactivity, hippocampal neurons burst synchronously, constit

  8. Electronic implementation of associative memory based on neural network models

    Science.gov (United States)

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

    1987-01-01

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

  9. Multivalued associative memories based on recurrent networks.

    Science.gov (United States)

    Chiueh, T D; Tsai, H K

    1993-01-01

    A multivalued neural associative memory model based on a recurrent network structure is proposed. This model adopts the same principle proposed in the authors' previous work, the exponential correlation associative memories (ECAM). The model also has a very high storage capacity and strong error-correction capability. The major components of the new model include a weighted average process and some similarity-measure computation. As in ECAM, in order to enhance the differences among the weights and make the largest weights more overwhelming, the new model incorporates a nonlinear function in the calculation of weights. Several possible similarity measures suitable for this model are suggested. Simulation results of the performance of the new model with different measures show that, loaded with 500 64-component patterns, the model can sustain noise with power about one fifth to three fifths of the average signal power.

  10. Sleep, plasticity and memory from molecules to whole-brain networks

    NARCIS (Netherlands)

    Abel, Ted; Havekes, Robbert; Saletin, Jared M; Walker, Matthew P

    2013-01-01

    Despite the ubiquity of sleep across phylogeny, its function remains elusive. In this review, we consider one compelling candidate: brain plasticity associated with memory processing. Focusing largely on hippocampus-dependent memory in rodents and humans, we describe molecular, cellular, network, wh

  11. Targeted enhancement of cortical-hippocampal brain networks and associative memory.

    Science.gov (United States)

    Wang, Jane X; Rogers, Lynn M; Gross, Evan Z; Ryals, Anthony J; Dokucu, Mehmet E; Brandstatt, Kelly L; Hermiller, Molly S; Voss, Joel L

    2014-08-29

    The influential notion that the hippocampus supports associative memory by interacting with functionally distinct and distributed brain regions has not been directly tested in humans. We therefore used targeted noninvasive electromagnetic stimulation to modulate human cortical-hippocampal networks and tested effects of this manipulation on memory. Multiple-session stimulation increased functional connectivity among distributed cortical-hippocampal network regions and concomitantly improved associative memory performance. These alterations involved localized long-term plasticity because increases were highly selective to the targeted brain regions, and enhancements of connectivity and associative memory persisted for ~24 hours after stimulation. Targeted cortical-hippocampal networks can thus be enhanced noninvasively, demonstrating their role in associative memory.

  12. Associative memory realized by a reconfigurable memristive Hopfield neural network.

    Science.gov (United States)

    Hu, S G; Liu, Y; Liu, Z; Chen, T P; Wang, J J; Yu, Q; Deng, L J; Yin, Y; Hosaka, Sumio

    2015-06-25

    Although synaptic behaviours of memristors have been widely demonstrated, implementation of an even simple artificial neural network is still a great challenge. In this work, we demonstrate the associative memory on the basis of a memristive Hopfield network. Different patterns can be stored into the memristive Hopfield network by tuning the resistance of the memristors, and the pre-stored patterns can be successfully retrieved directly or through some associative intermediate states, being analogous to the associative memory behaviour. Both single-associative memory and multi-associative memories can be realized with the memristive Hopfield network.

  13. From network heterogeneities to familiarity detection and hippocampal memory management

    Science.gov (United States)

    Wang, Jane X.; Poe, Gina; Zochowski, Michal

    2008-10-01

    Hippocampal-neocortical interactions are key to the rapid formation of novel associative memories in the hippocampus and consolidation to long term storage sites in the neocortex. We investigated the role of network correlates during information processing in hippocampal-cortical networks. We found that changes in the intrinsic network dynamics due to the formation of structural network heterogeneities alone act as a dynamical and regulatory mechanism for stimulus novelty and familiarity detection, thereby controlling memory management in the context of memory consolidation. This network dynamic, coupled with an anatomically established feedback between the hippocampus and the neocortex, recovered heretofore unexplained properties of neural activity patterns during memory management tasks which we observed during sleep in multiunit recordings from behaving animals. Our simple dynamical mechanism shows an experimentally matched progressive shift of memory activation from the hippocampus to the neocortex and thus provides the means to achieve an autonomous off-line progression of memory consolidation.

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

    Science.gov (United States)

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

    2016-05-01

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

  15. Segmented-memory recurrent neural networks.

    Science.gov (United States)

    Chen, Jinmiao; Chaudhari, Narendra S

    2009-08-01

    Conventional recurrent neural networks (RNNs) have difficulties in learning long-term dependencies. To tackle this problem, we propose an architecture called segmented-memory recurrent neural network (SMRNN). A symbolic sequence is broken into segments and then presented as inputs to the SMRNN one symbol per cycle. The SMRNN uses separate internal states to store symbol-level context, as well as segment-level context. The symbol-level context is updated for each symbol presented for input. The segment-level context is updated after each segment. The SMRNN is trained using an extended real-time recurrent learning algorithm. We test the performance of SMRNN on the information latching problem, the "two-sequence problem" and the problem of protein secondary structure (PSS) prediction. Our implementation results indicate that SMRNN performs better on long-term dependency problems than conventional RNNs. Besides, we also theoretically analyze how the segmented memory of SMRNN helps learning long-term temporal dependencies and study the impact of the segment length.

  16. Memory and burstiness in dynamic networks

    CERN Document Server

    Colman, Ewan R

    2015-01-01

    We introduce a class of complex network models which evolve through the addition of edges between nodes selected randomly according to their intrinsic fitness, and the deletion of edges according to their age. We add to this a memory effect where the attractiveness of a node is increased by the number of edges it is currently attached to, and observe that this creates burst-like activity in the attachment events of each individual node which is characterised by a power-law distribution of inter-event times. The fitness of each node depends on the probability distribution from which it is drawn; we find exact solutions for the expectation of the degree distribution for a variety of possible fitness distributions, and for both cases where the memory effect either is, or is not present. This work can potentially lead to methods to uncover hidden fitness distributions from fast changing, temporal network data such as online social communications and fMRI scans.

  17. Mnemonic Training Reshapes Brain Networks to Support Superior Memory

    NARCIS (Netherlands)

    Dresler, M.; Shirer, W.R.; Konrad, B.N.; Muller, N.C.J.; Wagner, I.; Fernandez, G.S.E.; Czisch, M.; Greicius, M.D.

    2017-01-01

    Memory skills strongly differ across the general population; however, little is known about the brain characteristics supporting superior memory performance. Here we assess functional brain network organization of 23 of the world's most successful memory athletes and matched controls with fMRI

  18. Oscillatory Correlates of Memory in Non-human Primates

    Science.gov (United States)

    Jutras, Michael J.; Buffalo, Elizabeth A.

    2013-01-01

    The ability to navigate through our environment, explore with our senses, track the passage of time, and integrate these various components to form the experiences which make up our lives is shared among humans and animals. The use of animal models to study memory, coupled with electrophysiological techniques that permit the direct measurement of neural activity as memories are formed and retrieved, has provided a wealth of knowledge about these mechanisms. Here, we discuss current knowledge regarding the specific role of neural oscillations in memory, with particular emphasis on findings derived from non-human primates. Some of these findings provide evidence for the existence in the primate brain of mechanisms previously identified only in rodents and other lower mammals, while other findings suggest parallels between memory-related activity and processes observed in other cognitive modalities, including attention and sensory perception. Taken together, these results provide insight into how network activity may be organized to promote memory formation, and suggest that key aspects of this activity are similar across species, providing important information about the organization of human memory. PMID:23867554

  19. A Time-predictable Memory Network-on-Chip

    DEFF Research Database (Denmark)

    Schoeberl, Martin; Chong, David VH; Puffitsch, Wolfgang

    2014-01-01

    To derive safe bounds on worst-case execution times (WCETs), all components of a computer system need to be time-predictable: the processor pipeline, the caches, the memory controller, and memory arbitration on a multicore processor. This paper presents a solution for time-predictable memory...... arbitration and access for chip-multiprocessors. The memory network-on-chip is organized as a tree with time-division multiplexing (TDM) of accesses to the shared memory. The TDM based arbitration completely decouples processor cores and allows WCET analysis of the memory accesses on individual cores without...

  20. A Time-predictable Memory Network-on-Chip

    DEFF Research Database (Denmark)

    Schoeberl, Martin; Chong, David VH; Puffitsch, Wolfgang

    2014-01-01

    To derive safe bounds on worst-case execution times (WCETs), all components of a computer system need to be time-predictable: the processor pipeline, the caches, the memory controller, and memory arbitration on a multicore processor. This paper presents a solution for time-predictable memory...... arbitration and access for chip-multiprocessors. The memory network-on-chip is organized as a tree with time-division multiplexing (TDM) of accesses to the shared memory. The TDM based arbitration completely decouples processor cores and allows WCET analysis of the memory accesses on individual cores without...

  1. A New Conceptualization of Human Visual Sensory-Memory

    OpenAIRE

    Ogmen, Haluk; Herzog, Michael H.

    2016-01-01

    Memory is an essential component of cognition and disorders of memory have significant individual and societal costs. The Atkinson–Shiffrin “modal model” forms the foundation of our understanding of human memory. It consists of three stores: Sensory Memory (SM), whose visual component is called iconic memory, Short-Term Memory (STM; also called working memory, WM), and Long-Term Memory (LTM). Since its inception, shortcomings of all three components of the modal model have been identified. Wh...

  2. Orbitofrontal contributions to human working memory.

    Science.gov (United States)

    Barbey, Aron K; Koenigs, Michael; Grafman, Jordan

    2011-04-01

    Although cognitive neuroscience has made remarkable progress in understanding the involvement of the prefrontal cortex in human memory, the necessity of the orbitofrontal cortex for key competencies of working memory remains largely unexplored. We therefore studied human brain lesion patients to determine whether the orbitofrontal cortex is necessary for working memory function, administering subtests of the Wechsler memory scale, the Wechsler adult intelligence scale, and the n-back task to 3 participant groups: orbitofrontal lesions (n = 24), prefrontal lesions not involving orbitofrontal cortex (n = 40), and no brain lesions (n = 54). Orbitofrontal damage was reliably associated with deficits on neuropsychological tests involving the coordination of working memory maintenance, manipulation, and monitoring processes (n-back task) but not on pure tests of working memory maintenance (digit/spatial span forward) or manipulation (digit/spatial span backward and letter-number sequencing). Our findings elucidate a central component of the neural architecture of working memory, providing key neuropsychological evidence for the necessity of the orbitofrontal cortex in executive control functions underlying the joint maintenance, manipulation, and monitoring of information in working memory.

  3. Short-term memory in networks of dissociated cortical neurons.

    Science.gov (United States)

    Dranias, Mark R; Ju, Han; Rajaram, Ezhilarasan; VanDongen, Antonius M J

    2013-01-30

    Short-term memory refers to the ability to store small amounts of stimulus-specific information for a short period of time. It is supported by both fading and hidden memory processes. Fading memory relies on recurrent activity patterns in a neuronal network, whereas hidden memory is encoded using synaptic mechanisms, such as facilitation, which persist even when neurons fall silent. We have used a novel computational and optogenetic approach to investigate whether these same memory processes hypothesized to support pattern recognition and short-term memory in vivo, exist in vitro. Electrophysiological activity was recorded from primary cultures of dissociated rat cortical neurons plated on multielectrode arrays. Cultures were transfected with ChannelRhodopsin-2 and optically stimulated using random dot stimuli. The pattern of neuronal activity resulting from this stimulation was analyzed using classification algorithms that enabled the identification of stimulus-specific memories. Fading memories for different stimuli, encoded in ongoing neural activity, persisted and could be distinguished from each other for as long as 1 s after stimulation was terminated. Hidden memories were detected by altered responses of neurons to additional stimulation, and this effect persisted longer than 1 s. Interestingly, network bursts seem to eliminate hidden memories. These results are similar to those that have been reported from similar experiments in vivo and demonstrate that mechanisms of information processing and short-term memory can be studied using cultured neuronal networks, thereby setting the stage for therapeutic applications using this platform.

  4. Generalized memory associativity in a network model for the neuroses

    Science.gov (United States)

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

    2009-03-01

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

  5. Generalized memory associativity in a network model for the neuroses.

    Science.gov (United States)

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

    2009-03-01

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

  6. Human factors in network security

    OpenAIRE

    Jones, Francis B.

    1991-01-01

    Human factors, such as ethics and education, are important factors in network information security. This thesis determines which human factors have significant influence on network security. Those factors are examined in relation to current security devices and procedures. Methods are introduced to evaluate security effectiveness by incorporating the appropriate human factors into network security controls

  7. Increased functional connectivity within memory networks following memory rehabilitation in multiple sclerosis.

    Science.gov (United States)

    Leavitt, Victoria M; Wylie, Glenn R; Girgis, Peter A; DeLuca, John; Chiaravalloti, Nancy D

    2014-09-01

    Identifying effective behavioral treatments to improve memory in persons with learning and memory impairment is a primary goal for neurorehabilitation researchers. Memory deficits are the most common cognitive symptom in multiple sclerosis (MS), and hold negative professional and personal consequences for people who are often in the prime of their lives when diagnosed. A 10-session behavioral treatment, the modified Story Memory Technique (mSMT), was studied in a randomized, placebo-controlled clinical trial. Behavioral improvements and increased fMRI activation were shown after treatment. Here, connectivity within the neural networks underlying memory function was examined with resting-state functional connectivity (RSFC) in a subset of participants from the clinical trial. We hypothesized that the treatment would result in increased integrity of connections within two primary memory networks of the brain, the hippocampal memory network, and the default network (DN). Seeds were placed in left and right hippocampus, and the posterior cingulate cortex. Increased connectivity was found between left hippocampus and cortical regions specifically involved in memory for visual imagery, as well as among critical hubs of the DN. These results represent the first evidence for efficacy of a behavioral intervention to impact the integrity of neural networks subserving memory functions in persons with MS.

  8. Dynamics of the Human Structural Connectome Underlying Working Memory Training

    Science.gov (United States)

    Metzler-Baddeley, Claudia; Foley, Sonya; Jones, Derek K.

    2016-01-01

    Brain region-specific changes have been demonstrated with a variety of cognitive training interventions. The effect of cognitive training on brain subnetworks in humans, however, remains largely unknown, with studies limited to functional networks. Here, we used a well-established working memory training program and state-of-the art neuroimaging methods in 40 healthy adults (21 females, mean age 26.5 years). Near and far-transfer training effects were assessed using computerized working memory and executive function tasks. Adaptive working memory training led to improvement on (non)trained working memory tasks and generalization to tasks of reasoning and inhibition. Graph theoretical analysis of the structural (white matter) network connectivity (“connectome”) revealed increased global integration within a frontoparietal attention network following adaptive working memory training compared with the nonadaptive group. Furthermore, the impact on the outcome of graph theoretical analyses of different white matter metrics to infer “connection strength” was evaluated. Increased efficiency of the frontoparietal network was best captured when using connection strengths derived from MR metrics that are thought to be more sensitive to differences in myelination (putatively indexed by the [quantitative] longitudinal relaxation rate, R1) than previously used diffusion MRI metrics (fractional anisotropy or fiber-tracking recovered streamlines). Our findings emphasize the critical role of specific microstructural markers in providing important hints toward the mechanisms underpinning training-induced plasticity that may drive working memory improvement in clinical populations. SIGNIFICANCE STATEMENT This is the first study to explore training-induced changes in the structural connectome using a well-controlled design to examine cognitive training with up-to-date neuroimaging methods. We found changes in global integration based on white matter connectivity within a

  9. Human Environmental Disease Network

    DEFF Research Database (Denmark)

    Taboureau, Olivier; Audouze, Karine

    2017-01-01

    During the past decades, many epidemiological, toxicological and biological studies have been performed to assess the role of environmental chemicals as potential toxicants for diverse human disorders. However, the relationships between diseases based on chemical exposure have been rarely studied...... by computational biology. We developed a human environmental disease network (EDN) to explore and suggest novel disease-disease and chemical-disease relationships. The presented scored EDN model is built upon the integration on systems biology and chemical toxicology using chemical contaminants information...

  10. Cognitive memory: cellular and network machineries and their top-down control.

    Science.gov (United States)

    Miyashita, Yasushi

    2004-10-15

    A brain-wide distributed network orchestrates cognitive memorizing and remembering of explicit memory (i.e., memory of facts and events). The network was initially identified in humans and is being systematically investigated in molecular/genetic, single-unit, lesion, and imaging studies in animals. The types of memory identified in humans are extended into animals as episodic-like (event) memory or semantic-like (fact) memory. The unique configurational association between environmental stimuli and behavioral context, which is likely the basis of episodic-like memory, depends on neural circuits in the medial temporal lobe, whereas memory traces representing repeated associations, which is likely the basis of semantic-like memory, are consolidated in the domain-specific regions in the temporal cortex. These regions are reactivated during remembering and contribute to the contents of a memory. Two types of retrieval signal reach the cortical representations. One runs from the frontal cortex for active (or effortful) retrieval (top-down signal), and the other spreads backward from the medial temporal lobe for automatic retrieval. By sending the top-down signal to the temporal cortex, frontal regions manipulate and organize to-be-remembered information, devise strategies for retrieval, and also monitor the outcome, with dissociated frontal regions making functionally separate contributions. The challenge is to understand the hierarchical interactions between these multiple cortical areas, not only with a correlational analysis but also with an interventional study demonstrating the causal necessity and the direction of the causality.

  11. Recurrent Network Models of Sequence Generation and Memory.

    Science.gov (United States)

    Rajan, Kanaka; Harvey, Christopher D; Tank, David W

    2016-04-01

    Sequential activation of neurons is a common feature of network activity during a variety of behaviors, including working memory and decision making. Previous network models for sequences and memory emphasized specialized architectures in which a principled mechanism is pre-wired into their connectivity. Here we demonstrate that, starting from random connectivity and modifying a small fraction of connections, a largely disordered recurrent network can produce sequences and implement working memory efficiently. We use this process, called Partial In-Network Training (PINning), to model and match cellular resolution imaging data from the posterior parietal cortex during a virtual memory-guided two-alternative forced-choice task. Analysis of the connectivity reveals that sequences propagate by the cooperation between recurrent synaptic interactions and external inputs, rather than through feedforward or asymmetric connections. Together our results suggest that neural sequences may emerge through learning from largely unstructured network architectures.

  12. Two-Layer Feedback Neural Networks with Associative Memories

    Institute of Scientific and Technical Information of China (English)

    WU Gui-Kun; ZHAO Hong

    2008-01-01

    We construct a two-layer feedback neural network by a Monte Carlo based algorithm to store memories as fixed-point attractors or as limit-cycle attractors. Special attention is focused on comparing the dynamics of the network with limit-cycle attractors and with fixed-point attractors. It is found that the former has better retrieval property than the latter. Particularly, spurious memories may be suppressed completely when the memories are stored as a long-limit cycle. Potential application of limit-cycle-attractor networks is discussed briefly.

  13. An evolutionary approach to associative memory in recurrent neural networks

    CERN Document Server

    Fujita, Sh; Fujita, Sh; Nishimura, H

    1994-01-01

    Abstract: In this paper, we investigate the associative memory in recurrent neural networks, based on the model of evolving neural networks proposed by Nolfi, Miglino and Parisi. Experimentally developed network has highly asymmetric synaptic weights and dilute connections, quite different from those of the Hopfield model. Some results on the effect of learning efficiency on the evolution are also presented.

  14. Tetanic stimulation of cortical networks induces parallel memory

    NARCIS (Netherlands)

    Veenendaal, van Tamar; Witteveen, Tim; Feber, le Joost; Akay, M

    2013-01-01

    The mechanisms behind memory have been studied mainly in artificial neural networks. Several mechanisms have been proposed, but it remains unclear yet if and how these findings can be translated to biological networks. Here we unravel part of the mechanism by showing that cultured neuronal networks

  15. Double-pattern associative memory neural network with pattern loop

    Institute of Scientific and Technical Information of China (English)

    Jian WANG; Zongyuan MAO

    2004-01-01

    A double-patrern associative memory neural network with "pattern loop" is proposed. It can store 2N bit bipolar binary Patterns up to the order of 22N, retrieve part or all of the stored patrems which all have the minimum Hamming distance with input Pattern, completely eliminate spurious Patterns, and has higher storing efficiency and reliability than conventional associative memory. The length of a Pattern stored in this associative memory can be easily extended from 2N to kN.

  16. Memory, scene construction, and the human hippocampus.

    Science.gov (United States)

    Kim, Soyun; Dede, Adam J O; Hopkins, Ramona O; Squire, Larry R

    2015-04-14

    We evaluated two different perspectives about the function of the human hippocampus--one that emphasizes the importance of memory and another that emphasizes the importance of spatial processing and scene construction. We gave tests of boundary extension, scene construction, and memory to patients with lesions limited to the hippocampus or large lesions of the medial temporal lobe. The patients were intact on all of the spatial tasks and impaired on all of the memory tasks. We discuss earlier studies that associated performance on these spatial tasks to hippocampal function. Our results demonstrate the importance of medial temporal lobe structures for memory and raise doubts about the idea that these structures have a prominent role in spatial cognition.

  17. Social working memory: Neurocognitive networks and directions for future research

    Directory of Open Access Journals (Sweden)

    Meghan L Meyer

    2012-12-01

    Full Text Available Navigating the social world requires the ability to maintain and manipulate information about people’s beliefs, traits, and mental states. We characterize this capacity as social working memory. To date, very little research has explored this phenomenon, in part because of the assumption that general working memory systems would support working memory for social information. Various lines of research, however, suggest that social cognitive processing relies on a neurocognitive network (i.e., the ‘mentalizing network’ that is functionally distinct from, and considered antagonistic with, the canonical working memory network. Here, we review evidence suggesting that demanding social cognition requires social working memory and that both the mentalizing and canonical working memory neurocognitive networks support social working memory. The neural data run counter to the common finding of parametric decreases in mentalizing regions as a function of working memory demand and suggest that the mentalizing network can support demanding cognition, when it is demanding social cognition. Implications for individual differences in social cognition and pathologies of social cognition are discussed.

  18. Mnemonic Training Reshapes Brain Networks to Support Superior Memory.

    Science.gov (United States)

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

    2017-03-08

    Memory skills strongly differ across the general population; however, little is known about the brain characteristics supporting superior memory performance. Here we assess functional brain network organization of 23 of the world's most successful memory athletes and matched controls with fMRI during both task-free resting state baseline and active memory encoding. We demonstrate that, in a group of naive controls, functional connectivity changes induced by 6 weeks of mnemonic training were correlated with the network organization that distinguishes athletes from controls. During rest, this effect was mainly driven by connections between rather than within the visual, medial temporal lobe and default mode networks, whereas during task it was driven by connectivity within these networks. Similarity with memory athlete connectivity patterns predicted memory improvements up to 4 months after training. In conclusion, mnemonic training drives distributed rather than regional changes, reorganizing the brain's functional network organization to enable superior memory performance. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Using chaotic artificial neural networks to model memory in the brain

    Science.gov (United States)

    Aram, Zainab; Jafari, Sajad; Ma, Jun; Sprott, Julien C.; Zendehrouh, Sareh; Pham, Viet-Thanh

    2017-03-01

    In the current study, a novel model for human memory is proposed based on the chaotic dynamics of artificial neural networks. This new model explains a biological fact about memory which is not yet explained by any other model: There are theories that the brain normally works in a chaotic mode, while during attention it shows ordered behavior. This model uses the periodic windows observed in a previously proposed model for the brain to store and then recollect the information.

  20. ABOUT HYBRID BIDIRECTIONAL ASSOCIATIVE MEMORY NEURAL NETWORKS WITH DISCRETE DELAYS

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    In this paper, hybrid bidirectional associative memory neural networks with discrete delays is considered. By ingeniously importing real parameters di > 0(i = 1,2,···,n) which can be adjusted, we establish some new sufficient conditions for the dynamical characteristics of hybrid bidirectional associative memory neural networks with discrete delays by the method of variation of parameters and some analysis techniques. Our results generalize and improve the related results in [10,11]. Our work is significant...

  1. Quantifying the reconfiguration of intrinsic networks during working memory.

    Directory of Open Access Journals (Sweden)

    Jessica R Cohen

    Full Text Available Rapid, flexible reconfiguration of connections across brain regions is thought to underlie successful cognitive control. Two intrinsic networks in particular, the cingulo-opercular (CO and fronto-parietal (FP, are thought to underlie two operations critical for cognitive control: task-set maintenance/tonic alertness and adaptive, trial-by-trial updating. Using functional magnetic resonance imaging, we directly tested whether the functional connectivity of the CO and FP networks was related to cognitive demands and behavior. We focused on working memory because of evidence that during working memory tasks the entire brain becomes more integrated. When specifically probing the CO and FP cognitive control networks, we found that individual regions of both intrinsic networks were active during working memory and, as expected, integration across the two networks increased during task blocks that required cognitive control. Crucially, increased integration between each of the cognitive control networks and a task-related, non-cognitive control network (the hand somatosensory-motor network; SM was related to increased accuracy. This implies that dynamic reconfiguration of the CO and FP networks so as to increase their inter-network communication underlies successful working memory.

  2. Canonical correlation between LFP network and spike network during working memory task in rat.

    Science.gov (United States)

    Yi, Hu; Zhang, Xiaofan; Bai, Wenwen; Liu, Tiaotiao; Tian, Xin

    2015-08-01

    Working memory refers to a system to temporary holding and manipulation of information. Previous studies suggested that local field potentials (LFPs) and spikes as well as their coordination provide potential mechanism of working memory. Popular methods for LFP-spike coordination only focus on the two modality signals, isolating each channel from multi-channel data, ignoring the entirety of the networked brain. Therefore, we investigated the coordination between the LFP network and spike network to achieve a better understanding of working memory. Multi-channel LFPs and spikes were simultaneously recorded in rat prefrontal cortex via microelectrode array during a Y-maze working memory task. Functional connectivity in the LFP network and spike network was respectively estimated by the directed transfer function (DTF) and maximum likelihood estimation (MLE). Then the coordination between the two networks was quantified via canonical correlation analysis (CCA). The results show that the canonical correlation (CC) varied during the working memory task. The CC-curve peaked before the choice point, describing the coordination between LFP network and spike network enhanced greatly. The CC value in working memory showed a significant higher level than inter-trial interval. Our results indicate that the enhanced canonical correlation between the LFP network and spike network may provide a potential network integration mechanism for working memory.

  3. Hippocampal sleep features: relations to human memory function.

    Science.gov (United States)

    Ferrara, Michele; Moroni, Fabio; De Gennaro, Luigi; Nobili, Lino

    2012-01-01

    The recent spread of intracranial electroencephalographic (EEG) recording techniques for presurgical evaluation of drug-resistant epileptic patients is providing new information on the activity of different brain structures during both wakefulness and sleep. The interest has been mainly focused on the medial temporal lobe, and in particular the hippocampal formation, whose peculiar local sleep features have been recently described, providing support to the idea that sleep is not a spatially global phenomenon. The study of the hippocampal sleep electrophysiology is particularly interesting because of its central role in the declarative memory formation. Recent data indicate that sleep contributes to memory formation. Therefore, it is relevant to understand whether specific patterns of activity taking place during sleep are related to memory consolidation processes. Fascinating similarities between different states of consciousness (wakefulness, REM sleep, non-REM sleep) in some electrophysiological mechanisms underlying cognitive processes have been reported. For instance, large-scale synchrony in gamma activity is important for waking memory and perception processes, and its changes during sleep may be the neurophysiological substrate of sleep-related deficits of declarative memory. Hippocampal activity seems to specifically support memory consolidation during sleep, through specific coordinated neurophysiological events (slow waves, spindles, ripples) that would facilitate the integration of new information into the pre-existing cortical networks. A few studies indeed provided direct evidence that rhinal ripples as well as slow hippocampal oscillations are correlated with memory consolidation in humans. More detailed electrophysiological investigations assessing the specific relations between different types of memory consolidation and hippocampal EEG features are in order. These studies will add an important piece of knowledge to the elucidation of the ultimate

  4. Hippocampal sleep features: relations to human memory function

    Directory of Open Access Journals (Sweden)

    Michele eFerrara

    2012-04-01

    Full Text Available The recent spread of intracranial EEG recordings techniques for presurgical evaluation of drug-resistant epileptic patients is providing new information on the activity of different brain structures during both wakefulness and sleep. The interest has been mainly focused on the medial temporal lobe, and in particular the hippocampal formation, whose peculiar local sleep features have been recently described, providing support to the idea that sleep is not a spatially global phenomenon. The study of the hippocampal sleep electrophysiology is particularly interesting because of its central role in the declarative memory formation. Recent data indicate that sleep contributes to memory formation. Therefore, it is relevant to understand whether specific pattern of activity taking place during sleep are related to memory consolidation processes. Fascinating similarities between different states of consciousness (wakefulness, REM sleep, NREM sleep in some electrophysiological mechanisms underlying cognitive processes have been reported. For instance, large-scale synchrony in gamma activity is important for waking memory and perception processes, and its changes during sleep may be the neurophysiological substrate of sleep-related deficits of declarative memory. Hippocampal activity seems to specifically support memory consolidation during sleep, through specific coordinated neurophysiological events (slow waves, spindles, ripples that would facilitate the integration of new information into the pre-existing cortical networks. A few studies indeed provided direct evidence that rhinal ripples as well as slow hippocampal oscillations are correlated with memory consolidation in humans. More detailed electrophysiological investigations assessing the specific relations between different types of memory consolidation and hippocampal EEG features are in order. These studies will add an important piece of knowledge to the elucidation of the ultimate sleep

  5. Human T Cell Memory: A Dynamic View

    Directory of Open Access Journals (Sweden)

    Derek C. Macallan

    2017-02-01

    Full Text Available Long-term T cell-mediated protection depends upon the formation of a pool of memory cells to protect against future pathogen challenge. In this review we argue that looking at T cell memory from a dynamic viewpoint can help in understanding how memory populations are maintained following pathogen exposure or vaccination. For example, a dynamic view resolves the apparent paradox between the relatively short lifespans of individual memory cells and very long-lived immunological memory by focussing on the persistence of clonal populations, rather than individual cells. Clonal survival is achieved by balancing proliferation, death and differentiation rates within and between identifiable phenotypic pools; such pools correspond broadly to sequential stages in the linear differentiation pathway. Each pool has its own characteristic kinetics, but only when considered as a population; single cells exhibit considerable heterogeneity. In humans, we tend to concentrate on circulating cells, but memory T cells in non-lymphoid tissues and bone marrow are increasingly recognised as critical for immune defence; their kinetics, however, remain largely unexplored. Considering vaccination from this viewpoint shifts the focus from the size of the primary response to the survival of the clone and enables identification of critical system pinch-points and opportunities to improve vaccine efficacy.

  6. Strategies to associate memories by unsupervised learning in neural networks

    Science.gov (United States)

    Agnes, E. J.; Mizusaki, B. E. P.; Erichsen, R., Jr.; Brunnet, L. G.

    2013-01-01

    In this work we study the effects of three different strategies to associate memories in a neural network composed by both excitatory and inhibitory spiking neurons, which are randomly connected through recurrent excitatory and inhibitory synapses. The system is intended to store a number of memories, associated to spatial external inputs. The strategies consist in the presentation of the input patterns through trials in: i) ordered sequence; ii) random sequence; iii) clustered sequences. In addition, an order parameter indicating the correlation between the trials' activities is introduced to compute associative memory capacities and the quality of memory retrieval.

  7. How Human Memory and Working Memory Work in Second Language Acquisition

    OpenAIRE

    小那覇, 洋子; Onaha, Hiroko

    2014-01-01

    We often draw an analogy between human memory and computers. Information around us is taken into our memory storage first, and then we use the information in storage whatever we need it in our daily life. Linguistic information is also in storage and we process our thoughts based on the memory that is stored. Memory storage consists of multiple memory systems; one of which is called working memory that includes short-term memory. Working memory is the central system that underpins the process...

  8. External-Memory Network Analysis Algorithms for Naturally Sparse Graphs

    CERN Document Server

    Goodrich, Michael T

    2011-01-01

    In this paper, we present a number of network-analysis algorithms in the external-memory model. We focus on methods for large naturally sparse graphs, that is, n-vertex graphs that have O(n) edges and are structured so that this sparsity property holds for any subgraph of such a graph. We give efficient external-memory algorithms for the following problems for such graphs: - Finding an approximate d-degeneracy ordering; - Finding a cycle of length exactly c; - Enumerating all maximal cliques. Such problems are of interest, for example, in the analysis of social networks, where they are used to study network cohesion.

  9. NATO Human View Architecture and Human Networks

    Science.gov (United States)

    Handley, Holly A. H.; Houston, Nancy P.

    2010-01-01

    The NATO Human View is a system architectural viewpoint that focuses on the human as part of a system. Its purpose is to capture the human requirements and to inform on how the human impacts the system design. The viewpoint contains seven static models that include different aspects of the human element, such as roles, tasks, constraints, training and metrics. It also includes a Human Dynamics component to perform simulations of the human system under design. One of the static models, termed Human Networks, focuses on the human-to-human communication patterns that occur as a result of ad hoc or deliberate team formation, especially teams distributed across space and time. Parameters of human teams that effect system performance can be captured in this model. Human centered aspects of networks, such as differences in operational tempo (sense of urgency), priorities (common goal), and team history (knowledge of the other team members), can be incorporated. The information captured in the Human Network static model can then be included in the Human Dynamics component so that the impact of distributed teams is represented in the simulation. As the NATO militaries transform to a more networked force, the Human View architecture is an important tool that can be used to make recommendations on the proper mix of technological innovations and human interactions.

  10. On neural networks that design neural associative memories.

    Science.gov (United States)

    Chan, H Y; Zak, S H

    1997-01-01

    The design problem of generalized brain-state-in-a-box (GBSB) type associative memories is formulated as a constrained optimization program, and "designer" neural networks for solving the program in real time are proposed. The stability of the designer networks is analyzed using Barbalat's lemma. The analyzed and synthesized neural associative memories do not require symmetric weight matrices. Two types of the GBSB-based associative memories are analyzed, one when the network trajectories are constrained to reside in the hypercube [-1, 1](n) and the other type when the network trajectories are confined to stay in the hypercube [0, 1](n). Numerical examples and simulations are presented to illustrate the results obtained.

  11. Effect of memory in non-Markovian Boolean networks

    CERN Document Server

    Ebadi, Haleh; Ausloos, Marcel; Jafari, GholamReza

    2016-01-01

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

  12. Memory Compression Techniques for Network Address Management in MPI

    Energy Technology Data Exchange (ETDEWEB)

    Guo, Yanfei; Archer, Charles J.; Blocksome, Michael; Parker, Scott; Bland, Wesley; Raffenetti, Ken; Balaji, Pavan

    2017-05-29

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

  13. How memory generates heterogeneous dynamics in temporal networks

    CERN Document Server

    Vestergaard, Christian L; Barrat, Alain

    2014-01-01

    Empirical temporal networks display strong heterogeneities in their dynamics, which profoundly affect processes taking place on these networks, such as rumor and epidemic spreading. Despite the recent wealth of data on temporal networks, little work has been devoted to the understanding of how such heterogeneities can emerge from microscopic mechanisms at the level of nodes and links. Here we show that long-term memory effects are present in the creation and disappearance of links in empirical networks. We thus consider a simple generative modeling framework for temporal networks able to incorporate these memory mechanisms. This allows us to study separately the role of each of these mechanisms in the emergence of heterogeneous network dynamics. In particular, we show analytically and numerically how heterogeneous distributions of contact durations, of inter-contact durations and of numbers of contacts per link emerge. We also study the individual effect of heterogeneities on dynamical processes, such as the ...

  14. Hybrid computing using a neural network with dynamic external memory.

    Science.gov (United States)

    Graves, Alex; Wayne, Greg; Reynolds, Malcolm; Harley, Tim; Danihelka, Ivo; Grabska-Barwińska, Agnieszka; Colmenarejo, Sergio Gómez; Grefenstette, Edward; Ramalho, Tiago; Agapiou, John; Badia, Adrià Puigdomènech; Hermann, Karl Moritz; Zwols, Yori; Ostrovski, Georg; Cain, Adam; King, Helen; Summerfield, Christopher; Blunsom, Phil; Kavukcuoglu, Koray; Hassabis, Demis

    2016-10-27

    Artificial neural networks are remarkably adept at sensory processing, sequence learning and reinforcement learning, but are limited in their ability to represent variables and data structures and to store data over long timescales, owing to the lack of an external memory. Here we introduce a machine learning model called a differentiable neural computer (DNC), which consists of a neural network that can read from and write to an external memory matrix, analogous to the random-access memory in a conventional computer. Like a conventional computer, it can use its memory to represent and manipulate complex data structures, but, like a neural network, it can learn to do so from data. When trained with supervised learning, we demonstrate that a DNC can successfully answer synthetic questions designed to emulate reasoning and inference problems in natural language. We show that it can learn tasks such as finding the shortest path between specified points and inferring the missing links in randomly generated graphs, and then generalize these tasks to specific graphs such as transport networks and family trees. When trained with reinforcement learning, a DNC can complete a moving blocks puzzle in which changing goals are specified by sequences of symbols. Taken together, our results demonstrate that DNCs have the capacity to solve complex, structured tasks that are inaccessible to neural networks without external read-write memory.

  15. Supramodal parametric working memory processing in humans.

    Science.gov (United States)

    Spitzer, Bernhard; Blankenburg, Felix

    2012-03-07

    Previous studies of delayed-match-to-sample (DMTS) frequency discrimination in animals and humans have succeeded in delineating the neural signature of frequency processing in somatosensory working memory (WM). During retention of vibrotactile frequencies, stimulus-dependent single-cell and population activity in prefrontal cortex was found to reflect the task-relevant memory content, whereas increases in occipital alpha activity signaled the disengagement of areas not relevant for the tactile task. Here, we recorded EEG from human participants to determine the extent to which these mechanisms can be generalized to frequency retention in the visual and auditory domains. Subjects performed analogous variants of a DMTS frequency discrimination task, with the frequency information presented either visually, auditorily, or by vibrotactile stimulation. Examining oscillatory EEG activity during frequency retention, we found characteristic topographical distributions of alpha power over visual, auditory, and somatosensory cortices, indicating systematic patterns of inhibition and engagement of early sensory areas, depending on stimulus modality. The task-relevant frequency information, in contrast, was found to be represented in right prefrontal cortex, independent of presentation mode. In each of the three modality conditions, parametric modulations of prefrontal upper beta activity (20-30 Hz) emerged, in a very similar manner as recently found in vibrotactile tasks. Together, the findings corroborate a view of parametric WM as supramodal internal scaling of abstract quantity information and suggest strong relevance of previous evidence from vibrotactile work for a more general framework of quantity processing in human working memory.

  16. Attentional networks and visuospatial working memory capacity in social anxiety.

    Science.gov (United States)

    Moriya, Jun

    2016-12-02

    Social anxiety is associated with attentional bias and working memory for emotional stimuli; however, the ways in which social anxiety affects cognitive functions involving non-emotional stimuli remains unclear. The present study focused on the role of attentional networks (i.e. alerting, orienting, and executive control networks) and visuospatial working memory capacity (WMC) for non-emotional stimuli in the context of social anxiety. One hundred and seventeen undergraduates completed questionnaires on social anxiety. They then performed an attentional network test and a change detection task to measure visuospatial WMC. Orienting network and visuospatial WMC were positively correlated with social anxiety. A multiple regression analysis showed significant positive associations of alerting, orienting, and visuospatial WMC with social anxiety. Alerting, orienting networks, and high visuospatial WMC for non-emotional stimuli may predict degree of social anxiety.

  17. Meeting the memory challenges of brain-scale network simulation

    Directory of Open Access Journals (Sweden)

    Susanne eKunkel

    2012-01-01

    Full Text Available The development of high-performance simulation software is crucial for studying the brain connectome. Using connectome data to generate neurocomputational models requires software capable of coping with models on a variety of scales: from the microscale, investigating plasticity and dynamics of circuits in local networks, to the macroscale, investigating the interactions between distinct brain regions. Prior to any serious dynamical investigation, the first task of network simulations is to check the consistency of data integrated in the connectome and constrain ranges for yet unknown parameters. Thanks to distributed computing techniques, it is possible today to routinely simulate local cortical networks of around 10^5 neurons with up to 10^9 synapses on clusters and multi-processor shared-memory machines. However, brain-scale networks are one or two orders of magnitude larger than such local networks, in terms of numbers of neurons and synapses as well as in terms of computational load. Such networks have been studied in individual studies, but the underlying simulation technologies have neither been described in sufficient detail to be reproducible nor made publicly available. Here, we discover that as the network model sizes approach the regime of meso- and macroscale simulations, memory consumption on individual compute nodes becomes a critical bottleneck. This is especially relevant on modern supercomputers such as the Bluegene/P architecture where the available working memory per CPU core is rather limited. We develop a simple linear model to analyze the memory consumption of the constituent components of a neuronal simulator as a function of network size and the number of cores used. This approach has multiple benefits. The model enables identification of key contributing components to memory saturation and prediction of the effects of potential improvements to code before any implementation takes place.

  18. Musical and verbal semantic memory: two distinct neural networks?

    Science.gov (United States)

    Groussard, M; Viader, F; Hubert, V; Landeau, B; Abbas, A; Desgranges, B; Eustache, F; Platel, H

    2010-02-01

    Semantic memory has been investigated in numerous neuroimaging and clinical studies, most of which have used verbal or visual, but only very seldom, musical material. Clinical studies have suggested that there is a relative neural independence between verbal and musical semantic memory. In the present study, "musical semantic memory" is defined as memory for "well-known" melodies without any knowledge of the spatial or temporal circumstances of learning, while "verbal semantic memory" corresponds to general knowledge about concepts, again without any knowledge of the spatial or temporal circumstances of learning. Our aim was to compare the neural substrates of musical and verbal semantic memory by administering the same type of task in each modality. We used high-resolution PET H(2)O(15) to observe 11 young subjects performing two main tasks: (1) a musical semantic memory task, where the subjects heard the first part of familiar melodies and had to decide whether the second part they heard matched the first, and (2) a verbal semantic memory task with the same design, but where the material consisted of well-known expressions or proverbs. The musical semantic memory condition activated the superior temporal area and inferior and middle frontal areas in the left hemisphere and the inferior frontal area in the right hemisphere. The verbal semantic memory condition activated the middle temporal region in the left hemisphere and the cerebellum in the right hemisphere. We found that the verbal and musical semantic processes activated a common network extending throughout the left temporal neocortex. In addition, there was a material-dependent topographical preference within this network, with predominantly anterior activation during musical tasks and predominantly posterior activation during semantic verbal tasks. Copyright (c) 2009 Elsevier Inc. All rights reserved.

  19. Noradrenergic enhancement of associative fear memory in humans

    NARCIS (Netherlands)

    Soeter, M.; Kindt, M.

    2011-01-01

    Ample evidence in animals and humans supports the noradrenergic modulation in the formation of emotional memory. However, in humans the effects of stress on emotional memory are traditionally investigated by declarative memory tests (e.g., recall, recognition) for non-associative emotional stimuli (

  20. Episodic memory and appetite regulation in humans.

    Directory of Open Access Journals (Sweden)

    Jeffrey M Brunstrom

    Full Text Available Psychological and neurobiological evidence implicates hippocampal-dependent memory processes in the control of hunger and food intake. In humans, these have been revealed in the hyperphagia that is associated with amnesia. However, it remains unclear whether 'memory for recent eating' plays a significant role in neurologically intact humans. In this study we isolated the extent to which memory for a recently consumed meal influences hunger and fullness over a three-hour period. Before lunch, half of our volunteers were shown 300 ml of soup and half were shown 500 ml. Orthogonal to this, half consumed 300 ml and half consumed 500 ml. This process yielded four separate groups (25 volunteers in each. Independent manipulation of the 'actual' and 'perceived' soup portion was achieved using a computer-controlled peristaltic pump. This was designed to either refill or draw soup from a soup bowl in a covert manner. Immediately after lunch, self-reported hunger was influenced by the actual and not the perceived amount of soup consumed. However, two and three hours after meal termination this pattern was reversed - hunger was predicted by the perceived amount and not the actual amount. Participants who thought they had consumed the larger 500-ml portion reported significantly less hunger. This was also associated with an increase in the 'expected satiation' of the soup 24-hours later. For the first time, this manipulation exposes the independent and important contribution of memory processes to satiety. Opportunities exist to capitalise on this finding to reduce energy intake in humans.

  1. The encoding/retrieval flip: interactions between memory performance and memory stage and relationship to intrinsic cortical networks.

    Science.gov (United States)

    Huijbers, Willem; Schultz, Aaron P; Vannini, Patrizia; McLaren, Donald G; Wigman, Sarah E; Ward, Andrew M; Hedden, Trey; Sperling, Reisa A

    2013-07-01

    fMRI studies have linked the posteromedial cortex to episodic learning (encoding) and remembering (retrieval) processes. The posteromedial cortex is considered part of the default network and tends to deactivate during encoding but activate during retrieval, a pattern known as the encoding/retrieval flip. Yet, the exact relationship between the neural correlates of memory performance (hit/miss) and memory stage (encoding/retrieval) and the extent of overlap with intrinsic cortical networks remains to be elucidated. Using task-based fMRI, we isolated the pattern of activity associated with memory performance, memory stage, and the interaction between both. Using resting-state fMRI, we identified which intrinsic large-scale functional networks overlapped with regions showing task-induced effects. Our results demonstrated an effect of successful memory performance in regions associated with the control network and an effect of unsuccessful memory performance in the ventral attention network. We found an effect of memory retrieval in brain regions that span the default and control networks. Finally, we found an interaction between memory performance and memory stage in brain regions associated with the default network, including the posteromedial cortex, posterior parietal cortex, and parahippocampal cortex. We discuss these findings in relation to the encoding/retrieval flip. In general, the findings demonstrate that task-induced effects cut across intrinsic cortical networks. Furthermore, regions within the default network display functional dissociations, and this may have implications for the neural underpinnings of age-related memory disorders.

  2. Human intelligence and brain networks.

    Science.gov (United States)

    Colom, Roberto; Karama, Sherif; Jung, Rex E; Haier, Richard J

    2010-01-01

    Intelligence can be defined as a general mental ability for reasoning, problem solving, and learning. Because of its general nature, intelligence integrates cognitive functions such as perception, attention, memory, language, or planning. On the basis of this definition, intelligence can be reliably measured by standardized tests with obtained scores predicting several broad social outcomes such as educational achievement, job performance, health, and longevity. A detailed understanding of the brain mechanisms underlying this general mental ability could provide significant individual and societal benefits. Structural and functional neuroimaging studies have generally supported a frontoparietal network relevant for intelligence. This same network has also been found to underlie cognitive functions related to perception, short-term memory storage, and language. The distributed nature of this network and its involvement in a wide range of cognitive functions fits well with the integrative nature of intelligence. A new key phase of research is beginning to investigate how functional networks relate to structural networks, with emphasis on how distributed brain areas communicate with each other.

  3. Common Kibra alleles are associated with human memory performance.

    Science.gov (United States)

    Papassotiropoulos, Andreas; Stephan, Dietrich A; Huentelman, Matthew J; Hoerndli, Frederic J; Craig, David W; Pearson, John V; Huynh, Kim-Dung; Brunner, Fabienne; Corneveaux, Jason; Osborne, David; Wollmer, M Axel; Aerni, Amanda; Coluccia, Daniel; Hänggi, Jürgen; Mondadori, Christian R A; Buchmann, Andreas; Reiman, Eric M; Caselli, Richard J; Henke, Katharina; de Quervain, Dominique J-F

    2006-10-20

    Human memory is a polygenic trait. We performed a genome-wide screen to identify memory-related gene variants. A genomic locus encoding the brain protein KIBRA was significantly associated with memory performance in three independent, cognitively normal cohorts from Switzerland and the United States. Gene expression studies showed that KIBRA was expressed in memory-related brain structures. Functional magnetic resonance imaging detected KIBRA allele-dependent differences in hippocampal activations during memory retrieval. Evidence from these experiments suggests a role for KIBRA in human memory.

  4. Social networks: Evolving graphs with memory dependent edges

    Science.gov (United States)

    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.

  5. Application of neural network to humanoid robots-development of co-associative memory model.

    Science.gov (United States)

    Itoh, Kazuko; Miwa, Hiroyasu; Takanobu, Hideaki; Takanishi, Atsuo

    2005-01-01

    We have been studying a system of many harmonic oscillators (neurons) interacting via a chaotic force since 2002. Each harmonic oscillator is driven by chaotic force whose bifurcation parameter is modulated by the position of the harmonic oscillator. Moreover, a system of mutually coupled chaotic neural networks was investigated. Different patterns were stored in each network and the associative memory problem was discussed in these networks. Each network can retrieve the pattern stored in the other network. On the other hand, we have been developing new mechanisms and functions for a humanoid robot with the ability to express emotions and communicate with humans in a human-like manner. We introduced a mental model which consisted of the mental space, the mood, the equations of emotion, the robot personality, the need model, the consciousness model and the behavior model. This type of mental model was implemented in Emotion Expression Humanoid Robot WE-4RII (Waseda Eye No.4 Refined II). In this paper, an associative memory model using mutually coupled chaotic neural networks is proposed for retrieving optimum memory (recognition) in response to a stimulus. We implemented this model in Emotion Expression Humanoid Robot WE-4RII (Waseda Eye No.4 Refined II).

  6. Meeting the memory challenges of brain-scale network simulation.

    Science.gov (United States)

    Kunkel, Susanne; Potjans, Tobias C; Eppler, Jochen M; Plesser, Hans Ekkehard; Morrison, Abigail; Diesmann, Markus

    2011-01-01

    The development of high-performance simulation software is crucial for studying the brain connectome. Using connectome data to generate neurocomputational models requires software capable of coping with models on a variety of scales: from the microscale, investigating plasticity, and dynamics of circuits in local networks, to the macroscale, investigating the interactions between distinct brain regions. Prior to any serious dynamical investigation, the first task of network simulations is to check the consistency of data integrated in the connectome and constrain ranges for yet unknown parameters. Thanks to distributed computing techniques, it is possible today to routinely simulate local cortical networks of around 10(5) neurons with up to 10(9) synapses on clusters and multi-processor shared-memory machines. However, brain-scale networks are orders of magnitude larger than such local networks, in terms of numbers of neurons and synapses as well as in terms of computational load. Such networks have been investigated in individual studies, but the underlying simulation technologies have neither been described in sufficient detail to be reproducible nor made publicly available. Here, we discover that as the network model sizes approach the regime of meso- and macroscale simulations, memory consumption on individual compute nodes becomes a critical bottleneck. This is especially relevant on modern supercomputers such as the Blue Gene/P architecture where the available working memory per CPU core is rather limited. We develop a simple linear model to analyze the memory consumption of the constituent components of neuronal simulators as a function of network size and the number of cores used. This approach has multiple benefits. The model enables identification of key contributing components to memory saturation and prediction of the effects of potential improvements to code before any implementation takes place. As a consequence, development cycles can be shorter and

  7. Memory in linear recurrent neural networks in continuous time.

    Science.gov (United States)

    Hermans, Michiel; Schrauwen, Benjamin

    2010-04-01

    Reservoir Computing is a novel technique which employs recurrent neural networks while circumventing difficult training algorithms. A very recent trend in Reservoir Computing is the use of real physical dynamical systems as implementation platforms, rather than the customary digital emulations. Physical systems operate in continuous time, creating a fundamental difference with the classic discrete time definitions of Reservoir Computing. The specific goal of this paper is to study the memory properties of such systems, where we will limit ourselves to linear dynamics. We develop an analytical model which allows the calculation of the memory function for continuous time linear dynamical systems, which can be considered as networks of linear leaky integrator neurons. We then use this model to research memory properties for different types of reservoir. We start with random connection matrices with a shifted eigenvalue spectrum, which perform very poorly. Next, we transform two specific reservoir types, which are known to give good performance in discrete time, to the continuous time domain. Reservoirs based on uniform spreading of connection matrix eigenvalues on the unit disk in discrete time give much better memory properties than reservoirs with random connection matrices, where reservoirs based on orthogonal connection matrices in discrete time are very robust against noise and their memory properties can be tuned. The overall results found in this work yield important insights into how to design networks for continuous time.

  8. Robust sequential working memory recall in heterogeneous cognitive networks

    Science.gov (United States)

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

    2014-01-01

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

  9. Alcohol Expectancy Multiaxial Assessment: A Memory Network-Based Approach

    Science.gov (United States)

    Goldman, Mark S.; Darkes, Jack

    2004-01-01

    Despite several decades of activity, alcohol expectancy research has yet to merge measurement approaches with developing memory theory. This article offers an expectancy assessment approach built on a conceptualization of expectancy as an information processing network. The authors began with multidimensional scaling models of expectancy space,…

  10. Graph properties of synchronized cortical networks during visual working memory maintenance.

    Science.gov (United States)

    Palva, Satu; Monto, Simo; Palva, J Matias

    2010-02-15

    Oscillatory synchronization facilitates communication in neuronal networks and is intimately associated with human cognition. Neuronal activity in the human brain can be non-invasively imaged with magneto- (MEG) and electroencephalography (EEG), but the large-scale structure of synchronized cortical networks supporting cognitive processing has remained uncharacterized. We combined simultaneous MEG and EEG (MEEG) recordings with minimum-norm-estimate-based inverse modeling to investigate the structure of oscillatory phase synchronized networks that were active during visual working memory (VWM) maintenance. Inter-areal phase-synchrony was quantified as a function of time and frequency by single-trial phase-difference estimates of cortical patches covering the entire cortical surfaces. The resulting networks were characterized with a number of network metrics that were then compared between delta/theta- (3-6 Hz), alpha- (7-13 Hz), beta- (16-25 Hz), and gamma- (30-80 Hz) frequency bands. We found several salient differences between frequency bands. Alpha- and beta-band networks were more clustered and small-world like but had smaller global efficiency than the networks in the delta/theta and gamma bands. Alpha- and beta-band networks also had truncated-power-law degree distributions and high k-core numbers. The data converge on showing that during the VWM-retention period, human cortical alpha- and beta-band networks have a memory-load dependent, scale-free small-world structure with densely connected core-like structures. These data further show that synchronized dynamic networks underlying a specific cognitive state can exhibit distinct frequency-dependent network structures that could support distinct functional roles.

  11. Memory formation: from network structure to neural dynamics.

    Science.gov (United States)

    Feldt, Sarah; Wang, Jane X; Hetrick, Vaughn L; Berke, Joshua D; Zochowski, Michal

    2010-05-13

    Understanding the neural correlates of brain function is an extremely challenging task, since any cognitive process is distributed over a complex and evolving network of neurons that comprise the brain. In order to quantify observed changes in neuronal dynamics during hippocampal memory formation, we present metrics designed to detect directional interactions and the formation of functional neuronal ensembles. We apply these metrics to both experimental and model-derived data in an attempt to link anatomical network changes with observed changes in neuronal dynamics during hippocampal memory formation processes. We show that the developed model provides a consistent explanation of the anatomical network modifications that underlie the activity changes observed in the experimental data.

  12. [Network Research on Human Papillomavirus].

    Science.gov (United States)

    Almeida-Gutiérrez, Eduardo; Paniagua, Ramón; Furuya, María ElenaYuriko

    2015-01-01

    In order to increase the research in important health questions at a national and institutional levels, the Human Papillomavirus Research Network of the Health Research Coordination of the Instituto Mexicano del Seguro Social offers this supplement with the purpose of assisting patients that daily look for attention due to the human papillomavirus or to cervical cancer.

  13. Human memory research: Current hypotheses and new perspectives

    Directory of Open Access Journals (Sweden)

    Antônio Jaeger

    Full Text Available Abstract Research on human memory has increased significantly in the last few decades. Inconsistencies and controversies inherent to such research, however, are rarely articulated on published reports. The goal of the present article is to present and discuss a series of open questions related to major topics on human memory research that can be addressed by future research. The topics covered here are visual working memory, recognition memory, emotion and memory interaction, and methodological issues of false memories studies. Overall, the present work reveals a series of open questions and alternative analysis which could be useful for the process of hypothesis generation, and consequently for the design and implementation of future research on human memory.

  14. A New Conceptualization of Human Visual Sensory-Memory.

    Science.gov (United States)

    Öğmen, Haluk; Herzog, Michael H

    2016-01-01

    Memory is an essential component of cognition and disorders of memory have significant individual and societal costs. The Atkinson-Shiffrin "modal model" forms the foundation of our understanding of human memory. It consists of three stores: Sensory Memory (SM), whose visual component is called iconic memory, Short-Term Memory (STM; also called working memory, WM), and Long-Term Memory (LTM). Since its inception, shortcomings of all three components of the modal model have been identified. While the theories of STM and LTM underwent significant modifications to address these shortcomings, models of the iconic memory remained largely unchanged: A high capacity but rapidly decaying store whose contents are encoded in retinotopic coordinates, i.e., according to how the stimulus is projected on the retina. The fundamental shortcoming of iconic memory models is that, because contents are encoded in retinotopic coordinates, the iconic memory cannot hold any useful information under normal viewing conditions when objects or the subject are in motion. Hence, half-century after its formulation, it remains an unresolved problem whether and how the first stage of the modal model serves any useful function and how subsequent stages of the modal model receive inputs from the environment. Here, we propose a new conceptualization of human visual sensory memory by introducing an additional component whose reference-frame consists of motion-grouping based coordinates rather than retinotopic coordinates. We review data supporting this new model and discuss how it offers solutions to the paradoxes of the traditional model of sensory memory.

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

    Science.gov (United States)

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

    2015-01-01

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

  16. Manganese oxide microswitch for electronic memory based on neural networks

    Science.gov (United States)

    Ramesham, R.; Daud, T.; Moopenn, A.; Thakoor, A. P.; Khanna, S. K.

    1989-01-01

    A solid-state, resistance tailorable, programmable-once, binary, nonvolatile memory switch based on manganese oxide thin films is reported. MnO(x) exhibits irreversible memory switching from conducting (on) to insulating (off) state, with the off and on resistance ratio of greater than 10,000. The switching mechanism is current-triggered chemical transformation of a conductive MnO(2-Delta) to an insulating Mn2O3 state. The energy required for switching is of the order of 4-20 nJ/sq micron. The low switching energy, stability of the on and off states, and tailorability of the on state resistance make these microswitches well suited as programmable binary synapses in electronic associative memories based on neural network models.

  17. Learning, memory, and the role of neural network architecture.

    Science.gov (United States)

    Hermundstad, Ann M; Brown, Kevin S; Bassett, Danielle S; Carlson, Jean M

    2011-06-01

    The performance of information processing systems, from artificial neural networks to natural neuronal ensembles, depends heavily on the underlying system architecture. In this study, we compare the performance of parallel and layered network architectures during sequential tasks that require both acquisition and retention of information, thereby identifying tradeoffs between learning and memory processes. During the task of supervised, sequential function approximation, networks produce and adapt representations of external information. Performance is evaluated by statistically analyzing the error in these representations while varying the initial network state, the structure of the external information, and the time given to learn the information. We link performance to complexity in network architecture by characterizing local error landscape curvature. We find that variations in error landscape structure give rise to tradeoffs in performance; these include the ability of the network to maximize accuracy versus minimize inaccuracy and produce specific versus generalizable representations of information. Parallel networks generate smooth error landscapes with deep, narrow minima, enabling them to find highly specific representations given sufficient time. While accurate, however, these representations are difficult to generalize. In contrast, layered networks generate rough error landscapes with a variety of local minima, allowing them to quickly find coarse representations. Although less accurate, these representations are easily adaptable. The presence of measurable performance tradeoffs in both layered and parallel networks has implications for understanding the behavior of a wide variety of natural and artificial learning systems.

  18. Learning, memory, and the role of neural network architecture.

    Directory of Open Access Journals (Sweden)

    Ann M Hermundstad

    2011-06-01

    Full Text Available The performance of information processing systems, from artificial neural networks to natural neuronal ensembles, depends heavily on the underlying system architecture. In this study, we compare the performance of parallel and layered network architectures during sequential tasks that require both acquisition and retention of information, thereby identifying tradeoffs between learning and memory processes. During the task of supervised, sequential function approximation, networks produce and adapt representations of external information. Performance is evaluated by statistically analyzing the error in these representations while varying the initial network state, the structure of the external information, and the time given to learn the information. We link performance to complexity in network architecture by characterizing local error landscape curvature. We find that variations in error landscape structure give rise to tradeoffs in performance; these include the ability of the network to maximize accuracy versus minimize inaccuracy and produce specific versus generalizable representations of information. Parallel networks generate smooth error landscapes with deep, narrow minima, enabling them to find highly specific representations given sufficient time. While accurate, however, these representations are difficult to generalize. In contrast, layered networks generate rough error landscapes with a variety of local minima, allowing them to quickly find coarse representations. Although less accurate, these representations are easily adaptable. The presence of measurable performance tradeoffs in both layered and parallel networks has implications for understanding the behavior of a wide variety of natural and artificial learning systems.

  19. Exploiting human memory B cell heterogeneity for improved vaccine efficacy

    Directory of Open Access Journals (Sweden)

    Noel Thomas Pauli

    2011-12-01

    Full Text Available The major goal in vaccination is establishment of long-term, prophylactic humoral memory to a pathogen. Two major components to long-lived humoral memory are plasma cells for the production of specific immunoglobulin and memory B cells that survey for their specific antigen in the periphery for later affinity maturation, proliferation, and differentiation. The study of human B cell memory has been aided by the discovery of a general marker for B cell memory, expression of CD27; however, new data suggests the existence of CD27- memory B cells as well. These recently described non-canonical memory populations have increasingly pointed to the heterogeneity of the memory compartment. The novel B memory subsets in humans appear to have unique origins, localization, and functions compared to what was considered to be a classical memory B cell. In this article, we review the known B cell memory subsets, the establishment of B cell memory in vaccination and infection, and how understanding these newly described subsets can inform vaccine design and disease treatment.

  20. Glucocorticoids boost stimulus-response memory formation in humans.

    Science.gov (United States)

    Guenzel, Friederike M; Wolf, Oliver T; Schwabe, Lars

    2014-07-01

    Stress affects memory beyond hippocampus-dependent spatial or episodic memory processes. In particular, stress may influence also striatum-dependent stimulus-response (S-R) memory processes. Rodent studies point to an important role of glucocorticoids in the modulation of S-R memory. However, whether glucocorticoids influence S-R memory processes in humans is still unknown. Therefore, we examined in the current experiment the impact of glucocorticoids on the formation of S-R memories in humans. For this purpose, healthy men and women received either hydrocortisone or a placebo 45 min before completing an S-R association learning task and an S-R navigation task. In addition, participants performed also a virtual spatial navigation task and a spatial navigation task in a real environment. Memory of all four learning tasks was tested one week later. Our data showed that hydrocortisone before learning enhanced memory of the S-R association learning task. Moreover, hydrocortisone enhanced the memory of the virtual spatial navigation task, mainly in women. Memory performance in the other tasks remained unaffected by hydrocortisone. These findings provide first evidence that glucocorticoids may facilitate S-R memory formation processes in humans.

  1. Memory Efficient String Matching Algorithm for Network Intrusion Management System

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    As the core algorithm and the most time consuming part of almost every modern network intrusion management system (NIMS), string matching is essential for the inspection of network flows at the line speed. This paper presents a memory and time efficient string matching algorithm specifically designed for NIMS on commodity processors. Modifications of the Aho-Corasick (AC) algorithm based on the distribution characteristics of NIMS patterns drastically reduce the memory usage without sacrificing speed in software implementations. In tests on the Snort pattern set and traces that represent typical NIMS workloads, the Snort performance was enhanced 1.48%-20% compared to other well-known alternatives with an automaton size reduction of 4.86-6.11 compared to the standard AC implementation. The results show that special characteristics of the NIMS can be used into a very effective method to optimize the algorithm design.

  2. Evolving neural networks with iterative learning scheme for associative memory

    CERN Document Server

    Fujita, Sh

    1995-01-01

    A locally iterative learning (LIL) rule is adapted to a model of the associative memory based on the evolving recurrent-type neural networks composed of growing neurons. There exist extremely different scale parameters of time, the individual learning time and the generation in evolution. This model allows us definite investigation on the interaction between learning and evolution. And the reinforcement of the robustness against the noise is also achieved in the evolutional scheme.

  3. GLOBAL DYNAMICS OF DELAYED BIDIRECTIONAL ASSOCIATIVE MEMORY (BAM) NEURAL NETWORKS

    Institute of Scientific and Technical Information of China (English)

    ZHOU Jin; LIU Zeng-rong; XIANG Lan

    2005-01-01

    Without assuming the smoothness, monotonicity and boundedness of the activation functions, some novel criteria on the existence and global exponential stability of equilibrium point for delayed bidirectional associative memory (BAM) neural networks are established by applying the Liapunov functional methods and matrix-algebraic techniques. It is shown that the new conditions presented in terms of a nonsingular M matrix described by the networks parameters, the connection matrix and the Lipschitz constant of the activation functions, are not only simple and practical, but also easier to check and less conservative than those imposed by similar results in recent literature.

  4. Memory-Assisted Universal Compression of Network Flows

    CERN Document Server

    Sardari, Mohsen; Fekri, Faramarz

    2012-01-01

    Recently, the existence of considerable amount of redundancy in the Internet traffic has stimulated the deployment of several redundancy elimination techniques within the network. These techniques are often based on either packet-level Redundancy Elimination (RE) or Content-Centric Networking (CCN). However, these techniques cannot exploit sub-packet redundancies. Further, other alternative techniques such as the end-to-end universal compression solutions would not perform well either over the Internet traffic, as such techniques require infinite length traffic to effectively remove redundancy. This paper proposes a memory-assisted universal compression technique that holds a significant promise for reducing the amount of traffic in the networks. The proposed work is based on the observation that if a source is to be compressed and sent over a network, the associated universal code entails a substantial overhead in transmission due to finite length traffic. However, intermediate nodes can learn the source sta...

  5. Memory consolidation in human sleep depends on inhibition of glucocorticoid release.

    Science.gov (United States)

    Plihal, W; Born, J

    1999-09-09

    Early sleep dominated by slow-wave sleep has been found to be particularly relevant for declarative memory formation via hippocampo-neocortical networks. Concurrently, early nocturnal sleep is characterized by an inhibition of glucocorticoid release from the adrenals. Here, we show in healthy humans that this inhibition serves to support declarative memory consolidation during sleep. Elevating plasma glucocorticoid concentration during early sleep by administration of cortisol impaired consolidation of paired associate words, but not of non-declarative memory of visuomotor skills. Since glucocorticoid concentration was enhanced only during retention sleep, but not during acquisition or retrieval, a specific effect on the consolidation process is indicated. Blocking mineralocorticoid receptors by canrenoate did not affect memory, suggesting inactivation of glucocorticoid receptors to be the essential prerequisite for memory consolidation during early sleep.

  6. IL-10 is excluded from the functional cytokine memory of human CD4+ memory T lymphocytes.

    Science.gov (United States)

    Dong, Jun; Ivascu, Claudia; Chang, Hyun-Dong; Wu, Peihua; Angeli, Roberta; Maggi, Laura; Eckhardt, Florian; Tykocinski, Lars; Haefliger, Carolina; Möwes, Beate; Sieper, Jochen; Radbruch, Andreas; Annunziato, Francesco; Thiel, Andreas

    2007-08-15

    Epigenetic modifications, including DNA methylation, profoundly influence gene expression of CD4(+) Th-specific cells thereby shaping memory Th cell function. We demonstrate here a correlation between a lacking fixed potential of human memory Th cells to re-express the immunoregulatory cytokine gene IL10 and its DNA methylation status. Memory Th cells secreting IL-10 or IFN-gamma were directly isolated ex vivo from peripheral blood of healthy volunteers, and the DNA methylation status of IL10 and IFNG was assessed. Limited difference in methylation was found for the IL10 gene locus in IL-10-secreting Th cells, as compared with Th cells not secreting IL-10 isolated directly ex vivo or from in vitro-established human Th1 and Th2 clones. In contrast, in IFN-gamma(+) memory Th cells the promoter of the IFNG gene was hypomethylated, as compared with IFN-gamma-nonsecreting memory Th cells. In accordance with the lack of epigenetic memory, almost 90% of ex vivo-isolated IL-10-secreting Th cells lacked a functional memory for IL-10 re-expression after restimulation. Our data indicate that IL10 does not become epigenetically marked in human memory Th cells unlike effector cytokine genes such as IFNG. The exclusion of IL-10, but not effector cytokines, from the functional memory of human CD4(+) T lymphocytes ex vivo may reflect the need for appropriate regulation of IL-10 secretion, due to its potent immunoregulatory potential.

  7. Memory Allocation in Distributed Storage Networks

    CERN Document Server

    Sardari, Mohsen; Fekri, Faramarz; Soljanin, Emina

    2010-01-01

    We consider the problem of distributing a file in a network of storage nodes whose storage budget is limited but at least equals to the size file. We first generate $T$ encoded symbols (from the file) which are then distributed among the nodes. We investigate the optimal allocation of $T$ encoded packets to the storage nodes such that the probability of reconstructing the file by using any $r$ out of $n$ nodes is maximized. Since the optimal allocation of encoded packets is difficult to find in general, we find another objective function which well approximates the original problem and yet is easier to optimize. We find the optimal symmetric allocation for all coding redundancy constraints using the equivalent approximate problem. We also investigate the optimal allocation in random graphs. Finally, we provide simulations to verify the theoretical results.

  8. Stressed memories: How acute stress affects memory formation in humans

    NARCIS (Netherlands)

    Henckens, M.J.A.G.; Hermans, E.J.; Pu, Z.; Joels, M.; Fernandez, G.S.E.

    2009-01-01

    Stressful, aversive events are extremely well remembered. Such a declarative memory enhancement is evidently beneficial for survival, but the same mechanism may become maladaptive and culminate in mental diseases such as posttraumatic stress disorder (PTSD). Stress hormones are known to enhance

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Anders Lansner

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

  11. An annulus fibrosus closure device based on a biodegradable shape-memory polymer network.

    Science.gov (United States)

    Sharifi, Shahriar; van Kooten, Theo G; Kranenburg, Hendrik-Jan C; Meij, Björn P; Behl, Marc; Lendlein, Andreas; Grijpma, Dirk W

    2013-11-01

    Injuries to the intervertebral disc caused by degeneration or trauma often lead to tearing of the annulus fibrosus (AF) and extrusion of the nucleus pulposus (NP). This can compress nerves and cause lower back pain. In this study, the characteristics of poly(D,L-lactide-co-trimethylene carbonate) networks with shape-memory properties have been evaluated in order to prepare biodegradable AF closure devices that can be implanted minimally invasively. Four different macromers with (D,L-lactide) to trimethylene carbonate (DLLA:TMC) molar ratios of 80:20, 70:30, 60:40 and 40:60 with terminal methacrylate groups and molecular weights of approximately 30 kg mol(-1) were used to prepare the networks by photo-crosslinking. The mechanical properties of the samples and their shape-memory properties were determined at temperatures of 0 °C and 40 °C by tensile tests- and cyclic, thermo-mechanical measurements. At 40 °C all networks showed rubber-like behavior and were flexible with elastic modulus values of 1.7-2.5 MPa, which is in the range of the modulus values of human annulus fibrosus tissue. The shape-memory characteristics of the networks were excellent with values of the shape-fixity and the shape-recovery ratio higher than 98 and 95%, respectively. The switching temperatures were between 10 and 39 °C. In vitro culture and qualitative immunocytochemistry of human annulus fibrosus cells on shape-memory films with DLLA:TMC molar ratios of 60:40 showed very good ability of the networks to support the adhesion and growth of human AF cells. When the polymer network films were coated by adsorption of fibronectin, cell attachment, cell spreading, and extracellular matrix production was further improved. Annulus fibrosus closure devices were prepared from these AF cell-compatible materials by photo-polymerizing the reactive precursors in a mold. Insertion of the multifunctional implant in the disc of a cadaveric canine spine showed that these shape-memory devices could be

  12. Phantom percepts: Tinnitus and pain as persisting aversive memory networks

    Science.gov (United States)

    De Ridder, Dirk; Elgoyhen, Ana Belen; Romo, Ranulfo; Langguth, Berthold

    2011-01-01

    Phantom perception refers to the conscious awareness of a percept in the absence of an external stimulus. On the basis of basic neuroscience on perception and clinical research in phantom pain and phantom sound, we propose a working model for their origin. Sensory deafferentation results in high-frequency, gamma band, synchronized neuronal activity in the sensory cortex. This activity becomes a conscious percept only if it is connected to larger coactivated “(self-)awareness” and “salience” brain networks. Through the involvement of learning mechanisms, the phantom percept becomes associated to distress, which in turn is reflected by a simultaneously coactivated nonspecific distress network consisting of the anterior cingulate cortex, anterior insula, and amygdala. Memory mechanisms play a role in the persistence of the awareness of the phantom percept, as well as in the reinforcement of the associated distress. Thus, different dynamic overlapping brain networks should be considered as targets for the treatment of this disorder. PMID:21502503

  13. Scale-free networks as an epiphenomenon of memory

    CERN Document Server

    Caravelli, Francesco; Di Ventra, Massimiliano

    2013-01-01

    Scale-free networks have small characteristic path lengths, high clustering, and feature a power law in their degree distribution. They can be obtained by the well-known preferential attachment. However, this mechanism is non-local, in the sense that it requires knowledge of the entire graph in order for the graph to be updated. This strongly suggests that in both physical and practical realizations this mechanism is likely to be the epiphenomenon of some spatially local rule. Here, we present a completely local model that features preferential attachment as an emergent property of self-organized dynamics with memory. This model employs a mechanism similar to that used by ants to search for the optimal path as a consequence of the graph bearing more memory wherever more ants have walked. Such a model can also be realized in solid-state circuits, using non-linear passive elements with memory such as memristors, and thus can be tested experimentally. Since memory is a common trait of physical systems, we expect...

  14. CPEB3 is associated with human episodic memory.

    Science.gov (United States)

    Vogler, Christian; Spalek, Klara; Aerni, Amanda; Demougin, Philippe; Müller, Ariane; Huynh, Kim-Dung; Papassotiropoulos, Andreas; de Quervain, Dominique J-F

    2009-01-01

    Cytoplasmic polyadenylation element-binding (CPEB) proteins are crucial for synaptic plasticity and memory in model organisms. A highly conserved, mammalian-specific short intronic sequence within CPEB3 has been identified as a ribozyme with self-cleavage properties. In humans, the ribozyme sequence is polymorphic and harbors a single nucleotide polymorphism that influences cleavage activity of the ribozyme. Here we show that this variation is related to performance in an episodic memory task and that the effect of the variation depends on the emotional valence of the presented material. Our data suggest a role for human CPEB3 in human episodic memory.

  15. CPEB3 is associated with human episodic memory

    Directory of Open Access Journals (Sweden)

    Christian Vogler

    2009-05-01

    Full Text Available Cytoplasmic polyadenylation element-binding (CPEB proteins are crucial for synaptic plasticity and memory in model organisms. A highly conserved, mammalian-specific short intronic sequence within CPEB3 has been identified as a ribozyme with self-cleavage properties. In humans the ribozyme sequence is polymorphic and harbors a single nucleotide polymorphism which influences cleavage activity of the ribozyme. Here we show that this variation is related to performance in an episodic memory task and that the effect of the variation depends on the emotional valence of the presented material. Our data support a role for human CPEB3 in human episodic memory.

  16. Controlled architecture for improved macromolecular memory within polymer networks.

    Science.gov (United States)

    DiPasquale, Stephen A; Byrne, Mark E

    2016-08-01

    This brief review analyzes recent developments in the field of living/controlled polymerization and the potential of this technique for creating imprinted polymers with highly structured architecture with macromolecular memory. As a result, it is possible to engineer polymers at the molecular level with increased homogeneity relating to enhanced template binding and transport. Only recently has living/controlled polymerization been exploited to decrease heterogeneity and substantially improve the efficiency of the imprinting process for both highly and weakly crosslinked imprinted polymers. Living polymerization can be utilized to create imprinted networks that are vastly more efficient than similar polymers produced using conventional free radical polymerization, and these improvements increase the role that macromolecular memory can play in the design and engineering of new drug delivery and sensing platforms.

  17. The Hippocampus Is Coupled with the Default Network during Memory Retrieval but Not during Memory Encoding

    Science.gov (United States)

    Huijbers, Willem; Pennartz, Cyriel M. A.; Cabeza, Roberto; Daselaar, Sander M.

    2011-01-01

    The brain's default mode network (DMN) is activated during internally-oriented tasks and shows strong coherence in spontaneous rest activity. Despite a surge of recent interest, the functional role of the DMN remains poorly understood. Interestingly, the DMN activates during retrieval of past events but deactivates during encoding of novel events into memory. One hypothesis is that these opposing effects reflect a difference between attentional orienting towards internal events, such as retrieved memories, vs. external events, such as to-be-encoded stimuli. Another hypothesis is that hippocampal regions are coupled with the DMN during retrieval but decoupled from the DMN during encoding. The present fMRI study investigated these two hypotheses by combining a resting-state coherence analysis with a task that measured the encoding and retrieval of both internally-generated and externally-presented events. Results revealed that the main DMN regions were activated during retrieval but deactivated during encoding. Counter to the internal orienting hypothesis, this pattern was not modulated by whether memory events were internal or external. Consistent with the hippocampal coupling hypothesis, the hippocampus behaved like other DMN regions during retrieval but not during encoding. Taken together, our findings clarify the relationship between the DMN and the neural correlates of memory retrieval and encoding. PMID:21494597

  18. The hippocampus is coupled with the default network during memory retrieval but not during memory encoding.

    Directory of Open Access Journals (Sweden)

    Willem Huijbers

    Full Text Available The brain's default mode network (DMN is activated during internally-oriented tasks and shows strong coherence in spontaneous rest activity. Despite a surge of recent interest, the functional role of the DMN remains poorly understood. Interestingly, the DMN activates during retrieval of past events but deactivates during encoding of novel events into memory. One hypothesis is that these opposing effects reflect a difference between attentional orienting towards internal events, such as retrieved memories, vs. external events, such as to-be-encoded stimuli. Another hypothesis is that hippocampal regions are coupled with the DMN during retrieval but decoupled from the DMN during encoding. The present fMRI study investigated these two hypotheses by combining a resting-state coherence analysis with a task that measured the encoding and retrieval of both internally-generated and externally-presented events. Results revealed that the main DMN regions were activated during retrieval but deactivated during encoding. Counter to the internal orienting hypothesis, this pattern was not modulated by whether memory events were internal or external. Consistent with the hippocampal coupling hypothesis, the hippocampus behaved like other DMN regions during retrieval but not during encoding. Taken together, our findings clarify the relationship between the DMN and the neural correlates of memory retrieval and encoding.

  19. A functional magnetic resonance imaging study mapping the episodic memory encoding network in temporal lobe epilepsy

    OpenAIRE

    Sidhu, Meneka K; Stretton, Jason; Winston, Gavin P.; Bonelli, Silvia; Centeno, Maria; Vollmar, Christian; Symms, Mark; Thompson, Pamela J; Koepp, Matthias J; Duncan, John S.

    2013-01-01

    Functional magnetic resonance imaging has demonstrated reorganization of memory encoding networks within the temporal lobe in temporal lobe epilepsy, but little is known of the extra-temporal networks in these patients. We investigated the temporal and extra-temporal reorganization of memory encoding networks in refractory temporal lobe epilepsy and the neural correlates of successful subsequent memory formation. We studied 44 patients with unilateral temporal lobe epilepsy and hippocampal sc...

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

    Science.gov (United States)

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

    2013-10-01

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

  1. False memory for face in short-term memory and neural activity in human amygdala.

    Science.gov (United States)

    Iidaka, Tetsuya; Harada, Tokiko; Sadato, Norihiro

    2014-12-03

    Human memory is often inaccurate. Similar to words and figures, new faces are often recognized as seen or studied items in long- and short-term memory tests; however, the neural mechanisms underlying this false memory remain elusive. In a previous fMRI study using morphed faces and a standard false memory paradigm, we found that there was a U-shaped response curve of the amygdala to old, new, and lure items. This indicates that the amygdala is more active in response to items that are salient (hit and correct rejection) compared to items that are less salient (false alarm), in terms of memory retrieval. In the present fMRI study, we determined whether the false memory for faces occurs within the short-term memory range (a few seconds), and assessed which neural correlates are involved in veridical and illusory memories. Nineteen healthy participants were scanned by 3T MRI during a short-term memory task using morphed faces. The behavioral results indicated that the occurrence of false memories was within the short-term range. We found that the amygdala displayed a U-shaped response curve to memory items, similar to those observed in our previous study. These results suggest that the amygdala plays a common role in both long- and short-term false memory for faces. We made the following conclusions: First, the amygdala is involved in detecting the saliency of items, in addition to fear, and supports goal-oriented behavior by modulating memory. Second, amygdala activity and response time might be related with a subject's response criterion for similar faces. Copyright © 2014 Elsevier B.V. All rights reserved.

  2. Genetics of human episodic memory: dealing with complexity.

    Science.gov (United States)

    Papassotiropoulos, Andreas; de Quervain, Dominique J-F

    2011-09-01

    Episodic memory is a polygenic behavioral trait with substantial heritability estimates. Despite its complexity, recent empirical evidence supports the notion that behavioral genetic studies of episodic memory might successfully identify trait-associated molecules and pathways. The development of high-throughput genotyping methods, of elaborated statistical analyses and of phenotypic assessment methods at the neural systems level will facilitate the reliable identification of novel memory-related genes. Importantly, a necessary crosstalk between behavioral genetic studies and investigation of causality by molecular genetic studies will ultimately pave the way towards the identification of biologically important, and hopefully druggable, genes and molecular pathways related to human episodic memory.

  3. Motor threshold predicts working memory performance in healthy humans.

    Science.gov (United States)

    Schicktanz, Nathalie; Schwegler, Kyrill; Fastenrath, Matthias; Spalek, Klara; Milnik, Annette; Papassotiropoulos, Andreas; Nyffeler, Thomas; de Quervain, Dominique J-F

    2014-01-01

    Cognitive functions, such as working memory, depend on neuronal excitability in a distributed network of cortical regions. It is not known, however, if interindividual differences in cortical excitability are related to differences in working memory performance. In the present transcranial magnetic stimulation study, which included 188 healthy young subjects, we show that participants with lower resting motor threshold, which is related to higher corticospinal excitability, had increased 2-back working memory performance. The findings may help to better understand the link between cortical excitability and cognitive functions and may also have important clinical implications with regard to conditions of altered cortical excitability.

  4. Modular structure of functional networks in olfactory memory.

    Science.gov (United States)

    Meunier, David; Fonlupt, Pierre; Saive, Anne-Lise; Plailly, Jane; Ravel, Nadine; Royet, Jean-Pierre

    2014-07-15

    Graph theory enables the study of systems by describing those systems as a set of nodes and edges. Graph theory has been widely applied to characterize the overall structure of data sets in the social, technological, and biological sciences, including neuroscience. Modular structure decomposition enables the definition of sub-networks whose components are gathered in the same module and work together closely, while working weakly with components from other modules. This processing is of interest for studying memory, a cognitive process that is widely distributed. We propose a new method to identify modular structure in task-related functional magnetic resonance imaging (fMRI) networks. The modular structure was obtained directly from correlation coefficients and thus retained information about both signs and weights. The method was applied to functional data acquired during a yes-no odor recognition memory task performed by young and elderly adults. Four response categories were explored: correct (Hit) and incorrect (False alarm, FA) recognition and correct and incorrect rejection. We extracted time series data for 36 areas as a function of response categories and age groups and calculated condition-based weighted correlation matrices. Overall, condition-based modular partitions were more homogeneous in young than elderly subjects. Using partition similarity-based statistics and a posteriori statistical analyses, we demonstrated that several areas, including the hippocampus, caudate nucleus, and anterior cingulate gyrus, belonged to the same module more frequently during Hit than during all other conditions. Modularity values were negatively correlated with memory scores in the Hit condition and positively correlated with bias scores (liberal/conservative attitude) in the Hit and FA conditions. We further demonstrated that the proportion of positive and negative links between areas of different modules (i.e., the proportion of correlated and anti-correlated areas

  5. Shape memory polymers based on uniform aliphatic urethane networks

    Energy Technology Data Exchange (ETDEWEB)

    Wilson, T S; Bearinger, J P; Herberg, J L; Marion III, J E; Wright, W J; Evans, C L; Maitland, D J

    2007-01-19

    Aliphatic urethane polymers have been synthesized and characterized, using monomers with high molecular symmetry, in order to form amorphous networks with very uniform supermolecular structures which can be used as photo-thermally actuable shape memory polymers (SMPs). The monomers used include hexamethylene diisocyanate (HDI), trimethylhexamethylenediamine (TMHDI), N,N,N{prime},N{prime}-tetrakis(hydroxypropyl)ethylenediamine (HPED), triethanolamine (TEA), and 1,3-butanediol (BD). The new polymers were characterized by solvent extraction, NMR, XPS, UV/VIS, DSC, DMTA, and tensile testing. The resulting polymers were found to be single phase amorphous networks with very high gel fraction, excellent optical clarity, and extremely sharp single glass transitions in the range of 34 to 153 C. Thermomechanical testing of these materials confirms their excellent shape memory behavior, high recovery force, and low mechanical hysteresis (especially on multiple cycles), effectively behaving as ideal elastomers above T{sub g}. We believe these materials represent a new and potentially important class of SMPs, and should be especially useful in applications such as biomedical microdevices.

  6. Phenotype and functions of memory Tfh cells in human blood.

    Science.gov (United States)

    Schmitt, Nathalie; Bentebibel, Salah-Eddine; Ueno, Hideki

    2014-09-01

    Our understanding of the origin and functions of human blood CXCR5(+) CD4(+) T cells found in human blood has changed dramatically in the past years. These cells are currently considered to represent a circulating memory compartment of T follicular helper (Tfh) lineage cells. Recent studies have shown that blood memory Tfh cells are composed of phenotypically and functionally distinct subsets. Here, we review the current understanding of human blood memory Tfh cells and the subsets within this compartment. We present a strategy to define these subsets based on cell surface profiles. Finally, we discuss how increased understanding of the biology of blood memory Tfh cells may contribute insight into the pathogenesis of autoimmune diseases and the mode of action of vaccines.

  7. Neural populations in human posteromedial cortex display opposing responses during memory and numerical processing

    Science.gov (United States)

    Foster, Brett L.; Dastjerdi, Mohammad; Parvizi, Josef

    2012-01-01

    Our understanding of the human default mode network derives primarily from neuroimaging data but its electrophysiological correlates remain largely unexplored. To address this limitation, we recorded intracranially from the human posteromedial cortex (PMC), a core structure of the default mode network, during various conditions of internally directed (e.g., autobiographical memory) as opposed to externally directed focus (e.g., arithmetic calculation). We observed late-onset (>400 ms) increases in broad high γ-power (70–180 Hz) within PMC subregions during memory retrieval. High γ-power was significantly reduced or absent when subjects retrieved self-referential semantic memories or responded to self-judgment statements, respectively. Conversely, a significant deactivation of high γ-power was observed during arithmetic calculation, the duration of which correlated with reaction time at the signal-trial level. Strikingly, at each recording site, the magnitude of activation during episodic autobiographical memory retrieval predicted the degree of suppression during arithmetic calculation. These findings provide important anatomical and temporal details—at the neural population level—of PMC engagement during autobiographical memory retrieval and address how the same populations are actively suppressed during tasks, such as numerical processing, which require externally directed attention. PMID:22949666

  8. Altered Intrinsic Hippocmapus Declarative Memory Network and Its Association with Impulsivity in Abstinent Heroin Dependent Subjects

    Science.gov (United States)

    Zhai, Tian-Ye; Shao, Yong-Cong; Xie, Chun-Ming; Ye, En-Mao; Zou, Feng; Fu, Li-Ping; Li, Wen-Jun; Chen, Gang; Chen, Guang-Yu; Zhang, Zheng-Guo; Li, Shi-Jiang; Yang, Zheng

    2014-01-01

    Converging evidence suggests that addiction can be considered a disease of aberrant learning and memory with impulsive decision-making. In the past decades, numerous studies have demonstrated that drug addiction is involved in multiple memory systems such as classical conditioned drug memory, instrumental learning memory and the habitual learning memory. However, most of these studies have focused on the contributions of non-declarative memory, and declarative memory has largely been neglected in the research of addiction. Based on a recent finding that hippocampus, as a core functioning region of declarative memory, was proved biased the decision-making process based on past experiences by spreading associated reward values throughout memory. Our present study focused on the hippocampus. By utilizing seed-based network analysis on the resting-state functional MRI datasets with the seed hippocampus we tested how the intrinsic hippocampal memory network altered towards drug addiction, and examined how the functional connectivity strength within the altered hippocampal network correlated with behavioral index ‘impulsivity’. Our results demonstrated that HD group showed enhanced coherence between hippocampus which represents declarative memory system and non-declarative rewardguided learning memory system, and also showed attenuated intrinsic functional link between hippocampus and top-down control system, compared to the CN group. This alteration was furthered found to have behavioral significance over the behavioral index ‘impulsivity’ measured with Barratt Impulsiveness Scale (BIS). These results provide insights into the mechanism of declarative memory underlying the impulsive behavior in drug addiction. PMID:25008351

  9. Stability analysis of associative memory network composed of stochastic neurons and dynamic synapses.

    Science.gov (United States)

    Katori, Yuichi; Otsubo, Yosuke; Okada, Masato; Aihara, Kazuyuki

    2013-01-01

    We investigate the dynamical properties of an associative memory network consisting of stochastic neurons and dynamic synapses that show short-term depression and facilitation. In the stochastic neuron model used in this study, the efficacy of the synaptic transmission changes according to the short-term depression or facilitation mechanism. We derive a macroscopic mean field model that captures the overall dynamical properties of the stochastic model. We analyze the stability and bifurcation structure of the mean field model, and show the dependence of the memory retrieval performance on the noise intensity and parameters that determine the properties of the dynamic synapses, i.e., time constants for depressing and facilitating processes. The associative memory network exhibits a variety of dynamical states, including the memory and pseudo-memory states, as well as oscillatory states among memory patterns. This study provides comprehensive insight into the dynamical properties of the associative memory network with dynamic synapses.

  10. Memory-related brain lateralisation in birds and humans.

    Science.gov (United States)

    Moorman, Sanne; Nicol, Alister U

    2015-03-01

    Visual imprinting in chicks and song learning in songbirds are prominent model systems for the study of the neural mechanisms of memory. In both systems, neural lateralisation has been found to be involved in memory formation. Although many processes in the human brain are lateralised--spatial memory and musical processing involves mostly right hemisphere dominance, whilst language is mostly left hemisphere dominant--it is unclear what the function of lateralisation is. It might enhance brain capacity, make processing more efficient, or prevent occurrence of conflicting signals. In both avian paradigms we find memory-related lateralisation. We will discuss avian lateralisation findings and propose that birds provide a strong model for studying neural mechanisms of memory-related lateralisation. Copyright © 2014. Published by Elsevier Ltd.

  11. Human Uniqueness, Cognition by Description, and Procedural Memory

    Directory of Open Access Journals (Sweden)

    John Bolender

    2008-06-01

    Full Text Available Evidence will be reviewed suggesting a fairly direct link between the human ability to think about entities which one has never perceived — here called “cognition by description” — and procedural memory. Cognition by description is a uniquely hominid trait which makes religion, science, and history possible. It is hypothesized that cognition by description (in the manner of Bertrand Russell’s “knowledge by description” requires variable binding, which in turn utilizes quantifier raising. Quantifier raising plausibly depends upon the computational core of language, specifically the element of it which Noam Chomsky calls “internal Merge”. Internal Merge produces hierarchical structures by means of a memory of derivational steps, a process plausibly involving procedural memory. The hypothesis is testable, predicting that procedural memory deficits will be accompanied by impairments in cognition by description. We also discuss neural mechanisms plausibly underlying procedural memory and also, by our hypothesis, cognition by description.

  12. Memory network plasticity after temporal lobe resection: a longitudinal functional imaging study

    OpenAIRE

    Sidhu, Meneka K; Stretton, Jason; Winston, Gavin P.; McEvoy, Andrew W; Symms, Mark; Thompson, Pamela J; Koepp, Matthias J; Duncan, John S.

    2016-01-01

    Anterior temporal lobe resection can control seizures in up to 80% of patients with temporal lobe epilepsy. Memory decrements are the main neurocognitive complication. Preoperative functional reorganization has been described in memory networks, but less is known of postoperative reorganization. We investigated reorganization of memory-encoding networks preoperatively and 3 and 12 months after surgery. We studied 36 patients with unilateral medial temporal lobe epilepsy (19 right) before and ...

  13. Network dynamics mediated by heterogeneous topology as related to hippocampal memory management

    Science.gov (United States)

    Wang, Jane; Poe, Gina; Zochowski, Michal

    2009-03-01

    Hippocampal-cortical network interactions, including reactivation of recently acquired memories in the hippocampus during sleep, are key to the consolidation of memory traces to long-term storage sites in the neocortex. Network heterogeneities, in the form of regional changes in the connectivity densities of excitatory synapses, support this process in simulated hippocampal-cortical networks by regulating intrinsic network dynamics and thus mediating stimulus familiarity detection as well as selective memory consolidation. We characterize this network model by investigating dynamics due to distributed and overlapping memory structures and examine the ability of regional heterogeneities to both selectively activate in the presence of controlled stimuli and reactivate in the absence of stimuli, the former being indicative of active exploration and the latter of memory replay during sleep.

  14. Stress and memory in humans: twelve years of progress?

    Science.gov (United States)

    Wolf, Oliver T

    2009-10-13

    Stress leads to an enhanced activity of the hypothalamus-pituitary adrenal (HPA) axis resulting in an increased release of glucocorticoids from the adrenal cortex. These hormones influence target systems in the periphery as well as in the brain. The present review paper describes the impact of the human stress hormone cortisol on episodic long-term memory. Starting out with our early observation that stress as well as cortisol treatment impaired declarative memory, experiments by the author are described, which result in an enhanced understanding of how cortisol influences memory. The main conclusions are that stress or cortisol treatment temporarily blocks memory retrieval. The effect is stronger for emotional arousing material independent of its valence. In addition cortisol only influences memory when a certain amount of testing induced arousal occurs. A functional magnetic resonance imaging (fMRI) study suggests that the neuronal correlate of the cortisol induced retrieval blockade is a reduced activity of the hippocampus. In contrast to the effects on retrieval cortisol enhances memory consolidation. Again this effect is often stronger for emotionally arousing material and sometimes occurs at the cost of memory for neutral material. A fMRI study revealed that higher cortisol levels were associated with a stronger amygdala response to emotional stimuli. Thus stimulatory effects of cortisol on this structure might underlie the cortisol induced enhancement of emotional memory consolidation. The findings presented are in line with models derived from experiments in rodents and are of relevance for our understanding of stress associated psychiatric disorders.

  15. Brain computer interface to enhance episodic memory in human participants

    Directory of Open Access Journals (Sweden)

    John F Burke

    2015-01-01

    Full Text Available Recent research has revealed that neural oscillations in the theta (4-8 Hz and alpha (9-14 Hz bands are predictive of future success in memory encoding. Because these signals occur before the presentation of an upcoming stimulus, they are considered stimulus-independent in that they correlate with enhanced memory encoding independent of the item being encoded. Thus, such stimulus-independent activity has important implications for the neural mechanisms underlying episodic memory as well as the development of cognitive neural prosthetics. Here, we developed a brain computer interface (BCI to test the ability of such pre-stimulus activity to modulate subsequent memory encoding. We recorded intracranial electroencephalography (iEEG in neurosurgical patients as they performed a free recall memory task, and detected iEEG theta and alpha oscillations that correlated with optimal memory encoding. We then used these detected oscillatory changes to trigger the presentation of items in the free recall task. We found that item presentation contingent upon the presence of prestimulus theta and alpha oscillations modulated memory performance in more sessions than expected by chance. Our results suggest that an electrophysiological signal may be causally linked to a specific behavioral condition, and contingent stimulus presentation has the potential to modulate human memory encoding.

  16. Human temporal cortical single neuron activity during working memory maintenance.

    Science.gov (United States)

    Zamora, Leona; Corina, David; Ojemann, George

    2016-06-01

    The Working Memory model of human memory, first introduced by Baddeley and Hitch (1974), has been one of the most influential psychological constructs in cognitive psychology and human neuroscience. However the neuronal correlates of core components of this model have yet to be fully elucidated. Here we present data from two studies where human temporal cortical single neuron activity was recorded during tasks differentially affecting the maintenance component of verbal working memory. In Study One we vary the presence or absence of distracting items for the entire period of memory storage. In Study Two we vary the duration of storage so that distractors filled all, or only one-third of the time the memory was stored. Extracellular single neuron recordings were obtained from 36 subjects undergoing awake temporal lobe resections for epilepsy, 25 in Study one, 11 in Study two. Recordings were obtained from a total of 166 lateral temporal cortex neurons during performance of one of these two tasks, 86 study one, 80 study two. Significant changes in activity with distractor manipulation were present in 74 of these neurons (45%), 38 Study one, 36 Study two. In 48 (65%) of those there was increased activity during the period when distracting items were absent, 26 Study One, 22 Study Two. The magnitude of this increase was greater for Study One, 47.6%, than Study Two, 8.1%, paralleling the reduction in memory errors in the absence of distracters, for Study One of 70.3%, Study Two 26.3% These findings establish that human lateral temporal cortex is part of the neural system for working memory, with activity during maintenance of that memory that parallels performance, suggesting it represents active rehearsal. In 31 of these neurons (65%) this activity was an extension of that during working memory encoding that differed significantly from the neural processes recorded during overt and silent language tasks without a recent memory component, 17 Study one, 14 Study two

  17. Shape memory polymer network with thermally distinct elasticity and plasticity.

    Science.gov (United States)

    Zhao, Qian; Zou, Weike; Luo, Yingwu; Xie, Tao

    2016-01-01

    Stimuli-responsive materials with sophisticated yet controllable shape-changing behaviors are highly desirable for real-world device applications. Among various shape-changing materials, the elastic nature of shape memory polymers allows fixation of temporary shapes that can recover on demand, whereas polymers with exchangeable bonds can undergo permanent shape change via plasticity. We integrate the elasticity and plasticity into a single polymer network. Rational molecular design allows these two opposite behaviors to be realized at different temperature ranges without any overlap. By exploring the cumulative nature of the plasticity, we demonstrate easy manipulation of highly complex shapes that is otherwise extremely challenging. The dynamic shape-changing behavior paves a new way for fabricating geometrically complex multifunctional devices.

  18. Memory elements in the electrical network of Mimosa pudica L.

    Science.gov (United States)

    Volkov, Alexander G; Reedus, Jada; Mitchell, Colee M; Tuckett, Clayton; Volkova, Maya I; Markin, Vladislav S; Chua, Leon

    2014-01-01

    The fourth basic circuit element, a memristor, is a resistor with memory that was postulated by Chua in 1971. Here we found that memristors exist in vivo. The electrostimulation of the Mimosa pudica by bipolar sinusoidal or triangle periodic waves induce electrical responses with fingerprints of memristors. Uncouplers carbonylcyanide-3-chlorophenylhydrazone and carbonylcyanide-4-trifluoromethoxy-phenyl hydrazone decrease the amplitude of electrical responses at low and high frequencies of bipolar sinusoidal or triangle periodic electrostimulating waves. Memristive behavior of an electrical network in the Mimosa pudica is linked to the properties of voltage gated ion channels: the channel blocker TEACl reduces the electric response to a conventional resistor. Our results demonstrate that a voltage gated K(+) channel in the excitable tissue of plants has properties of a memristor. The discovery of memristors in plants creates a new direction in the modeling and understanding of electrical phenomena in plants.

  19. Damage to the default mode network disrupts autobiographical memory retrieval.

    Science.gov (United States)

    Philippi, Carissa L; Tranel, Daniel; Duff, Melissa; Rudrauf, David

    2015-03-01

    Functional neuroimaging studies have implicated the default mode network (DMN) in autobiographical memory (AM). Convergent evidence from a lesion approach would help clarify the role of the DMN in AM. In this study, we used a voxelwise lesion-deficit approach to test the hypothesis that regions of the DMN are necessary for AM. We also explored whether the neural correlates of semantic AM (SAM) and episodic AM (EAM) were overlapping or distinct. Using the Iowa Autobiographical Memory Questionnaire, we tested AM retrieval in 92 patients with focal, stable brain lesions. In support of our hypothesis, damage to regions within the DMN (medial prefrontal cortex, mPFC; posterior cingulate cortex, PCC; inferior parietal lobule, IPL; medial temporal lobe, MTL) was associated with AM impairments. Within areas of effective lesion coverage, the neural correlates of SAM and EAM were largely distinct, with limited areas of overlap in right IPL. Whereas SAM deficits were associated with left mPFC and MTL damage, EAM deficits were associated with right mPFC and MTL damage. These results provide novel neuropsychological evidence for the necessary role of parts of the DMN in AM. More broadly, the findings shed new light on how the DMN participates in self-referential processing.

  20. Modeling aspects of human memory for scientific study.

    Energy Technology Data Exchange (ETDEWEB)

    Caudell, Thomas P. (University of New Mexico); Watson, Patrick (University of Illinois - Champaign-Urbana Beckman Institute); McDaniel, Mark A. (Washington University); Eichenbaum, Howard B. (Boston University); Cohen, Neal J. (University of Illinois - Champaign-Urbana Beckman Institute); Vineyard, Craig Michael; Taylor, Shawn Ellis; Bernard, Michael Lewis; Morrow, James Dan; Verzi, Stephen J.

    2009-10-01

    Working with leading experts in the field of cognitive neuroscience and computational intelligence, SNL has developed a computational architecture that represents neurocognitive mechanisms associated with how humans remember experiences in their past. The architecture represents how knowledge is organized and updated through information from individual experiences (episodes) via the cortical-hippocampal declarative memory system. We compared the simulated behavioral characteristics with those of humans measured under well established experimental standards, controlling for unmodeled aspects of human processing, such as perception. We used this knowledge to create robust simulations of & human memory behaviors that should help move the scientific community closer to understanding how humans remember information. These behaviors were experimentally validated against actual human subjects, which was published. An important outcome of the validation process will be the joining of specific experimental testing procedures from the field of neuroscience with computational representations from the field of cognitive modeling and simulation.

  1. Working memory cells' behavior may be explained by cross-regional networks with synaptic facilitation.

    Directory of Open Access Journals (Sweden)

    Sergio Verduzco-Flores

    Full Text Available Neurons in the cortex exhibit a number of patterns that correlate with working memory. Specifically, averaged across trials of working memory tasks, neurons exhibit different firing rate patterns during the delay of those tasks. These patterns include: 1 persistent fixed-frequency elevated rates above baseline, 2 elevated rates that decay throughout the tasks memory period, 3 rates that accelerate throughout the delay, and 4 patterns of inhibited firing (below baseline analogous to each of the preceding excitatory patterns. Persistent elevated rate patterns are believed to be the neural correlate of working memory retention and preparation for execution of behavioral/motor responses as required in working memory tasks. Models have proposed that such activity corresponds to stable attractors in cortical neural networks with fixed synaptic weights. However, the variability in patterned behavior and the firing statistics of real neurons across the entire range of those behaviors across and within trials of working memory tasks are typical not reproduced. Here we examine the effect of dynamic synapses and network architectures with multiple cortical areas on the states and dynamics of working memory networks. The analysis indicates that the multiple pattern types exhibited by cells in working memory networks are inherent in networks with dynamic synapses, and that the variability and firing statistics in such networks with distributed architectures agree with that observed in the cortex.

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

    Science.gov (United States)

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

    2015-08-10

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

  3. Epidemic Spread in Human Networks

    CERN Document Server

    Sahneh, Faryad Darabi

    2011-01-01

    One of the popular dynamics on complex networks is the epidemic spreading. An epidemic model describes how infections spread throughout a network. Among the compartmental models used to describe epidemics, the Susceptible-Infected-Susceptible (SIS) model has been widely used. In the SIS model, each node can be susceptible, become infected with a given infection rate, and become again susceptible with a given curing rate. In this paper, we add a new compartment to the classic SIS model to account for human response to epidemic spread. Each individual can be infected, susceptible, or alert. Susceptible individuals can become alert with an alerting rate if infected individuals exist in their neighborhood. An individual in the alert state is less probable to become infected than an individual in the susceptible state; due to a newly adopted cautious behavior. The problem is formulated as a continuous-time Markov process on a general static graph and then modeled into a set of ordinary differential equations using...

  4. Interdisciplinary Approach to the Mental Lexicon: Neural Network and Text Extraction From Long-term Memory

    Directory of Open Access Journals (Sweden)

    Vardan G. Arutyunyan

    2013-01-01

    Full Text Available The paper touches upon the principles of mental lexicon organization in the light of recent research in psycho- and neurolinguistics. As a focal point of discussion two main approaches to mental lexicon functioning are considered: modular or dual-system approach, developed within generativism and opposite single-system approach, representatives of which are the connectionists and supporters of network models. The paper is an endeavor towards advocating the viewpoint that mental lexicon is complex psychological organization based upon specific composition of neural network. In this regard, the paper further elaborates on the matter of storing text in human mental space and introduces a model of text extraction from long-term memory. Based upon data available, the author develops a methodology of modeling structures of knowledge representation in the systems of artificial intelligence.

  5. A system for simulating shared memory in heterogeneous distributed-memory networks with specialization for robotics applications

    Energy Technology Data Exchange (ETDEWEB)

    Jones, J.P.; Bangs, A.L.; Butler, P.L.

    1991-01-01

    Hetero Helix is a programming environment which simulates shared memory on a heterogeneous network of distributed-memory computers. The machines in the network may vary with respect to their native operating systems and internal representation of numbers. Hetero Helix presents a simple programming model to developers, and also considers the needs of designers, system integrators, and maintainers. The key software technology underlying Hetero Helix is the use of a compiler'' which analyzes the data structures in shared memory and automatically generates code which translates data representations from the format native to each machine into a common format, and vice versa. The design of Hetero Helix was motivated in particular by the requirements of robotics applications. Hetero Helix has been used successfully in an integration effort involving 27 CPUs in a heterogeneous network and a body of software totaling roughly 100,00 lines of code. 25 refs., 6 figs.

  6. Interactome Networks and Human Disease

    OpenAIRE

    Vidal, Marc; Cusick, Michael E.; Barabási, Albert-László

    2011-01-01

    Complex biological systems and cellular networks may underlie most genotype to phenotype relationships. Here we review basic concepts in network biology, discussing different types of interactome networks and the insights that can come from analyzing them. We elaborate on why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties ma...

  7. Human genome-guided identification of memory-modulating drugs.

    Science.gov (United States)

    Papassotiropoulos, Andreas; Gerhards, Christiane; Heck, Angela; Ackermann, Sandra; Aerni, Amanda; Schicktanz, Nathalie; Auschra, Bianca; Demougin, Philippe; Mumme, Eva; Elbert, Thomas; Ertl, Verena; Gschwind, Leo; Hanser, Edveena; Huynh, Kim-Dung; Jessen, Frank; Kolassa, Iris-Tatjana; Milnik, Annette; Paganetti, Paolo; Spalek, Klara; Vogler, Christian; Muhs, Andreas; Pfeifer, Andrea; de Quervain, Dominique J-F

    2013-11-12

    In the last decade there has been an exponential increase in knowledge about the genetic basis of complex human traits, including neuropsychiatric disorders. It is not clear, however, to what extent this knowledge can be used as a starting point for drug identification, one of the central hopes of the human genome project. The aim of the present study was to identify memory-modulating compounds through the use of human genetic information. We performed a multinational collaborative study, which included assessment of aversive memory--a trait central to posttraumatic stress disorder--and a gene-set analysis in healthy individuals. We identified 20 potential drug target genes in two genomewide-corrected gene sets: the neuroactive ligand-receptor interaction and the long-term depression gene set. In a subsequent double-blind, placebo-controlled study in healthy volunteers, we aimed at providing a proof of concept for the genome-guided identification of memory modulating compounds. Pharmacological intervention at the neuroactive ligand-receptor interaction gene set led to significant reduction of aversive memory. The findings demonstrate that genome information, along with appropriate data mining methodology, can be used as a starting point for the identification of memory-modulating compounds.

  8. Is the HM story only a "remote memory"? Some facts about hippocampus and memory in humans.

    Science.gov (United States)

    Deweer, B; Pillon, B; Pochon, J B; Dubois, B

    2001-12-14

    In this review, we argue that a number of current data support the notion that the hippocampal formations play an important role in episodic memory in humans. We will focus on data gathered from three topics within this field: (1) the neuropsychological study of memory in degenerative diseases, which provides striking dissociations of processes, as a function of the location of cerebral lesions and of their functional consequences; (2) the description of patients' memory difficulties after unilateral medial temporal lobectomy. Given the visuo-verbal dissociation, we may anticipate that the study of the effects of such lesions may help in the understanding of the role of the hippocampus in memory, in terms of: (i) the stage of memory processing where the hippocampus is really involved (encoding, consolidation and/or retrieval); (ii) the specificity of the impairments as a function of the nature (verbal vs. visuo-spatial) of the to-be-remembered material; (3) recent evidence from imaging studies: (i) the morphological approach, which provides interesting information with the study of correlations between the volumes of diverse cerebral regions-particularly the volume of the hippocampus-and episodic memory performance and other cognitive measures; (ii) metabolic studies, using PET scan, which were first designed for correlational analyses between performance in episodic memory tasks and glucose utilization at rest in diverse regions of interest, such as the hippocampal formations; (iii) activation studies with PET and functional MRI, which are actually more straightforward, since they allow correlations between the metabolism in regions of interest and performance on line (e.g. during encoding or retrieval of information). In our view, inasmuch as such different approaches-degenerative diseases, lesions or imagery-provide convergent information, they give renewed weight to the notion according to which the hippocampal formations are critically concerned in episodic

  9. Changes in brain network efficiency and working memory performance in aging.

    Science.gov (United States)

    Stanley, Matthew L; Simpson, Sean L; Dagenbach, Dale; Lyday, Robert G; Burdette, Jonathan H; Laurienti, Paul J

    2015-01-01

    Working memory is a complex psychological construct referring to the temporary storage and active processing of information. We used functional connectivity brain network metrics quantifying local and global efficiency of information transfer for predicting individual variability in working memory performance on an n-back task in both young (n = 14) and older (n = 15) adults. Individual differences in both local and global efficiency during the working memory task were significant predictors of working memory performance in addition to age (and an interaction between age and global efficiency). Decreases in local efficiency during the working memory task were associated with better working memory performance in both age cohorts. In contrast, increases in global efficiency were associated with much better working performance for young participants; however, increases in global efficiency were associated with a slight decrease in working memory performance for older participants. Individual differences in local and global efficiency during resting-state sessions were not significant predictors of working memory performance. Significant group whole-brain functional network decreases in local efficiency also were observed during the working memory task compared to rest, whereas no significant differences were observed in network global efficiency. These results are discussed in relation to recently developed models of age-related differences in working memory.

  10. Changes in brain network efficiency and working memory performance in aging.

    Directory of Open Access Journals (Sweden)

    Matthew L Stanley

    Full Text Available Working memory is a complex psychological construct referring to the temporary storage and active processing of information. We used functional connectivity brain network metrics quantifying local and global efficiency of information transfer for predicting individual variability in working memory performance on an n-back task in both young (n = 14 and older (n = 15 adults. Individual differences in both local and global efficiency during the working memory task were significant predictors of working memory performance in addition to age (and an interaction between age and global efficiency. Decreases in local efficiency during the working memory task were associated with better working memory performance in both age cohorts. In contrast, increases in global efficiency were associated with much better working performance for young participants; however, increases in global efficiency were associated with a slight decrease in working memory performance for older participants. Individual differences in local and global efficiency during resting-state sessions were not significant predictors of working memory performance. Significant group whole-brain functional network decreases in local efficiency also were observed during the working memory task compared to rest, whereas no significant differences were observed in network global efficiency. These results are discussed in relation to recently developed models of age-related differences in working memory.

  11. Functional brain network modularity captures inter- and intra-individual variation in working memory capacity.

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    Alexander A Stevens

    Full Text Available BACKGROUND: Cognitive abilities, such as working memory, differ among people; however, individuals also vary in their own day-to-day cognitive performance. One potential source of cognitive variability may be fluctuations in the functional organization of neural systems. The degree to which the organization of these functional networks is optimized may relate to the effective cognitive functioning of the individual. Here we specifically examine how changes in the organization of large-scale networks measured via resting state functional connectivity MRI and graph theory track changes in working memory capacity. METHODOLOGY/PRINCIPAL FINDINGS: Twenty-two participants performed a test of working memory capacity and then underwent resting-state fMRI. Seventeen subjects repeated the protocol three weeks later. We applied graph theoretic techniques to measure network organization on 34 brain regions of interest (ROI. Network modularity, which measures the level of integration and segregation across sub-networks, and small-worldness, which measures global network connection efficiency, both predicted individual differences in memory capacity; however, only modularity predicted intra-individual variation across the two sessions. Partial correlations controlling for the component of working memory that was stable across sessions revealed that modularity was almost entirely associated with the variability of working memory at each session. Analyses of specific sub-networks and individual circuits were unable to consistently account for working memory capacity variability. CONCLUSIONS/SIGNIFICANCE: The results suggest that the intrinsic functional organization of an a priori defined cognitive control network measured at rest provides substantial information about actual cognitive performance. The association of network modularity to the variability in an individual's working memory capacity suggests that the organization of this network into high

  12. Abnormal Functional Activation and Connectivity in the Working Memory Network in Early-Onset Schizophrenia

    Science.gov (United States)

    Kyriakopoulos, Marinos; Dima, Danai; Roiser, Jonathan P.; Corrigall, Richard; Barker, Gareth J.; Frangou, Sophia

    2012-01-01

    Objective: Disruption within the working memory (WM) neural network is considered an integral feature of schizophrenia. The WM network, and the dorsolateral prefrontal cortex (DLPFC) in particular, undergo significant remodeling in late adolescence. Potential interactions between developmental changes in the WM network and disease-related…

  13. Tactile perception and working memory in rats and humans.

    Science.gov (United States)

    Fassihi, Arash; Akrami, Athena; Esmaeili, Vahid; Diamond, Mathew E

    2014-02-11

    Primates can store sensory stimulus parameters in working memory for subsequent manipulation, but until now, there has been no demonstration of this capacity in rodents. Here we report tactile working memory in rats. Each stimulus is a vibration, generated as a series of velocity values sampled from a normal distribution. To perform the task, the rat positions its whiskers to receive two such stimuli, "base" and "comparison," separated by a variable delay. It then judges which stimulus had greater velocity SD. In analogous experiments, humans compare two vibratory stimuli on the fingertip. We demonstrate that the ability of rats to hold base stimulus information (for up to 8 s) and their acuity in assessing stimulus differences overlap the performance demonstrated by humans. This experiment highlights the ability of rats to perceive the statistical structure of vibrations and reveals their previously unknown capacity to store sensory information in working memory.

  14. Tactile perception and working memory in rats and humans

    Science.gov (United States)

    Fassihi, Arash; Akrami, Athena; Esmaeili, Vahid; Diamond, Mathew E.

    2014-01-01

    Primates can store sensory stimulus parameters in working memory for subsequent manipulation, but until now, there has been no demonstration of this capacity in rodents. Here we report tactile working memory in rats. Each stimulus is a vibration, generated as a series of velocity values sampled from a normal distribution. To perform the task, the rat positions its whiskers to receive two such stimuli, “base” and “comparison,” separated by a variable delay. It then judges which stimulus had greater velocity SD. In analogous experiments, humans compare two vibratory stimuli on the fingertip. We demonstrate that the ability of rats to hold base stimulus information (for up to 8 s) and their acuity in assessing stimulus differences overlap the performance demonstrated by humans. This experiment highlights the ability of rats to perceive the statistical structure of vibrations and reveals their previously unknown capacity to store sensory information in working memory. PMID:24449850

  15. Musical and verbal semantic memory: two distinct neural networks?

    OpenAIRE

    Groussard, Mathilde; Viader, Fausto; Hubert, Valérie; Landeau, Brigitte; Abbas, Ahmed; Desgranges, Béatrice; Eustache, Francis; Platel, Hervé

    2010-01-01

    International audience; Semantic memory has been investigated in numerous neuroimaging and clinical studies, most of which have used verbal or visual, but only very seldom, musical material. Clinical studies have suggested that there is a relative neural independence between verbal and musical semantic memory. In the present study, "musical semantic memory" is defined as memory for "well-known" melodies without any knowledge of the spatial or temporal circumstances of learning, while "verbal ...

  16. Dynamically Allocated Hub in Task-Evoked Network Predicts the Vulnerable Prefrontal Locus for Contextual Memory Retrieval in Macaques.

    Directory of Open Access Journals (Sweden)

    Takahiro Osada

    2015-06-01

    Full Text Available Neuroimaging and neurophysiology have revealed that multiple areas in the prefrontal cortex (PFC are activated in a specific memory task, but severity of impairment after PFC lesions is largely different depending on which activated area is damaged. The critical relationship between lesion sites and impairments has not yet been given a clear mechanistic explanation. Although recent works proposed that a whole-brain network contains hubs that play integrative roles in cortical information processing, this framework relying on an anatomy-based structural network cannot account for the vulnerable locus for a specific task, lesioning of which would bring impairment. Here, we hypothesized that (i activated PFC areas dynamically form an ordered network centered at a task-specific "functional hub" and (ii the lesion-effective site corresponds to the "functional hub," but not to a task-invariant "structural hub." To test these hypotheses, we conducted functional magnetic resonance imaging experiments in macaques performing a temporal contextual memory task. We found that the activated areas formed a hierarchical hub-centric network based on task-evoked directed connectivity, differently from the anatomical network reflecting axonal projection patterns. Using a novel simulated-lesion method based on support vector machine, we estimated severity of impairment after lesioning of each area, which accorded well with a known dissociation in contextual memory impairment in macaques (impairment after lesioning in area 9/46d, but not in area 8Ad. The predicted severity of impairment was proportional to the network "hubness" of the virtually lesioned area in the task-evoked directed connectivity network, rather than in the anatomical network known from tracer studies. Our results suggest that PFC areas dynamically and cooperatively shape a functional hub-centric network to reallocate the lesion-effective site depending on the cognitive processes, apart from

  17. Dynamically Allocated Hub in Task-Evoked Network Predicts the Vulnerable Prefrontal Locus for Contextual Memory Retrieval in Macaques.

    Science.gov (United States)

    Osada, Takahiro; Adachi, Yusuke; Miyamoto, Kentaro; Jimura, Koji; Setsuie, Rieko; Miyashita, Yasushi

    2015-06-01

    Neuroimaging and neurophysiology have revealed that multiple areas in the prefrontal cortex (PFC) are activated in a specific memory task, but severity of impairment after PFC lesions is largely different depending on which activated area is damaged. The critical relationship between lesion sites and impairments has not yet been given a clear mechanistic explanation. Although recent works proposed that a whole-brain network contains hubs that play integrative roles in cortical information processing, this framework relying on an anatomy-based structural network cannot account for the vulnerable locus for a specific task, lesioning of which would bring impairment. Here, we hypothesized that (i) activated PFC areas dynamically form an ordered network centered at a task-specific "functional hub" and (ii) the lesion-effective site corresponds to the "functional hub," but not to a task-invariant "structural hub." To test these hypotheses, we conducted functional magnetic resonance imaging experiments in macaques performing a temporal contextual memory task. We found that the activated areas formed a hierarchical hub-centric network based on task-evoked directed connectivity, differently from the anatomical network reflecting axonal projection patterns. Using a novel simulated-lesion method based on support vector machine, we estimated severity of impairment after lesioning of each area, which accorded well with a known dissociation in contextual memory impairment in macaques (impairment after lesioning in area 9/46d, but not in area 8Ad). The predicted severity of impairment was proportional to the network "hubness" of the virtually lesioned area in the task-evoked directed connectivity network, rather than in the anatomical network known from tracer studies. Our results suggest that PFC areas dynamically and cooperatively shape a functional hub-centric network to reallocate the lesion-effective site depending on the cognitive processes, apart from static anatomical

  18. Reputation drives cooperative behaviour and network formation in human groups.

    Science.gov (United States)

    Cuesta, Jose A; Gracia-Lázaro, Carlos; Ferrer, Alfredo; Moreno, Yamir; Sánchez, Angel

    2015-01-19

    Cooperativeness is a defining feature of human nature. Theoreticians have suggested several mechanisms to explain this ubiquitous phenomenon, including reciprocity, reputation, and punishment, but the problem is still unsolved. Here we show, through experiments conducted with groups of people playing an iterated Prisoner's Dilemma on a dynamic network, that it is reputation what really fosters cooperation. While this mechanism has already been observed in unstructured populations, we find that it acts equally when interactions are given by a network that players can reconfigure dynamically. Furthermore, our observations reveal that memory also drives the network formation process, and cooperators assort more, with longer link lifetimes, the longer the past actions record. Our analysis demonstrates, for the first time, that reputation can be very well quantified as a weighted mean of the fractions of past cooperative acts and the last action performed. This finding has potential applications in collaborative systems and e-commerce.

  19. Impact of memory on human dynamics

    CERN Document Server

    Vazquez, A

    2006-01-01

    Our experience of web access slowing down is a consequence of the aggregated web access pattern of web users. This is just one example among several human oriented services which are strongly affected by human activity patterns. Recent empirical evidence is indicating that human activity patterns are characterized by power law distributions of inter-event times, where large fluctuations rather than regularity is the common case. I show that this temporal heterogeneity can be explained by two mechanisms: (i) humans have some perception of their past activity rate and (ii) based on that they react by accelerating or reducing their activity rate. Using these two mechanisms I explain the inter-event time statistics of Darwin's and Einstein's correspondence and the email activity within an university environment. Moreover, they are typical examples of the the accelerating and reducing class, respectively. These results are relevant to the system design of human oriented services.

  20. Approaching human language with complex networks

    Science.gov (United States)

    Cong, Jin; Liu, Haitao

    2014-12-01

    The interest in modeling and analyzing human language with complex networks is on the rise in recent years and a considerable body of research in this area has already been accumulated. We survey three major lines of linguistic research from the complex network approach: 1) characterization of human language as a multi-level system with complex network analysis; 2) linguistic typological research with the application of linguistic networks and their quantitative measures; and 3) relationships between the system-level complexity of human language (determined by the topology of linguistic networks) and microscopic linguistic (e.g., syntactic) features (as the traditional concern of linguistics). We show that the models and quantitative tools of complex networks, when exploited properly, can constitute an operational methodology for linguistic inquiry, which contributes to the understanding of human language and the development of linguistics. We conclude our review with suggestions for future linguistic research from the complex network approach: 1) relationships between the system-level complexity of human language and microscopic linguistic features; 2) expansion of research scope from the global properties to other levels of granularity of linguistic networks; and 3) combination of linguistic network analysis with other quantitative studies of language (such as quantitative linguistics).

  1. Combined, Independent Small Molecule Release and Shape Memory via Nanogel-Coated Thiourethane Polymer Networks.

    Science.gov (United States)

    Dailing, Eric A; Nair, Devatha P; Setterberg, Whitney K; Kyburz, Kyle A; Yang, Chun; D'Ovidio, Tyler; Anseth, Kristi S; Stansbury, Jeffrey W

    2016-01-28

    Drug releasing shape memory polymers (SMPs) were prepared from poly(thiourethane) networks that were coated with drug loaded nanogels through a UV initiated, surface mediated crosslinking reaction. Multifunctional thiol and isocyanate monomers were crosslinked through a step-growth mechanism to produce polymers with a homogeneous network structure that exhibited a sharp glass transition with 97% strain recovery and 96% shape fixity. Incorporating a small stoichiometric excess of thiol groups left pendant functionality for a surface coating reaction. Nanogels with diameter of approximately 10 nm bearing allyl and methacrylate groups were prepared separately via solution free radical polymerization. Coatings with thickness of 10-30 μm were formed via dip-coating and subsequent UV-initiated thiol-ene crosslinking between the SMP surface and the nanogel, and through inter-nanogel methacrylate homopolymerization. No significant change in mechanical properties or shape memory behavior was observed after the coating process, indicating that functional coatings can be integrated into an SMP without altering its original performance. Drug bioactivity was confirmed via in vitro culturing of human mesenchymal stem cells with SMPs coated with dexamethasone-loaded nanogels. This article offers a new strategy to independently tune multiple functions on a single polymeric device, and has broad application toward implantable, minimally invasive medical devices such as vascular stents and ocular shunts, where local drug release can greatly prolong device function.

  2. Automatic Cloud Resource Scaling Algorithm based on Long Short-Term Memory Recurrent Neural Network

    National Research Council Canada - National Science Library

    Ashraf A. Shahin

    2016-01-01

    .... This paper has proposed dynamic threshold based auto-scaling algorithms that predict required resources using Long Short-Term Memory Recurrent Neural Network and auto-scale virtual resources based on predicted values...

  3. Repeated Stimulation of Cultured Networks of Rat Cortical Neurons Induces Parallel Memory Traces

    Science.gov (United States)

    le Feber, Joost; Witteveen, Tim; van Veenendaal, Tamar M.; Dijkstra, Jelle

    2015-01-01

    During systems consolidation, memories are spontaneously replayed favoring information transfer from hippocampus to neocortex. However, at present no empirically supported mechanism to accomplish a transfer of memory from hippocampal to extra-hippocampal sites has been offered. We used cultured neuronal networks on multielectrode arrays and…

  4. Externally induced frontoparietal synchronization modulates network dynamics and enhances working memory performance

    Science.gov (United States)

    Violante, Ines R; Li, Lucia M; Carmichael, David W; Lorenz, Romy; Leech, Robert; Hampshire, Adam; Rothwell, John C; Sharp, David J

    2017-01-01

    Cognitive functions such as working memory (WM) are emergent properties of large-scale network interactions. Synchronisation of oscillatory activity might contribute to WM by enabling the coordination of long-range processes. However, causal evidence for the way oscillatory activity shapes network dynamics and behavior in humans is limited. Here we applied transcranial alternating current stimulation (tACS) to exogenously modulate oscillatory activity in a right frontoparietal network that supports WM. Externally induced synchronization improved performance when cognitive demands were high. Simultaneously collected fMRI data reveals tACS effects dependent on the relative phase of the stimulation and the internal cognitive processing state. Specifically, synchronous tACS during the verbal WM task increased parietal activity, which correlated with behavioral performance. Furthermore, functional connectivity results indicate that the relative phase of frontoparietal stimulation influences information flow within the WM network. Overall, our findings demonstrate a link between behavioral performance in a demanding WM task and large-scale brain synchronization. DOI: http://dx.doi.org/10.7554/eLife.22001.001 PMID:28288700

  5. Memory Networks in Tinnitus: A Functional Brain Image Study

    Science.gov (United States)

    Laureano, Maura Regina; Onishi, Ektor Tsuneo; Bressan, Rodrigo Affonseca; Castiglioni, Mario Luiz Vieira; Batista, Ilza Rosa; Reis, Marilia Alves; Garcia, Michele Vargas; de Andrade, Adriana Neves; de Almeida, Roberta Ribeiro; Garrido, Griselda J.; Jackowski, Andrea Parolin

    2014-01-01

    Tinnitus is characterized by the perception of sound in the absence of an external auditory stimulus. The network connectivity of auditory and non-auditory brain structures associated with emotion, memory and attention are functionally altered in debilitating tinnitus. Current studies suggest that tinnitus results from neuroplastic changes in the frontal and limbic temporal regions. The objective of this study was to use Single-Photon Emission Computed Tomography (SPECT) to evaluate changes in the cerebral blood flow in tinnitus patients with normal hearing compared with healthy controls. Methods: Twenty tinnitus patients with normal hearing and 17 healthy controls, matched for sex, age and years of education, were subjected to Single Photon Emission Computed Tomography using the radiotracer ethylenedicysteine diethyl ester, labeled with Technetium 99 m (99 mTc-ECD SPECT). The severity of tinnitus was assessed using the “Tinnitus Handicap Inventory” (THI). The images were processed and analyzed using “Statistical Parametric Mapping” (SPM8). Results: A significant increase in cerebral perfusion in the left parahippocampal gyrus (pFWE <0.05) was observed in patients with tinnitus compared with healthy controls. The average total THI score was 50.8+18.24, classified as moderate tinnitus. Conclusion: It was possible to identify significant changes in the limbic system of the brain perfusion in tinnitus patients with normal hearing, suggesting that central mechanisms, not specific to the auditory pathway, are involved in the pathophysiology of symptoms, even in the absence of clinically diagnosed peripheral changes. PMID:24516567

  6. Functional neural networks underlying semantic encoding of associative memories.

    Science.gov (United States)

    Crespo-Garcia, M; Cantero, J L; Pomyalov, A; Boccaletti, S; Atienza, M

    2010-04-15

    Evidence suggests that theta oscillations recruit distributed cortical representations to improve associative encoding under semantically congruent conditions. Here we show that positive effects of semantic context on encoding and retrieval of associations are mediated by changes in the coupling pattern between EEG theta sources. During successful encoding of semantically congruent face-location associations, the right superior parietal lobe showed enhanced theta phase synchronization with other regions within the lateral posterior parietal lobe (PPL) and left medial temporal lobe (MTL). However, functional coordination involving the inferior parietal lobe was higher in the incongruent condition. These results suggest a differential engagement of top-down and bottom-up mechanisms during encoding of semantically congruent and incongruent episodic associations, respectively. Although retrieval processes operated on a similar neural network, the main difference with the study phase was the larger amount of functional links shown by the lateral prefrontal cortex with regions of the MTL and PPL. All together, these results suggest that theta oscillations mediate, at least partially, the positive effect of semantic congruence on associative memory by (i) optimizing top-down attentional mechanisms through enhanced theta phase synchronization between dorsal regions of the PPL and MTL and (ii) by adjusting the control of automatic attention to sensory and contextual information reactivated in the MTL through functional connections with the inferior parietal lobe during both encoding and retrieval processes.

  7. Memory networks in tinnitus: a functional brain image study.

    Directory of Open Access Journals (Sweden)

    Maura Regina Laureano

    Full Text Available Tinnitus is characterized by the perception of sound in the absence of an external auditory stimulus. The network connectivity of auditory and non-auditory brain structures associated with emotion, memory and attention are functionally altered in debilitating tinnitus. Current studies suggest that tinnitus results from neuroplastic changes in the frontal and limbic temporal regions. The objective of this study was to use Single-Photon Emission Computed Tomography (SPECT to evaluate changes in the cerebral blood flow in tinnitus patients with normal hearing compared with healthy controls.Twenty tinnitus patients with normal hearing and 17 healthy controls, matched for sex, age and years of education, were subjected to Single Photon Emission Computed Tomography using the radiotracer ethylenedicysteine diethyl ester, labeled with Technetium 99 m (99 mTc-ECD SPECT. The severity of tinnitus was assessed using the "Tinnitus Handicap Inventory" (THI. The images were processed and analyzed using "Statistical Parametric Mapping" (SPM8.A significant increase in cerebral perfusion in the left parahippocampal gyrus (pFWE <0.05 was observed in patients with tinnitus compared with healthy controls. The average total THI score was 50.8+18.24, classified as moderate tinnitus.It was possible to identify significant changes in the limbic system of the brain perfusion in tinnitus patients with normal hearing, suggesting that central mechanisms, not specific to the auditory pathway, are involved in the pathophysiology of symptoms, even in the absence of clinically diagnosed peripheral changes.

  8. Memory regulatory T cells reside in human skin.

    Science.gov (United States)

    Sanchez Rodriguez, Robert; Pauli, Mariela L; Neuhaus, Isaac M; Yu, Siegrid S; Arron, Sarah T; Harris, Hobart W; Yang, Sara Hsin-Yi; Anthony, Bryan A; Sverdrup, Francis M; Krow-Lucal, Elisabeth; MacKenzie, Tippi C; Johnson, David S; Meyer, Everett H; Löhr, Andrea; Hsu, Andro; Koo, John; Liao, Wilson; Gupta, Rishu; Debbaneh, Maya G; Butler, Daniel; Huynh, Monica; Levin, Ethan C; Leon, Argentina; Hoffman, William Y; McGrath, Mary H; Alvarado, Michael D; Ludwig, Connor H; Truong, Hong-An; Maurano, Megan M; Gratz, Iris K; Abbas, Abul K; Rosenblum, Michael D

    2014-03-01

    Regulatory T cells (Tregs), which are characterized by expression of the transcription factor Foxp3, are a dynamic and heterogeneous population of cells that control immune responses and prevent autoimmunity. We recently identified a subset of Tregs in murine skin with properties typical of memory cells and defined this population as memory Tregs (mTregs). Due to the importance of these cells in regulating tissue inflammation in mice, we analyzed this cell population in humans and found that almost all Tregs in normal skin had an activated memory phenotype. Compared with mTregs in peripheral blood, cutaneous mTregs had unique cell surface marker expression and cytokine production. In normal human skin, mTregs preferentially localized to hair follicles and were more abundant in skin with high hair density. Sequence comparison of TCRs from conventional memory T helper cells and mTregs isolated from skin revealed little homology between the two cell populations, suggesting that they recognize different antigens. Under steady-state conditions, mTregs were nonmigratory and relatively unresponsive; however, in inflamed skin from psoriasis patients, mTregs expanded, were highly proliferative, and produced low levels of IL-17. Taken together, these results identify a subset of Tregs that stably resides in human skin and suggest that these cells are qualitatively defective in inflammatory skin disease.

  9. Altered neural network supporting declarative long-term memory in mild cognitive impairment.

    Science.gov (United States)

    Poettrich, Katrin; Weiss, Peter H; Werner, Annett; Lux, Silke; Donix, Markus; Gerber, Johannes; von Kummer, Rüdiger; Fink, Gereon R; Holthoff, Vjera A

    2009-02-01

    Autobiographical episodic memory represents a subsystem of declarative long-term memory and largely depends on combining information from multiple sources. The purpose of this study was to assess neural correlates of declarative long-term memory in patients with amnestic mild cognitive impairment (MCI) and controls using fMRI and a task requiring autobiographical and semantic memory retrieval. Comparison of the network supporting episodic autobiographical and semantic memory irrespective of remoteness (recent and remote) revealed significant activations in right parietal cortex and precuneus bilaterally in the patients. Autobiographical episodic versus semantic memory retrieval in the controls led to significant bilateral activations of the parietal-temporal junction, left temporal pole, anterior cingulate, retrosplenial cortex and cerebellum. In contrast, MCI patients activated left supplementary motor area, left premotor and superior temporal cortex. In MCI patients compared to controls a dysfunction of the retrosplenial cortex during memory retrieval was revealed by a lack of differential activation in relation to recency of memories and memory type. Our data suggest that MCI leads to a loss of specificity in the neural network supporting declarative long-term memory.

  10. The structural connectivity pattern of the default mode network and its association with memory and anxiety

    Directory of Open Access Journals (Sweden)

    Yan eTao

    2015-11-01

    Full Text Available The default mode network (DMN is one of the most widely studied resting state functional networks. The structural basis for the DMN is of particular interest and has been studied by several researchers using diffusion tensor imaging (DTI. Most of these previous studies focused on a few regions or white matter tracts of the DMN so that the global structural connectivity pattern and network properties of the DMN remain unclear. Moreover, evidences indicate that the DMN is involved in both memory and emotion, but how the DMN regulates memory and anxiety from the perspective of the whole DMN structural network remains unknown. We used multimodal neuroimaging methods to investigate the structural connectivity pattern of the DMN and the association of its network properties with memory and anxiety in 205 young healthy subjects. Using a probabilistic fiber tractography technique based on DTI data and graph theory methods, we constructed the global structural connectivity pattern of the DMN and found that memory quotient (MQ score was significantly positively correlated with the global and local efficiency of the DMN whereas anxiety was found to be negatively correlated with the efficiency. The strong structural connectivity between multiple brain regions within DMN may reflect that the DMN has certain structural basis. Meanwhile, we found the network efficiency of the DMN were related to memory and anxiety measures, which indicated that the DMN may play a role in the memory and anxiety.

  11. A model of working memory: bridging the gap between electrophysiology and human brain imaging.

    Science.gov (United States)

    Tagamets, M A; Horwitz, B

    2000-01-01

    Human neuroimaging methods such as positron emission tomography and functional magnetic resonance imaging have made possible the study of large-scale distributed networks in the behaving human brain. Although many imaging studies support and extend knowledge gained from other experimental modalities such as animal single-cell recordings, there have also been a substantial number of experiments that appear to contradict the animal studies. Part of the reason for this is that neuroimaging is an indirect measure of neuronal firing activity, and thus interpretation is difficult. Computational modeling can help to bridge the gap by providing a substrate for making explicit the assumptions and constraints provided from other sources such as anatomy, physiology and behavior. We describe a large-scale model of working memory that we have used to examine a number of issues relating to the interpretation of imaging data. The gating mechanism that regulates engagement and retention of short-term memory is revised to better reflect hypothesized underlying neuromodulatory mechanisms. It is shown that in addition to imparting better performance for the memory circuit, this mechanism also provides a better match to imaging data from working memory studies.

  12. Hierarchical modularity in human brain functional networks

    CERN Document Server

    Meunier, D; Fornito, A; Ersche, K D; Bullmore, E T; 10.3389/neuro.11.037.2009

    2010-01-01

    The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or "modules-within-modules") decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI) in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at ...

  13. Enhanced memory for emotional material following stress-level cortisol treatment in humans.

    Science.gov (United States)

    Buchanan, T W; Lovallo, W R

    2001-04-01

    Memory tends to be better for emotionally arousing information than for neutral information. Evidence from animal studies indicates that corticosteroids may be necessary for this memory enhancement to occur. We extend these findings to human memory performance. Following administration of cortisol (20 mg) or placebo, participants were exposed to pictures varying in emotional arousal. Incidental memory for the pictures was assessed one week later. We show that elevated cortisol levels during memory encoding enhances the long-term recall performance of emotionally arousing pictures relative to neutral pictures. These results extend previous work on corticosteroid enhancement of memory and suggest that high cortisol levels during arousing events result in enhanced memory in humans.

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

    Directory of Open Access Journals (Sweden)

    Laura Dempere-Marco

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

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

    Science.gov (United States)

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

    2012-01-01

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

  16. Networks of self-defining memories as a contributing factor to emotional openness.

    Science.gov (United States)

    Houle, Iliane; Philippe, Frederick L; Lecours, Serge; Roulez, Josiane

    2017-02-06

    Emotional openness is characterised by a capacity to tolerate threatening self-relevant material and an interest towards new emotional situations. We investigated how specific networks of memories could be an important contributing factor to emotional openness. At Phase 1, participants completed measures of personality traits and emotional intelligence, described a self-defining memory, provided other memories associated with it, and rated the valence of each of their memories. A score assessing the complexity of this memory network, comprising the number of memories reported and their valence diversity, was created. Two weeks later, in laboratory, participants watched an anxiety-inducing film and took part in an interview assessing their emotional openness to the film. They completed a cognitive task before and after the film to measure ego depletion. Controlling for traits and emotional intelligence, memory network complexity was positively associated with emotional openness and negatively with ego depletion. The mental organisation of self-defining memories thus appears to be a critical factor contributing to emotional openness.

  17. NCI’s Cooperative Human Tissue Network

    Science.gov (United States)

    Quality biospecimens are a foundational resource for cancer research. One of NCI’s longest running biospecimen programs is the Cooperative Human Tissue Network, a resource mainly for basic discovery and early translational research.

  18. Out-of-Sequence Preventative Cell Dispatching for Multicast Input-Queued Space-Memory-Memory Clos-Network

    DEFF Research Database (Denmark)

    Yu, Hao; Ruepp, Sarah Renée; Berger, Michael Stübert

    2011-01-01

    This paper proposes two out-of-sequence (OOS) preventative cell dispatching algorithms for the multicast input-queued space-memory-memory (IQ-SMM) Clos-network switch architecture, i.e. the multicast flow-based DSRR (MF-DSRR) and the multicast flow-based round-robin (MFRR). Treating each cell...... independently, the desynchronized static round-robin (DSRR) cell dispatching scheme can evenly distribute cells to the central switching modules, however, its frequent change of the input switching module connection pattern causes a serious OOS problem to the IQ-SMM architecture. Therefore large reassembly...

  19. Preventing Out-of-Sequence for Multicast Input-Queued Space-Memory-Memory Clos-Network

    DEFF Research Database (Denmark)

    Yu, Hao; Ruepp, Sarah Renée; Berger, Michael Stübert

    2011-01-01

    This paper proposes an out-of-sequence (OOS) preventative cell dispatching algorithm, the multicast flow-based round robin (MFRR), for multicast input-queued space-memory-memory (IQ-SMM) Clos-network architecture. Independently treating each incoming cell, such as the desynchronized static round...... robin (DSRR), can lead to cells of the same packet being disordered after traversing the switch fabric. Extra reassembly buffer and delay are thus required at the outputs of the switch fabric to reorder the cells. Simulation results obtained by OPNET Modeler show that the MFRR can eliminate such OOS...

  20. A Novel Lightweight Main Memory Database for Telecom Network Performance Management System

    Directory of Open Access Journals (Sweden)

    Lina Lan

    2012-04-01

    Full Text Available Today telecom network are growing complex. Although the amount of network performance data increased dramatically, telecom network operators require better performance on network performance data collection and analysis. Database is the important component in modern network management model. Since main memory database (MMDB store data in main physical memory and provide very high-speed access, MMDB can suffice the requirements on data intensive and real time response in network performance management system. This paper presents a novel lightweight design on MMDB for network performance data persistence. This design improves data access performance in following aspects.  The data persistence mechanism employs user mode memory map provided by UNIX OS. To reduce the cost of data copy and data interpretation, the data storage format is designed as consistent with binary format in application memory. The database is provided as program library and the application can access data in shared memory to avoid the cost on inter-process communication. Once data is updated in memory, query application can get updated data without disk I/O cost. The data access methods adopt multi-level RB-Tree structure. In best case, the algorithm complexity is O(N. In worst case, the algorithm complexity is O(N*lgN. In real performance data distribution scenarios, the complexity is nearly O(N. The system approach has been tested in laboratory using benchmark data. The result shows the performances of the application fully meet the requirements of the product index. The CPU and memory consumption are also lower than network management system requirements.

  1. Complex network structure influences processing in long-term and short-term memory

    Science.gov (United States)

    Vitevitch, Michael S.; Chan, Kit Ying; Roodenrys, Steven

    2012-01-01

    Complex networks describe how entities in systems interact; the structure of such networks is argued to influence processing. One measure of network structure, clustering coefficient, C, measures the extent to which neighbors of a node are also neighbors of each other. Previous psycholinguistic experiments found that the C of phonological word-forms influenced retrieval from the mental lexicon (that portion of long-term memory dedicated to language) during the on-line recognition and production of spoken words. In the present study we examined how network structure influences other retrieval processes in long- and short-term memory. In a false-memory task—examining long-term memory—participants falsely recognized more words with low- than high-C. In a recognition memory task—examining veridical memories in long-term memory—participants correctly recognized more words with low- than high-C. However, participants in a serial recall task—examining redintegration in short-term memory—recalled lists comprised of high-C words more accurately than lists comprised of low-C words. These results demonstrate that network structure influences cognitive processes associated with several forms of memory including lexical, long-term, and short-term. PMID:22745522

  2. Automatic temporal segment detection via bilateral long short-term memory recurrent neural networks

    Science.gov (United States)

    Sun, Bo; Cao, Siming; He, Jun; Yu, Lejun; Li, Liandong

    2017-03-01

    Constrained by the physiology, the temporal factors associated with human behavior, irrespective of facial movement or body gesture, are described by four phases: neutral, onset, apex, and offset. Although they may benefit related recognition tasks, it is not easy to accurately detect such temporal segments. An automatic temporal segment detection framework using bilateral long short-term memory recurrent neural networks (BLSTM-RNN) to learn high-level temporal-spatial features, which synthesizes the local and global temporal-spatial information more efficiently, is presented. The framework is evaluated in detail over the face and body database (FABO). The comparison shows that the proposed framework outperforms state-of-the-art methods for solving the problem of temporal segment detection.

  3. Remapping of memory encoding and retrieval networks: insights from neuroimaging in primates.

    Science.gov (United States)

    Miyamoto, Kentaro; Osada, Takahiro; Adachi, Yusuke

    2014-12-15

    Advancements in neuroimaging techniques have allowed for the investigation of the neural correlates of memory functions in the whole human brain. Thus, the involvement of various cortical regions, including the medial temporal lobe (MTL) and posterior parietal cortex (PPC), has been repeatedly reported in the human memory processes of encoding and retrieval. However, the functional roles of these sites could be more fully characterized utilizing nonhuman primate models, which afford the potential for well-controlled, finer-scale experimental procedures that are inapplicable to humans, including electrophysiology, histology, genetics, and lesion approaches. Yet, the presence and localization of the functional counterparts of these human memory-related sites in the macaque monkey MTL or PPC were previously unknown. Therefore, to bridge the inter-species gap, experiments were required in monkeys using functional magnetic resonance imaging (fMRI), the same methodology adopted in human studies. Here, we briefly review the history of experimentation on memory systems using a nonhuman primate model and our recent fMRI studies examining memory processing in monkeys performing recognition memory tasks. We will discuss the memory systems common to monkeys and humans and future directions of finer cell-level characterization of memory-related processes using electrophysiological recording and genetic manipulation approaches. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. Default Mode Network Activity Predicts Early Memory Decline in Healthy Young Adults Aged 18-31.

    Science.gov (United States)

    Nelson, Steven M; Savalia, Neil K; Fishell, Andrew K; Gilmore, Adrian W; Zou, Fan; Balota, David A; McDermott, Kathleen B

    2016-08-01

    Functional magnetic resonance imaging (fMRI) research conducted in healthy young adults is typically done with the assumption that this sample is largely homogeneous. However, studies from cognitive psychology suggest that long-term memory and attentional control begin to diminish in the third decade of life. Here, 100 participants between the ages of 18 and 31 learned Lithuanian translations of English words in an individual differences study using fMRI. Long-term memory ability was operationalized for each participant by deriving a memory score from 3 convergent measures. Age of participant predicted memory score in this cohort. In addition, degree of deactivation during initial encoding in a set of regions occurring largely in the default mode network (DMN) predicted both age and memory score. The current study demonstrates that early memory decline may partially be accounted for by failure to modulate activity in the DMN.

  5. Human Memory Limitations in Multi-Object Tracking.

    Science.gov (United States)

    1982-06-01

    Atkinson , R. C., & Shiffrin , R. M. Human memory : A proposed system and its control processes. In K. W. Spence & J. T. Spence (eds.), The psychology of...informa- tion-processing concepts of Norman (1968) and Atkinson and Shiffrin (1968), and from the "levels of processing" formulation of Craik and Lockhart...this selection. These strategies (referred to as "control processes" by Atkinson & Shiffrin , 1968) include the processes that direct attention among

  6. Simulation of Human Episodic Memory by Using a Computational Model of the Hippocampus

    Directory of Open Access Journals (Sweden)

    Naoyuki Sato

    2010-01-01

    Full Text Available The episodic memory, the memory of personal events and history, is essential for understanding the mechanism of human intelligence. Neuroscience evidence has shown that the hippocampus, a part of the limbic system, plays an important role in the encoding and the retrieval of the episodic memory. This paper reviews computational models of the hippocampus and introduces our own computational model of human episodic memory based on neural synchronization. Results from computer simulations demonstrate that our model provides advantage for instantaneous memory formation and selective retrieval enabling memory search. Moreover, this model was found to have the ability to predict human memory recall by integrating human eye movement data during encoding. The combined approach between computational models and experiment is efficient for theorizing the human episodic memory.

  7. HOLA: Human-like Orthogonal Network Layout.

    Science.gov (United States)

    Kieffer, Steve; Dwyer, Tim; Marriott, Kim; Wybrow, Michael

    2016-01-01

    Over the last 50 years a wide variety of automatic network layout algorithms have been developed. Some are fast heuristic techniques suitable for networks with hundreds of thousands of nodes while others are multi-stage frameworks for higher-quality layout of smaller networks. However, despite decades of research currently no algorithm produces layout of comparable quality to that of a human. We give a new "human-centred" methodology for automatic network layout algorithm design that is intended to overcome this deficiency. User studies are first used to identify the aesthetic criteria algorithms should encode, then an algorithm is developed that is informed by these criteria and finally, a follow-up study evaluates the algorithm output. We have used this new methodology to develop an automatic orthogonal network layout method, HOLA, that achieves measurably better (by user study) layout than the best available orthogonal layout algorithm and which produces layouts of comparable quality to those produced by hand.

  8. EDUCATIONAL NETWORKING: HUMAN VIEW TO CYBER DEFENSE

    Directory of Open Access Journals (Sweden)

    Oleksandr Yu. Burov

    2016-05-01

    Full Text Available Networks play more and more important role for human life and activity, both in critical occupations (aviation, power industry, military missions etc., and in everyday life (home computers, education, leisure. Interaction between human and other elements of human-machine system have changed, because they coincide in the information habitat. Human-system integration has reached new level of defense needs. The paper will introduce features of information society in respect of a human and corresponding changes in HF/E: (1 information becomes a tool, goal, mean and environment of a human activity, (2 it becomes a part of the human nature and this makes him/her unprotected, (3 human psycho-physiological status becomes not only a basis of effective performance, but an object of control and support, and means of a human security and safety should be a part of information habitat, (4 networking environment becomes an independent actor in a human activity. Accompanying cyber-security challenges and tasks are discussed, as well as types of networking threats and Human View regarding the cyber security challenges.

  9. Human memory retention and recall processes. A review of EEG and fMRI studies.

    Science.gov (United States)

    Amin, Hafeezullah; Malik, Aamir S

    2013-10-01

    Human memory is an important concept in cognitive psychology and neuroscience. Our brain is actively engaged in functions of learning and memorization. Generally, human memory has been classified into 2 groups: short-term/working memory, and long-term memory. Using different memory paradigms and brain mapping techniques, psychologists and neuroscientists have identified 3 memory processes: encoding, retention, and recall. These processes have been studied using EEG and functional MRI (fMRI) in cognitive and neuroscience research. This study reviews previous research reported for human memory processes, particularly brain behavior in memory retention and recall processes with the use of EEG and fMRI. We discuss issues and challenges related to memory research with EEG and fMRI techniques.

  10. Development of a superior frontal-intraparietal network for visuo-spatial working memory.

    Science.gov (United States)

    Klingberg, Torkel

    2006-01-01

    Working memory capacity increases throughout childhood and adolescence, which is important for the development of a wide range of cognitive abilities, including complex reasoning. The spatial-span task, in which subjects retain information about the order and position of a number of objects, is a sensitive task to measure development of spatial working memory. This review considers results from previous neuroimaging studies investigating the neural correlates of this development. Older children and adolescents, with higher capacity, have been found to have higher brain activity in the intraparietal cortex and in the posterior part of the superior frontal sulcus, during the performance of working memory tasks. The structural maturation of white matter has been investigated by diffusion tensor magnetic resonance imaging (DTI). This has revealed several regions in the frontal lobes in which white matter maturation is correlated with the development of working memory. Among these is a superior fronto-parietal white matter region, located close to the grey matter regions that are implicated in the development of working memory. Furthermore, the degree of white matter maturation is positively correlated with the degree of cortical activation in the frontal and parietal regions. This suggests that during childhood and adolescence, there is development of networks related to specific cognitive functions, such as visuo-spatial working memory. These networks not only consist of cortical areas but also the white matter tracts connecting them. For visuo-spatial working memory, this network could consist of the superior frontal and intraparietal cortex.

  11. Stability analysis of associative memory network composed of stochastic neurons and dynamic synapses

    Directory of Open Access Journals (Sweden)

    Yuichi eKatori

    2013-02-01

    Full Text Available We investigate the dynamical properties of an associative memory network consisting of stochastic neurons and dynamic synapses that show short-term depression and facilitation. In the stochastic neuron model used in this study, the efficacy of the synaptic transmission changes according to the short-term depression or facilitation mechanism. We derive a macroscopic mean field model that captures the overall dynamical properties of the stochastic model. We analyze the stability and bifurcation structure of the mean field model, and show the dependence of the memory retrieval performance on the noise intensity and parameters that determine the properties of the dynamic synapses, i.e., time constants for depressing and facilitating processes. The associative memory network exhibits a variety of dynamical states, including the memory and pseudo-memory states, as well as oscillatory states among memory patterns. This study provides comprehensive insight into the dynamical properties of the associative memory network with dynamic synapses.

  12. Team performance in networked supervisory control of unmanned air vehicles: effects of automation, working memory, and communication content.

    Science.gov (United States)

    McKendrick, Ryan; Shaw, Tyler; de Visser, Ewart; Saqer, Haneen; Kidwell, Brian; Parasuraman, Raja

    2014-05-01

    Assess team performance within a net-worked supervisory control setting while manipulating automated decision aids and monitoring team communication and working memory ability. Networked systems such as multi-unmanned air vehicle (UAV) supervision have complex properties that make prediction of human-system performance difficult. Automated decision aid can provide valuable information to operators, individual abilities can limit or facilitate team performance, and team communication patterns can alter how effectively individuals work together. We hypothesized that reliable automation, higher working memory capacity, and increased communication rates of task-relevant information would offset performance decrements attributed to high task load. Two-person teams performed a simulated air defense task with two levels of task load and three levels of automated aid reliability. Teams communicated and received decision aid messages via chat window text messages. Task Load x Automation effects were significant across all performance measures. Reliable automation limited the decline in team performance with increasing task load. Average team spatial working memory was a stronger predictor than other measures of team working memory. Frequency of team rapport and enemy location communications positively related to team performance, and word count was negatively related to team performance. Reliable decision aiding mitigated team performance decline during increased task load during multi-UAV supervisory control. Team spatial working memory, communication of spatial information, and team rapport predicted team success. An automated decision aid can improve team performance under high task load. Assessment of spatial working memory and the communication of task-relevant information can help in operator and team selection in supervisory control systems.

  13. Altered Effective Connectivity of Hippocampus-Dependent Episodic Memory Network in mTBI Survivors

    Science.gov (United States)

    2016-01-01

    Traumatic brain injuries (TBIs) are generally recognized to affect episodic memory. However, less is known regarding how external force altered the way functionally connected brain structures of the episodic memory system interact. To address this issue, we adopted an effective connectivity based analysis, namely, multivariate Granger causality approach, to explore causal interactions within the brain network of interest. Results presented that TBI induced increased bilateral and decreased ipsilateral effective connectivity in the episodic memory network in comparison with that of normal controls. Moreover, the left anterior superior temporal gyrus (aSTG, the concept forming hub), left hippocampus (the personal experience binding hub), and left parahippocampal gyrus (the contextual association hub) were no longer network hubs in TBI survivors, who compensated for hippocampal deficits by relying more on the right hippocampus (underlying perceptual memory) and the right medial frontal gyrus (MeFG) in the anterior prefrontal cortex (PFC). We postulated that the overrecruitment of the right anterior PFC caused dysfunction of the strategic component of episodic memory, which caused deteriorating episodic memory in mTBI survivors. Our findings also suggested that the pattern of brain network changes in TBI survivors presented similar functional consequences to normal aging. PMID:28074162

  14. Altered Effective Connectivity of Hippocampus-Dependent Episodic Memory Network in mTBI Survivors

    Directory of Open Access Journals (Sweden)

    Hao Yan

    2016-01-01

    Full Text Available Traumatic brain injuries (TBIs are generally recognized to affect episodic memory. However, less is known regarding how external force altered the way functionally connected brain structures of the episodic memory system interact. To address this issue, we adopted an effective connectivity based analysis, namely, multivariate Granger causality approach, to explore causal interactions within the brain network of interest. Results presented that TBI induced increased bilateral and decreased ipsilateral effective connectivity in the episodic memory network in comparison with that of normal controls. Moreover, the left anterior superior temporal gyrus (aSTG, the concept forming hub, left hippocampus (the personal experience binding hub, and left parahippocampal gyrus (the contextual association hub were no longer network hubs in TBI survivors, who compensated for hippocampal deficits by relying more on the right hippocampus (underlying perceptual memory and the right medial frontal gyrus (MeFG in the anterior prefrontal cortex (PFC. We postulated that the overrecruitment of the right anterior PFC caused dysfunction of the strategic component of episodic memory, which caused deteriorating episodic memory in mTBI survivors. Our findings also suggested that the pattern of brain network changes in TBI survivors presented similar functional consequences to normal aging.

  15. Analysis of naming game over networks in the presence of memory loss

    Science.gov (United States)

    Fu, Guiyuan; Cai, Yunze; Zhang, Weidong

    2017-08-01

    In this paper, we study the dynamics of naming game where individuals are under the influence of memory loss. An extended naming game incorporating memory loss is proposed. Different from the existing naming game models, the individual in the proposed model would forget some words with a probability in his memory during interaction and keep his conveyed word unchanged until he reaches a local agreement. We analyze the dynamics of the proposed model through extensive and comprehensive simulations, where four typical networks with different configuration are employed. The influence of memory loss as well as the population size on the performance of the proposed model is investigated. The simulation results show that (i) the stronger memory loss, the larger convergence time; (ii) as the strength of memory loss becomes stronger, maximum number of total words will decrease, while the maximum number of different words among the population remains almost unchanged; (iii) the maximum number of different words increases linearly with the increase of the population size and coincides with each other under different strength of memory loss. The findings in the proposed model may give an insight to understand better the influence of memory loss on the transient dynamics of language evolution and opinion formation over networks.

  16. Animal Hairs as Water-stimulated Shape Memory Materials: Mechanism and Structural Networks in Molecular Assemblies

    Science.gov (United States)

    Xiao, Xueliang; Hu, Jinlian

    2016-05-01

    Animal hairs consisting of α-keratin biopolymers existing broadly in nature may be responsive to water for recovery to the innate shape from their fixed deformation, thus possess smart behavior, namely shape memory effect (SME). In this article, three typical animal hair fibers were first time investigated for their water-stimulated SME, and therefrom to identify the corresponding net-points and switches in their molecular and morphological structures. Experimentally, the SME manifested a good stability of high shape fixation ratio and reasonable recovery rate after many cycles of deformation programming under water stimulation. The effects of hydration on hair lateral size, recovery kinetics, dynamic mechanical behaviors and structural components (crystal, disulfide and hydrogen bonds) were then systematically studied. SME mechanisms were explored based on the variations of structural components in molecular assemblies of such smart fibers. A hybrid structural network model with single-switch and twin-net-points was thereafter proposed to interpret the water-stimulated shape memory mechanism of animal hairs. This original work is expected to provide inspiration for exploring other natural materials to reveal their smart functions and natural laws in animals including human as well as making more remarkable synthetic smart materials.

  17. The Impact of Auditory Working Memory Training on the Fronto-Parietal Working Memory Network

    Directory of Open Access Journals (Sweden)

    Julia eSchneiders

    2012-06-01

    Full Text Available Working memory training has been widely used to investigate working memory processes. We have shown previously that visual working memory benefits only from intra-modal visual but not from across-modal auditory working memory training. In the present functional magnetic resonance imaging study we examined whether auditory working memory processes can also be trained specifically and which training-induced activation changes accompany theses effects. It was investigated whether working memory training with strongly distinct auditory materials transfers exclusively to an auditory (intra-modal working memory task or whether it generalizes to an (across-modal visual working memory task. We used an adaptive n-back training with tonal sequences and a passive control condition. The memory training led to a reliable training gain. Transfer effects were found for the (intra-modal auditory but not for the (across-modal visual 2-back task. Training-induced activation changes in the auditory 2-back task were found in two regions in the right inferior frontal gyrus. These effects confirm our previous findings in the visual modality and extends intra-modal effects to the auditory modality. These results might reflect increased neural efficiency in auditory working memory processes as in the right inferior frontal gyrus is frequently found in maintaining modality-specific auditory information. By this, these effects are analogical to the activation decreases in the right middle frontal gyrus for the visual modality in our previous study. Furthermore, task-unspecific (across-modal activation decreases in the visual and auditory 2-back task were found in the right inferior parietal lobule and the superior portion of the right middle frontal gyrus reflecting less demands on general attentional control processes. These data are in good agreement with across-modal activation decreases within the same brain regions on a visual 2-back task reported previously.

  18. Memory

    Science.gov (United States)

    ... it has to decide what is worth remembering. Memory is the process of storing and then remembering this information. There are different types of memory. Short-term memory stores information for a few ...

  19. Inhibitory networks of the amygdala for emotional memory

    Directory of Open Access Journals (Sweden)

    Seungho eLee

    2013-08-01

    Full Text Available The amygdala is important for emotional memory, including learned fear. A number of studies for amygdala neural circuits that underlie fear conditioning have elucidated specific cellular and molecular mechanisms of emotional memory. Recent technical advances such as optogenetic approaches have not only confirmed the importance of excitatory circuits in fear conditioning, but have also shed new light for a direct role of inhibitory circuits in both the acquisition and extinction of fear memory in addition to their role in fine tuning of excitatory neural circuitry. As a result, the circuits in amygdala could be drawn more elaborately, and it led us to understand how fear or extinction memories are formed in the detailed circuit level, and various neuromodulators affect these circuit activities, inducing subtle behavioral changes.

  20. The core regulatory network in human cells.

    Science.gov (United States)

    Kim, Man-Sun; Kim, Dongsan; Kang, Nam Sook; Kim, Jeong-Rae

    2017-03-04

    In order to discover the common characteristics of various cell types in the human body, many researches have been conducted to find the set of genes commonly expressed in various cell types and tissues. However, the functional characteristics of a cell is determined by the complex regulatory relationships among the genes rather than by expressed genes themselves. Therefore, it is more important to identify and analyze a core regulatory network where all regulatory relationship between genes are active across all cell types to uncover the common features of various cell types. Here, based on hundreds of tissue-specific gene regulatory networks constructed by recent genome-wide experimental data, we constructed the core regulatory network. Interestingly, we found that the core regulatory network is organized by simple cascade and has few complex regulations such as feedback or feed-forward loops. Moreover, we discovered that the regulatory links from genes in the core regulatory network to genes in the peripheral regulatory network are much more abundant than the reverse direction links. These results suggest that the core regulatory network locates at the top of regulatory network and plays a role as a 'hub' in terms of information flow, and the information that is common to all cells can be modified to achieve the tissue-specific characteristics through various types of feedback and feed-forward loops in the peripheral regulatory networks. We also found that the genes in the core regulatory network are evolutionary conserved, essential and non-disease, non-druggable genes compared to the peripheral genes. Overall, our study provides an insight into how all human cells share a common function and generate tissue-specific functional traits by transmitting and processing information through regulatory network.

  1. Dynamic synchronization and chaos in an associative neural network with multiple active memories.

    Science.gov (United States)

    Raffone, Antonino; van Leeuwen, Cees

    2003-09-01

    Associative memory dynamics in neural networks are generally based on attractors. Retrieval based on fixed-point attractors works if only one memory pattern is retrieved at the time, but cannot enable the simultaneous retrieval of more than one pattern. Stable phase-locking of periodic oscillations or limit cycle attractors leads to incorrect feature bindings if the simultaneously retrieved patterns share some of their features. We investigate retrieval dynamics of multiple active patterns in a network of chaotic model neurons. Several memory patterns are kept simultaneously active and separated from each other by a dynamic itinerant synchronization between neurons. Neurons representing shared features alternate their synchronization between patterns, thus multiplexing their binding relationships. Our model includes a mechanism for self-organized readout or decoding of memory pattern coherence in terms of short-term potentiation and short-term depression of synaptic weights.

  2. The Human Dimension of Networks

    Science.gov (United States)

    2008-06-01

    Missions and Means Framework to analyze network models "without scales" and "with rich scales", which...reflect the execution of pre-defined military tasks in a manner consistent with the military Missions and Means Framework (MMF) [xxviii]. Through the use...exploration is to develop techniques for collaborating across disciplines represented in the ASO. Employ the ‘ Missions and Means Framework ’

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

    Science.gov (United States)

    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

  4. Network Medicine: A Network-based Approach to Human Diseases

    Science.gov (United States)

    Ghiassian, Susan Dina

    With the availability of large-scale data, it is now possible to systematically study the underlying interaction maps of many complex systems in multiple disciplines. Statistical physics has a long and successful history in modeling and characterizing systems with a large number of interacting individuals. Indeed, numerous approaches that were first developed in the context of statistical physics, such as the notion of random walks and diffusion processes, have been applied successfully to study and characterize complex systems in the context of network science. Based on these tools, network science has made important contributions to our understanding of many real-world, self-organizing systems, for example in computer science, sociology and economics. Biological systems are no exception. Indeed, recent studies reflect the necessity of applying statistical and network-based approaches in order to understand complex biological systems, such as cells. In these approaches, a cell is viewed as a complex network consisting of interactions among cellular components, such as genes and proteins. Given the cellular network as a platform, machinery, functionality and failure of a cell can be studied with network-based approaches, a field known as systems biology. Here, we apply network-based approaches to explore human diseases and their associated genes within the cellular network. This dissertation is divided in three parts: (i) A systematic analysis of the connectivity patterns among disease proteins within the cellular network. The quantification of these patterns inspires the design of an algorithm which predicts a disease-specific subnetwork containing yet unknown disease associated proteins. (ii) We apply the introduced algorithm to explore the common underlying mechanism of many complex diseases. We detect a subnetwork from which inflammatory processes initiate and result in many autoimmune diseases. (iii) The last chapter of this dissertation describes the

  5. From working memory to epilepsy: Dynamics of facilitation and inhibition in a cortical network

    Science.gov (United States)

    Verduzco-Flores, Sergio; Ermentrout, Bard; Bodner, Mark

    2009-03-01

    Persistent states are believed to be the correlate for short-term or working memory. Using a previously derived model for working memory, we show that disruption of the lateral inhibition can lead to a variety of pathological states. These states are analogs of reflex or pattern-sensitive epilepsy. Simulations, numerical bifurcation analysis, and fast-slow decomposition are used to explore the dynamics of this network.

  6. Neural networks of human nature and nurture

    Directory of Open Access Journals (Sweden)

    Daniel S. Levine

    2008-06-01

    Full Text Available Neural network methods have facilitated the unifi - cation of several unfortunate splits in psychology, including nature versus nurture. We review the contributions of this methodology and then discuss tentative network theories of caring behavior, of uncaring behavior, and of how the frontal lobes are involved in the choices between them. The implications of our theory are optimistic about the prospects of society to encourage the human potential for caring.

  7. Neural networks of human nature and nurture

    Directory of Open Access Journals (Sweden)

    Daniel S. Levine

    2009-11-01

    Full Text Available Neural network methods have facilitated the unification of several unfortunate splits in psychology, including nature versus nurture. We review the contributions of this methodology and then discuss tentative network theories of caring behavior, of uncaring behavior, and of how the frontal lobes are involved in the choices between them. The implications of our theory are optimistic about the prospects of society to encourage the human potential for caring.

  8. An Incremental Time-delay Neural Network for Dynamical Recurrent Associative Memory

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    An incremental time-delay neural network based on synapse growth, which is suitable for dynamic control and learning of autonomous robots, is proposed to improve the learning and retrieving performance of dynamical recurrent associative memory architecture. The model allows steady and continuous establishment of associative memory for spatio-temporal regularities and time series in discrete sequence of inputs. The inserted hidden units can be taken as the long-term memories that expand the capacity of network and sometimes may fade away under certain condition. Preliminary experiment has shown that this incremental network may be a promising approach to endow autonomous robots with the ability of adapting to new data without destroying the learned patterns. The system also benefits from its potential chaos character for emergence.

  9. POLYMER NETWORK-POLY(ETHYLENE GLYCOL) COMPLEXES WITH SHAPE MEMORY EFFECT

    Institute of Scientific and Technical Information of China (English)

    Min Yu; Qin Zhang; Qiang Fu

    2003-01-01

    The complexes of poly(methacrylic acid-co-methyl methacrylate) network with poly(ethylene glycol) stabilized by hydrogen bonds were prepared. By introducing the poly(ethylene glycol), a large difference in storage modulus below and above the glass transition temperature occurred and the complexes exhibited shape memory behaviors. The morphology of complexes was studied by using DSC, WAXD, and DMA. The results indicate that the fixed phase of this kind of novel shape memory materials is the network, and the reversible phase is the amorphous state of PEG:PMAA complex phase. The shape recoverability almost reaches 100%. This type of complexes can be regarded as a novel shape memory network.

  10. Binary synaptic connections based on memory switching in a-Si:H for artificial neural networks

    Science.gov (United States)

    Thakoor, A. P.; Lamb, J. L.; Moopenn, A.; Khanna, S. K.

    1987-01-01

    A scheme for nonvolatile associative electronic memory storage with high information storage density is proposed which is based on neural network models and which uses a matrix of two-terminal passive interconnections (synapses). It is noted that the massive parallelism in the architecture would require the ON state of a synaptic connection to be unusually weak (highly resistive). Memory switching using a-Si:H along with ballast resistors patterned from amorphous Ge-metal alloys is investigated for a binary programmable read only memory matrix. The fabrication of a 1600 synapse test array of uniform connection strengths and a-Si:H switching elements is discussed.

  11. Synchronization and associative memory of FitzHugh-Nagumo neuronal networks with randomly distributed time delays

    Energy Technology Data Exchange (ETDEWEB)

    Peng, J H; Wu, Y J [School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237 (China); Yu, H J [Department of Mechanics, Shanghai Jiao Tong University, Shanghai 200240 (China)], E-mail: jhpeng@ecust.edu.cn

    2008-02-15

    Synchronization and associative memory in a neural network composed of the widely discussed FitzHugh-Nagumo neurons is investigated in this paper. Based on the reality of the microscopic biological structure in the neural system, the couplings among those neurons are accompanied with randomly distributed time delays which models the times needed for pulses propagating on the axons from the presynaptic neurons to the postsynaptic neurons. The memory is represented in the spatiotemporal firing pattern of the neurons, and the memory retrieval is accomplished with the fluctuations of the noise in the system.

  12. Elaboration versus suppression of cued memories: influence of memory recall instruction and success on parietal lobe, default network, and hippocampal activity.

    Science.gov (United States)

    Gimbel, Sarah I; Brewer, James B

    2014-01-01

    Functional imaging studies of episodic memory retrieval consistently report task-evoked and memory-related activity in the medial temporal lobe, default network and parietal lobe subregions. Associated components of memory retrieval, such as attention-shifts, search, retrieval success, and post-retrieval processing also influence regional activity, but these influences remain ill-defined. To better understand how top-down control affects the neural bases of memory retrieval, we examined how regional activity responses were modulated by task goals during recall success or failure. Specifically, activity was examined during memory suppression, recall, and elaborative recall of paired-associates. Parietal lobe was subdivided into dorsal (BA 7), posterior ventral (BA 39), and anterior ventral (BA 40) regions, which were investigated separately to examine hypothesized distinctions in sub-regional functional responses related to differential attention-to-memory and memory strength. Top-down suppression of recall abolished memory strength effects in BA 39, which showed a task-negative response, and BA 40, which showed a task-positive response. The task-negative response in default network showed greater negatively-deflected signal for forgotten pairs when task goals required recall. Hippocampal activity was task-positive and was influenced by memory strength only when task goals required recall. As in previous studies, we show a memory strength effect in parietal lobe and hippocampus, but we show that this effect is top-down controlled and sensitive to whether the subject is trying to suppress or retrieve a memory. These regions are all implicated in memory recall, but their individual activity patterns show distinct memory-strength-related responses when task goals are varied. In parietal lobe, default network, and hippocampus, top-down control can override the commonly identified effects of memory strength.

  13. Identification of a genetic cluster influencing memory performance and hippocampal activity in humans.

    Science.gov (United States)

    de Quervain, Dominique J-F; Papassotiropoulos, Andreas

    2006-03-14

    Experimental work in animals has shown that memory formation depends on a cascade of molecular events. Here we show that variability of human memory performance is related to variability in genes encoding proteins of this signaling cascade, including the NMDA and metabotrobic glutamate receptors, adenylyl cyclase, CAMKII, PKA, and PKC. The individual profile of genetic variability in these signaling molecules correlated significantly with episodic memory performance (P < 0.00001). Moreover, functional MRI during memory formation revealed that this genetic profile correlated with activations in memory-related brain regions, including the hippocampus and parahippocampal gyrus. The present study indicates that genetic variability in the human homologues of memory-related signaling molecules contributes to interindividual differences in human memory performance and memory-related brain activations.

  14. Brain functional network changes following Prelimbic area inactivation in a spatial memory extinction task.

    Science.gov (United States)

    Méndez-Couz, Marta; Conejo, Nélida M; Vallejo, Guillermo; Arias, Jorge L

    2015-01-01

    Several studies suggest a prefrontal cortex involvement during the acquisition and consolidation of spatial memory, suggesting an active modulating role at late stages of acquisition processes. Recently, we have reported that the prelimbic and infralimbic areas of the prefrontal cortex, among other structures, are also specifically involved in the late phases of spatial memory extinction. This study aimed to evaluate whether the inactivation of the prelimbic area of the prefrontal cortex impaired spatial memory extinction. For this purpose, male Wistar rats were implanted bilaterally with cannulae into the prelimbic region of the prefrontal cortex. Animals were trained during 5 consecutive days in a hidden platform task and tested for reference spatial memory immediately after the last training session. One day after completing the training task, bilateral infusion of the GABAA receptor agonist Muscimol was performed before the extinction protocol was carried out. Additionally, cytochrome c oxidase histochemistry was applied to map the metabolic brain activity related to the spatial memory extinction under prelimbic cortex inactivation. Results show that animals acquired the reference memory task in the water maze, and the extinction task was successfully completed without significant impairment. However, analysis of the functional brain networks involved by cytochrome oxidase activity interregional correlations showed changes in brain networks between the group treated with Muscimol as compared to the saline-treated group, supporting the involvement of the mammillary bodies at a the late stage in the memory extinction process.

  15. Preparation and characterization of shape memory composite foams with interpenetrating polymer networks

    Science.gov (United States)

    Yao, Yongtao; Zhou, Tianyang; Yang, Cheng; Liu, Yanju; Leng, Jinsong

    2016-03-01

    The present study reports a feasible approach of fabricating shape memory composite foams with an interpenetrating polymer network (IPN) based on polyurethane (PU) and shape memory epoxy resin (SMER) via a simultaneous polymerization technique. The PU component is capable of constructing a foam structure and the SMER is grafted on the PU network to offer its shape memory property in the final IPN foams. A series of IPN foams without phase separation were produced due to good compatibility and a tight chemical interaction between PU and SMER components. The relationships of the geometry of the foam cell were investigated via varying compositions of PU and SMER. The physical property and shape memory property were also evaluated. The stimulus temperature of IPN shape memory composite foams, glass temperature (Tg), could be tunable by varying the constituents and Tg of PU and SMER. The mechanism of the shape memory effect of IPN foams has been proposed. The shape memory composite foam with IPN developed in this study has the potential to extend its application field.

  16. Mechanisms and neuronal networks involved in reactive and proactive cognitive control of interference in working memory.

    Science.gov (United States)

    Irlbacher, Kerstin; Kraft, Antje; Kehrer, Stefanie; Brandt, Stephan A

    2014-10-01

    Cognitive control can be reactive or proactive in nature. Reactive control mechanisms, which support the resolution of interference, start after its onset. Conversely, proactive control involves the anticipation and prevention of interference prior to its occurrence. The interrelation of both types of cognitive control is currently under debate: Are they mediated by different neuronal networks? Or are there neuronal structures that have the potential to act in a proactive as well as in a reactive manner? This review illustrates the way in which integrating knowledge gathered from behavioral studies, functional imaging, and human electroencephalography proves useful in answering these questions. We focus on studies that investigate interference resolution at the level of working memory representations. In summary, different mechanisms are instrumental in supporting reactive and proactive control. Distinct neuronal networks are involved, though some brain regions, especially pre-SMA, possess functions that are relevant to both control modes. Therefore, activation of these brain areas could be observed in reactive, as well as proactive control, but at different times during information processing.

  17. Simple models of human brain functional networks.

    Science.gov (United States)

    Vértes, Petra E; Alexander-Bloch, Aaron F; Gogtay, Nitin; Giedd, Jay N; Rapoport, Judith L; Bullmore, Edward T

    2012-04-10

    Human brain functional networks are embedded in anatomical space and have topological properties--small-worldness, modularity, fat-tailed degree distributions--that are comparable to many other complex networks. Although a sophisticated set of measures is available to describe the topology of brain networks, the selection pressures that drive their formation remain largely unknown. Here we consider generative models for the probability of a functional connection (an edge) between two cortical regions (nodes) separated by some Euclidean distance in anatomical space. In particular, we propose a model in which the embedded topology of brain networks emerges from two competing factors: a distance penalty based on the cost of maintaining long-range connections; and a topological term that favors links between regions sharing similar input. We show that, together, these two biologically plausible factors are sufficient to capture an impressive range of topological properties of functional brain networks. Model parameters estimated in one set of functional MRI (fMRI) data on normal volunteers provided a good fit to networks estimated in a second independent sample of fMRI data. Furthermore, slightly detuned model parameters also generated a reasonable simulation of the abnormal properties of brain functional networks in people with schizophrenia. We therefore anticipate that many aspects of brain network organization, in health and disease, may be parsimoniously explained by an economical clustering rule for the probability of functional connectivity between different brain areas.

  18. Analogue spin-orbit torque device for artificial-neural-network-based associative memory operation

    Science.gov (United States)

    Borders, William A.; Akima, Hisanao; Fukami, Shunsuke; Moriya, Satoshi; Kurihara, Shouta; Horio, Yoshihiko; Sato, Shigeo; Ohno, Hideo

    2017-01-01

    We demonstrate associative memory operations reminiscent of the brain using nonvolatile spintronics devices. Antiferromagnet-ferromagnet bilayer-based Hall devices, which show analogue-like spin-orbit torque switching under zero magnetic fields and behave as artificial synapses, are used. An artificial neural network is used to associate memorized patterns from their noisy versions. We develop a network consisting of a field-programmable gate array and 36 spin-orbit torque devices. An effect of learning on associative memory operations is successfully confirmed for several 3 × 3-block patterns. A discussion on the present approach for realizing spintronics-based artificial intelligence is given.

  19. Influenza vaccine induces intracellular immune memory of human NK cells.

    Directory of Open Access Journals (Sweden)

    Yaling Dou

    Full Text Available Influenza vaccines elicit antigen-specific antibodies and immune memory to protect humans from infection with drift variants. However, what supports or limits vaccine efficacy and duration is unclear. Here, we vaccinated healthy volunteers with annual vaccine formulations and investigated the dynamics of T cell, natural killer (NK cell and antibody responses upon restimulation with heterologous or homologous influenza virus strains. Influenza vaccines induced potential memory NK cells with increased antigen-specific recall IFN-γ responses during the first 6 months. In the absence of significant changes in other NK cell markers (CD45RO, NKp44, CXCR6, CD57, NKG2C, CCR7, CD62L and CD27, influenza vaccines induced memory NK cells with the distinct feature of intracellular NKp46 expression. Indeed, surface NKp46 was internalized, and the dynamic increase in NKp46(intracellular+CD56dim NK cells positively correlated with increased IFN-γ production to influenza virus restimulation after vaccination. In addition, anti-NKp46 antibodies blocked IFN-γ responses. These findings provide insights into a novel mechanism underlying vaccine-induced immunity and NK-related diseases, which may help to design persisting and universal vaccines in the future.

  20. Influenza vaccine induces intracellular immune memory of human NK cells.

    Science.gov (United States)

    Dou, Yaling; Fu, Binqing; Sun, Rui; Li, Wenting; Hu, Wanfu; Tian, Zhigang; Wei, Haiming

    2015-01-01

    Influenza vaccines elicit antigen-specific antibodies and immune memory to protect humans from infection with drift variants. However, what supports or limits vaccine efficacy and duration is unclear. Here, we vaccinated healthy volunteers with annual vaccine formulations and investigated the dynamics of T cell, natural killer (NK) cell and antibody responses upon restimulation with heterologous or homologous influenza virus strains. Influenza vaccines induced potential memory NK cells with increased antigen-specific recall IFN-γ responses during the first 6 months. In the absence of significant changes in other NK cell markers (CD45RO, NKp44, CXCR6, CD57, NKG2C, CCR7, CD62L and CD27), influenza vaccines induced memory NK cells with the distinct feature of intracellular NKp46 expression. Indeed, surface NKp46 was internalized, and the dynamic increase in NKp46(intracellular)+CD56dim NK cells positively correlated with increased IFN-γ production to influenza virus restimulation after vaccination. In addition, anti-NKp46 antibodies blocked IFN-γ responses. These findings provide insights into a novel mechanism underlying vaccine-induced immunity and NK-related diseases, which may help to design persisting and universal vaccines in the future.

  1. Rhythmic Working Memory Activation in the Human Hippocampus

    Directory of Open Access Journals (Sweden)

    Marcin Leszczyński

    2015-11-01

    Full Text Available Working memory (WM maintenance is assumed to rely on a single sustained process throughout the entire maintenance period. This assumption, although fundamental, has never been tested. We used intracranial electroencephalography (EEG recordings from the human hippocampus in two independent experiments to investigate the neural dynamics underlying WM maintenance. We observed periodic fluctuations between two different oscillatory regimes: Periods of “memory activation” were reflected by load-dependent alpha power reductions and lower levels of cross-frequency coupling (CFC. They occurred interleaved with periods characterized by load-independent high levels of alpha power and CFC. During memory activation periods, a relevant CFC parameter (load-dependent changes of the peak modulated frequency correlated with individual WM capacity. Fluctuations between these two periods predicted successful performance and were locked to the phase of endogenous delta oscillations. These results show that hippocampal maintenance is a dynamic rather than constant process and depends critically on a hierarchy of oscillations.

  2. Scaling Behaviour and Memory in Heart Rate of Healthy Human

    Institute of Scientific and Technical Information of China (English)

    CAI Shi-Min; PENG Hu; YANG Hui-Jie; ZHOU Tao; ZHOU Pei-Ling; WANG Bing-Hong

    2007-01-01

    We investigate a set of complex heart rate time series from healthy human in different behaviour states with the detrended fluctuation analysis and diffusion entropy (DE) method. It is proposed that the scaling properties are influenced by behaviour states. The memory detected by DE exhibits an approximately same pattern after a detrending procedure. Both of them demonstrate the long-range strong correlations in heart rate. These findings may be helpful to understand the underlying dynamical evolution process in the heart rate control system, as well as to model the cardiac dynamic process.

  3. Analysis of global exponential stability for a class of bi—directional associative memory networks

    Institute of Scientific and Technical Information of China (English)

    王宏霞; 何晨

    2003-01-01

    In real-time applications of bi-directional associative memory (BAM) networks.a global exponentially stable equilibrium is highly desired.The existence,uniqueness and global exponential stability for a class of BAM networks are studied in this paper,the signal function of neurons is assumed to be piece-wise linear from the engineering point of view.A very concise condition for the equilbrium of such a network being globally exponentially stable is derived.which makes the pactical design of this kind of networks an easy job.

  4. Analysis of global exponential stability for a class of bi-directional associative memory networks

    Institute of Scientific and Technical Information of China (English)

    王宏霞; 何晨

    2003-01-01

    In real-time applications of bi-directional associative memory (BAM) networks, a global exponentially stable equilibrium is highly desired. The existence, uniqueness and global exponential stability for a class of BAM networks are studied in this paper, the signal function of neurons is assumed to be piece-wise linear from the engineering point of view. A very concise condition for the equilibrium of such a network being globally exponentially stable is derived,which makes the practical design of this kind of networks an easy job.

  5. Characterizing spatial and temporal features of autobiographical memory retrieval networks: a partial least squares approach.

    Science.gov (United States)

    Addis, Donna Rose; McIntosh, Anthony R; Moscovitch, Morris; Crawley, Adrian P; McAndrews, Mary Pat

    2004-12-01

    Conway (Conway, M.A., 1992. A structural model of autobiographical memory. In: Conway, M.A., Spinnler, H., Wagenaar, W.A. (Eds.), Theoretical Perspectives on Autobiological Memory. Kluwer Academic Publishers, Dordrecht, The Netherlands, pp. 167-194) proposed that two types of autobiographical memories (AMs) exist within a hierarchical AM system: unique, specific events and repeated, general memories. There is little research on whether retrieval of these AMs relies on different neural substrates. To investigate this issue, we used a multivariate image analysis technique, spatiotemporal partial least squares (PLS), to identify distributed patterns of activity most related to AM tasks that we have found to be associated with a medial and left-lateralized network. Using PLS, specific and general memories were more strongly associated with different parts of this retrieval network. Specific AM retrieval was associated more with activation of regions involved in imagery in episodic memory, including the left precuneus, left superior parietal lobule and right cuneus, whereas general AM retrieval was associated with activation of the right inferior temporal gyrus, right medial frontal cortex, and left thalamus. These two patterns emerged at different lags after stimulus onset, with the general AM pattern peaking between 2 and 6 s, and the specific AM pattern between 6 and 8 s. These lag differences are consistent with Conway's theory which posits that general AMs are the preferred level of entry to the AM system. A seed PLS analysis revealed that the regions functionally connected to the hippocampus during retrieval did not differentiate specific from general AM retrieval, which confirms our earlier univariate analysis indicating that some aspects of the memory retrieval network are shared by these memories.

  6. Search-related suppression of hippocampus and default network activity during associative memory retrieval

    Directory of Open Access Journals (Sweden)

    Emilie T Reas

    2011-10-01

    Full Text Available Episodic memory retrieval involves the coordinated interaction of several cognitive processing stages such as mental search, access to a memory store, associative re-encoding and post-retrieval monitoring. The neural response during memory retrieval is an integration of signals from multiple regions that may subserve supportive cognitive control, attention, sensory association, encoding or working memory functions. It is particularly challenging to dissociate contributions of these distinct components to brain responses in regions such as the hippocampus, which lies at the interface between overlapping memory encoding and retrieval, and default networks. In the present study, event-related functional magnetic resonance imaging and measures of memory performance were used to differentiate brain responses to memory search from sub-components of episodic memory retrieval associated with successful recall. During the attempted retrieval of both poorly and strongly remembered word pair associates, the hemodynamic response was negatively deflected below baseline in anterior hippocampus and regions of the default network. Activations in anterior hippocampus were functionally distinct from those in posterior hippocampus and negatively correlated with response times. Thus, relative to the pre-stimulus period, the hippocampus shows reduced activity during intensive engagement in episodic memory search. Such deactivation was most salient during trials that engaged only pre-retrieval search processes in the absence of successful recollection or post-retrieval processing. Implications for interpretation of hippocampal fMRI responses during retrieval are discussed. A model is presented to interpret such activations as representing modulation of encoding-related activity, rather than retrieval-related activity. Engagement in intensive mental search may reduce neural and attentional resources that are otherwise tonically devoted to encoding an individual

  7. The hippocampus: A central node in a large-scale brain network for memory.

    Science.gov (United States)

    Huijgen, J; Samson, S

    2015-03-01

    The medial temporal lobe is a key region in the formation and consolidation of conscious or declarative memories. In this review, we will first consider the role of the hippocampus and its surrounding medial temporal lobe structures in recognition memory from a historical perspective. According to the dual process model of recognition memory, recognition judgments can be based on the recollection of details about previous presented stimuli or on the feeling of familiarity. Studies in humans, primates and rodents suggest that the hippocampus, the parahippocampal cortex and the perirhinal cortex play different roles in recollection and familiarity. Then, we will describe the role of the hippocampus and neocortex in memory consolidation: a process in which novel memories become integrated into long-term memory. After presenting possible mechanisms underlying sleep-dependent declarative memory consolidation, we will discuss the phenomenon of accelerated long-term forgetting. This type of memory deficit is often observed in epileptic patients with a hippocampal lesion, and provides a novel opportunity to investigate post-encoding and memory consolidation processes. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  8. Clustering predicts memory performance in networks of spiking and non-spiking neurons

    Directory of Open Access Journals (Sweden)

    Weiliang eChen

    2011-03-01

    Full Text Available The problem we address in this paper is that of finding effective and parsimonious patterns of connectivity in sparse associative memories. This problem must be addressed in real neuronal systems, so that results in artificial systems could throw light on real systems. We show that there are efficient patterns of connectivity and that these patterns are effective in models with either spiking or non-spiking neurons. This suggests that there may be some underlying general principles governing good connectivity in such networks. We also show that the clustering of the network, measured by Clustering Coefficient, has a strong linear correlation to the performance of associative memory. This result is important since a purely static measure of network connectivity appears to determine an important dynamic property of the network.

  9. One Packet Suffices - Highly Efficient Packetized Network Coding With Finite Memory

    CERN Document Server

    Haeupler, Bernhard

    2011-01-01

    Random Linear Network Coding (RLNC) has emerged as a powerful tool for robust high-throughput multicast. Projection analysis - a recently introduced technique - shows that the distributed packetized RLNC protocol achieves (order) optimal and perfectly pipelined information dissemination in many settings. In the original approach to RNLC intermediate nodes code together all available information. This requires intermediate nodes to keep considerable data available for coding. Moreover, it results in a coding complexity that grows linearly with the size of this data. While this has been identified as a problem, approaches that combine queuing theory and network coding have heretofore not provided a succinct representation of the memory needs of network coding at intermediates nodes. This paper shows the surprising result that, in all settings with a continuous stream of data, network coding continues to perform optimally even if only one packet per node is kept in active memory and used for computations. This l...

  10. Cortisol has different effects on human memory for emotional and neutral stimuli.

    Science.gov (United States)

    Rimmele, Ulrike; Domes, Gregor; Mathiak, Klaus; Hautzinger, Martin

    2003-12-19

    Adrenal stress hormones are considered to play a role in memory enhancement of emotionally arousing events. To investigate the effects of cortisol on human emotional memory, subjects were administered hydrocortisone (25 mg) or placebo and presented with either an emotionally arousing or a neutral story. Memory for the story was tested 1 week later. In all memory tests, subjects who viewed the emotional story scored better for the emotionally arousing story parts, indicating that arousal enhances memory. In memory of details, cortisol showed an interaction with story valence but no main effect: cortisol enhanced memory for details of the neutral story version, but impaired memory for details of the emotionally arousing version. We thus confirm a non-linear interaction between cortisol and arousal on memory formation.

  11. Short-term memory capacity in networks via the restricted isometry property.

    Science.gov (United States)

    Charles, Adam S; Yap, Han Lun; Rozell, Christopher J

    2014-06-01

    Cortical networks are hypothesized to rely on transient network activity to support short-term memory (STM). In this letter, we study the capacity of randomly connected recurrent linear networks for performing STM when the input signals are approximately sparse in some basis. We leverage results from compressed sensing to provide rigorous nonasymptotic recovery guarantees, quantifying the impact of the input sparsity level, the input sparsity basis, and the network characteristics on the system capacity. Our analysis demonstrates that network memory capacities can scale superlinearly with the number of nodes and in some situations can achieve STM capacities that are much larger than the network size. We provide perfect recovery guarantees for finite sequences and recovery bounds for infinite sequences. The latter analysis predicts that network STM systems may have an optimal recovery length that balances errors due to omission and recall mistakes. Furthermore, we show that the conditions yielding optimal STM capacity can be embodied in several network topologies, including networks with sparse or dense connectivities.

  12. Initial investigation of the effects of an experimentally learned schema on spatial associative memory in humans.

    Science.gov (United States)

    van Buuren, Mariët; Kroes, Marijn C W; Wagner, Isabella C; Genzel, Lisa; Morris, Richard G M; Fernández, Guillén

    2014-12-10

    Networks of interconnected neocortical representations of prior knowledge, "schemas," facilitate memory for congruent information. This facilitation is thought to be mediated by augmented encoding and accelerated consolidation. However, it is less clear how schema affects retrieval. Rodent and human studies to date suggest that schema-related memories are differently retrieved. However, these studies differ substantially as most human studies implement pre-experimental world-knowledge as schemas and tested item or nonspatial associative memory, whereas animal studies have used intraexperimental schemas based on item-location associations within a complex spatial layout that, in humans, could engage more strategic retrieval processes. Here, we developed a paradigm conceptually linked to rodent studies to examine the effects of an experimentally learned spatial associative schema on learning and retrieval of new object-location associations and to investigate the neural mechanisms underlying schema-related retrieval. Extending previous findings, we show that retrieval of schema-defining associations is related to activity along anterior and posterior midline structures and angular gyrus. The existence of such spatial associative schema resulted in more accurate learning and retrieval of new, related associations, and increased time allocated to retrieve these associations. This retrieval was associated with right dorsolateral prefrontal and lateral parietal activity, as well as interactions between the right dorsolateral prefrontal cortex and medial and lateral parietal regions, and between the medial prefrontal cortex and posterior midline regions, supporting the hypothesis that retrieval of new, schema-related object-location associations in humans also involves augmented monitoring and systematic search processes.

  13. Order recall in verbal short-term memory: The role of semantic networks.

    Science.gov (United States)

    Poirier, Marie; Saint-Aubin, Jean; Mair, Ali; Tehan, Gerry; Tolan, Anne

    2015-04-01

    In their recent article, Acheson, MacDonald, and Postle (Journal of Experimental Psychology: Learning, Memory, and Cognition 37:44-59, 2011) made an important but controversial suggestion: They hypothesized that (a) semantic information has an effect on order information in short-term memory (STM) and (b) order recall in STM is based on the level of activation of items within the relevant lexico-semantic long-term memory (LTM) network. However, verbal STM research has typically led to the conclusion that factors such as semantic category have a large effect on the number of correctly recalled items, but little or no impact on order recall (Poirier & Saint-Aubin, Quarterly Journal of Experimental Psychology 48A:384-404, 1995; Saint-Aubin, Ouellette, & Poirier, Psychonomic Bulletin & Review 12:171-177, 2005; Tse, Memory 17:874-891, 2009). Moreover, most formal models of short-term order memory currently suggest a separate mechanism for order coding-that is, one that is separate from item representation and not associated with LTM lexico-semantic networks. Both of the experiments reported here tested the predictions that we derived from Acheson et al. The findings show that, as predicted, manipulations aiming to affect the activation of item representations significantly impacted order memory.

  14. Global stability of bidirectional associative memory neural networks with continuously distributed delays

    Institute of Scientific and Technical Information of China (English)

    张强; 马润年; 许进

    2003-01-01

    Global asymptotic stability of the equilibrium point of bidirectional associative memory (BAM) neural networks with continuously distributed delays is studied. Under two mild assumptions on the acti-vation functions, two sufficient conditions ensuring global stability of such networks are derived by utiliz-ing Lyapunov functional and some inequality analysis technique. The results here extend some previous results. A numerical example is given showing the validity of our method.

  15. Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks

    OpenAIRE

    Tai, Kai Sheng; Socher, Richard; Manning, Christopher D

    2015-01-01

    Because of their superior ability to preserve sequence information over time, Long Short-Term Memory (LSTM) networks, a type of recurrent neural network with a more complex computational unit, have obtained strong results on a variety of sequence modeling tasks. The only underlying LSTM structure that has been explored so far is a linear chain. However, natural language exhibits syntactic properties that would naturally combine words to phrases. We introduce the Tree-LSTM, a generalization of...

  16. Cannabinoid facilitation of fear extinction memory recall in humans

    Science.gov (United States)

    Rabinak, Christine A.; Angstadt, Mike; Sripada, Chandra S.; Abelson, James L.; Liberzon, Israel; Milad, Mohammed R.; Phan, K. Luan

    2012-01-01

    A first-line approach to treat anxiety disorders is exposure-based therapy, which relies on extinction processes such as repeatedly exposing the patient to stimuli (conditioned stimuli; CS) associated with the traumatic, fear-related memory. However, a significant number of patients fail to maintain their gains, partly attributed to the fact that this inhibitory learning and its maintenance is temporary and conditioned fear responses can return. Animal studies have shown that activation of the cannabinoid system during extinction learning enhances fear extinction and its retention. Specifically, CB1 receptor agonists, such as Δ9-tetrahydrocannibinol (THC), can facilitate extinction recall by preventing recovery of extinguished fear in rats. However, this phenomenon has not been investigated in humans. We conducted a study using a randomized, double-blind, placebo-controlled, between-subjects design, coupling a standard Pavlovian fear extinction paradigm and simultaneous skin conductance response (SCR) recording with an acute pharmacological challenge with oral dronabinol (synthetic THC) or placebo (PBO) 2 hours prior to extinction learning in 29 healthy adult volunteers (THC = 14; PBO = 15) and tested extinction retention 24 hours after extinction learning. Compared to subjects that received PBO, subjects that received THC showed low SCR to a previously extinguished CS when extinction memory recall was tested 24 hours after extinction learning, suggesting that THC prevented the recovery of fear. These results provide the first evidence that pharmacological enhancement of extinction learning is feasible in humans using cannabinoid system modulators, which may thus warrant further development and clinical testing. PMID:22796109

  17. Effects of Δ9-tetrahydrocannabinol administration on human encoding and recall memory function: a pharmacological FMRI study.

    Science.gov (United States)

    Bossong, Matthijs G; Jager, Gerry; van Hell, Hendrika H; Zuurman, Lineke; Jansma, J Martijn; Mehta, Mitul A; van Gerven, Joop M A; Kahn, René S; Ramsey, Nick F

    2012-03-01

    Deficits in memory function are an incapacitating aspect of various psychiatric and neurological disorders. Animal studies have recently provided strong evidence for involvement of the endocannabinoid (eCB) system in memory function. Neuropsychological studies in humans have shown less convincing evidence but suggest that administration of cannabinoid substances affects encoding rather than recall of information. In this study, we examined the effects of perturbation of the eCB system on memory function during both encoding and recall. We performed a pharmacological MRI study with a placebo-controlled, crossover design, investigating the effects of Δ9-tetrahydrocannabinol (THC) inhalation on associative memory-related brain function in 13 healthy volunteers. Performance and brain activation during associative memory were assessed using a pictorial memory task, consisting of separate encoding and recall conditions. Administration of THC caused reductions in activity during encoding in the right insula, the right inferior frontal gyrus, and the left middle occipital gyrus and a network-wide increase in activity during recall, which was most prominent in bilateral cuneus and precuneus. THC administration did not affect task performance, but while during placebo recall activity significantly explained variance in performance, this effect disappeared after THC. These findings suggest eCB involvement in encoding of pictorial information. Increased precuneus activity could reflect impaired recall function, but the absence of THC effects on task performance suggests a compensatory mechanism. These results further emphasize the eCB system as a potential novel target for treatment of memory disorders and a promising target for development of new therapies to reduce memory deficits in humans.

  18. Memory: Organization and Control

    Science.gov (United States)

    Eichenbaum, Howard

    2017-01-01

    A major goal of memory research is to understand how cognitive processes in memory are supported at the level of brain systems and network representations. Especially promising in this direction are new findings in humans and animals that converge in indicating a key role for the hippocampus in the systematic organization of memories. New findings also indicate that the prefrontal cortex may play an equally important role in the active control of memory organization during both encoding and retrieval. Observations about the dialog between the hippocampus and prefrontal cortex provide new insights into the operation of the larger brain system that serves memory. PMID:27687117

  19. A Hopfield-like hippocampal CA3 neural network model for studying associative memory in Alzheimer's disease

    Institute of Scientific and Technical Information of China (English)

    Wangxiong Zhao; Qingli Qiao; Dan Wang

    2010-01-01

    Associative memory, one of the major cognitive functions in the hippocampal CA3 region, includes auto-associative memory and hetero-associative memory. Many previous studies have shown that Alzheimer's disease (AD) can lead to loss of functional synapses in the central nervous system, and associative memory functions in patients with AD are often impaired, but few studies have addressed the effect of AD on hetero-associative memory in the hippocampal CA3 region. In this study, based on a simplified anatomical structure and synaptic connections in the hippocampal CA3 region, a three-layered Hopfield-like neural network model of hippocampal CA3 was proposed and then used to simulate associative memory functions in three circumstances: normal, synaptic deletion and synaptic compensation, according to Ruppin's synaptic deletion and compensation theory. The influences of AD on hetero-associative memory were further analyzed. The simulated results showed that the established three-layered Hopfield-like neural network model of hippocampal CA3 has both auto-associative and hetero-associative memory functions. With increasing synaptic deletion level, both associative memory functions were gradually impaired and the mean firing rates of the neurons within the network model were decreased. With gradual increasing synaptic compensation, the associative memory functions of the network were improved and the mean firing rates were increased. The simulated results suggest that the Hopfield-like neural network model can effectively simulate both associative memory functions of the hippocampal CA3 region. Synaptic deletion affects both auto-associative and hetero-associative memory functions in the hippocampal CA3 region, and can also result in memory dysfunction. To some extent, synaptic compensation measures can offset two kinds of associative memory dysfunction caused by synaptic deletion in the hippocampal CA3 area.

  20. Folk music style modelling by recurrent neural networks with long short term memory units

    OpenAIRE

    Sturm, Bob; Santos, João Felipe; Korshunova, Iryna

    2015-01-01

    We demonstrate two generative models created by training a recurrent neural network (RNN) with three hidden layers of long short-term memory (LSTM) units. This extends past work in numerous directions, including training deeper models with nearly 24,000 high-level transcriptions of folk tunes. We discuss our on-going work.

  1. Parvalbumin-expressing interneurons coordinate hippocampal network dynamics required for memory consolidation

    Science.gov (United States)

    Ognjanovski, Nicolette; Schaeffer, Samantha; Wu, Jiaxing; Mofakham, Sima; Maruyama, Daniel; Zochowski, Michal; Aton, Sara J.

    2017-04-01

    Activity in hippocampal area CA1 is essential for consolidating episodic memories, but it is unclear how CA1 activity patterns drive memory formation. We find that in the hours following single-trial contextual fear conditioning (CFC), fast-spiking interneurons (which typically express parvalbumin (PV)) show greater firing coherence with CA1 network oscillations. Post-CFC inhibition of PV+ interneurons blocks fear memory consolidation. This effect is associated with loss of two network changes associated with normal consolidation: (1) augmented sleep-associated delta (0.5-4 Hz), theta (4-12 Hz) and ripple (150-250 Hz) oscillations; and (2) stabilization of CA1 neurons' functional connectivity patterns. Rhythmic activation of PV+ interneurons increases CA1 network coherence and leads to a sustained increase in the strength and stability of functional connections between neurons. Our results suggest that immediately following learning, PV+ interneurons drive CA1 oscillations and reactivation of CA1 ensembles, which directly promotes network plasticity and long-term memory formation.

  2. Intrinsic default mode network connectivity predicts spontaneous verbal descriptions of autobiographical memories during social processing

    Directory of Open Access Journals (Sweden)

    Xiao-Fei eYang

    2013-01-01

    Full Text Available Neural systems activated in a coordinated way during rest, known as the default mode network (DMN, also support autobiographical memory (AM retrieval and social processing/mentalizing. However, little is known about how individual variability in reliance on personal memories during social processing relates to individual differences in DMN functioning during rest (intrinsic functional connectivity. Here we examined 18 participants’ spontaneous descriptions of autobiographical memories during a two-hour, private, open-ended interview in which they reacted to a series of true stories about real people’s social situations and responded to the prompt, how does this person’s story make you feel? We classified these descriptions as either containing factual information (semantic AMs or more elaborate descriptions of emotionally meaningful events (episodic AMs. We also collected resting state fMRI scans from the participants and related individual differences in frequency of described AMs to participants’ intrinsic functional connectivity within regions of the DMN. We found that producing more descriptions of either memory type correlated with stronger intrinsic connectivity in the parahippocampal and middle temporal gyri. Additionally, episodic AM descriptions correlated with connectivity in the bilateral hippocampi and medial prefrontal cortex, and semantic memory descriptions correlated with connectivity in right inferior lateral parietal cortex. These findings suggest that in individuals who naturally invoke more memories during social processing, brain regions involved in memory retrieval and self/social processing are more strongly coupled to the DMN during rest.

  3. Applying long short-term memory recurrent neural networks to intrusion detection

    Directory of Open Access Journals (Sweden)

    Ralf C. Staudemeyer

    2015-07-01

    Full Text Available We claim that modelling network traffic as a time series with a supervised learning approach, using known genuine and malicious behaviour, improves intrusion detection. To substantiate this, we trained long short-term memory (LSTM recurrent neural networks with the training data provided by the DARPA / KDD Cup ’99 challenge. To identify suitable LSTM-RNN network parameters and structure we experimented with various network topologies. We found networks with four memory blocks containing two cells each offer a good compromise between computational cost and detection performance. We applied forget gates and shortcut connections respectively. A learning rate of 0.1 and up to 1,000 epochs showed good results. We tested the performance on all features and on extracted minimal feature sets respectively. We evaluated different feature sets for the detection of all attacks within one network and also to train networks specialised on individual attack classes. Our results show that the LSTM classifier provides superior performance in comparison to results previously published results of strong static classifiers. With 93.82% accuracy and 22.13 cost, LSTM outperforms the winning entries of the KDD Cup ’99 challenge by far. This is due to the fact that LSTM learns to look back in time and correlate consecutive connection records. For the first time ever, we have demonstrated the usefulness of LSTM networks to intrusion detection.

  4. Synthesization of high-capacity auto-associative memories using complex-valued neural networks

    Science.gov (United States)

    Huang, Yu-Jiao; Wang, Xiao-Yan; Long, Hai-Xia; Yang, Xu-Hua

    2016-12-01

    In this paper, a novel design procedure is proposed for synthesizing high-capacity auto-associative memories based on complex-valued neural networks with real-imaginary-type activation functions and constant delays. Stability criteria dependent on external inputs of neural networks are derived. The designed networks can retrieve the stored patterns by external inputs rather than initial conditions. The derivation can memorize the desired patterns with lower-dimensional neural networks than real-valued neural networks, and eliminate spurious equilibria of complex-valued neural networks. One numerical example is provided to show the effectiveness and superiority of the presented results. Project supported by the National Natural Science Foundation of China (Grant Nos. 61503338, 61573316, 61374152, and 11302195) and the Natural Science Foundation of Zhejiang Province, China (Grant No. LQ15F030005).

  5. EXPONENTIAL STABILITY AND PERIODIC SOLUTION OF HYBRID BIDIRECTIONAL ASSOCIATIVE MEMORY NEURAL NETWORKS WITH DISCRETE DELAYS

    Institute of Scientific and Technical Information of China (English)

    谢惠琴; 王全义

    2004-01-01

    In this paper, we study the existence, uniqueness, and the global exponential stability of the periodic solution and equilibrium of hybrid bidirectional associative memory neural networks with discrete delays. By ingeniously importing real parameters di > 0 (i = 1, 2,..., n) which can be adjusted, making use of the Lyapunov functional method and some analysis techniques, some new sufficient conditions are established. Our results generalize and improve the related results in [9]. These conditions can be used both to design globally exponentially stable and periodical oscillatory hybrid bidirectional associative neural networks with discrete delays, and to enlarge the area of designing neural networks. Our work has important significance in related theory and its application.

  6. Assessing Two-Mode Semantic Network Story Representations Using a False Memory Paradigm

    OpenAIRE

    Corman, Steven R.; Ball, B. Hunter; Talboom, Kimberly M.; GENE A. BREWER

    2013-01-01

    This paper describes a novel method of representing semantic networks of stories (and other text) as a two-mode graph. This method has some advantages over traditional one-mode semantic networks, but has the potential drawback (shared with n-gram text networks) that it contains paths that are not present in the text. An empirical study was devised using a false memory paradigm to determine whether these induced paths are remembered as being true of a set of stories. Results indicate that part...

  7. Spatiotemporal memory is an intrinsic property of networks of dissociated cortical neurons.

    Science.gov (United States)

    Ju, Han; Dranias, Mark R; Banumurthy, Gokulakrishna; VanDongen, Antonius M J

    2015-03-04

    The ability to process complex spatiotemporal information is a fundamental process underlying the behavior of all higher organisms. However, how the brain processes information in the temporal domain remains incompletely understood. We have explored the spatiotemporal information-processing capability of networks formed from dissociated rat E18 cortical neurons growing in culture. By combining optogenetics with microelectrode array recording, we show that these randomly organized cortical microcircuits are able to process complex spatiotemporal information, allowing the identification of a large number of temporal sequences and classification of musical styles. These experiments uncovered spatiotemporal memory processes lasting several seconds. Neural network simulations indicated that both short-term synaptic plasticity and recurrent connections are required for the emergence of this capability. Interestingly, NMDA receptor function is not a requisite for these short-term spatiotemporal memory processes. Indeed, blocking the NMDA receptor with the antagonist APV significantly improved the temporal processing ability of the networks, by reducing spontaneously occurring network bursts. These highly synchronized events have disastrous effects on spatiotemporal information processing, by transiently erasing short-term memory. These results show that the ability to process and integrate complex spatiotemporal information is an intrinsic property of generic cortical networks that does not require specifically designed circuits. Copyright © 2015 the authors 0270-6474/15/354040-12$15.00/0.

  8. Wavelet network based predistortion method for wideband RF power amplifiers exhibiting memory effects

    Institute of Scientific and Technical Information of China (English)

    JIN Zhe; SONG Zhi-huan; HE Jia-ming

    2007-01-01

    RF power amplifiers (PAs) are usually considered as memoryless devices in most existing predistortion techniques.Nevertheless, in wideband communication systems, PA memory effects can no longer be ignored and memoryless predistortion cannot linearize PAs effectively. After analyzing PA memory effects, a novel predistortion method based on wavelet networks (WNs) is proposed to linearize wideband RF power amplifiers. A complex wavelet network with tapped delay lines is applied to construct the predistorter and then a complex backpropagation algorithm is developed to train the predistorter parameters. The simulation results show that compared with the previously published feed-forward neural network predistortion method, the proposed method provides faster convergence rate and better performance in reducing out-of-band spectral regrowth.

  9. A reassessment of IgM memory subsets in humans

    Science.gov (United States)

    Bagnara, Davide; Squillario, Margherita; Kipling, David; Mora, Thierry; Walczak, Aleksandra M.; Da Silva, Lucie; Weller, Sandra; Dunn-Walters, Deborah K.; Weill, Jean-Claude; Reynaud, Claude-Agnès

    2015-01-01

    From paired blood and spleen samples from three adult donors we performed high-throughput V-h sequencing of human B-cell subsets defined by IgD and CD27 expression: IgD+CD27+ (“MZ”), IgD−CD27+(“memory”, including IgM (“IgM-only”), IgG and IgA) and IgD−CD27− cells (“double-negative”, including IgM, IgG and IgA). 91,294 unique sequences clustered in 42,670 clones, revealing major clonal expansions in each of these subsets. Among these clones, we further analyzed those shared sequences from different subsets or tissues for Vh-gene mutation, H-CDR3-length, and Vh/Jh usage, comparing these different characteristics with all sequences from their subset of origin, for which these parameters constitute a distinct signature. The IgM-only repertoire profile differed notably from that of MZ B cells by a higher mutation frequency, and lower Vh4 and higher Jh6 gene usage. Strikingly, IgM sequences from clones shared between the MZ and the memory IgG/IgA compartments showed a mutation and repertoire profile of IgM-only and not of MZ B cells. Similarly, all IgM clonal relationships (between MZ, IgM-only, and double-negative compartments) involved sequences with the characteristics of IgM-only B cells. Finally, clonal relationships between tissues suggested distinct recirculation characteristics between MZ and switched B cells. The “IgM-only” subset (including cells with its repertoire signature but higher IgD or lower CD27 expression levels) thus appear as the only subset showing precursor-product relationships with CD27+ switched memory B cells, indicating that they represent germinal center-derived IgM memory B cells, and that IgM memory and MZ B cells constitute two distinct entities. PMID:26355154

  10. Fast effects of glucocorticoids on memory-related network oscillations in the mouse hippocampus.

    Science.gov (United States)

    Weiss, E K; Krupka, N; Bähner, F; Both, M; Draguhn, A

    2008-05-01

    Transient or lasting increases in glucocorticoids accompany deficits in hippocampus-dependent memory formation. Recent data indicate that the formation and consolidation of declarative and spatial memory are mechanistically related to different patterns of hippocampal network oscillations. These include gamma oscillations during memory acquisition and the faster ripple oscillations (approximately 200 Hz) during subsequent memory consolidation. We therefore analysed the effects of acutely applied glucocorticoids on network activity in mouse hippocampal slices. Evoked field population spikes and paired-pulse responses were largely unaltered by corticosterone or cortisol, respectively, despite a slight increase in maximal population spike amplitude by 10 microm corticosterone. Several characteristics of sharp waves and superimposed ripple oscillations were affected by glucocorticoids, most prominently the frequency of spontaneously occurring sharp waves. At 0.1 microm, corticosterone increased this frequency, whereas maximal (10 microm) concentrations led to a reduction. In addition, gamma oscillations became slightly faster and less regular in the presence of high doses of corticosteroids. The present study describes acute effects of glucocorticoids on sharp wave-ripple complexes and gamma oscillations in mouse hippocampal slices, revealing a potential background for memory deficits in the presence of elevated levels of these hormones.

  11. Using model-based functional MRI to locate working memory updates and declarative memory retrievals in the fronto-parietal network

    OpenAIRE

    Borst, Jelmer P.; Anderson, John R.

    2013-01-01

    In this study, we used model-based functional MRI (fMRI) to locate two functions of the fronto-parietal network: declarative memory retrievals and updating of working memory. Because regions in the fronto-parietal network are by definition coherently active, locating functions within this network is difficult. To overcome this problem, we applied model-based fMRI, an analysis method that uses predictions of a computational model to inform the analysis. We applied model-based fMRI to five prev...

  12. Cantorian Fractal Spacetime and Quantum-like Chaos in Neural Networks of the Human Brain

    CERN Document Server

    Selvam, A M

    1998-01-01

    The neural networks of the human brain act as very efficient parallel processing computers co-ordinating memory related responses to a multitude of input signals from sensory organs. Information storage, update and appropriate retrieval are controlled at the molecular level by the neuronal cytoskeleton which serves as the internal communication network within neurons. Information flow in the highly ordered parallel networks of the filamentous protein polymers which make up the cytoskeleton may be compared to atmospheric flows which exhibit long-range spatiotemporal correlations, i.e. long-term memory. Such long-range spatiotemporal correlations are ubiquitous to real world dynamical systems and is recently identified as signature of self-organized criticality or chaos. The signatures of self-organized criticality i.e. long-range temporal correlations have recently been identified in the electrical activity of the brain. A recently developed non-deterministic cell dynamical system model for atmospheric flows p...

  13. Differential network analysis in human cancer research.

    Science.gov (United States)

    Gill, Ryan; Datta, Somnath; Datta, Susmita

    2014-01-01

    A complex disease like cancer is hardly caused by one gene or one protein singly. It is usually caused by the perturbation of the network formed by several genes or proteins. In the last decade several research teams have attempted to construct interaction maps of genes and proteins either experimentally or reverse engineer interaction maps using computational techniques. These networks were usually created under a certain condition such as an environmental condition, a particular disease, or a specific tissue type. Lately, however, there has been greater emphasis on finding the differential structure of the existing network topology under a novel condition or disease status to elucidate the perturbation in a biological system. In this review/tutorial article we briefly mention some of the research done in this area; we mainly illustrate the computational/statistical methods developed by our team in recent years for differential network analysis using publicly available gene expression data collected from a well known cancer study. This data includes a group of patients with acute lymphoblastic leukemia and a group with acute myeloid leukemia. In particular, we describe the statistical tests to detect the change in the network topology based on connectivity scores which measure the association or interaction between pairs of genes. The tests under various scores are applied to this data set to perform a differential network analysis on gene expression for human leukemia. We believe that, in the future, differential network analysis will be a standard way to view the changes in gene expression and protein expression data globally and these types of tests could be useful in analyzing the complex differential signatures.

  14. Gamma oscillations correlate with working memory load in humans

    National Research Council Canada - National Science Library

    Howard, Marc W; Rizzuto, Daniel S; Caplan, Jeremy B; Madsen, Joseph R; Lisman, John; Aschenbrenner-Scheibe, Richard; Schulze-Bonhage, Andreas; Kahana, Michael J

    2003-01-01

    .... Spectral analyses revealed that, in both patients, gamma (30-60 Hz) oscillations increased approximately linearly with memory load, tracking closely with memory load over the course of the trial...

  15. Automata Networks Model of Memory Loss Effects on the Formation of Linguistic Conventions

    CERN Document Server

    Vera, Javier

    2015-01-01

    This paper proposes an Automata Networks approach to address the influence of memory loss on the formation of shared conventions. We focus our analysis on a numerical description of the dynamics over one and two dimensional periodic lattices, through an energy function that measures the local agreement between the individuals. For the two dimensional case, it exhibits a sharp transition on the relation between the energy and the parameter defined to measure the amount of memory loss. Finally, we briefly discuss the implications for the formation of language.

  16. Training Working Memory in Childhood Enhances Coupling between Frontoparietal Control Network and Task-Related Regions.

    Science.gov (United States)

    Barnes, Jessica J; Nobre, Anna Christina; Woolrich, Mark W; Baker, Kate; Astle, Duncan E

    2016-08-24

    Working memory is a capacity upon which many everyday tasks depend and which constrains a child's educational progress. We show that a child's working memory can be significantly enhanced by intensive computer-based training, relative to a placebo control intervention, in terms of both standardized assessments of working memory and performance on a working memory task performed in a magnetoencephalography scanner. Neurophysiologically, we identified significantly increased cross-frequency phase amplitude coupling in children who completed training. Following training, the coupling between the upper alpha rhythm (at 16 Hz), recorded in superior frontal and parietal cortex, became significantly coupled with high gamma activity (at ∼90 Hz) in inferior temporal cortex. This altered neural network activity associated with cognitive skill enhancement is consistent with a framework in which slower cortical rhythms enable the dynamic regulation of higher-frequency oscillatory activity related to task-related cognitive processes. Whether we can enhance cognitive abilities through intensive training is one of the most controversial topics of cognitive psychology in recent years. This is particularly controversial in childhood, where aspects of cognition, such as working memory, are closely related to school success and are implicated in numerous developmental disorders. We provide the first neurophysiological account of how working memory training may enhance ability in childhood, using a brain recording technique called magnetoencephalography. We borrowed an analysis approach previously used with intracranial recordings in adults, or more typically in other animal models, called "phase amplitude coupling." Copyright © 2016 Barnes et al.

  17. Training Working Memory in Childhood Enhances Coupling between Frontoparietal Control Network and Task-Related Regions

    Science.gov (United States)

    Barnes, Jessica J.; Nobre, Anna Christina; Woolrich, Mark W.; Baker, Kate

    2016-01-01

    Working memory is a capacity upon which many everyday tasks depend and which constrains a child's educational progress. We show that a child's working memory can be significantly enhanced by intensive computer-based training, relative to a placebo control intervention, in terms of both standardized assessments of working memory and performance on a working memory task performed in a magnetoencephalography scanner. Neurophysiologically, we identified significantly increased cross-frequency phase amplitude coupling in children who completed training. Following training, the coupling between the upper alpha rhythm (at 16 Hz), recorded in superior frontal and parietal cortex, became significantly coupled with high gamma activity (at ∼90 Hz) in inferior temporal cortex. This altered neural network activity associated with cognitive skill enhancement is consistent with a framework in which slower cortical rhythms enable the dynamic regulation of higher-frequency oscillatory activity related to task-related cognitive processes. SIGNIFICANCE STATEMENT Whether we can enhance cognitive abilities through intensive training is one of the most controversial topics of cognitive psychology in recent years. This is particularly controversial in childhood, where aspects of cognition, such as working memory, are closely related to school success and are implicated in numerous developmental disorders. We provide the first neurophysiological account of how working memory training may enhance ability in childhood, using a brain recording technique called magnetoencephalography. We borrowed an analysis approach previously used with intracranial recordings in adults, or more typically in other animal models, called “phase amplitude coupling.” PMID:27559180

  18. Experimental Evaluation of Memory Effects on TCP Traffic in Congested Networks

    Directory of Open Access Journals (Sweden)

    Kulvinder Singh

    2010-09-01

    Full Text Available Today the Internet is a worldwide-interconnected computer network that transmits data by packet switching based on the TCP/IP protocol suite. Internet has TCP as the main protocol of the transport layer. The performance of TCP is studied by many researchers. They are trying to analytically characterizing the throughput of TCP's congestion control mechanism. Internet routers were widely believed to need big memory spaces. Commercial routers today have huge packet memory spaces, often storing millions of packets, under the assumption that big memory spaces lead to good statistical multiplexing and hence efficient use of expensive long-haul links. In this paper, we summarize the works and present the experimental study result with big memory space size and give a qualitative analysis of the result. Our conclusion is that the, round-trip time (RTT is not increased by linear, but by quadric when the memory space size of the bottleneck is big enough. Our goal is to estimate the average queue length of the memory space size and develop a TCP model based on RTT and the average queue length.

  19. The influence of age and mild cognitive impairment on associative memory performance and underlying brain networks.

    Science.gov (United States)

    Oedekoven, Christiane S H; Jansen, Andreas; Keidel, James L; Kircher, Tilo; Leube, Dirk

    2015-12-01

    Associative memory is essential to everyday activities, such as the binding of faces and corresponding names to form single bits of information. However, this ability often becomes impaired with increasing age. The most important neural substrate of associative memory is the hippocampus, a structure crucially implicated in the pathogenesis of Alzheimer's disease (AD). The main aim of this study was to compare neural correlates of associative memory in healthy aging and mild cognitive impairment (MCI), an at-risk state for AD. We used fMRI to investigate differences in brain activation and connectivity between young controls (n = 20), elderly controls (n = 32) and MCI patients (n = 21) during associative memory retrieval. We observed lower hippocampal activation in MCI patients than control groups during a face-name recognition task, and the magnitude of this decrement was correlated with lower associative memory performance. Further, increased activation in precentral regions in all older adults indicated a stronger involvement of the task positive network (TPN) with age. Finally, functional connectivity analysis revealed a stronger link of hippocampal and striatal components in older adults in comparison to young controls, regardless of memory impairment. In elderly controls, this went hand-in-hand with a stronger activation of striatal areas. Increased TPN activation may be linked to greater reliance on cognitive control in both older groups, while increased functional connectivity between the hippocampus and the striatum may suggest dedifferentiation, especially in elderly controls.

  20. A consensus network of gene regulatory factors in the human frontal lobe

    Directory of Open Access Journals (Sweden)

    Stefano eBerto

    2016-03-01

    Full Text Available Cognitive abilities, such as memory, learning, language, problem solving, and planning, involve the frontal lobe and other brain areas. Not much is known yet about the molecular basis of cognitive abilities, but it seems clear that cognitive abilities are determined by the interplay of many genes. One approach for analyzing the genetic networks involved in cognitive functions is to study the coexpression networks of genes with known importance for proper cognitive functions, such as genes that have been associated with cognitive disorders like intellectual disability (ID or autism spectrum disorders (ASD. Because many of these genes are gene regulatory factors (GRFs we aimed to provide insights into the gene regulatory networks active in the human frontal lobe. Using genome wide human frontal lobe expression data from 10 independent data sets, we first derived 10 individual coexpression networks for all GRFs including their potential target genes. We observed a high level of variability among these 10 independently derived networks, pointing out that relying on results from a single study can only provide limited biological insights. To instead focus on the most confident information from these 10 networks we developed a method for integrating such independently derived networks into a consensus network. This consensus network revealed robust GRF interactions that are conserved across the frontal lobes of different healthy human individuals. Within this network, we detected a strong central module that is enriched for 166 GRFs known to be involved in brain development and/or cognitive disorders. Interestingly, several hubs of the consensus network encode for GRFs that have not yet been associated with brain functions. Their central role in the network suggests them as excellent new candidates for playing an essential role in the regulatory network of the human frontal lobe, which should be investigated in future studies.

  1. A Consensus Network of Gene Regulatory Factors in the Human Frontal Lobe.

    Science.gov (United States)

    Berto, Stefano; Perdomo-Sabogal, Alvaro; Gerighausen, Daniel; Qin, Jing; Nowick, Katja

    2016-01-01

    Cognitive abilities, such as memory, learning, language, problem solving, and planning, involve the frontal lobe and other brain areas. Not much is known yet about the molecular basis of cognitive abilities, but it seems clear that cognitive abilities are determined by the interplay of many genes. One approach for analyzing the genetic networks involved in cognitive functions is to study the coexpression networks of genes with known importance for proper cognitive functions, such as genes that have been associated with cognitive disorders like intellectual disability (ID) or autism spectrum disorders (ASD). Because many of these genes are gene regulatory factors (GRFs) we aimed to provide insights into the gene regulatory networks active in the human frontal lobe. Using genome wide human frontal lobe expression data from 10 independent data sets, we first derived 10 individual coexpression networks for all GRFs including their potential target genes. We observed a high level of variability among these 10 independently derived networks, pointing out that relying on results from a single study can only provide limited biological insights. To instead focus on the most confident information from these 10 networks we developed a method for integrating such independently derived networks into a consensus network. This consensus network revealed robust GRF interactions that are conserved across the frontal lobes of different healthy human individuals. Within this network, we detected a strong central module that is enriched for 166 GRFs known to be involved in brain development and/or cognitive disorders. Interestingly, several hubs of the consensus network encode for GRFs that have not yet been associated with brain functions. Their central role in the network suggests them as excellent new candidates for playing an essential role in the regulatory network of the human frontal lobe, which should be investigated in future studies.

  2. New insights in human memory interference and consolidation.

    Science.gov (United States)

    Robertson, Edwin M

    2012-01-24

    Learning new facts and skills in succession can be frustrating because no sooner has new knowledge been acquired than its retention is being jeopardized by learning another set of skills or facts. Interference between memories has recently provided important new insights into the neural and psychological systems responsible for memory processing. For example, interference not only occurs between the same types of memories, but can also occur between different types of memories, which has important implications for our understanding of memory organization. Converging evidence has begun to reveal that the brain produces interference independently from other aspects of memory processing, which suggests that interference may have an important but previously overlooked function. A memory's initial susceptibility to interference and subsequent resistance to interference after its acquisition has revealed that memories continue to be processed 'off-line' during consolidation. Recent work has demonstrated that off-line processing is not limited to just the stabilization of a memory, which was once the defining characteristic of consolidation; instead, off-line processing can have a rich diversity of effects, from enhancing performance to making hidden rules explicit. Off-line processing also occurs after memory retrieval when memories are destabilized and then subsequently restabalized during reconsolidation. Studies are beginning to reveal the function of reconsolidation, its mechanistic relationship to consolidation and its potential as a therapeutic target for the modification of memories. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. Working memory network plasticity after anterior temporal lobe resection: a longitudinal functional magnetic resonance imaging study

    Science.gov (United States)

    Stretton, Jason; Sidhu, Meneka K.; Winston, Gavin P.; Bartlett, Philippa; McEvoy, Andrew W.; Symms, Mark R.; Koepp, Matthias J.; Thompson, Pamela J.

    2014-01-01

    Working memory is a crucial cognitive function that is disrupted in temporal lobe epilepsy. It is unclear whether this impairment is a consequence of temporal lobe involvement in working memory processes or due to seizure spread to extratemporal eloquent cortex. Anterior temporal lobe resection controls seizures in 50–80% of patients with drug-resistant temporal lobe epilepsy and the effect of surgery on working memory are poorly understood both at a behavioural and neural level. We investigated the impact of temporal lobe resection on the efficiency and functional anatomy of working memory networks. We studied 33 patients with unilateral medial temporal lobe epilepsy (16 left) before, 3 and 12 months after anterior temporal lobe resection. Fifteen healthy control subjects were also assessed in parallel. All subjects had neuropsychological testing and performed a visuospatial working memory functional magnetic resonance imaging paradigm on these three separate occasions. Changes in activation and deactivation patterns were modelled individually and compared between groups. Changes in task performance were included as regressors of interest to assess the efficiency of changes in the networks. Left and right temporal lobe epilepsy patients were impaired on preoperative measures of working memory compared to controls. Working memory performance did not decline following left or right temporal lobe resection, but improved at 3 and 12 months following left and, to a lesser extent, following right anterior temporal lobe resection. After left anterior temporal lobe resection, improved performance correlated with greater deactivation of the left hippocampal remnant and the contralateral right hippocampus. There was a failure of increased deactivation of the left hippocampal remnant at 3 months after left temporal lobe resection compared to control subjects, which had normalized 12 months after surgery. Following right anterior temporal lobe resection there was a

  4. Altered small-world brain networks in schizophrenia patients during working memory performance.

    Science.gov (United States)

    He, Hao; Sui, Jing; Yu, Qingbao; Turner, Jessica A; Ho, Beng-Choon; Sponheim, Scott R; Manoach, Dara S; Clark, Vincent P; Calhoun, Vince D

    2012-01-01

    Impairment of working memory (WM) performance in schizophrenia patients (SZ) is well-established. Compared to healthy controls (HC), SZ patients show aberrant blood oxygen level dependent (BOLD) activations and disrupted functional connectivity during WM performance. In this study, we examined the small-world network metrics computed from functional magnetic resonance imaging (fMRI) data collected as 35 HC and 35 SZ performed a Sternberg Item Recognition Paradigm (SIRP) at three WM load levels. Functional connectivity networks were built by calculating the partial correlation on preprocessed time courses of BOLD signal between task-related brain regions of interest (ROIs) defined by group independent component analysis (ICA). The networks were then thresholded within the small-world regime, resulting in undirected binarized small-world networks at different working memory loads. Our results showed: 1) at the medium WM load level, the networks in SZ showed a lower clustering coefficient and less local efficiency compared with HC; 2) in SZ, most network measures altered significantly as the WM load level increased from low to medium and from medium to high, while the network metrics were relatively stable in HC at different WM loads; and 3) the altered structure at medium WM load in SZ was related to their performance during the task, with longer reaction time related to lower clustering coefficient and lower local efficiency. These findings suggest brain connectivity in patients with SZ was more diffuse and less strongly linked locally in functional network at intermediate level of WM when compared to HC. SZ show distinctly inefficient and variable network structures in response to WM load increase, comparing to stable highly clustered network topologies in HC.

  5. Altered small-world brain networks in schizophrenia patients during working memory performance.

    Directory of Open Access Journals (Sweden)

    Hao He

    Full Text Available Impairment of working memory (WM performance in schizophrenia patients (SZ is well-established. Compared to healthy controls (HC, SZ patients show aberrant blood oxygen level dependent (BOLD activations and disrupted functional connectivity during WM performance. In this study, we examined the small-world network metrics computed from functional magnetic resonance imaging (fMRI data collected as 35 HC and 35 SZ performed a Sternberg Item Recognition Paradigm (SIRP at three WM load levels. Functional connectivity networks were built by calculating the partial correlation on preprocessed time courses of BOLD signal between task-related brain regions of interest (ROIs defined by group independent component analysis (ICA. The networks were then thresholded within the small-world regime, resulting in undirected binarized small-world networks at different working memory loads. Our results showed: 1 at the medium WM load level, the networks in SZ showed a lower clustering coefficient and less local efficiency compared with HC; 2 in SZ, most network measures altered significantly as the WM load level increased from low to medium and from medium to high, while the network metrics were relatively stable in HC at different WM loads; and 3 the altered structure at medium WM load in SZ was related to their performance during the task, with longer reaction time related to lower clustering coefficient and lower local efficiency. These findings suggest brain connectivity in patients with SZ was more diffuse and less strongly linked locally in functional network at intermediate level of WM when compared to HC. SZ show distinctly inefficient and variable network structures in response to WM load increase, comparing to stable highly clustered network topologies in HC.

  6. A Recurrent Network Model of Somatosensory Parametric Working Memory in the Prefrontal Cortex

    Science.gov (United States)

    Miller, Paul; Brody, Carlos D; Romo, Ranulfo; Wang, Xiao-Jing

    2015-01-01

    A parametric working memory network stores the information of an analog stimulus in the form of persistent neural activity that is monotonically tuned to the stimulus. The family of persistent firing patterns with a continuous range of firing rates must all be realizable under exactly the same external conditions (during the delay when the transient stimulus is withdrawn). How this can be accomplished by neural mechanisms remains an unresolved question. Here we present a recurrent cortical network model of irregularly spiking neurons that was designed to simulate a somatosensory working memory experiment with behaving monkeys. Our model reproduces the observed positively and negatively monotonic persistent activity, and heterogeneous tuning curves of memory activity. We show that fine-tuning mathematically corresponds to a precise alignment of cusps in the bifurcation diagram of the network. Moreover, we show that the fine-tuned network can integrate stimulus inputs over several seconds. Assuming that such time integration occurs in neural populations downstream from a tonically persistent neural population, our model is able to account for the slow ramping-up and ramping-down behaviors of neurons observed in prefrontal cortex. PMID:14576212

  7. Reconstruction of human protein interolog network using evolutionary conserved network

    Directory of Open Access Journals (Sweden)

    Lin Chung-Yen

    2007-05-01

    Full Text Available Abstract Background The recent increase in the use of high-throughput two-hybrid analysis has generated large quantities of data on protein interactions. Specifically, the availability of information about experimental protein-protein interactions and other protein features on the Internet enables human protein-protein interactions to be computationally predicted from co-evolution events (interolog. This study also considers other protein interaction features, including sub-cellular localization, tissue-specificity, the cell-cycle stage and domain-domain combination. Computational methods need to be developed to integrate these heterogeneous biological data to facilitate the maximum accuracy of the human protein interaction prediction. Results This study proposes a relative conservation score by finding maximal quasi-cliques in protein interaction networks, and considering other interaction features to formulate a scoring method. The scoring method can be adopted to discover which protein pairs are the most likely to interact among multiple protein pairs. The predicted human protein-protein interactions associated with confidence scores are derived from six eukaryotic organisms – rat, mouse, fly, worm, thale cress and baker's yeast. Conclusion Evaluation results of the proposed method using functional keyword and Gene Ontology (GO annotations indicate that some confidence is justified in the accuracy of the predicted interactions. Comparisons among existing methods also reveal that the proposed method predicts human protein-protein interactions more accurately than other interolog-based methods.

  8. Computational dissection of human episodic memory reveals mental process-specific genetic profiles.

    Science.gov (United States)

    Luksys, Gediminas; Fastenrath, Matthias; Coynel, David; Freytag, Virginie; Gschwind, Leo; Heck, Angela; Jessen, Frank; Maier, Wolfgang; Milnik, Annette; Riedel-Heller, Steffi G; Scherer, Martin; Spalek, Klara; Vogler, Christian; Wagner, Michael; Wolfsgruber, Steffen; Papassotiropoulos, Andreas; de Quervain, Dominique J-F

    2015-09-01

    Episodic memory performance is the result of distinct mental processes, such as learning, memory maintenance, and emotional modulation of memory strength. Such processes can be effectively dissociated using computational models. Here we performed gene set enrichment analyses of model parameters estimated from the episodic memory performance of 1,765 healthy young adults. We report robust and replicated associations of the amine compound SLC (solute-carrier) transporters gene set with the learning rate, of the collagen formation and transmembrane receptor protein tyrosine kinase activity gene sets with the modulation of memory strength by negative emotional arousal, and of the L1 cell adhesion molecule (L1CAM) interactions gene set with the repetition-based memory improvement. Furthermore, in a large functional MRI sample of 795 subjects we found that the association between L1CAM interactions and memory maintenance revealed large clusters of differences in brain activity in frontal cortical areas. Our findings provide converging evidence that distinct genetic profiles underlie specific mental processes of human episodic memory. They also provide empirical support to previous theoretical and neurobiological studies linking specific neuromodulators to the learning rate and linking neural cell adhesion molecules to memory maintenance. Furthermore, our study suggests additional memory-related genetic pathways, which may contribute to a better understanding of the neurobiology of human memory.

  9. Reliability characteristics of quadratic Hebbian-type associative memories in optical and electronic network implementations.

    Science.gov (United States)

    Chung, P C; Krile, T F

    1995-01-01

    The performance capability of quadratic Hebbian type associative memories (QHAM's) in the presence of interconnection faults is examined, and equations for predicting the probability of direct convergence P(dc) given a fraction of interconnection faults are developed. The interconnection faults considered are the equivalent of open circuit and short circuit synaptic interconnections in electronic implementations. Our results show that a network with open circuit interconnection faults has a higher probability of direct convergence P (dc) than a network with short circuit interconnection faults, when the fraction of failed interconnections p is small and the short circuit signal G is large. Certain values of G are found to have only mild effects on network performance degradation. Network reliability characteristics taking the generalization capability into account are also analyzed. All of these results are compared with those of Hebbian type associative memories (HAM's), which have linear association network models. Our results indicate that QHAM's have much higher network capacity and fault tolerance capability in the presence of interconnection faults. However, the fault tolerance to input errors in QHAM's is much less than that of HAM's.

  10. Shape memory polymers

    Energy Technology Data Exchange (ETDEWEB)

    Wilson, Thomas S.; Bearinger, Jane P.

    2017-08-29

    New shape memory polymer compositions, methods for synthesizing new shape memory polymers, and apparatus comprising an actuator and a shape memory polymer wherein the shape memory polymer comprises at least a portion of the actuator. A shape memory polymer comprising a polymer composition which physically forms a network structure wherein the polymer composition has shape-memory behavior and can be formed into a permanent primary shape, re-formed into a stable secondary shape, and controllably actuated to recover the permanent primary shape. Polymers have optimal aliphatic network structures due to minimization of dangling chains by using monomers that are symmetrical and that have matching amine and hydroxl groups providing polymers and polymer foams with clarity, tight (narrow temperature range) single transitions, and high shape recovery and recovery force that are especially useful for implanting in the human body.

  11. Shape memory polymers

    Science.gov (United States)

    Wilson, Thomas S.; Bearinger, Jane P.

    2015-06-09

    New shape memory polymer compositions, methods for synthesizing new shape memory polymers, and apparatus comprising an actuator and a shape memory polymer wherein the shape memory polymer comprises at least a portion of the actuator. A shape memory polymer comprising a polymer composition which physically forms a network structure wherein the polymer composition has shape-memory behavior and can be formed into a permanent primary shape, re-formed into a stable secondary shape, and controllably actuated to recover the permanent primary shape. Polymers have optimal aliphatic network structures due to minimization of dangling chains by using monomers that are symmetrical and that have matching amine and hydroxyl groups providing polymers and polymer foams with clarity, tight (narrow temperature range) single transitions, and high shape recovery and recovery force that are especially useful for implanting in the human body.

  12. False memory susceptibility is correlated with categorisation ability in humans.

    Science.gov (United States)

    Hunt, Kathryn; Chittka, Lars

    2014-01-01

    Our memory is often surprisingly inaccurate, with errors ranging from misremembering minor details of events to generating illusory memories of entire episodes. The pervasiveness of such false memories generates a puzzle: in the face of selection pressure for accuracy of memory, how could such systematic failures have persisted over evolutionary time? It is possible that memory errors are an inevitable by-product of our adaptive memories and that semantic false memories are specifically connected to our ability to learn rules and concepts and to classify objects by category memberships. Here we test this possibility using a standard experimental false memory paradigm and inter-individual variation in verbal categorisation ability. Indeed it turns out that the error scores are significantly negatively correlated, with those individuals scoring fewer errors on the categorisation test being more susceptible to false memory intrusions in a free recall test. A similar trend, though not significant, was observed between individual categorisation ability and false memory susceptibility in a word recognition task. Our results therefore indicate that false memories, to some extent, might be a by-product of our ability to learn rules, categories and concepts.

  13. The dynamics of zero: on digital memories of Mars and the human foetus in the globital memory field

    Directory of Open Access Journals (Sweden)

    Anna READING

    2012-01-01

    Full Text Available The dynamics of digitisation and globalisation are synergetically and dialectically changing the ways in which human beings individually and collectively capture, document, share and preserve memories of the past. This paper develops further the concept of the “globital memory field” with a discursive overview of the development of “digital memory” and the significance of zero in the meaning and practice of digital memory. The paper then explains the key elements of this epistemology, with an emphasis on the significance of zero or nothing in relation to two contrasting examples of the medical imaging of the human fœtus to the capturing and sending back to Earth by NASA’s Curiosity robot images from the surface of Mars.

  14. A maze learning comparison of Elman, long short-term memory, and Mona neural networks.

    Science.gov (United States)

    Portegys, Thomas E

    2010-03-01

    This study compares the maze learning performance of three artificial neural network architectures: an Elman recurrent neural network, a long short-term memory (LSTM) network, and Mona, a goal-seeking neural network. The mazes are networks of distinctly marked rooms randomly interconnected by doors that open probabilistically. The mazes are used to examine two important problems related to artificial neural networks: (1) the retention of long-term state information and (2) the modular use of learned information. For the former, mazes impose a context learning demand: at the beginning of the maze, an initial door choice forms a context that must be remembered until the end of the maze, where the same numbered door must be chosen again in order to reach the goal. For the latter, the effect of modular and non-modular training is examined. In modular training, the door associations are trained in separate trials from the intervening maze paths, and only presented together in testing trials. All networks performed well on mazes without the context learning requirement. The Mona and LSTM networks performed well on context learning with non-modular training; the Elman performance degraded as the task length increased. Mona also performed well for modular training; both the LSTM and Elman networks performed poorly with modular training.

  15. Hopf bifurcation of an (n + 1) -neuron bidirectional associative memory neural network model with delays.

    Science.gov (United States)

    Xiao, Min; Zheng, Wei Xing; Cao, Jinde

    2013-01-01

    Recent studies on Hopf bifurcations of neural networks with delays are confined to simplified neural network models consisting of only two, three, four, five, or six neurons. It is well known that neural networks are complex and large-scale nonlinear dynamical systems, so the dynamics of the delayed neural networks are very rich and complicated. Although discussing the dynamics of networks with a few neurons may help us to understand large-scale networks, there are inevitably some complicated problems that may be overlooked if simplified networks are carried over to large-scale networks. In this paper, a general delayed bidirectional associative memory neural network model with n + 1 neurons is considered. By analyzing the associated characteristic equation, the local stability of the trivial steady state is examined, and then the existence of the Hopf bifurcation at the trivial steady state is established. By applying the normal form theory and the center manifold reduction, explicit formulae are derived to determine the direction and stability of the bifurcating periodic solution. Furthermore, the paper highlights situations where the Hopf bifurcations are particularly critical, in the sense that the amplitude and the period of oscillations are very sensitive to errors due to tolerances in the implementation of neuron interconnections. It is shown that the sensitivity is crucially dependent on the delay and also significantly influenced by the feature of the number of neurons. Numerical simulations are carried out to illustrate the main results.

  16. Memory network plasticity after temporal lobe resection: a longitudinal functional imaging study.

    Science.gov (United States)

    Sidhu, Meneka K; Stretton, Jason; Winston, Gavin P; McEvoy, Andrew W; Symms, Mark; Thompson, Pamela J; Koepp, Matthias J; Duncan, John S

    2016-02-01

    Anterior temporal lobe resection can control seizures in up to 80% of patients with temporal lobe epilepsy. Memory decrements are the main neurocognitive complication. Preoperative functional reorganization has been described in memory networks, but less is known of postoperative reorganization. We investigated reorganization of memory-encoding networks preoperatively and 3 and 12 months after surgery. We studied 36 patients with unilateral medial temporal lobe epilepsy (19 right) before and 3 and 12 months after anterior temporal lobe resection. Fifteen healthy control subjects were studied at three equivalent time points. All subjects had neuropsychological testing at each of the three time points. A functional magnetic resonance imaging memory-encoding paradigm of words and faces was performed with subsequent out-of-scanner recognition assessments. Changes in activations across the time points in each patient group were compared to changes in the control group in a single flexible factorial analysis. Postoperative change in memory across the time points was correlated with postoperative activations to investigate the efficiency of reorganized networks. Left temporal lobe epilepsy patients showed increased right anterior hippocampal and frontal activation at both 3 and 12 months after surgery relative to preoperatively, for word and face encoding, with a concomitant reduction in left frontal activation 12 months postoperatively. Right anterior hippocampal activation 12 months postoperatively correlated significantly with improved verbal learning in patients with left temporal lobe epilepsy from preoperatively to 12 months postoperatively. Preoperatively, there was significant left posterior hippocampal activation that was sustained 3 months postoperatively at word encoding, and increased at face encoding. For both word and face encoding this was significantly reduced from 3 to 12 months postoperatively. Patients with right temporal lobe epilepsy showed increased

  17. Classifying Human Body Acceleration Patterns Using a Hierarchical Temporal Memory

    Science.gov (United States)

    Sassi, Federico; Ascari, Luca; Cagnoni, Stefano

    This paper introduces a novel approach to the detection of human body movements during daily life. With the sole use of one wearable wireless triaxial accelerometer attached to one's chest, this approach aims at classifying raw acceleration data robustly, to detect many common human behaviors without requiring any specific a-priori knowledge about movements. The proposed approach consists of feeding sensory data into a specifically trained Hierarchical Temporal Memory (HTM) to extract invariant spatial-temporal patterns that characterize different body movements. The HTM output is then classified using a Support Vector Machine (SVM) into different categories. The performance of this new HTM+SVM combination is compared with a single SVM using real-word data corresponding to movements like "standing", "walking", "jumping" and "falling", acquired from a group of different people. Experimental results show that the HTM+SVM approach can detect behaviors with very high accuracy and is more robust, with respect to noise, than a classifier based solely on SVMs.

  18. Developmental changes of BOLD signal correlations with global human EEG power and synchronization during working memory.

    Science.gov (United States)

    Michels, Lars; Lüchinger, Rafael; Koenig, Thomas; Martin, Ernst; Brandeis, Daniel

    2012-01-01

    In humans, theta band (5-7 Hz) power typically increases when performing cognitively demanding working memory (WM) tasks, and simultaneous EEG-fMRI recordings have revealed an inverse relationship between theta power and the BOLD (blood oxygen level dependent) signal in the default mode network during WM. However, synchronization also plays a fundamental role in cognitive processing, and the level of theta and higher frequency band synchronization is modulated during WM. Yet, little is known about the link between BOLD, EEG power, and EEG synchronization during WM, and how these measures develop with human brain maturation or relate to behavioral changes. We examined EEG-BOLD signal correlations from 18 young adults and 15 school-aged children for age-dependent effects during a load-modulated Sternberg WM task. Frontal load (in-)dependent EEG theta power was significantly enhanced in children compared to adults, while adults showed stronger fMRI load effects. Children demonstrated a stronger negative correlation between global theta power and the BOLD signal in the default mode network relative to adults. Therefore, we conclude that theta power mediates the suppression of a task-irrelevant network. We further conclude that children suppress this network even more than adults, probably from an increased level of task-preparedness to compensate for not fully mature cognitive functions, reflected in lower response accuracy and increased reaction time. In contrast to power, correlations between instantaneous theta global field synchronization and the BOLD signal were exclusively positive in both age groups but only significant in adults in the frontal-parietal and posterior cingulate cortices. Furthermore, theta synchronization was weaker in children and was--in contrast to EEG power--positively correlated with response accuracy in both age groups. In summary we conclude that theta EEG-BOLD signal correlations differ between spectral power and synchronization and that

  19. Developmental changes of BOLD signal correlations with global human EEG power and synchronization during working memory.

    Directory of Open Access Journals (Sweden)

    Lars Michels

    Full Text Available In humans, theta band (5-7 Hz power typically increases when performing cognitively demanding working memory (WM tasks, and simultaneous EEG-fMRI recordings have revealed an inverse relationship between theta power and the BOLD (blood oxygen level dependent signal in the default mode network during WM. However, synchronization also plays a fundamental role in cognitive processing, and the level of theta and higher frequency band synchronization is modulated during WM. Yet, little is known about the link between BOLD, EEG power, and EEG synchronization during WM, and how these measures develop with human brain maturation or relate to behavioral changes. We examined EEG-BOLD signal correlations from 18 young adults and 15 school-aged children for age-dependent effects during a load-modulated Sternberg WM task. Frontal load (in-dependent EEG theta power was significantly enhanced in children compared to adults, while adults showed stronger fMRI load effects. Children demonstrated a stronger negative correlation between global theta power and the BOLD signal in the default mode network relative to adults. Therefore, we conclude that theta power mediates the suppression of a task-irrelevant network. We further conclude that children suppress this network even more than adults, probably from an increased level of task-preparedness to compensate for not fully mature cognitive functions, reflected in lower response accuracy and increased reaction time. In contrast to power, correlations between instantaneous theta global field synchronization and the BOLD signal were exclusively positive in both age groups but only significant in adults in the frontal-parietal and posterior cingulate cortices. Furthermore, theta synchronization was weaker in children and was--in contrast to EEG power--positively correlated with response accuracy in both age groups. In summary we conclude that theta EEG-BOLD signal correlations differ between spectral power and

  20. Time varying effective connectivity for describing brain network changes induced by a memory rehabilitation treatment.

    Science.gov (United States)

    Toppi, J; Mattia, D; Anzolin, A; Risetti, M; Petti, M; Cincotti, F; Babiloni, F; Astolfi, L

    2014-01-01

    In clinical practice, cognitive impairment is often observed after stroke. The efficacy of rehabilitative interventions is routinely assessed by means of a neuropsychological test battery. Nowadays, more evidences indicate that the neuroplasticity which occurs after stroke can be better understood by investigating changes in brain networks. In this study we applied advanced methodologies for effective connectivity estimation in combination with graph theory approach, to define EEG derived descriptors of brain networks underlying memory tasks. In particular, we proposed such descriptors to identify substrates of efficacy of a Brain-Computer Interface (BCI) controlled neurofeedback intervention to improve cognitive function after stroke. Electroencephalographic (EEG) data were collected from two stroke patients before and after a neurofeedback-based training for memory deficits. We show that the estimated brain connectivity indices were sensitive to different training intervention outcomes, thus suggesting an effective support to the neuropsychological assessment in the evaluation of the changes induced by the BCI-based cognitive rehabilitative intervention.

  1. Development of deactivation of the default-mode network during episodic memory formation

    Science.gov (United States)

    Chai, Xiaoqian J.; Ofen, Noa; Gabrieli, John D. E.; Whitfield-Gabrieli, Susan

    2014-01-01

    Task-induced deactivation of the default-mode network (DMN) has been associated in adults with successful episodic memory formation, possibly as a mechanism to focus allocation of mental resources for successful encoding of external stimuli. We investigated developmental changes of deactivation of the DMN (posterior cingulate, medial prefrontal, and bilateral lateral parietal cortices) during episodic memory formation in children, adolescents, and young adults (ages 8–24), who studied scenes during functional magnetic resonance imaging (fMRI). Recognition memory improved with age. We defined DMN regions of interest from a different sample of participants with the same age range, using resting-state fMRI. In adults, there was greater deactivation of the DMN for scenes that were later remembered than scenes that were later forgotten. In children, deactivation of the default-network did not differ reliably between scenes that were later remembered or forgotten. Adolescents exhibited a pattern of activation intermediate to that of children and adults. The hippocampal region, often considered part of the DMN, showed a functional dissociation with the rest of the DMN by exhibiting increased activation for later remembered than later forgotten scene that was similar across age groups. These findings suggest that development of memory ability from childhood through adulthood may involve increased deactivation of the neocortical DMN during learning. PMID:24064072

  2. Inferring long memory processes in the climate network via ordinal pattern analysis

    CERN Document Server

    Barreiro, Marcelo; Masoller, Cristina

    2010-01-01

    We use ordinal patterns and symbolic analysis to construct global climate networks and uncover long and short term memory processes. The data analyzed is the monthly averaged surface air temperature (SAT field) and the results suggest that the time variability of the SAT field is determined by patterns of oscillatory behavior that repeat from time to time, with a periodicity related to intraseasonal oscillations and to El Ni\\~{n}o on seasonal-to-interannual time scales.

  3. Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition

    OpenAIRE

    Li, Xiangang; Wu, Xihong

    2014-01-01

    Long short-term memory (LSTM) based acoustic modeling methods have recently been shown to give state-of-the-art performance on some speech recognition tasks. To achieve a further performance improvement, in this research, deep extensions on LSTM are investigated considering that deep hierarchical model has turned out to be more efficient than a shallow one. Motivated by previous research on constructing deep recurrent neural networks (RNNs), alternative deep LSTM architectures are proposed an...

  4. Programming Memory-Constrained Networked Embedded Systems. PhD thesis

    OpenAIRE

    Dunkels, Adam

    2007-01-01

    Ten years after the Internet revolution are we standing on the brink of another revolution: networked embedded systems that connect the physical world with the computers, enabling new applications ranging from environmental monitoring and wildlife tracking to improvements in health care and medicine. 98% of all microprocessors sold today are used in embedded systems. Those systems have much smaller amounts of memory than PC computers. An embedded system may have as little has a few hundred by...

  5. GLOBAL EXPONENTIAL STABILITY IN HOPFIELD AND BIDIRECTIONAL ASSOCIATIVE MEMORY NEURAL NETWORKS WITH TIME DELAYS

    Institute of Scientific and Technical Information of China (English)

    RONG LIBIN; LU WENLIAN; CHEN TIANPING

    2004-01-01

    Without assuming the boundedness, strict monotonicity and differentiability of the activation functions, the authors utilize the Lyapunov functional method to analyze the global convergence of some delayed models. For the Hopfield neural network with time delays, a new sufficient condition ensuring the existence, uniqueness and global exponential stability of the equilibrium point is derived. This criterion concerning the signs of entries in the connection matrix imposes constraints on the feedback matrix independently of the delay parameters. From a new viewpoint, the bidirectional associative memory neural network with time delays is investigated and a new global exponential stability result is given.

  6. Global Exponential Stability Criteria for Bidirectional Associative Memory Neural Networks with Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    J. Thipcha

    2013-01-01

    Full Text Available The global exponential stability for bidirectional associative memory neural networks with time-varying delays is studied. In our study, the lower and upper bounds of the activation functions are allowed to be either positive, negative, or zero. By constructing new and improved Lyapunov-Krasovskii functional and introducing free-weighting matrices, a new and improved delay-dependent exponential stability for BAM neural networks with time-varying delays is derived in the form of linear matrix inequality (LMI. Numerical examples are given to demonstrate that the derived condition is less conservative than some existing results given in the literature.

  7. A Neural Network Model of the Visual Short-Term Memory

    DEFF Research Database (Denmark)

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

    2009-01-01

    In this paper a neural network model of Visual Short-Term Memory (VSTM) is presented. The model links closely with Bundesen’s (1990) well-established mathematical theory of visual attention. We evaluate the model’s ability to fit experimental data from a classical whole and partial report study....... Previous statistic models have successfully assessed the spatial distribution of visual attention; our neural network meets this standard and offers a neural interpretation of how objects are consolidated in VSTM at the same time. We hope that in the future, the model will be able to fit temporally...

  8. Singular-Value-Decomposition Analysis of Associative Memory in a Neural Network

    Science.gov (United States)

    Kumamoto, Tatsuya; Suzuki, Mao; Matsueda, Hiroaki

    2017-02-01

    We evaluate performance of associative memory in a neural network by based on the singular value decomposition (SVD) of image data stored in the network. We consider the situation in which the original image and its highly coarse-grained one by SVD are stored in the network and the intermediate one is taken as an input. We find that the performance is characterized by the snapshot-entropy scaling inherent in the SVD: the network retrieves the original image when the entropy of the input image is larger than the critical value determined from the scaling. The result indicates efficiency of the SVD as a criterion of the performance and also indicates universality of the scaling for realistic problems beyond theoretical physics.

  9. Effect of Memory on the Dynamics of Random Walks on Networks

    CERN Document Server

    Lambiotte, Renaud; Rosvall, Martin

    2014-01-01

    Pathways of diffusion observed in real-world systems often require stochastic processes going beyond first-order Markov models, as implicitly assumed in network theory. In this work, we focus on second-order Markov models, and derive an analytical expression for the effect of memory on the spectral gap and thus, equivalently, on the characteristic time needed for the stochastic process to asymptotically reach equilibrium. Perturbation analysis shows that standard first-order Markov models can either overestimate or underestimate the diffusion rate of flows across the modular structure of a system captured by a second-order Markov network. We test the theoretical predictions on a toy example and on numerical data, and discuss their implications for network theory, in particular in the case of temporal or multiplex networks.

  10. Synchronization and long-time memory in neural networks with inhibitory hubs and synaptic plasticity

    Science.gov (United States)

    Bertolotti, Elena; Burioni, Raffaella; di Volo, Matteo; Vezzani, Alessandro

    2017-01-01

    We investigate the dynamical role of inhibitory and highly connected nodes (hub) in synchronization and input processing of leaky-integrate-and-fire neural networks with short term synaptic plasticity. We take advantage of a heterogeneous mean-field approximation to encode the role of network structure and we tune the fraction of inhibitory neurons fI and their connectivity level to investigate the cooperation between hub features and inhibition. We show that, depending on fI, highly connected inhibitory nodes strongly drive the synchronization properties of the overall network through dynamical transitions from synchronous to asynchronous regimes. Furthermore, a metastable regime with long memory of external inputs emerges for a specific fraction of hub inhibitory neurons, underlining the role of inhibition and connectivity also for input processing in neural networks.

  11. Cytotoxicity and thermomechanical behavior of biomedical shape-memory polymer networks post-sterilization.

    Science.gov (United States)

    Yakacki, C M; Lyons, M B; Rech, B; Gall, K; Shandas, R

    2008-03-01

    Shape-memory polymers (SMPs) are being increasingly proposed for use in biomedical devices. This paper investigates the cytotoxicity, surface characteristics and thermomechanics of two acrylate-based SMP networks as a function of sterilization using a minimal essential media elution test, FTIR-ATR and dynamic mechanical analysis (DMA). Networks sterilized by low-temperature plasma elicited a cytotoxic response and are shown to completely destroy the cell monolayer. FTIR-ATR analysis showed evidence of surface oxidation with an increase and broadening of the absorbance peak from approximately 3500 to 3100 cm(-1), which is associated with an increase in hydroxyl groups. DMA revealed small, but statistically significant, differences in reduction of the glass transition temperatures of both networks when sterilized with gamma irradiation. One network showed an increase in rubbery modulus, which is an indication of crosslink density, after gamma irradiation. Lastly, practical sterilization concerns of SMP devices are discussed in light of the different methods.

  12. Fundamental short-term memory of semi-artificial neuronal network.

    Science.gov (United States)

    Ito, Hidekatsu; Kudoh, Suguru N

    2013-01-01

    Spatiotemporal pattern of neuronal network activity is a key component of brain information processing. Cultured rat hippocampal neurons on the multielectrodes array dish are suitable for analyzing and manipulating network dynamics and its developmental changes. We applied paired electrical inputs at various inter-stimulus intervals (ISi) and analyzed the spatio-temporal pattern of evoked responses. We found that the pattern of evoked electrical activity was affected by existence of a prior input in the case that ISi of paired stimuli was within 2 s. These results suggest that a semi-artificial neuronal network on a culture dish has a fundamental component of short-term memory, and the origin of this hysteresis is transition among the internal states of the network, undertaken by synaptic transmissions.

  13. MicroRNA-138 is a potential regulator of memory performance in humans

    OpenAIRE

    Schröder, Julia; Ansaloni, Sara; Schilling, Marcel; Liu, Tian; Radke, Josefine; Jaedicke, Marian; Schjeide, Brit-Maren M.; Mashychev, Andriy; Tegeler, Christina; Radbruch, Helena; Papenberg, Goran; Düzel, Sandra; Demuth, Ilja; Bucholtz, Nina; Lindenberger, Ulman

    2014-01-01

    Genetic factors underlie a substantial proportion of individual differences in cognitive functions in humans, including processes related to episodic and working memory. While genetic association studies have proposed several candidate "memory genes," these currently explain only a minor fraction of the phenotypic variance. Here, we performed genome-wide screening on 13 episodic and working memory phenotypes in 1318 participants of the Berlin Aging Study II aged 60 years or older. The analyse...

  14. MicroRNA-138 is a potential regulator of memory performance in humans

    OpenAIRE

    Julia eSchröder; Sara eAnsaloni; Marcel eSchilling; Tian eLiu; Josefine eRadke; Marian eJädicke; Schjeide, Brit-Maren M.; Andriy eMashychev; Christina eTegeler; Helena eRadbruch; Goran ePapenberg; Sandra eDüzel; Ilja eDemuth; Nina eBucholtz; Ulman eLindenberger

    2014-01-01

    Genetic factors underlie a substantial proportion of individual differences in cognitive functions in humans, including processes related to episodic and working memory. While genetic association studies have proposed several candidate memory genes, these currently explain only a minor fraction of the phenotypic variance. Here, we performed genome-wide screening on 13 episodic and working memory phenotypes in 1,318 participants of the Berlin Aging Study II aged 60 years or older. The analyses...

  15. The Memory of Science: Inflation, Myopia, and the Knowledge Network

    CERN Document Server

    Pan, Raj K; Pammolli, Fabio; Fortunato, Santo

    2016-01-01

    Science is a growing system, exhibiting ~4% annual growth in publications and ~1.8% annual growth in the number of references per publication. Combined these trends correspond to a 12-year doubling period in the total supply of references, thereby challenging traditional methods of evaluating scientific production, from researchers to institutions. Against this background, we analyzed a citation network comprised of 837 million references produced by 32.6 million publications over the period 1965-2012, allowing for a temporal analysis of the `attention economy' in science. Unlike previous studies, we analyzed the entire probability distribution of reference ages - the time difference between a citing and cited paper - thereby capturing previously overlooked trends. Over this half-century period we observe a narrowing range of attention - both classic and recent literature are being cited increasingly less, pointing to the important role of socio-technical processes. To better understand the impact of exponent...

  16. Retrieval under stress decreases the long-term expression of a human declarative memory via reconsolidation.

    Science.gov (United States)

    Larrosa, Pablo Nicolás Fernández; Ojea, Alejandro; Ojea, Ignacio; Molina, Victor Alejandro; Zorrilla-Zubilete, María Aurelia; Delorenzi, Alejandro

    2017-07-01

    Acute stress impairs memory retrieval of several types of memories. An increase in glucocorticoids, several minutes after stressful events, is described as essential to the impairing retrieval-effects of stressors. Moreover, memory retrieval under stress can have long-term consequences. Through what process does the reactivated memory under stress, despite the disrupting retrieval effects, modify long-term memories? The reconsolidation hypothesis proposes that a previously consolidated memory reactivated by a reminder enters a vulnerability phase (labilization) during which it is transiently sensitive to modulation, followed by a re-stabilization phase. However, previous studies show that the expression of memories during reminder sessions is not a condition to trigger the reconsolidation process since unexpressed memories can be reactivated and labilized. Here we evaluate whether it is possible to reactivate-labilize a memory under the impairing-effects of a mild stressor. We used a paradigm of human declarative memory whose reminder structure allows us to differentiate between a reactivated-labile memory state and a reactivated but non-labile state. Subjects memorized a list of five cue-syllables associated with their respective response-syllables. Seventy-two hours later, results showed that the retrieval of the paired-associate memory was impaired when tested 20min after a mild stressor (cold pressor stress (CPS)) administration, coincident with cortisol levels increase. Then, we investigated the long-term effects of CPS administration prior to the reminder session. Under conditions where the reminder initiates the reconsolidation process, CPS impaired the long-term memory expression tested 24h later. In contrast, CPS did not show effects when administered before a reminder session that does not trigger reconsolidation. Results showed that memory reactivation-labilization occurs even when retrieval was impaired. Memory reactivation under stress could hinder

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

    Science.gov (United States)

    Luhmann, Christian C; Rajaram, Suparna

    2015-12-01

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

  18. Dissecting the human CD4+T cell memory pool

    OpenAIRE

    Rivino, Laura; Rusconi, Sandro; Geginat, Jens

    2007-01-01

    Memory cells can persist for a whole lifetime. Consequently, these cells must possess characteristics which endows them with the capacity to survive in the absence of their cognate antigen, to self-renewal and to rapidly and efficiently respond upon secondary encounter of antigen. It has become increasingly clear that the memory pool can fulfil these diverse requirements because of its extreme heterogeneity which allows a division of labour among the different memory cell subsets. In my study...

  19. A Neural Network Model of the Effects of Entrenchment and Memory Development on Grammatical Gender Learning

    Science.gov (United States)

    Monner, Derek; Vatz, Karen; Morini, Giovanna; Hwang, So-One; DeKeyser, Robert

    2013-01-01

    To investigate potential causes of L2 performance deficits that correlate with age of onset, we use a computational model to explore the individual contributions of L1 entrenchment and aspects of memory development. Since development and L1 entrenchment almost invariably coincide, studying them independently is seldom possible in humans. To avoid…

  20. A Neural Network Model of the Effects of Entrenchment and Memory Development on Grammatical Gender Learning

    Science.gov (United States)

    Monner, Derek; Vatz, Karen; Morini, Giovanna; Hwang, So-One; DeKeyser, Robert

    2013-01-01

    To investigate potential causes of L2 performance deficits that correlate with age of onset, we use a computational model to explore the individual contributions of L1 entrenchment and aspects of memory development. Since development and L1 entrenchment almost invariably coincide, studying them independently is seldom possible in humans. To avoid…

  1. A simple neural network model of the hippocampus suggesting its pathfinding role in episodic memory retrieval.

    Science.gov (United States)

    Samsonovich, Alexei V; Ascoli, Giorgio A

    2005-01-01

    The goal of this work is to extend the theoretical understanding of the relationship between hippocampal spatial and memory functions to the level of neurophysiological mechanisms underlying spatial navigation and episodic memory retrieval. The proposed unifying theory describes both phenomena within a unique framework, as based on one and the same pathfinding function of the hippocampus. We propose a mechanism of reconstruction of the context of experience involving a search for a nearly shortest path in the space of remembered contexts. To analyze this concept in detail, we define a simple connectionist model consistent with available rodent and human neurophysiological data. Numerical study of the model begins with the spatial domain as a simple analogy for more complex phenomena. It is demonstrated how a nearly shortest path is quickly found in a familiar environment. We prove numerically that associative learning during sharp waves can account for the necessary properties of hippocampal place cells. Computational study of the model is extended to other cognitive paradigms, with the main focus on episodic memory retrieval. We show that the ability to find a correct path may be vital for successful retrieval. The model robustly exhibits the pathfinding capacity within a wide range of several factors, including its memory load (up to 30,000 abstract contexts), the number of episodes that become associated with potential target contexts, and the level of dynamical noise. We offer several testable critical predictions in both spatial and memory domains to validate the theory. Our results suggest that (1) the pathfinding function of the hippocampus, in addition to its associative and memory indexing functions, may be vital for retrieval of certain episodic memories, and (2) the hippocampal spatial navigation function could be a precursor of its memory function.

  2. Identifying familiar strangers in human encounter networks

    Science.gov (United States)

    Liang, Di; Li, Xiang; Zhang, Yi-Qing

    2016-10-01

    Familiar strangers, pairs of individuals who encounter repeatedly but never know each other, have been discovered for four decades yet lack an effective method to identify. Here we propose a novel method called familiar stranger classifier (FSC) to identify familiar strangers from three empirical datasets, and classify human relationships into four types, i.e., familiar stranger (FS), in-role (IR), friend (F) and stranger (S). The analyses of the human encounter networks show that the average number of FS one may encounter is finite but larger than the Dunbar Number, and their encounters are structurally more stable and denser than those of S, indicating the encounters of FS are not limited by the social capacity, and more robust than the random scenario. Moreover, the temporal statistics of encounters between FS over the whole time span show strong periodicity, which are diverse from the bursts of encounters within one day, suggesting the significance of longitudinal patterns of human encounters. The proposed method to identify FS in this paper provides a valid framework to understand human encounter patterns and analyse complex human social behaviors.

  3. Segregation between the parietal memory network and the default mode network: effects of spatial smoothing and model order in ICA.

    Science.gov (United States)

    Hu, Yang; Wang, Jijun; Li, Chunbo; Wang, Yin-Shan; Yang, Zhi; Zuo, Xi-Nian

    2016-01-01

    A brain network consisting of two key parietal nodes, the precuneus and the posterior cingulate cortex, has emerged from recent fMRI studies. Though it is anatomically adjacent to and spatially overlaps with the default mode network (DMN), its function has been associated with memory processing, and it has been referred to as the parietal memory network (PMN). Independent component analysis (ICA) is the most common data-driven method used to extract PMN and DMN simultaneously. However, the effects of data preprocessing and parameter determination in ICA on PMN-DMN segregation are completely unknown. Here, we employ three typical algorithms of group ICA to assess how spatial smoothing and model order influence the degree of PMN-DMN segregation. Our findings indicate that PMN and DMN can only be stably separated using a combination of low-level spatial smoothing and high model order across the three ICA algorithms. We thus argue for more considerations on parametric settings for interpreting DMN data.

  4. How activation, entanglement, and searching a semantic network contribute to event memory.

    Science.gov (United States)

    Nelson, Douglas L; Kitto, Kirsty; Galea, David; McEvoy, Cathy L; Bruza, Peter D

    2013-08-01

    Free-association norms indicate that words are organized into semantic/associative neighborhoods within a larger network of words and links that bind the net together. We present evidence indicating that memory for a recent word event can depend on implicitly and simultaneously activating related words in its neighborhood. Processing a word during encoding primes its network representation as a function of the density of the links in its neighborhood. Such priming increases recall and recognition and can have long-lasting effects when the word is processed in working memory. Evidence for this phenomenon is reviewed in extralist-cuing, primed free-association, intralist-cuing, and single-item recognition tasks. The findings also show that when a related word is presented in order to cue the recall of a studied word, the cue activates the target in an array of related words that distract and reduce the probability of the target's selection. The activation of the semantic network produces priming benefits during encoding, and search costs during retrieval. In extralist cuing, recall is a negative function of cue-to-distractor strength, and a positive function of neighborhood density, cue-to-target strength, and target-to-cue strength. We show how these four measures derived from the network can be combined and used to predict memory performance. These measures play different roles in different tasks, indicating that the contribution of the semantic network varies with the context provided by the task. Finally, we evaluate spreading-activation and quantum-like entanglement explanations for the priming effects produced by neighborhood density.

  5. Young and Old Pavlovian Fear Memories Can Be Modified with Extinction Training during Reconsolidation in Humans

    Science.gov (United States)

    Steinfurth, Elisa C. K.; Kanen, Jonathan W.; Raio, Candace M.; Clem, Roger L.; Huganir, Richard L.; Phelps, Elizabeth A.

    2014-01-01

    Extinction training during reconsolidation has been shown to persistently diminish conditioned fear responses across species. We investigated in humans if older fear memories can benefit similarly. Using a Pavlovian fear conditioning paradigm we compared standard extinction and extinction after memory reactivation 1 d or 7 d following acquisition.…

  6. An electroconvulsive therapy procedure impairs reconsolidation of episodic memories in humans

    NARCIS (Netherlands)

    Kroes, M.C.W.; Tendolkar, I.; Wingen, G.A. van; Waarde, J.A. van; Strange, B.A.; Fernandez, G.S.E.

    2014-01-01

    Despite accumulating evidence for a reconsolidation process in animals, support in humans, especially for episodic memory, is limited. Using a within-subjects manipulation, we found that a single application of electroconvulsive therapy following memory reactivation in patients with unipolar depress

  7. Spontaneous Recovery of Human Spatial Memory in a Virtual Water Maze

    Science.gov (United States)

    Luna, David; Martínez, Héctor

    2015-01-01

    The occurrence of spontaneous recovery in human spatial memory was assessed using a virtual environment. In Experiment 1, spatial memory was established by training participants to locate a hidden platform in a virtual water maze using a set of four distal landmarks. In Experiment 2, after learning about the location of a hidden platform, the…

  8. Young and Old Pavlovian Fear Memories Can Be Modified with Extinction Training during Reconsolidation in Humans

    Science.gov (United States)

    Steinfurth, Elisa C. K.; Kanen, Jonathan W.; Raio, Candace M.; Clem, Roger L.; Huganir, Richard L.; Phelps, Elizabeth A.

    2014-01-01

    Extinction training during reconsolidation has been shown to persistently diminish conditioned fear responses across species. We investigated in humans if older fear memories can benefit similarly. Using a Pavlovian fear conditioning paradigm we compared standard extinction and extinction after memory reactivation 1 d or 7 d following acquisition.…

  9. A Model of Genetic Variation in Human Social Networks

    CERN Document Server

    Fowler, James H; Christakis, Nicholas A

    2008-01-01

    Social networks influence the evolution of cooperation and they exhibit strikingly systematic patterns across a wide range of human contexts. Both of these facts suggest that variation in the topological attributes of human social networks might have a genetic basis. While genetic variation accounts for a significant portion of the variation in many complex social behaviors, the heritability of egocentric social network attributes is unknown. Here we show that three of these attributes (in-degree, transitivity, and centrality) are heritable. We then develop a "mirror network" method to test extant network models and show that none accounts for observed genetic variation in human social networks. We propose an alternative "attract and introduce" model that generates significant heritability as well as other important network features, and we show that this model with two simple forms of heterogeneity is well suited to the modeling of real social networks in humans. These results suggest that natural selection ...

  10. Human declarative memory formation: segregating rhinal and hippocampal contributions.

    NARCIS (Netherlands)

    Fernandez, G.S.E.; Klaver, P.; Fell, J.; Grunwald, T.; Elger, C.E.

    2002-01-01

    The medial temporal lobe (MTL) is the core structure of the declarative memory system, but which specific operation is performed by anatomically defined MTL substructures? One hypothesis proposes that the hippocampus carries out an exclusively mnemonic operation during declarative memory formation

  11. Development of the declarative memory system in the human brain.

    Science.gov (United States)

    Ofen, Noa; Kao, Yun-Ching; Sokol-Hessner, Peter; Kim, Heesoo; Whitfield-Gabrieli, Susan; Gabrieli, John D E

    2007-09-01

    Brain regions that are involved in memory formation, particularly medial temporal lobe (MTL) structures and lateral prefrontal cortex (PFC), have been identified in adults, but not in children. We investigated the development of brain regions involved in memory formation in 49 children and adults (ages 8-24), who studied scenes during functional magnetic resonance imaging. Recognition memory for vividly recollected scenes improved with age. There was greater activation for subsequently remembered scenes than there was for forgotten scenes in MTL and PFC regions. These activations increased with age in specific PFC, but not in MTL, regions. PFC, but not MTL, activations correlated with developmental gains in memory for details of experiences. Voxel-based morphometry indicated that gray matter volume in PFC, but not in MTL, regions reduced with age. These results suggest that PFC regions that are important for the formation of detailed memories for experiences have a prolonged maturational trajectory.

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

    Science.gov (United States)

    Manhart, Michael; Kion-Crosby, Willow; Morozov, Alexandre V

    2015-12-01

    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.

  13. Human Navigational Performance in a Complex Network with Progressive Disruptions

    CERN Document Server

    Ramesh, Amitash; Iyengar, Sudarshan; Sekhar, Vinod

    2012-01-01

    The current paper is an investigation towards understanding the navigational performance of humans on a network when the "landmark" nodes are blocked. We observe that humans learn to cope up, despite the continued introduction of blockages in the network. The experiment proposed involves the task of navigating on a word network based on a puzzle called the wordmorph. We introduce blockages in the network and report an incremental improvement in performance with respect to time. We explain this phenomenon by analyzing the evolution of the knowledge in the human participants of the underlying network as more and more landmarks are removed. We hypothesize that humans learn the bare essentials to navigate unless we introduce blockages in the network which would whence enforce upon them the need to explore newer ways of navigating. We draw a parallel to human problem solving and postulate that obstacles are catalysts for humans to innovate techniques to solve a restricted variant of a familiar problem.

  14. Face-name association task reveals memory networks in patients with left and right hippocampal sclerosis.

    Science.gov (United States)

    Klamer, Silke; Milian, Monika; Erb, Michael; Rona, Sabine; Lerche, Holger; Ethofer, Thomas

    2017-01-01

    We aimed to identify reorganization processes of episodic memory networks in patients with left and right temporal lobe epilepsy (TLE) due to hippocampal sclerosis as well as their relations to neuropsychological memory performance. We investigated 28 healthy subjects, 12 patients with left TLE (LTLE) and 9 patients with right TLE (RTLE) with hippocampal sclerosis by means of functional magnetic resonance imaging (fMRI) using a face-name association task, which combines verbal and non-verbal memory functions. Regions-of-interest (ROIs) were defined based on the group results of the healthy subjects. In each ROI, fMRI activations were compared across groups and correlated with verbal and non-verbal memory scores. The face-name association task yielded activations in bilateral hippocampus (HC), left inferior frontal gyrus (IFG), left superior frontal gyrus (SFG), left superior temporal gyrus, bilateral angular gyrus (AG), bilateral medial prefrontal cortex and right anterior temporal lobe (ATL). LTLE patients demonstrated significantly less activation in the left HC and left SFG, whereas RTLE patients showed significantly less activation in the HC bilaterally, the left SFG and right AG. Verbal memory scores correlated with activations in the left and right HC, left SFG and right ATL and non-verbal memory scores with fMRI activations in the left and right HC and left SFG. The face-name association task can be employed to examine functional alterations of hippocampal activation during encoding of both verbal and non-verbal material in one fMRI paradigm. Further, the left SFG seems to be a convergence region for encoding of verbal and non-verbal material.

  15. Cortisol variation in humans affects memory for emotionally laden and neutral information.

    Science.gov (United States)

    Abercrombie, Heather C; Kalin, Ned H; Thurow, Marchell E; Rosenkranz, Melissa A; Davidson, Richard J

    2003-06-01

    In a test of the effects of cortisol on emotional memory, 90 men were orally administered placebo or 20 or 40 mg cortisol and presented with emotionally arousing and neutral stimuli. On memory tests administered within 1 hr of stimulus presentation, cortisol elevations caused a reduction in the number of errors committed on free-recall tasks. Two evenings later, when cortisol levels were no longer manipulated, inverted-U quadratic trends were found for recognition memory tasks, reflecting memory facilitation in the 20-mg group for both negative and neutral information. Results suggest that the effects of cortisol on memory do not differ substantially for emotional and neutral information. The study provides evidence of beneficial effects of acute cortisol elevations on explicit memory in humans.

  16. New learning following reactivation in the human brain: targeting emotional memories through rapid serial visual presentation.

    Science.gov (United States)

    Wirkner, Janine; Löw, Andreas; Hamm, Alfons O; Weymar, Mathias

    2015-03-01

    Once reactivated, previously consolidated memories destabilize and have to be reconsolidated to persist, a process that might be altered non-invasively by interfering learning immediately after reactivation. Here, we investigated the influence of interference on brain correlates of reactivated episodic memories for emotional and neutral scenes using event-related potentials (ERPs). To selectively target emotional memories we applied a new reactivation method: rapid serial visual presentation (RSVP). RSVP leads to enhanced implicit processing (pop out) of the most salient memories making them vulnerable to disruption. In line, interference after reactivation of previously encoded pictures disrupted recollection particularly for emotional events. Furthermore, memory impairments were reflected in a reduced centro-parietal ERP old/new difference during retrieval of emotional pictures. These results provide neural evidence that emotional episodic memories in humans can be selectively altered through behavioral interference after reactivation, a finding with further clinical implications for the treatment of anxiety disorders. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. No Acute Effects of Choline Bitartrate Food Supplements on Memory in Healthy, Young, Human Adults.

    Science.gov (United States)

    Lippelt, D P; van der Kint, S; van Herk, K; Naber, M

    2016-01-01

    Choline is a dietary component and precursor of acetylcholine, a crucial neurotransmitter for memory-related brain functions. In two double-blind, placebo-controlled cross-over experiments, we investigated whether the food supplement choline bitartrate improved declarative memory and working memory in healthy, young students one to two hours after supplementation. In experiment 1, 28 participants performed a visuospatial working memory task. In experiment 2, 26 participants performed a declarative picture memorization task. In experiment 3, 40 participants performed a verbal working memory task in addition to the visuospatial working memory and declarative picture task. All tasks were conducted approximately 60 minutes after the ingestion of 2.0-2.5g of either choline bitartrate or placebo. We found that choline did not significantly enhance memory performance during any of the tasks. The null hypothesis that choline does not improve memory performance as compared to placebo was strongly supported by Bayesian statistics. These results are in contrast with animal studies suggesting that choline supplementation boosts memory performance and learning. We conclude that choline likely has no acute effects on cholinergic memory functions in healthy human participants.

  18. No Acute Effects of Choline Bitartrate Food Supplements on Memory in Healthy, Young, Human Adults.

    Directory of Open Access Journals (Sweden)

    D P Lippelt

    Full Text Available Choline is a dietary component and precursor of acetylcholine, a crucial neurotransmitter for memory-related brain functions. In two double-blind, placebo-controlled cross-over experiments, we investigated whether the food supplement choline bitartrate improved declarative memory and working memory in healthy, young students one to two hours after supplementation. In experiment 1, 28 participants performed a visuospatial working memory task. In experiment 2, 26 participants performed a declarative picture memorization task. In experiment 3, 40 participants performed a verbal working memory task in addition to the visuospatial working memory and declarative picture task. All tasks were conducted approximately 60 minutes after the ingestion of 2.0-2.5g of either choline bitartrate or placebo. We found that choline did not significantly enhance memory performance during any of the tasks. The null hypothesis that choline does not improve memory performance as compared to placebo was strongly supported by Bayesian statistics. These results are in contrast with animal studies suggesting that choline supplementation boosts memory performance and learning. We conclude that choline likely has no acute effects on cholinergic memory functions in healthy human participants.

  19. Broadband criticality of human brain network synchronization.

    Directory of Open Access Journals (Sweden)

    Manfred G Kitzbichler

    2009-03-01

    Full Text Available Self-organized criticality is an attractive model for human brain dynamics, but there has been little direct evidence for its existence in large-scale systems measured by neuroimaging. In general, critical systems are associated with fractal or power law scaling, long-range correlations in space and time, and rapid reconfiguration in response to external inputs. Here, we consider two measures of phase synchronization: the phase-lock interval, or duration of coupling between a pair of (neurophysiological processes, and the lability of global synchronization of a (brain functional network. Using computational simulations of two mechanistically distinct systems displaying complex dynamics, the Ising model and the Kuramoto model, we show that both synchronization metrics have power law probability distributions specifically when these systems are in a critical state. We then demonstrate power law scaling of both pairwise and global synchronization metrics in functional MRI and magnetoencephalographic data recorded from normal volunteers under resting conditions. These results strongly suggest that human brain functional systems exist in an endogenous state of dynamical criticality, characterized by a greater than random probability of both prolonged periods of phase-locking and occurrence of large rapid changes in the state of global synchronization, analogous to the neuronal "avalanches" previously described in cellular systems. Moreover, evidence for critical dynamics was identified consistently in neurophysiological systems operating at frequency intervals ranging from 0.05-0.11 to 62.5-125 Hz, confirming that criticality is a property of human brain functional network organization at all frequency intervals in the brain's physiological bandwidth.

  20. Dynamical Associative Memory: The Properties of the New Weighted Chaotic Adachi Neural Network

    Science.gov (United States)

    Luo, Guangchun; Ren, Jinsheng; Qin, Ke

    A new training algorithm for the chaotic Adachi Neural Network (AdNN) is investigated. The classical training algorithm for the AdNN and it's variants is usually a “one-shot” learning, for example, the Outer Product Rule (OPR) is the most used. Although the OPR is effective for conventional neural networks, its effectiveness and adequateness for Chaotic Neural Networks (CNNs) have not been discussed formally. As a complementary and tentative work in this field, we modified the AdNN's weights by enforcing an unsupervised Hebbian rule. Experimental analysis shows that the new weighted AdNN yields even stronger dynamical associative memory and pattern recognition phenomena for different settings than the primitive AdNN.

  1. Maps of sparse Markov chains efficiently reveal community structure in network flows with memory

    CERN Document Server

    Persson, Christian; Edler, Daniel; Rosvall, Martin

    2016-01-01

    To better understand the flows of ideas or information through social and biological systems, researchers develop maps that reveal important patterns in network flows. In practice, network flow models have implied memoryless first-order Markov chains, but recently researchers have introduced higher-order Markov chain models with memory to capture patterns in multi-step pathways. Higher-order models are particularly important for effectively revealing actual, overlapping community structure, but higher-order Markov chain models suffer from the curse of dimensionality: their vast parameter spaces require exponentially increasing data to avoid overfitting and therefore make mapping inefficient already for moderate-sized systems. To overcome this problem, we introduce an efficient cross-validated mapping approach based on network flows modeled by sparse Markov chains. To illustrate our approach, we present a map of citation flows in science with research fields that overlap in multidisciplinary journals. Compared...

  2. Same task, different strategies: how brain networks can be influenced by memory strategy.

    Science.gov (United States)

    Sanfratello, Lori; Caprihan, Arvind; Stephen, Julia M; Knoefel, Janice E; Adair, John C; Qualls, Clifford; Lundy, S Laura; Aine, Cheryl J

    2014-10-01

    Previous functional neuroimaging studies demonstrated that different neural networks underlie different types of cognitive processing by engaging participants in particular tasks, such as verbal or spatial working memory (WM) tasks. However, we report here that even when a WM task is defined as verbal or spatial, different types of memory strategies may be used to complete it, with concomitant variations in brain activity. We developed a questionnaire to characterize the type of strategy used by individual members in a group of 28 young healthy participants (18-25 years) during a spatial WM task. A cluster analysis was performed to differentiate groups. We acquired functional magnetoencephalography and structural diffusion tensor imaging measures to characterize the brain networks associated with the use of different strategies. We found two types of strategies were used during the spatial WM task, a visuospatial and a verbal strategy, and brain regions and time courses of activation differed between participants who used each. Task performance also varied by type of strategy used with verbal strategies showing an advantage. In addition, performance on neuropsychological tests (indices from Wechsler Adult Intelligence Scale-IV, Rey Complex Figure Test) correlated significantly with fractional anisotropy measures for the visuospatial strategy group in white matter tracts implicated in other WM and attention studies. We conclude that differences in memory strategy can have a pronounced effect on the locations and timing of brain activation and that these differences need further investigation as a possible confounding factor for studies using group averaging as a means for summarizing results.

  3. Changes in whole-brain functional networks and memory performance in aging.

    Science.gov (United States)

    Sala-Llonch, Roser; Junqué, Carme; Arenaza-Urquijo, Eider M; Vidal-Piñeiro, Dídac; Valls-Pedret, Cinta; Palacios, Eva M; Domènech, Sara; Salvà, Antoni; Bargalló, Nuria; Bartrés-Faz, David

    2014-10-01

    We used resting-functional magnetic resonance imaging data from 98 healthy older adults to analyze how local and global measures of functional brain connectivity are affected by age, and whether they are related to differences in memory performance. Whole-brain networks were created individually by parcellating the brain into 90 cerebral regions and obtaining pairwise connectivity. First, we studied age-associations in interregional connectivity and their relationship with the length of the connections. Aging was associated with less connectivity in the long-range connections of fronto-parietal and fronto-occipital systems and with higher connectivity of the short-range connections within frontal, parietal, and occipital lobes. We also used the graph theory to measure functional integration and segregation. The pattern of the overall age-related correlations presented positive correlations of average minimum path length (r = 0.380, p = 0.008) and of global clustering coefficients (r = 0.454, p < 0.001), leading to less integrated and more segregated global networks. Main correlations in clustering coefficients were located in the frontal and parietal lobes. Higher clustering coefficients of some areas were related to lower performance in verbal and visual memory functions. In conclusion, we found that older participants showed lower connectivity of long-range connections together with higher functional segregation of these same connections, which appeared to indicate a more local clustering of information processing. Higher local clustering in older participants was negatively related to memory performance.

  4. Memory loss in Alzheimer's disease.

    Science.gov (United States)

    Jahn, Holger

    2013-12-01

    Loss of memory is among the first symptoms reported by patients suffering from Alzheimer's disease (AD) and by their caretakers. Working memory and long-term declarative memory are affected early during the course of the disease. The individual pattern of impaired memory functions correlates with parameters of structural or functional brain integrity. AD pathology interferes with the formation of memories from the molecular level to the framework of neural networks. The investigation of AD memory loss helps to identify the involved neural structures, such as the default mode network, the influence of epigenetic and genetic factors, such as ApoE4 status, and evolutionary aspects of human cognition. Clinically, the analysis of memory assists the definition of AD subtypes, disease grading, and prognostic predictions. Despite new AD criteria that allow the earlier diagnosis of the disease by inclusion of biomarkers derived from cerebrospinal fluid or hippocampal volume analysis, neuropsychological testing remains at the core of AD diagnosis.

  5. An associative capacitive network based on nanoscale complementary resistive switches for memory-intensive computing.

    Science.gov (United States)

    Kavehei, Omid; Linn, Eike; Nielen, Lutz; Tappertzhofen, Stefan; Skafidas, Efstratios; Valov, Ilia; Waser, Rainer

    2013-06-07

    We report on the implementation of an Associative Capacitive Network (ACN) based on the nondestructive capacitive readout of two Complementary Resistive Switches (2-CRSs). ACNs are capable of performing a fully parallel search for Hamming distances (i.e. similarity) between input and stored templates. Unlike conventional associative memories where charge retention is a key function and hence, they require frequent refresh cycles, in ACNs, information is retained in a nonvolatile resistive state and normal tasks are carried out through capacitive coupling between input and output nodes. Each device consists of two CRS cells and no selective element is needed, therefore, CMOS circuitry is only required in the periphery, for addressing and read-out. Highly parallel processing, nonvolatility, wide interconnectivity and low-energy consumption are significant advantages of ACNs over conventional and emerging associative memories. These characteristics make ACNs one of the promising candidates for applications in memory-intensive and cognitive computing, switches and routers as binary and ternary Content Addressable Memories (CAMs) and intelligent data processing.

  6. Strong Memory in Time Series of Human Magnetoencephalograms Can Identify Photosensitive Epilepsy

    CERN Document Server

    Yulmetyev, R M; Hänggi, P; Khusaenova, E V; Shimojo, S; Yulmetyeva, D G

    2006-01-01

    o discuss the salient role of the statistical memory effects in the human brain functioning we have analyzed a set of stochastic memory quantifiers that reflects the dynamical characteristics of neuromagnetic brain responses to a flickering stimulus of different color combinations from a group of control subjects which is contrasted with those from a patient with photosensitive epilepsy (PSE). We have discovered the emergence of strong memory and the accompanying transition to a regular and robust regime of chaotic behavior of the signals in the separate areas for a patient with PSE. This finding most likely identifies the regions of the location the protective mechanism in a human organism against occurrence of PSE.

  7. Effects of clorazepate, diazepam, lorazepam, and placebo on human memory.

    Science.gov (United States)

    Healey, M; Pickens, R; Meisch, R; McKenna, T

    1983-12-01

    Healthy adults (N = 10) were given oral doses of lorazepam (1 and 2 mg), diazepam (5 and 10 mg), clorazepate (7.5 and 15 mg), or placebo and tested 30, 60, 90, and 120 minutes later on a word-recall memory task. All subjects received each drug dose once and placebo twice in randomized order at weekly intervals. Testing was double-blind. Lorazepam was found to have a significantly greater effect on memory than placebo. Diazepam and clorazepate did not differ significantly from placebo in their effect on word recall. High doses of lorazepam produced more pronounced memory effects than did low doses; neither diazepam nor clorazepate was found to exert a dose-related effect on memory.

  8. A generalized voter model with time-decaying memory on a multilayer network

    CERN Document Server

    Zhong, Li-Xin; Chen, Rong-Da; Zhong, Chen-Yang; Qiu, Tian; Shi, Yong-Dong; Wang, Li-Liang

    2016-01-01

    By incorporating a multilayer network and time-decaying memory into the original voter model, the coupled effects of spatial and temporal cumulation of peer pressure on consensus are investigated. Heterogeneity in peer pressure and time-decaying mechanism are both found to be detrimental to consensus. The transition points, below which a consensus can always be reached and above which two opposed opinions are more likely to coexist, are found. A mean-field analysis indicates that the phase transitions in the present model are governed by the cumulative influence of peer pressure and the updating threshold. A functional relation between the consensus threshold and the decaying rate of the influence of peer pressure is found. As to the time to reach a consensus, it is governed by the coupling of the memory length and the decaying rate. An intermediate decaying rate may lead to much lower time to reach a consensus.

  9. A generalized voter model with time-decaying memory on a multilayer network

    Science.gov (United States)

    Zhong, Li-Xin; Xu, Wen-Juan; Chen, Rong-Da; Zhong, Chen-Yang; Qiu, Tian; Shi, Yong-Dong; Wang, Li-Liang

    2016-09-01

    By incorporating a multilayer network and time-decaying memory into the original voter model, we investigate the coupled effects of spatial and temporal accumulation of peer pressure on the consensus. Heterogeneity in peer pressure and the time-decaying mechanism are both shown to be detrimental to the consensus. We find the transition points below which a consensus can always be reached and above which two opposed opinions are more likely to coexist. Our mean-field analysis indicates that the phase transitions in the present model are governed by the cumulative influence of peer pressure and the updating threshold. We find a functional relation between the consensus threshold and the decay rate of the influence of peer is found. As to the pressure. The time required to reach a consensus is governed by the coupling of the memory length and the decay rate. An intermediate decay rate may greatly reduce the time required to reach a consensus.

  10. Variation in individuals' semantic networks for common knowledge is associated with false memory.

    Science.gov (United States)

    Stevens-Adams, Susan M; Goldsmith, Timothy E; Butler, Karin M

    2012-01-01

    Three experiments assessed the relationships between false memories of words and their degree of connectedness within individual semantic networks. In the first two experiments, participants studied associated word lists (e.g., hot, winter, ice), completed a recognition test that included related nonstudied words (e.g., cold, snow), and then rated the semantic relatedness of all word pairs including studied and nonstudied words. In the third experiment, the task order was reversed; participants completed pairwise ratings and then, two weeks later, completed the false memory task. The relatedness ratings were analysed using the Pathfinder scaling algorithm. In all experiments, items that an individual falsely recognized had higher semantic Pathfinder node densities than those items correctly rejected.

  11. Interaction of multiple networks modulated by the working memory training based on real-time fMRI

    Science.gov (United States)

    Shen, Jiahui; Zhang, Gaoyan; Zhu, Chaozhe; Yao, Li; Zhao, Xiaojie

    2015-03-01

    Neuroimaging studies of working memory training have identified the alteration of brain activity as well as the regional interactions within the functional networks such as central executive network (CEN) and default mode network (DMN). However, how the interaction within and between these multiple networks is modulated by the training remains unclear. In this paper, we examined the interaction of three training-induced brain networks during working memory training based on real-time functional magnetic resonance imaging (rtfMRI). Thirty subjects assigned to the experimental and control group respectively participated in two times training separated by seven days. Three networks including silence network (SN), CEN and DMN were identified by the training data with the calculated function connections within each network. Structural equation modeling (SEM) approach was used to construct the directional connectivity patterns. The results showed that the causal influences from the percent signal changes of target ROI to the SN were positively changed in both two groups, as well as the causal influence from the SN to CEN was positively changed in experimental group but negatively changed in control group from the SN to DMN. Further correlation analysis of the changes in each network with the behavioral improvements showed that the changes in SN were stronger positively correlated with the behavioral improvement of letter memory task. These findings indicated that the SN was not only a switch between the target ROI and the other networks in the feedback training but also an essential factor to the behavioral improvement.

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

    Science.gov (United States)

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

    2016-11-01

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

  13. Fast entrainment of human electroencephalogram to a theta-band photic flicker during successful memory encoding

    Directory of Open Access Journals (Sweden)

    Naoyuki eSato

    2013-05-01

    Full Text Available Theta band power (4-8Hz in the scalp electroencephalogram (EEG is thought to be stronger during memory encoding for subsequently remembered items than for forgotten items. According to simultaneous EEG-functional magnetic resonance imaging (fMRI measurements, the memory-dependent EEG theta is associated with multiple regions of the brain. This suggests that the multiple regions cooperate with EEG theta synchronization during successful memory encoding. However, a question still remains: What kind of neural dynamic organizes such a memory-dependent global network? In this study, the modulation of the EEG theta entrainment property during successful encoding was hypothesized to lead to EEG theta synchronization among a distributed network. Then, a transient response of EEG theta to a theta-band photic flicker with a short duration was evaluated during memory encoding. In the results, flicker-induced EEG power increased and decreased with a time constant of several hundred milliseconds following the onset and the offset of the flicker, respectively. Importantly, the offset response of EEG power was found to be significantly decreased during successful encoding. Moreover, the offset response of the phase locking index was also found to associate with memory performance. According to computational simulations, the results are interpreted as a smaller time constant (i.e., faster response of a driven harmonic oscillator rather than a change in the spontaneous oscillatory input. This suggests that the fast response of EEG theta forms a global EEG theta network among memory-related regions during successful encoding, and it contributes to a flexible formation of the network along the time course.

  14. Same task, different strategies: How brain networks can be influenced by memory strategy

    Science.gov (United States)

    Sanfratello, Lori; Caprihan, Arvind; Stephen, Julia M.; Knoefel, Janice E.; Adair, John C.; Qualls, Clifford; Lundy, S. Laura; Aine, Cheryl J.

    2015-01-01

    Previous functional neuroimaging studies demonstrated that different neural networks underlie different types of cognitive processing by engaging participants in particular tasks, such as verbal or spatial working memory (WM) tasks. However, we report here that even when a working memory task is defined as verbal or spatial, different types of memory strategies may be employed to complete it, with concomitant variations in brain activity. We developed a questionnaire to characterize the type of strategy used by individual members in a group of 28 young healthy participants (18–25 years) during a spatial WM task. A cluster analysis was performed to differentiate groups. We acquired functional magnetoencephalography (MEG) and structural diffusion tensor imaging (DTI) measures to characterize the brain networks associated with the use of different strategies. We found two types of strategies were utilized during the spatial WM task, a visuospatial and a verbal strategy, and brain regions and timecourses of activation differed between participants who used each. Task performance also varied by type of strategy used, with verbal strategies showing an advantage. In addition, performance on neuropsychological tests (indices from WAIS-IV, REY-D Complex Figure) correlated significantly with fractional anisotropy (FA) measures for the visuospatial strategy group in white matter tracts implicated in other WM/attention studies. We conclude that differences in memory strategy can have a pronounced effect on the locations and timing of brain activation, and that these differences need further investigation as a possible confounding factor for studies using group averaging as a means for summarizing results. PMID:24931401

  15. Working memory in ALS patients: preserved performance but marked changes in underlying neuronal networks.

    Science.gov (United States)

    Zaehle, Tino; Becke, Andreas; Naue, Nicole; Machts, Judith; Abdulla, Susanne; Petri, Susanne; Kollewe, Katja; Dengler, Reinhard; Heinze, Hans-Jochen; Vielhaber, Stefan; Müller, Notger G

    2013-01-01

    Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease which affects the motor system but also other frontal brain regions. In this study we investigated changes in functional neuronal networks including posterior brain regions that are not directly affected by the neurodegenerative process. To this end, we analyzed the contralateral delay activity (CDA), an ERP component considered an online marker of memory storage in posterior cortex, while 23 ALS patients and their controls performed a delayed-matching-to-sample working memory (WM) task. The task required encoding of stimuli in the cued hemifield whilst ignoring stimuli in the other hemifield. Despite their unimpaired behavioral performance patients displayed several changes in the neuronal markers of the memory processes. Their CDA amplitude was smaller; it showed less load-dependent modulation and lacked the reduction observed when controls performed the same task three months later. The smaller CDA in the patients could be attributed to more ipsilateral cortical activity which may indicate that ALS patients unnecessarily processed the irrelevant stimuli as well. The latter is presumably related to deterioration of the frontal cortex in the patient group which was indicated by slight deficits in tests of their executive functions that increased over time. The frontal pathology presumably affected their top-down control of memory storage in remote regions in the posterior brain. In sum, the present results demonstrate functional changes in neuronal networks, i.e. neuroplasticity, in ALS that go well beyond the known structural changes. They also show that at least in WM tasks, in which strategic top-down control demands are relatively low, the frontal deficit can be compensated for by intact low level processes in posterior brain regions.

  16. Acute stress impairs the retrieval of extinction memory in humans.

    Science.gov (United States)

    Raio, Candace M; Brignoni-Perez, Edith; Goldman, Rachel; Phelps, Elizabeth A

    2014-07-01

    Extinction training is a form of inhibitory learning that allows an organism to associate a previously aversive cue with a new, safe outcome. Extinction does not erase a fear association, but instead creates a competing association that may or may not be retrieved when a cue is subsequently encountered. Characterizing the conditions under which extinction learning is expressed is important to enhancing the treatment of anxiety disorders that rely on extinction-based exposure therapy as a primary treatment technique. The ventromedial prefrontal cortex, which plays a critical role in the expression of extinction memory, has been shown to be functionally impaired after stress exposure. Further, recent work in rodents has demonstrated that exposure to stress leads to deficits in extinction retrieval, although this has yet to be tested in humans. To explore how stress might influence extinction retrieval in humans, participants underwent a differential aversive learning paradigm, in which one image was probabilistically paired with an aversive shock while the other image denoted safety. Extinction training directly followed, at which point reinforcement was omitted. A day later, participants returned to the lab and either completed an acute stress manipulation (i.e., cold pressor), or a control task, before undergoing an extinction retrieval test. Skin conductance responses and salivary cortisol concentrations were measured throughout each session as indices of fear arousal and neuroendocrine stress response, respectively. The efficacy of our stress induction was established by observing significant increases in cortisol for the stress condition only. We examined extinction retrieval by comparing conditioned responses during the last trial of extinction (day 1) with that of the first trial of re-extinction (day 2). Groups did not differ on initial fear acquisition or extinction, however, a day later participants in the stress group (n=27) demonstrated significantly

  17. Using Long-Short-Term-Memory Recurrent Neural Networks to Predict Aviation Engine Vibrations

    Science.gov (United States)

    ElSaid, AbdElRahman Ahmed

    This thesis examines building viable Recurrent Neural Networks (RNN) using Long Short Term Memory (LSTM) neurons to predict aircraft engine vibrations. The different networks are trained on a large database of flight data records obtained from an airline containing flights that suffered from excessive vibration. RNNs can provide a more generalizable and robust method for prediction over analytical calculations of engine vibration, as analytical calculations must be solved iteratively based on specific empirical engine parameters, and this database contains multiple types of engines. Further, LSTM RNNs provide a "memory" of the contribution of previous time series data which can further improve predictions of future vibration values. LSTM RNNs were used over traditional RNNs, as those suffer from vanishing/exploding gradients when trained with back propagation. The study managed to predict vibration values for 1, 5, 10, and 20 seconds in the future, with 2.84% 3.3%, 5.51% and 10.19% mean absolute error, respectively. These neural networks provide a promising means for the future development of warning systems so that suitable actions can be taken before the occurrence of excess vibration to avoid unfavorable situations during flight.

  18. Scarcity of autoreactive human blood IgA(+) memory B cells.

    Science.gov (United States)

    Prigent, Julie; Lorin, Valérie; Kök, Ayrin; Hieu, Thierry; Bourgeau, Salomé; Mouquet, Hugo

    2016-10-01

    Class-switched memory B cells are key components of the "reactive" humoral immunity, which ensures a fast and massive secretion of high-affinity antigen-specific antibodies upon antigenic challenge. In humans, IgA class-switched (IgA(+) ) memory B cells and IgA antibodies are abundant in the blood. Although circulating IgA(+) memory B cells and their corresponding secreted immunoglobulins likely possess major protective and/or regulatory immune roles, little is known about their specificity and function. Here, we show that IgA(+) and IgG(+) memory B-cell antibodies cloned from the same healthy humans share common immunoglobulin gene features. IgA and IgG memory antibodies have comparable lack of reactivity to vaccines, common mucosa-tropic viruses and commensal bacteria. However, the IgA(+) memory B-cell compartment contains fewer polyreactive clones and importantly, only rare self-reactive clones compared to IgG(+) memory B cells. Self-reactivity of IgAs is acquired following B-cell affinity maturation but not antibody class switching. Together, our data suggest the existence of different regulatory mechanisms for removing autoreactive clones from the IgG(+) and IgA(+) memory B-cell repertoires, and/or different maturation pathways potentially reflecting the distinct nature and localization of the cognate antigens recognized by individual B-cell populations.

  19. BAIAP2 is related to emotional modulation of human memory strength.

    Science.gov (United States)

    Luksys, Gediminas; Ackermann, Sandra; Coynel, David; Fastenrath, Matthias; Gschwind, Leo; Heck, Angela; Rasch, Bjoern; Spalek, Klara; Vogler, Christian; Papassotiropoulos, Andreas; de Quervain, Dominique

    2014-01-01

    Memory performance is the result of many distinct mental processes, such as memory encoding, forgetting, and modulation of memory strength by emotional arousal. These processes, which are subserved by partly distinct molecular profiles, are not always amenable to direct observation. Therefore, computational models can be used to make inferences about specific mental processes and to study their genetic underpinnings. Here we combined a computational model-based analysis of memory-related processes with high density genetic information derived from a genome-wide study in healthy young adults. After identifying the best-fitting model for a verbal memory task and estimating the best-fitting individual cognitive parameters, we found a common variant in the gene encoding the brain-specific angiogenesis inhibitor 1-associated protein 2 (BAIAP2) that was related to the model parameter reflecting modulation of verbal memory strength by negative valence. We also observed an association between the same genetic variant and a similar emotional modulation phenotype in a different population performing a picture memory task. Furthermore, using functional neuroimaging we found robust genotype-dependent differences in activity of the parahippocampal cortex that were specifically related to successful memory encoding of negative versus neutral information. Finally, we analyzed cortical gene expression data of 193 deceased subjects and detected significant BAIAP2 genotype-dependent differences in BAIAP2 mRNA levels. Our findings suggest that model-based dissociation of specific cognitive parameters can improve the understanding of genetic underpinnings of human learning and memory.

  20. Stress and the engagement of multiple memory systems: integration of animal and human studies.

    Science.gov (United States)

    Schwabe, Lars

    2013-11-01

    Learning and memory can be controlled by distinct memory systems. How these systems are coordinated to optimize learning and behavior has long been unclear. Accumulating evidence indicates that stress may modulate the engagement of multiple memory systems. In particular, rodent and human studies demonstrate that stress facilitates dorsal striatum-dependent "habit" memory, at the expense of hippocampus-dependent "cognitive" memory. Based on these data, a model is proposed which states that the impact of stress on the relative use of multiple memory systems is due to (i) differential effects of hormones and neurotransmitters that are released during stressful events on hippocampal and dorsal striatal memory systems, thus changing the relative strength of and the interactions between these systems, and (ii) a modulatory influence of the amygdala which biases learning toward dorsal striatum-based memory after stress. This shift to habit memory after stress can be adaptive with respect to current performance but might contribute to psychopathology in vulnerable individuals. Copyright © 2013 Wiley Periodicals, Inc.

  1. BAIAP2 is related to emotional modulation of human memory strength.

    Directory of Open Access Journals (Sweden)

    Gediminas Luksys

    Full Text Available Memory performance is the result of many distinct mental processes, such as memory encoding, forgetting, and modulation of memory strength by emotional arousal. These processes, which are subserved by partly distinct molecular profiles, are not always amenable to direct observation. Therefore, computational models can be used to make inferences about specific mental processes and to study their genetic underpinnings. Here we combined a computational model-based analysis of memory-related processes with high density genetic information derived from a genome-wide study in healthy young adults. After identifying the best-fitting model for a verbal memory task and estimating the best-fitting individual cognitive parameters, we found a common variant in the gene encoding the brain-specific angiogenesis inhibitor 1-associated protein 2 (BAIAP2 that was related to the model parameter reflecting modulation of verbal memory strength by negative valence. We also observed an association between the same genetic variant and a similar emotional modulation phenotype in a different population performing a picture memory task. Furthermore, using functional neuroimaging we found robust genotype-dependent differences in activity of the parahippocampal cortex that were specifically related to successful memory encoding of negative versus neutral information. Finally, we analyzed cortical gene expression data of 193 deceased subjects and detected significant BAIAP2 genotype-dependent differences in BAIAP2 mRNA levels. Our findings suggest that model-based dissociation of specific cognitive parameters can improve the understanding of genetic underpinnings of human learning and memory.

  2. Some surprising findings on the involvement of the parietal lobe in human memory.

    Science.gov (United States)

    Olson, Ingrid R; Berryhill, Marian

    2009-02-01

    The posterior parietal lobe is known to play some role in a far-flung list of mental processes: linking vision to action (saccadic eye movements, reaching, grasping), attending to visual space, numerical calculation, and mental rotation. Here, we review findings from humans and monkeys that illuminate an untraditional function of this region: memory. Our review draws on neuroimaging findings that have repeatedly identified parietal lobe activations associated with short-term or working memory and episodic memory. We also discuss recent neuropsychological findings showing that individuals with parietal lobe damage exhibit both working memory and long-term memory deficits. These deficits are not ubiquitous; they are only evident under certain retrieval demands. Our review elaborates on these findings and evaluates various theories about the mechanistic role of the posterior parietal lobe in memory. The available data point towards the conclusion that the posterior parietal lobe plays an important role in memory retrieval irrespective of elapsed time. However, the available data do not support simple dichotomies such as recall versus recognition, working versus long-term memory. We conclude by formalizing several open questions that are intended to encourage future research in this rapidly developing area of memory research.

  3. Neural networks for perception human and machine perception

    CERN Document Server

    Wechsler, Harry

    1991-01-01

    Neural Networks for Perception, Volume 1: Human and Machine Perception focuses on models for understanding human perception in terms of distributed computation and examples of PDP models for machine perception. This book addresses both theoretical and practical issues related to the feasibility of both explaining human perception and implementing machine perception in terms of neural network models. The book is organized into two parts. The first part focuses on human perception. Topics on network model ofobject recognition in human vision, the self-organization of functional architecture in t

  4. Resting-state coupling between core regions within the central-executive and salience networks contributes to working memory performance

    Directory of Open Access Journals (Sweden)

    Xiaojing eFang

    2016-02-01

    Full Text Available Previous studies investigated the distinct roles played by different cognitive regions and suggested that the patterns of connectivity of these regions are associated with working memory. However, the specific causal mechanism through which the neuronal circuits that involve these brain regions contribute to working memory is still unclear. Here, in a large sample of healthy young adults, we first identified the core working memory regions by linking working memory accuracy to resting-state functional connectivity with the bilateral dorsolateral prefrontal cortex (a principal region in the central-executive network. Then a spectral dynamic causal modeling analysis was performed to quantify the effective connectivity between these regions. Finally, the effective connectivity was correlated with working memory accuracy to characterize the relationship between these connections and working memory performance. We found that the functional connections between the bilateral dorsolateral prefrontal cortex and the dorsal anterior cingulate cortex and between the right dorsolateral prefrontal cortex and the left orbital fronto-insular cortex were correlated with working memory accuracy. Furthermore, the effective connectivity from the dorsal anterior cingulate cortex to the bilateral dorsolateral prefrontal cortex and from the right dorsolateral prefrontal cortex to the left orbital fronto-insular cortex could predict individual differences in working memory. Because the dorsal anterior cingulate cortex and orbital fronto-insular cortex are core regions of the salience network, we inferred that the inter- and causal-connectivity between core regions within the central-executive and salience networks is functionally relevant for working memory performance. In summary, the current study identified the dorsolateral prefrontal cortex-related resting-state effective connectivity underlying working memory and suggests that individual differences in cognitive

  5. Molecular networks and the evolution of human cognitive specializations

    OpenAIRE

    Fontenot, Miles; Konopka, Genevieve

    2014-01-01

    Inroads into elucidating the origins of human cognitive specializations have taken many forms, including genetic, genomic, anatomical, and behavioral assays that typically compare humans to non-human primates. While the integration of all of these approaches is essential for ultimately understanding human cognition, here, we review the usefulness of coexpression network analysis for specifically addressing this question. An increasing number of studies have incorporated coexpression networks ...

  6. Influence of stress on fear memory processes in an aversive differential conditioning paradigm in humans.

    Science.gov (United States)

    Bentz, Dorothée; Michael, Tanja; Wilhelm, Frank H; Hartmann, Francina R; Kunz, Sabrina; von Rohr, Isabelle R Rudolf; de Quervain, Dominique J-F

    2013-07-01

    It is widely assumed that learning and memory processes play an important role in the pathogenesis, expression, maintenance and therapy of anxiety disorders, such as phobias or post-traumatic stress disorder (PTSD). Memory retrieval is involved in symptom expression and maintenance of these disorders, while memory extinction is believed to be the underlying mechanism of behavioral exposure therapy of anxiety disorders. There is abundant evidence that stress and stress hormones can reduce memory retrieval of emotional information, whereas they enhance memory consolidation of extinction training. In this study we aimed at investigating if stress affects these memory processes in a fear conditioning paradigm in healthy human subjects. On day 1, fear memory was acquired through a standard differential fear conditioning procedure. On day 2 (24h after fear acquisition), participants either underwent a stressful cold pressor test (CPT) or a control condition, 20 min before memory retrieval testing and extinction training. Possible prolonged effects of the stress manipulation were investigated on day 3 (48 h after fear acquisition), when memory retrieval and extinction were tested again. On day 2, men in the stress group showed a robust cortisol response to stress and showed lower unconditioned stimulus (US) expectancy ratings than men in the control group. This reduction in fear memory retrieval was maintained on day 3. In women, who showed a significantly smaller cortisol response to stress than men, no stress effects on fear memory retrieval were observed. No group differences were observed with respect to extinction. In conclusion, the present study provides evidence that stress can reduce memory retrieval of conditioned fear in men. Our findings may contribute to the understanding of the effects of stress and glucocorticoids on fear symptoms in anxiety disorders and suggest that such effects may be sex-specific.

  7. Postretrieval new learning does not reliably induce human memory updating via reconsolidation.

    Science.gov (United States)

    Hardwicke, Tom E; Taqi, Mahdi; Shanks, David R

    2016-05-10

    Reconsolidation theory proposes that retrieval can destabilize an existing memory trace, opening a time-dependent window during which that trace is amenable to modification. Support for the theory is largely drawn from nonhuman animal studies that use invasive pharmacological or electroconvulsive interventions to disrupt a putative postretrieval restabilization ("reconsolidation") process. In human reconsolidation studies, however, it is often claimed that postretrieval new learning can be used as a means of "updating" or "rewriting" existing memory traces. This proposal warrants close scrutiny because the ability to modify information stored in the memory system has profound theoretical, clinical, and ethical implications. The present study aimed to replicate and extend a prominent 3-day motor-sequence learning study [Walker MP, Brakefield T, Hobson JA, Stickgold R (2003) Nature 425(6958):616-620] that is widely cited as a convincing demonstration of human reconsolidation. However, in four direct replication attempts (n = 64), we did not observe the critical impairment effect that has previously been taken to indicate disruption of an existing motor memory trace. In three additional conceptual replications (n = 48), we explored the broader validity of reconsolidation-updating theory by using a declarative recall task and sequences similar to phone numbers or computer passwords. Rather than inducing vulnerability to interference, memory retrieval appeared to aid the preservation of existing sequence knowledge relative to a no-retrieval control group. These findings suggest that memory retrieval followed by new learning does not reliably induce human memory updating via reconsolidation.

  8. High-throughput gene expression profiling of memory differentiation in primary human T cells

    Directory of Open Access Journals (Sweden)

    Russell Kate

    2008-08-01

    Full Text Available Abstract Background The differentiation of naive T and B cells into memory lymphocytes is essential for immunity to pathogens. Therapeutic manipulation of this cellular differentiation program could improve vaccine efficacy and the in vitro expansion of memory cells. However, chemical screens to identify compounds that induce memory differentiation have been limited by 1 the lack of reporter-gene or functional assays that can distinguish naive and memory-phenotype T cells at high throughput and 2 a suitable cell-line representative of naive T cells. Results Here, we describe a method for gene-expression based screening that allows primary naive and memory-phenotype lymphocytes to be discriminated based on complex genes signatures corresponding to these differentiation states. We used ligation-mediated amplification and a fluorescent, bead-based detection system to quantify simultaneously 55 transcripts representing naive and memory-phenotype signatures in purified populations of human T cells. The use of a multi-gene panel allowed better resolution than any constituent single gene. The method was precise, correlated well with Affymetrix microarray data, and could be easily scaled up for high-throughput. Conclusion This method provides a generic solution for high-throughput differentiation screens in primary human T cells where no single-gene or functional assay is available. This screening platform will allow the identification of small molecules, genes or soluble factors that direct memory differentiation in naive human lymphocytes.

  9. A synthesis procedure for associative memories based on space-varying cellular neural networks.

    Science.gov (United States)

    Park, J; Kim, H Y; Park, Y; Lee, S W

    2001-01-01

    In this paper, we consider the problem of realizing associative memories via space-varying CNNs (cellular neural networks). Based on some known results and a newly derived theorem for the CNN model, we propose a synthesis procedure for obtaining a space-varying CNN that can store given bipolar vectors with certain desirable properties. The major part of our synthesis procedure consists of solving generalized eigenvalue problems and/or linear matrix inequality problems, which can be efficiently solved by recently developed interior point methods. The validity of the proposed approach is illustrated by a design example.

  10. VMware vSphere performance designing CPU, memory, storage, and networking for performance-intensive workloads

    CERN Document Server

    Liebowitz, Matt; Spies, Rynardt

    2014-01-01

    Covering the latest VMware vSphere software, an essential book aimed at solving vSphere performance problems before they happen VMware vSphere is the industry's most widely deployed virtualization solution. However, if you improperly deploy vSphere, performance problems occur. Aimed at VMware administrators and engineers and written by a team of VMware experts, this resource provides guidance on common CPU, memory, storage, and network-related problems. Plus, step-by-step instructions walk you through techniques for solving problems and shed light on possible causes behind the problems. Divu

  11. Using recurrent neural networks to optimize dynamical decoupling for quantum memory

    Science.gov (United States)

    August, Moritz; Ni, Xiaotong

    2017-01-01

    We utilize machine learning models that are based on recurrent neural networks to optimize dynamical decoupling (DD) sequences. Dynamical decoupling is a relatively simple technique for suppressing the errors in quantum memory for certain noise models. In numerical simulations, we show that with minimum use of prior knowledge and starting from random sequences, the models are able to improve over time and eventually output DD sequences with performance better than that of the well known DD families. Furthermore, our algorithm is easy to implement in experiments to find solutions tailored to the specific hardware, as it treats the figure of merit as a black box.

  12. Dissociation between explicit memory and configural memory in the human medial temporal lobe.

    Science.gov (United States)

    Preston, Alison R; Gabrieli, John D E

    2008-09-01

    Using functional magnetic resonance imaging, the current study explored the differential mnemonic contributions of the hippocampus and surrounding medial temporal lobe (MTL) cortices to explicit recognition memory and configural learning. Using a task that required processing of repeated and novel visuospatial contexts across multiple trials, we examined MTL activation in relation to 3 forms of learning in a single paradigm: 1) context-independent procedural learning, 2) context-dependent configural learning, and 3) explicit recognition memory. Activations in hippocampus and parahippocampal cortex were associated with explicit memory, differentiating between subsequently remembered and forgotten repeated contexts, but were unrelated to context-dependent configural learning. Activations in regions of perirhinal and entorhinal cortex were associated with configural learning of repeated contexts independent from explicit memory for those contexts. Procedural learning was unrelated to activation in any MTL region. The time course of activation across learning further differed in MTL subregions with MTL cortex demonstrating repetition-related decreases and hippocampus repetition-related increases. These repetition effects were differentially sensitive to recognition with only activation in hippocampus and parahippocampal cortex tracking recognized items. These imaging findings converge with studies of amnesia and indicate dissociable roles for hippocampus in learning that supports explicit recognition and for anterior MTL cortex in configural learning.

  13. Changes in cognitive state alter human functional brain networks

    Directory of Open Access Journals (Sweden)

    Malaak Nasser Moussa

    2011-08-01

    Full Text Available The study of the brain as a whole system can be accomplished using network theory principles. Research has shown that human functional brain networks during a resting state exhibit small-world properties and high degree nodes, or hubs, localized to brain areas consistent with the default mode network (DMN. However, the study of brain networks across different tasks and or cognitive states has been inconclusive. Research in this field is important because the underpinnings of behavioral output are inherently dependent on whether or not brain networks are dynamic. This is the first comprehensive study to evaluate multiple network metrics at a voxel-wise resolution in the human brain at both the whole brain and regional level under various conditions: resting state, visual stimulation, and multisensory (auditory and visual stimulation. Our results show that despite global network stability, functional brain networks exhibit considerable task-induced changes in connectivity, efficiency, and community structure at the regional level.

  14. Forecasting display technique of human in network virtual environment

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The simulation of human in the distributed virtual environment is different from the simulation of ve hicle. Due to the human's many joints, to implement the real-time performance of the interaction between the virtual human and the environment, the quantity of information broadcasted in the network will be increased. So with the growing of the quantity of virtual human added to the network, the network burthen would augment rap idly. Therefore, for the simulation of virtual human this paper divides organically the motion parts of the body, which makes those body parts that often interact with the environment are described according to the joints while other parts are described according to the action information. Simultaneity, this paper adopts Dead Reckoning to reduce the quantity of information needed by maintaining the reality motion of virtual human. The experiment indicates that the forecasting display technique can efficiently reduce the network burthen and enhance the inter action of virtual human.

  15. Coupling of Thalamocortical Sleep Oscillations Are Important for Memory Consolidation in Humans.

    Directory of Open Access Journals (Sweden)

    Mohammad Niknazar

    Full Text Available Sleep, specifically non-rapid eye movement (NREM sleep, is thought to play a critical role in the consolidation of recent memories. Two main oscillatory activities observed during NREM, cortical slow oscillations (SO, 0.5-1.0 Hz and thalamic spindles (12-15 Hz, have been shown to independently correlate with memory improvement. Yet, it is not known how these thalamocortical events interact, or the significance of this interaction, during the consolidation process. Here, we found that systemic administration of the GABAergic drug (zolpidem increased both the phase-amplitude coupling between SO and spindles, and verbal memory improvement in humans. These results suggest that thalamic spindles that occur during transitions to the cortical SO Up state are optimal for memory consolidation. Our study predicts that the timely interactions between cortical and thalamic events during consolidation, contribute to memory improvement and is mediated by the level of inhibitory neurotransmission.

  16. Atypical evening cortisol profile induces visual recognition memory deficit in healthy human subjects

    Directory of Open Access Journals (Sweden)

    Gilpin Heather

    2008-08-01

    Full Text Available Abstract Background Diurnal rhythm-mediated endogenous cortisol levels in humans are characterised by a peak in secretion after awakening that declines throughout the day to an evening trough. However, a significant proportion of the population exhibits an atypical cycle of diurnal cortisol due to shift work, jet-lag, aging, and mental illness. Results The present study has demonstrated a correlation between elevation of cortisol in the evening and deterioration of visual object recognition memory. However, high evening cortisol levels have no effect on spatial memory. Conclusion This study suggests that atypical evening salivary cortisol levels have an important role in the early deterioration of recognition memory. The loss of recognition memory, which is vital for everyday life, is a major symptom of the amnesic syndrome and early stages of Alzheimer's disease. Therefore, this study will promote a potential physiologic marker of early deterioration of recognition memory and a possible diagnostic strategy for Alzheimer's disease.

  17. Restoring Latent Visual Working Memory Representations in Human Cortex.

    Science.gov (United States)

    Sprague, Thomas C; Ester, Edward F; Serences, John T

    2016-08-03

    Working memory (WM) enables the storage and manipulation of limited amounts of information over short periods. Prominent models posit that increasing the number of remembered items decreases the spiking activity dedicated to each item via mutual inhibition, which irreparably degrades the fidelity of each item's representation. We tested these models by determining if degraded memory representations could be recovered following a post-cue indicating which of several items in spatial WM would be recalled. Using an fMRI-based image reconstruction technique, we identified impaired behavioral performance and degraded mnemonic representations with elevated memory load. However, in several cortical regions, degraded mnemonic representations recovered substantially following a post-cue, and this recovery tracked behavioral performance. These results challenge pure spike-based models of WM and suggest that remembered items are additionally encoded within latent or hidden neural codes that can help reinvigorate active WM representations.

  18. Associative memories based on continuous-time cellular neural networks designed using space-invariant cloning templates.

    Science.gov (United States)

    Zeng, Zhigang; Wang, Jun

    2009-01-01

    Associative memories are brain-style devices designed to store a set of patterns as stable equilibria such that the stored patterns can be reliably retrieved with the initial probes containing sufficient information about the patterns. This paper presents a new design procedure for synthesizing associative memories based on continuous-time cellular neural networks with time delays characterized by input and output matrices obtained using two-dimensional space-invariant cloning templates. The design procedure enables hetero-associative or auto-associative memories to be synthesized by solving a set of linear inequalities with few design parameters and retrieval probes feeding from external inputs instead of initial states. The designed associative memories are robust in terms of design parameter selection. In addition, the hosting cellular neural networks are guaranteed to be globally exponentially stable. Simulation and experimental results of illustrative examples and Monte Carlo tests demonstrate the applicability and superiority of the methodology.

  19. The prion gene is associated with human long-term memory.

    Science.gov (United States)

    Papassotiropoulos, Andreas; Wollmer, M Axel; Aguzzi, Adriano; Hock, Christoph; Nitsch, Roger M; de Quervain, Dominique J-F

    2005-08-01

    Human cognitive processes are highly variable across individuals and are influenced by both genetic and environmental factors. Although genetic variations affect short-term memory in humans, it is unknown whether genetic variability has also an impact on long-term memory. Because prion-like conformational changes may be involved in the induction of long-lasting synaptic plasticity, we examined the impact of single-nucleotide polymorphisms (SNPs) of the prion protein gene (PRNP) on long-term memory in healthy young humans. SNPs in the genomic region of PRNP were associated with better long-term memory performance in two independent populations with different educational background. Among the examined PRNP SNPs, the common Met129Val polymorphism yielded the highest effect size. Twenty-four hours after a word list-learning task, carriers of either the 129MM or the 129MV genotype recalled 17% more information than 129VV carriers, but short-term memory was unaffected. These results suggest a role for the prion protein in the formation of long-term memory in humans.

  20. Social Networks and Memory over 15 Years of Followup in a Cohort of Older Australians: Results from the Australian Longitudinal Study of Ageing

    Directory of Open Access Journals (Sweden)

    Lynne C. Giles

    2012-01-01

    Full Text Available The purpose was to examine the relationship between different types of social networks and memory over 15 years of followup in a large cohort of older Australians who were cognitively intact at study baseline. Our specific aims were to investigate whether social networks were associated with memory, determine if different types of social networks had different relationships with memory, and examine if changes in memory over time differed according to types of social networks. We used five waves of data from the Australian Longitudinal Study of Ageing, and followed 706 participants with an average age of 78.6 years (SD 5.7 at baseline. The relationships between five types of social networks and changes in memory were assessed. The results suggested a gradient of effect; participants in the upper tertile of friends or overall social networks had better memory scores than those in the mid tertile, who in turn had better memory scores than participants in the lower tertile. There was evidence of a linear, but not quadratic, effect of time on memory, and an interaction between friends’ social networks and time was apparent. Findings are discussed with respect to mechanisms that might explain the observed relationships between social networks and memory.

  1. A mismatch-based model for memory reconsolidation and extinction in attractor networks.

    Directory of Open Access Journals (Sweden)

    Remus Osan

    Full Text Available The processes of memory reconsolidation and extinction have received increasing attention in recent experimental research, as their potential clinical applications begin to be uncovered. A number of studies suggest that amnestic drugs injected after reexposure to a learning context can disrupt either of the two processes, depending on the behavioral protocol employed. Hypothesizing that reconsolidation represents updating of a memory trace in the hippocampus, while extinction represents formation of a new trace, we have built a neural network model in which either simple retrieval, reconsolidation or extinction of a stored attractor can occur upon contextual reexposure, depending on the similarity between the representations of the original learning and reexposure sessions. This is achieved by assuming that independent mechanisms mediate Hebbian-like synaptic strengthening and mismatch-driven labilization of synaptic changes, with protein synthesis inhibition preferentially affecting the former. Our framework provides a unified mechanistic explanation for experimental data showing (a the effect of reexposure duration on the occurrence of reconsolidation or extinction and (b the requirement of memory updating during reexposure to drive reconsolidation.

  2. Serotonergic modulation of spatial working memory: predictions from a computational network model

    Directory of Open Access Journals (Sweden)

    Maria eCano-Colino

    2013-09-01

    Full Text Available Serotonin (5-HT receptors of types 1A and 2A are massively expressed in prefrontal cortex (PFC neurons, an area associated with cognitive function. Hence, 5-HT could be effective in modulating prefrontal-dependent cognitive functions, such as spatial working memory (SWM. However, a direct association between 5-HT and SWM has proved elusive in psycho-pharmacological studies. Recently, a computational network model of the PFC microcircuit was used to explore the relationship between 5‑HT and SWM (Cano-Colino et al. 2013. This study found that both excessive and insufficient 5-HT levels lead to impaired SWM performance in the network, and it concluded that analyzing behavioral responses based on confidence reports could facilitate the experimental identification of SWM behavioral effects of 5‑HT neuromodulation. Such analyses may have confounds based on our limited understanding of metacognitive processes. Here, we extend these results by deriving three additional predictions from the model that do not rely on confidence reports. Firstly, only excessive levels of 5-HT should result in SWM deficits that increase with delay duration. Secondly, excessive 5-HT baseline concentration makes the network vulnerable to distractors at distances that were robust to distraction in control conditions, while the network still ignores distractors efficiently for low 5‑HT levels that impair SWM. Finally, 5-HT modulates neuronal memory fields in neurophysiological experiments: Neurons should be better tuned to the cued stimulus than to the behavioral report for excessive 5-HT levels, while the reverse should happen for low 5-HT concentrations. In all our simulations agonists of 5-HT1A receptors and antagonists of 5-HT2A receptors produced behavioral and physiological effects in line with global 5-HT level increases. Our model makes specific predictions to be tested experimentally and advance our understanding of the neural basis of SWM and its neuromodulation

  3. Inefficient preparatory fMRI-BOLD network activations predict working memory dysfunctions in patients with schizophrenia

    Directory of Open Access Journals (Sweden)

    Anja eBaenninger

    2016-03-01

    Full Text Available Patients with schizophrenia show abnormal dynamics and structure of temporally coherent networks (TCNs assessed using fMRI, which undergo adaptive shifts in preparation for a cognitively demanding task. During working memory (WM tasks, patients with schizophrenia show persistent deficits in TCNs as well as EEG indices of WM. Studying their temporal relationship during WM tasks might provide novel insights into WM performance deficits seen in schizophrenia.Simultaneous EEG-fMRI data were acquired during the performance of a verbal Sternberg WM task with two load levels (load 2 & load 5 in 17 patients with schizophrenia and 17 matched healthy controls. Using covariance mapping, we investigated the relationship of the activity in the TCNs before the memoranda were encoded and EEG spectral power during the retention interval. We assessed four TCNs – default mode network (DMN, dorsal attention network (dAN, left and right working memory networks (WMNs – and three EEG bands – theta, alpha, and beta.In healthy controls, there was a load dependent inverse relation between DMN and frontal-midline theta power and an anti-correlation between DMN and dAN. Both effects were not significantly detectable in patients. In addition, healthy controls showed a left-lateralized load-dependent recruitment of the WMNs. Activation of the WMNs was bilateral in patients, suggesting more resources were recruited for successful performance on the WM task.Our findings support the notion of schizophrenia patients showing deviations in their neurophysiological responses before the retention of relevant information in a verbal WM task. Thus, treatment strategies as neurofeedback targeting pre-states could be beneficial as task performance relies on the preparatory state of the brain.

  4. Genetic variation of the RASGRF1 regulatory region affects human hippocampus-dependent memory

    Directory of Open Access Journals (Sweden)

    Adriana eBarman

    2014-04-01

    Full Text Available The guanine nucleotide exchange factor RASGRF1 is an important regulator of intracellular signaling and neural plasticity in the brain. RASGRF1-deficient mice exhibit a complex phenotype with learning deficits and ocular abnormalities. Also in humans, a genome-wide association study has identified the single nucleotide polymorphism (SNP rs8027411 in the putative transcription regulatory region of RASGRF1 as a risk variant of myopia. Here we aimed to assess whether, in line with the RASGRF1 knockout mouse phenotype, rs8027411 might also be associated with human memory function. We performed computer-based neuropsychological learning experiments in two independent cohorts of young, healthy participants. Tests included the Verbal Learning and Memory Test (VLMT and the logical memory section of the Wechsler Memory Scale (WMS. Two sub-cohorts additionally participated in functional magnetic resonance imaging (fMRI studies of hippocampus function. 119 participants performed a novelty encoding task that had previously been shown to engage the hippocampus, and 63 subjects participated in a reward-related memory encoding study. RASGRF1 rs8027411 genotype was indeed associated with memory performance in an allele dosage-dependent manner, with carriers of the T allele (i.e. the myopia risk allele showing better memory performance in the early encoding phase of the VLMT and in the recall phase of the WMS logical memory section. In fMRI, T allele carriers exhibited increased hippocampal activation during presentation of novel images and during encoding of pictures associated with monetary reward. Taken together, our results provide evidence for a role of the RASGRF1 gene locus in hippocampus-dependent memory and, along with the previous association with myopia, point towards pleitropic effects of RASGRF1 genetic variations on complex neural function in humans.

  5. The known unknowns of the human dendritic cell network

    Directory of Open Access Journals (Sweden)

    Mélanie eDurand

    2015-03-01

    Full Text Available Dendritic cells (DC initiate and orient immune responses and comprise several subsets that display distinct phenotypes and properties. Most of our knowledge of DC subsets biology is based on mouse studies. In the past few years, the alignment of the human DC network with the mouse DC network has been the focus of much attention. Although comparative phenotypic and transcriptomic analysis have shown a high level of homology between mouse and human DC subsets, significant differences in phenotype and function have also been evidenced. Here we review recent advances in our understanding of the human DC network and discuss some remaining gaps and future challenges of the human DC field.

  6. Effects of Aβ exposure on long-term associative memory and its neuronal mechanisms in a defined neuronal network.

    Science.gov (United States)

    Ford, Lenzie; Crossley, Michael; Williams, Thomas; Thorpe, Julian R; Serpell, Louise C; Kemenes, György

    2015-05-29

    Amyloid beta (Aβ) induced neuronal death has been linked to memory loss, perhaps the most devastating symptom of Alzheimer's disease (AD). Although Aβ-induced impairment of synaptic or intrinsic plasticity is known to occur before any cell death, the links between these neurophysiological changes and the loss of specific types of behavioral memory are not fully understood. Here we used a behaviorally and physiologically tractable animal model to investigate Aβ-induced memory loss and electrophysiological changes in the absence of neuronal death in a defined network underlying associative memory. We found similar behavioral but different neurophysiological effects for Aβ 25-35 and Aβ 1-42 in the feeding circuitry of the snail Lymnaea stagnalis. Importantly, we also established that both the behavioral and neuronal effects were dependent upon the animals having been classically conditioned prior to treatment, since Aβ application before training caused neither memory impairment nor underlying neuronal changes over a comparable period of time following treatment.

  7. Cognitive theories as reinforcement history surrogates: the case of likelihood ratio models of human recognition memory.

    Science.gov (United States)

    Wixted, John T; Gaitan, Santino C

    2002-11-01

    B. F. Skinner (1977) once argued that cognitive theories are essentially surrogates for the organism's (usually unknown) reinforcement history. In this article, we argue that this notion applies rather directly to a class of likelihood ratio models of human recognition memory. The point is not that such models are fundamentally flawed or that they are not useful and should be abandoned. Instead, the point is that the role of reinforcement history in shaping memory decisions could help to explain what otherwise must be explained by assuming that subjects are inexplicably endowed with the relevant distributional information and computational abilities. To the degree that a role for an organism's reinforcement history is appreciated, the importance of animal memory research in understanding human memory comes into clearer focus. As Skinner was also fond of pointing out, it is only in the animal laboratory that an organism's history of reinforcement can be precisely controlled and its effects on behavior clearly understood.

  8. The effects of cardiovascular exercise on human memory

    DEFF Research Database (Denmark)

    Roig, Marc; Nordbrandt, Sasja; Geertsen, Svend Sparre

    2013-01-01

    We reviewed the evidence for the use of cardiovascular exercise to improve memory and explored potential mechanisms. Data from 29 and 21 studies including acute and long-term cardiovascular interventions were retrieved. Meta-analyses revealed that acute exercise had moderate (SMD=0.26; 95% CI=0.0...

  9. Human memory retrieval as Lévy foraging

    Science.gov (United States)

    Rhodes, Theo; Turvey, Michael T.

    2007-11-01

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

  10. Human brain networks function in connectome-specific harmonic waves.

    Science.gov (United States)

    Atasoy, Selen; Donnelly, Isaac; Pearson, Joel

    2016-01-21

    A key characteristic of human brain activity is coherent, spatially distributed oscillations forming behaviour-dependent brain networks. However, a fundamental principle underlying these networks remains unknown. Here we report that functional networks of the human brain are predicted by harmonic patterns, ubiquitous throughout nature, steered by the anatomy of the human cerebral cortex, the human connectome. We introduce a new technique extending the Fourier basis to the human connectome. In this new frequency-specific representation of cortical activity, that we call 'connectome harmonics', oscillatory networks of the human brain at rest match harmonic wave patterns of certain frequencies. We demonstrate a neural mechanism behind the self-organization of connectome harmonics with a continuous neural field model of excitatory-inhibitory interactions on the connectome. Remarkably, the critical relation between the neural field patterns and the delicate excitation-inhibition balance fits the neurophysiological changes observed during the loss and recovery of consciousness.

  11. Human Metabolic Network: Reconstruction, Simulation, and Applications in Systems Biology

    Science.gov (United States)

    Wu, Ming; Chan, Christina

    2012-01-01

    Metabolism is crucial to cell growth and proliferation. Deficiency or alterations in metabolic functions are known to be involved in many human diseases. Therefore, understanding the human metabolic system is important for the study and treatment of complex diseases. Current reconstructions of the global human metabolic network provide a computational platform to integrate genome-scale information on metabolism. The platform enables a systematic study of the regulation and is applicable to a wide variety of cases, wherein one could rely on in silico perturbations to predict novel targets, interpret systemic effects, and identify alterations in the metabolic states to better understand the genotype-phenotype relationships. In this review, we describe the reconstruction of the human metabolic network, introduce the constraint based modeling approach to analyze metabolic networks, and discuss systems biology applications to study human physiology and pathology. We highlight the challenges and opportunities in network reconstruction and systems modeling of the human metabolic system. PMID:24957377

  12. Memory impairment in aged primates is associated with region-specific network dysfunction

    Science.gov (United States)

    Thomé, Alexander; Gray, Daniel T.; Erickson, Cynthia A.; Lipa, Peter; Barnes, Carol A.

    2015-01-01

    Age-related deficits in episodic memory result, in part, from declines in the integrity of medial temporal lobe structures, such as the hippocampus, but are not thought to be due to widespread loss of principal neurons. Studies in rodents suggest, however, that inhibitory interneurons may be particularly vulnerable in advanced age. Optimal encoding and retrieval of information depend on a balance of excitatory and inhibitory transmission. It is not known whether a disruption of this balance is observed in aging nonhuman primates, and whether such changes affect network function and behavior. To examine this question we combine large scale electrophysiological recordings with cell type-specific imaging in the medial temporal lobe of cognitively-assessed, aged rhesus macaques. We found that neuron excitability in hippocampal region CA3 is negatively correlated with the density of the somatostatin-expressing inhibitory interneurons in the vicinity of the recording electrodes in stratum oriens. By contrast, no hyperexcitability or interneuron loss was observed in the perirhinal cortex of these aged, memory-impaired monkeys. These data provide a link, for the first time, between selective increases in principal cell excitability and declines in a molecularly-defined population of interneurons that regulate network inhibition. PMID:26503764

  13. Apnea-Induced Rapid Eye Movement Sleep Disruption Impairs Human Spatial Navigational Memory

    OpenAIRE

    Varga, Andrew W.; Kishi, Akifumi; Mantua, Janna; Lim, Jason; Koushyk, Viachaslau; Leibert, David P.; Osorio, Ricardo S.; David M. Rapoport; Ayappa, Indu

    2014-01-01

    Hippocampal electrophysiology and behavioral evidence support a role for sleep in spatial navigational memory, but the role of particular sleep stages is less clear. Although rodent models suggest the importance of rapid eye movement (REM) sleep in spatial navigational memory, a similar role for REM sleep has never been examined in humans. We recruited subjects with severe obstructive sleep apnea (OSA) who were well treated and adherent with continuous positive airway pressure (CPAP). Restric...

  14. Caffeine attenuates scopolamine-induced memory impairment in humans.

    Science.gov (United States)

    Riedel, W; Hogervorst, E; Leboux, R; Verhey, F; van Praag, H; Jolles, J

    1995-11-01

    Caffeine consumption can be beneficial for cognitive functioning. Although caffeine is widely recognized as a mild CNS stimulant drug, the most important consequence of its adenosine antagonism is cholinergic stimulation, which might lead to improvement of higher cognitive functions, particularly memory. In this study, the scopolamine model of amnesia was used to test the cholinergic effects of caffeine, administered as three cups of coffee. Subjects were 16 healthy volunteers who received 250 mg caffeine and 2 mg nicotine separately, in a placebo-controlled double-blind cross-over design. Compared to placebo, nicotine attenuated the scopolamine-induced impairment of storage in short-term memory and attenuated the scopolamine-induced slowing of speed of short-term memory scanning. Nicotine also attenuated the scopolamine-induced slowing of reaction time in a response competition task. Caffeine attenuated the scopolamine-induced impairment of free recall from short- and long-term memory, quality and speed of retrieval from long-term memory in a word learning task, and other cognitive and non-cognitive measures, such as perceptual sensitivity in visual search, reading speed, and rate of finger-tapping. On the basis of these results it was concluded that caffeine possesses cholinergic cognition enhancing properties. Caffeine could be used as a control drug in studies using the scopolamine paradigm and possibly also in other experimental studies of cognitive enhancers, as the effects of a newly developed cognition enhancing drug should at least be superior to the effects of three cups of coffee.

  15. Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks.

    Science.gov (United States)

    Hanson, Jack; Yang, Yuedong; Paliwal, Kuldip; Zhou, Yaoqi

    2017-03-01

    Capturing long-range interactions between structural but not sequence neighbors of proteins is a long-standing challenging problem in bioinformatics. Recently, long short-term memory (LSTM) networks have significantly improved the accuracy of speech and image classification problems by remembering useful past information in long sequential events. Here, we have implemented deep bidirectional LSTM recurrent neural networks in the problem of protein intrinsic disorder prediction. The new method, named SPOT-Disorder, has steadily improved over a similar method using a traditional, window-based neural network (SPINE-D) in all datasets tested without separate training on short and long disordered regions. Independent tests on four other datasets including the datasets from critical assessment of structure prediction (CASP) techniques and >10 000 annotated proteins from MobiDB, confirmed SPOT-Disorder as one of the best methods in disorder prediction. Moreover, initial studies indicate that the method is more accurate in predicting functional sites in disordered regions. These results highlight the usefulness combining LSTM with deep bidirectional recurrent neural networks in capturing non-local, long-range interactions for bioinformatics applications. SPOT-disorder is available as a web server and as a standalone program at: http://sparks-lab.org/server/SPOT-disorder/index.php . j.hanson@griffith.edu.au or yuedong.yang@griffith.edu.au or yaoqi.zhou@griffith.edu.au. Supplementary data is available at Bioinformatics online.

  16. MULTI-TEMPORAL LAND COVER CLASSIFICATION WITH LONG SHORT-TERM MEMORY NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    M. Rußwurm

    2017-05-01

    Full Text Available Land cover classification (LCC is a central and wide field of research in earth observation and has already put forth a variety of classification techniques. Many approaches are based on classification techniques considering observation at certain points in time. However, some land cover classes, such as crops, change their spectral characteristics due to environmental influences and can thus not be monitored effectively with classical mono-temporal approaches. Nevertheless, these temporal observations should be utilized to benefit the classification process. After extensive research has been conducted on modeling temporal dynamics by spectro-temporal profiles using vegetation indices, we propose a deep learning approach to utilize these temporal characteristics for classification tasks. In this work, we show how long short-term memory (LSTM neural networks can be employed for crop identification purposes with SENTINEL 2A observations from large study areas and label information provided by local authorities. We compare these temporal neural network models, i.e., LSTM and recurrent neural network (RNN, with a classical non-temporal convolutional neural network (CNN model and an additional support vector machine (SVM baseline. With our rather straightforward LSTM variant, we exceeded state-of-the-art classification performance, thus opening promising potential for further research.

  17. Multi-Temporal Land Cover Classification with Long Short-Term Memory Neural Networks

    Science.gov (United States)

    Rußwurm, M.; Körner, M.

    2017-05-01

    Land cover classification (LCC) is a central and wide field of research in earth observation and has already put forth a variety of classification techniques. Many approaches are based on classification techniques considering observation at certain points in time. However, some land cover classes, such as crops, change their spectral characteristics due to environmental influences and can thus not be monitored effectively with classical mono-temporal approaches. Nevertheless, these temporal observations should be utilized to benefit the classification process. After extensive research has been conducted on modeling temporal dynamics by spectro-temporal profiles using vegetation indices, we propose a deep learning approach to utilize these temporal characteristics for classification tasks. In this work, we show how long short-term memory (LSTM) neural networks can be employed for crop identification purposes with SENTINEL 2A observations from large study areas and label information provided by local authorities. We compare these temporal neural network models, i.e., LSTM and recurrent neural network (RNN), with a classical non-temporal convolutional neural network (CNN) model and an additional support vector machine (SVM) baseline. With our rather straightforward LSTM variant, we exceeded state-of-the-art classification performance, thus opening promising potential for further research.

  18. Robust spatial memory maps in flickering neuronal networks: a topological model

    Science.gov (United States)

    Dabaghian, Yuri; Babichev, Andrey; Memoli, Facundo; Chowdhury, Samir; Rice University Collaboration; Ohio State University Collaboration

    It is widely accepted that the hippocampal place cells provide a substrate of the neuronal representation of the environment--the ``cognitive map''. However, hippocampal network, as any other network in the brain is transient: thousands of hippocampal neurons die every day and the connections formed by these cells constantly change due to various forms of synaptic plasticity. What then explains the remarkable reliability of our spatial memories? We propose a computational approach to answering this question based on a couple of insights. First, we propose that the hippocampal cognitive map is fundamentally topological, and hence it is amenable to analysis by topological methods. We then apply several novel methods from homology theory, to understand how dynamic connections between cells influences the speed and reliability of spatial learning. We simulate the rat's exploratory movements through different environments and study how topological invariants of these environments arise in a network of simulated neurons with ``flickering'' connectivity. We find that despite transient connectivity the network of place cells produces a stable representation of the topology of the environment.

  19. Enhanced Human Memory Consolidation With Post-Learning Stress: Interaction With the Degree of Arousal at Encoding

    OpenAIRE

    Cahill, Larry; Gorski, Lukasz; Le, Kathryn

    2003-01-01

    Abundant evidence indicates that endogenous stress hormones such as epinephrine and corticosterone modulate memory consolidation in animals. We recently provided the first demonstration that an endogenous stress hormone (epinephrine) can enhance human memory consolidation. However, these findings also suggested that post-learning stress hormone activation does not uniformly enhance memory for all recently acquired information; rather, that it interacts with the degree ...

  20. A memory efficient implementation scheme of Gauss error function in a Laguerre-Volterra network for neuroprosthetic devices.

    Science.gov (United States)

    Li, Will X Y; Cui, Ke; Zhang, Wei

    2017-04-01

    Cognitive neural prosthesis is a manmade device which can be used to restore or compensate for lost human cognitive modalities. The generalized Laguerre-Volterra (GLV) network serves as a robust mathematical underpinning for the development of such prosthetic instrument. In this paper, a hardware implementation scheme of Gauss error function for the GLV network targeting reconfigurable platforms is reported. Numerical approximations are formulated which transform the computation of nonelementary function into combinational operations of elementary functions, and memory-intensive look-up table (LUT) based approaches can therefore be circumvented. The computational precision can be made adjustable with the utilization of an error compensation scheme, which is proposed based on the experimental observation of the mathematical characteristics of the error trajectory. The precision can be further customizable by exploiting the run-time characteristics of the reconfigurable system. Compared to the polynomial expansion based implementation scheme, the utilization of slice LUTs, occupied slices, and DSP48E1s on a Xilinx XC6VLX240T field-programmable gate array has decreased by 94.2%, 94.1%, and 90.0%, respectively. While compared to the look-up table based scheme, 1.0×10(17) bits of storage can be spared under the maximum allowable error of 1.0×10(-3). The proposed implementation scheme can be employed in the study of large-scale neural ensemble activity and in the design and development of neural prosthetic device.

  1. Reversal Learning in Humans and Gerbils: Dynamic Control Network Facilitates Learning

    Directory of Open Access Journals (Sweden)

    Christian Jarvers

    2016-11-01

    Full Text Available Biologically plausible modeling of behavioral reinforcement learning tasks has seen great improvements over the past decades. Less work has been dedicated to tasks involving contingency reversals, i.e. tasks in which the original behavioral goal is reversed one or multiple times. The ability to adjust to such reversals is a key element of behavioral flexibility. Here, we investigate the neural mechanisms underlying contingency-reversal tasks. We first conduct experiments with humans and gerbils to demonstrate memory effects, including multiple reversals in which subjects (humans and animals show a faster learning rate when a previously learned contingency re-appears. Motivated by recurrent mechanisms of learning and memory for object categories, we propose a network architecture which involves reinforcement learning to steer an orienting system that monitors the success in reward acquisition. We suggest that a model sensory system provides feature representations which are further processed by category-related subnetworks which constitute a neural analog of expert networks. Categories are selected dynamically in a competitive field and predict the expected reward. Learning occurs in sequentialized phases to selectively focus the weight adaptation to synapses in the hierarchical network and modulate their weight changes by a global modulator signal. The orienting subsystem itself learns to bias the competition in the presence of continuous monotonic reward accumulation. In case of sudden changes in the discrepancy of predicted and acquired reward the activated motor category can be switched. We suggest that this subsystem is composed of a hierarchically organized network of dis-inhibitory mechanisms, dubbed a dynamic control network (DCN, which resembles components of the basal ganglia. The DCN selectively activates an expert network, corresponding to the current behavioral strategy. The trace of the accumulated reward is monitored such that

  2. Reversal Learning in Humans and Gerbils: Dynamic Control Network Facilitates Learning

    Science.gov (United States)

    Jarvers, Christian; Brosch, Tobias; Brechmann, André; Woldeit, Marie L.; Schulz, Andreas L.; Ohl, Frank W.; Lommerzheim, Marcel; Neumann, Heiko

    2016-01-01

    Biologically plausible modeling of behavioral reinforcement learning tasks has seen great improvements over the past decades. Less work has been dedicated to tasks involving contingency reversals, i.e., tasks in which the original behavioral goal is reversed one or multiple times. The ability to adjust to such reversals is a key element of behavioral flexibility. Here, we investigate the neural mechanisms underlying contingency-reversal tasks. We first conduct experiments with humans and gerbils to demonstrate memory effects, including multiple reversals in which subjects (humans and animals) show a faster learning rate when a previously learned contingency re-appears. Motivated by recurrent mechanisms of learning and memory for object categories, we propose a network architecture which involves reinforcement learning to steer an orienting system that monitors the success in reward acquisition. We suggest that a model sensory system provides feature representations which are further processed by category-related subnetworks which constitute a neural analog of expert networks. Categories are selected dynamically in a competitive field and predict the expected reward. Learning occurs in sequentialized phases to selectively focus the weight adaptation to synapses in the hierarchical network and modulate their weight changes by a global modulator signal. The orienting subsystem itself learns to bias the competition in the presence of continuous monotonic reward accumulation. In case of sudden changes in the discrepancy of predicted and acquired reward the activated motor category can be switched. We suggest that this subsystem is composed of a hierarchically organized network of dis-inhibitory mechanisms, dubbed a dynamic control network (DCN), which resembles components of the basal ganglia. The DCN selectively activates an expert network, corresponding to the current behavioral strategy. The trace of the accumulated reward is monitored such that large sudden

  3. Out-of-Sequence Prevention for Multicast Input-Queuing Space-Memory-Memory Clos-Network

    DEFF Research Database (Denmark)

    Yu, Hao; Ruepp, Sarah; Berger, Michael Stübert

    2011-01-01

    This paper proposes two cell dispatching algorithms for the input-queuing space-memory-memory (IQ-SMM) Closnetwork to reduce out-of-sequence (OOS) for multicast traffic. The frequent connection pattern change of DSRR results in a severe OOS problem. Based on the principle of DSRR, MFDSRR is able...

  4. Enhancing a declarative memory in humans: the effect of clonazepam on reconsolidation.

    Science.gov (United States)

    Rodríguez, M L C; Campos, J; Forcato, C; Leiguarda, R; Maldonado, H; Molina, V A; Pedreira, M E

    2013-01-01

    A consolidated memory recalled by a specific reminder can become unstable (labile) and susceptible to facilitation or impairment for a discrete period of time. This labilization phase is followed by a process of stabilization called reconsolidation. The phenomenon has been shown in diverse types of memory, and different pharmacological agents have been used to disclose its presence. Several studies have revealed the relevance of the GABAergic system to this process. Consequently, our hypothesis is that the system is involved in the reconsolidation of declarative memory in humans. Thus, using our verbal learning task, we analyzed the effect of benzodiazepines on the re-stabilization of the declarative memory. On Day 1, volunteers learned an association between five cue- response-syllables. On Day 2, the verbal memory was labilized by a reminder presentation, and then a placebo capsule or 0.25 mg or 0.03 mg of clonazepam was administered to the subjects. The verbal memory was evaluated on Day 3. The volunteers who had received the 0.25 mg clonazepam along with the specific reminder on Day 2, exhibited memory improvement. In contrast, there was no effect when the drug was given without retrieval, when the memory was simply retrieved instead of being reactivated or when short-term memory testing was performed 4 h after reactivation. We discuss the GABAergic role in reconsolidation, which shows a collateral effect on other memories when the treatment is aimed at treating anxiety disorders. Further studies might elucidate the role of GABA in the reconsolidation process associated with dissimilar scenarios. This article is part of a Special Issue entitled 'Cognitive Enhancers'.

  5. Distinct parietal sites mediate the influences of mood, arousal, and their interaction on human recognition memory.

    Science.gov (United States)

    Greene, Ciara M; Flannery, Oliver; Soto, David

    2014-12-01

    The two dimensions of emotion, mood valence and arousal, have independent effects on recognition memory. At present, however, it is not clear how those effects are reflected in the human brain. Previous research in this area has generally dealt with memory for emotionally valenced or arousing stimuli, but the manner in which interacting mood and arousal states modulate responses in memory substrates remains poorly understood. We investigated memory for emotionally neutral items while independently manipulating mood valence and arousal state by means of music exposure. Four emotional conditions were created: positive mood/high arousal, positive mood/low arousal, negative mood/high arousal, and negative mood/low arousal. We observed distinct effects of mood valence and arousal in parietal substrates of recognition memory. Positive mood increased activity in ventral posterior parietal cortex (PPC) and orbitofrontal cortex, whereas arousal condition modulated activity in dorsal PPC and the posterior cingulate. An interaction between valence and arousal was observed in left ventral PPC, notably in a parietal area distinct from the those identified for the main effects, with a stronger effect of mood on recognition memory responses here under conditions of relative high versus low arousal. We interpreted the PPC activations in terms of the attention-to-memory hypothesis: Increased arousal may lead to increased top-down control of memory, and hence dorsal PPC activation, whereas positive mood valence may result in increased activity in ventral PPC regions associated with bottom-up attention to memory. These findings indicate that distinct parietal sites mediate the influences of mood, arousal, and their interplay during recognition memory.

  6. Professional development and human resources management in networks

    Directory of Open Access Journals (Sweden)

    Evgeniy Rudnev

    2016-05-01

    Full Text Available Social networks occupy more places in development of people and organizations. Confidence in institutions and social networking are different and based on referentiality in Internet. For communication in network persons choose a different strategies and behavior in LinkedIn, resources of whom may be in different degree are interesting in Human Resources Management for organizations. Members of different social groups and cultures demonstrate some differences in interaction with Russian identity native. There are gender differences behavior in networks. Participating in groups need ethical behavior and norms in social networking for professional development and communication in future.

  7. Interaction of language, auditory and memory brain networks in auditory verbal hallucinations.

    Science.gov (United States)

    Ćurčić-Blake, Branislava; Ford, Judith M; Hubl, Daniela; Orlov, Natasza D; Sommer, Iris E; Waters, Flavie; Allen, Paul; Jardri, Renaud; Woodruff, Peter W; David, Olivier; Mulert, Christoph; Woodward, Todd S; Aleman, André

    2017-01-01

    Auditory verbal hallucinations (AVH) occur in psychotic disorders, but also as a symptom of other conditions and even in healthy people. Several current theories on the origin of AVH converge, with neuroimaging studies suggesting that the language, auditory and memory/limbic networks are of particular relevance. However, reconciliation of these theories with experimental evidence is missing. We review 50 studies investigating functional (EEG and fMRI) and anatomic (diffusion tensor imaging) connectivity in these networks, and explore the evidence supporting abnormal connectivity in these networks associated with AVH. We distinguish between functional connectivity during an actual hallucination experience (symptom capture) and functional connectivity during either the resting state or a task comparing individuals who hallucinate with those who do not (symptom association studies). Symptom capture studies clearly reveal a pattern of increased coupling among the auditory, language and striatal regions. Anatomical and symptom association functional studies suggest that the interhemispheric connectivity between posterior auditory regions may depend on the phase of illness, with increases in non-psychotic individuals and first episode patients and decreases in chronic patients. Leading hypotheses involving concepts as unstable memories, source monitoring, top-down attention, and hybrid models of hallucinations are supported in part by the published connectivity data, although several caveats and inconsistencies remain. Specifically, possible changes in fronto-temporal connectivity are still under debate. Precise hypotheses concerning the directionality of connections deduced from current theoretical approaches should be tested using experimental approaches that allow for discrimination of competing hypotheses. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  8. Hierarchy of Processing Memories in the Human Visual System

    Science.gov (United States)

    Williamson, S. J.; Uusitalo, M. A.

    1997-03-01

    Magnetic source imaging, obtained with an array of 122 superconducting sensors, reveals a dynamical organization of visual cortical areas suggesting that the participation of local memories is an essential component of visual information processing. Response recovery studies provide evidence that each responding cortical area supports a memory function with a well-defined lifetime. The areas fell into two groups: the earliest in occipital lobes with lifetimes ranging from 0.1 to 0.6 s, and the later ones in temporal, parietal, and frontal areas with lifetimes ranging from 7 to 30 s. Also, within each group the areas responding later tended to have longer lifetimes. These hierarchical features introduce a dynamic element that is lacking in many contemporary models of visual processing.

  9. Temporal entrainment of cognitive functions: musical mnemonics induce brain plasticity and oscillatory synchrony in neural networks underlying memory.

    Science.gov (United States)

    Thaut, Michael H; Peterson, David A; McIntosh, Gerald C

    2005-12-01

    In a series of experiments, we have begun to investigate the effect of music as a mnemonic device on learning and memory and the underlying plasticity of oscillatory neural networks. We used verbal learning and memory tests (standardized word lists, AVLT) in conjunction with electroencephalographic analysis to determine differences between verbal learning in either a spoken or musical (verbal materials as song lyrics) modality. In healthy adults, learning in both the spoken and music condition was associated with significant increases in oscillatory synchrony across all frequency bands. A significant difference between the spoken and music condition emerged in the cortical topography of the learning-related synchronization. When using EEG measures as predictors during learning for subsequent successful memory recall, significantly increased coherence (phase-locked synchronization) within and between oscillatory brain networks emerged for music in alpha and gamma bands. In a similar study with multiple sclerosis patients, superior learning and memory was shown in the music condition when controlled for word order recall, and subjects were instructed to sing back the word lists. Also, the music condition was associated with a significant power increase in the low-alpha band in bilateral frontal networks, indicating increased neuronal synchronization. Musical learning may access compensatory pathways for memory functions during compromised PFC functions associated with learning and recall. Music learning may also confer a neurophysiological advantage through the stronger synchronization of the neuronal cell assemblies underlying verbal learning and memory. Collectively our data provide evidence that melodic-rhythmic templates as temporal structures in music may drive internal rhythm formation in recurrent cortical networks involved in learning and memory.

  10. Joint Scaling Theory of Human Dynamics and Network Science

    CERN Document Server

    Song, Chaoming; Barabasi, Albert-Laszlo

    2012-01-01

    The increasing availability of large-scale data on human behavior has catalyzed simultaneous advances in network theory, capturing the scaling properties of the interactions between a large number of individuals, and human dynamics, quantifying the temporal characteristics of human activity patterns. These two areas remain disjoint, however, traditionally each pursuing as a separate modeling framework. Here we establish the first formal link between these two areas by showing that the exponents characterizing the degree and link weight distribution in social networks can be expressed in terms of the dynamical exponents characterizing human activity patterns. We test the validity of these theoretical predictions on datasets capturing various facets of human interactions, from mobile calls to tweets. We find evidence of a universal measure, that links networks and human dynamics, but whose value is independent of the means of communication, capturing a fundamental property of human activity.

  11. A Study on Associative Neural Memories

    OpenAIRE

    B.D.C.N.Prasad; P. E. S. N. Krishna Prasad; Sagar Yeruva; P Sita Rama Murty

    2011-01-01

    Memory plays a major role in Artificial Neural Networks. Without memory, Neural Network can not be learned itself. One of the primary concepts of memory in neural networks is Associative neural memories. A survey has been made on associative neural memories such as Simple associative memories (SAM), Dynamic associative memories (DAM), Bidirectional Associative memories (BAM), Hopfield memories, Context Sensitive Auto-associative memories (CSAM) and so on. These memories can be applied in vari...

  12. The attentional blink reveals serial working memory encoding: evidence from virtual and human event-related potentials.

    Science.gov (United States)

    Craston, Patrick; Wyble, Brad; Chennu, Srivas; Bowman, Howard

    2009-03-01

    Observers often miss a second target (T2) if it follows an identified first target item (T1) within half a second in rapid serial visual presentation (RSVP), a finding termed the attentional blink. If two targets are presented in immediate succession, however, accuracy is excellent (Lag 1 sparing). The resource sharing hypothesis proposes a dynamic distribution of resources over a time span of up to 600 msec during the attentional blink. In contrast, the ST(2) model argues that working memory encoding is serial during the attentional blink and that, due to joint consolidation, Lag 1 is the only case where resources are shared. Experiment 1 investigates the P3 ERP component evoked by targets in RSVP. The results suggest that, in this context, P3 amplitude is an indication of bottom-up strength rather than a measure of cognitive resource allocation. Experiment 2, employing a two-target paradigm, suggests that T1 consolidation is not affected by the presentation of T2 during the attentional blink. However, if targets are presented in immediate succession (Lag 1 sparing), they are jointly encoded into working memory. We use the ST(2) model's neural network implementation, which replicates a range of behavioral results related to the attentional blink, to generate "virtual ERPs" by summing across activation traces. We compare virtual to human ERPs and show how the results suggest a serial nature of working memory encoding as implied by the ST(2) model.

  13. Human-Centric Wireless Communication Networks

    OpenAIRE

    Cavallari, Riccardo

    2016-01-01

    This thesis covers two main topics: the design and performance evaluation of Wireless Body Area Networks (WBANs), and the simulation and mathematical modeling of Delay Tolerant Networks (DTNs). Different Medium Access Control (MAC) protocols for WBANs are implemented on dedicated hardware in order to evaluate, through extensive measurement campaigns, the performance of the network in terms of packet loss rate, delay and energy consumption. Novel solutions to cope with bo...

  14. A unique memory process modulated by emotion underpins successful odor recognition and episodic retrieval in humans

    Directory of Open Access Journals (Sweden)

    Anne-Lise eSaive

    2014-06-01

    Full Text Available We behaviorally explore the link between olfaction, emotion and memory by testing the hypothesis that the emotion carried by odors facilitates the memory of specific unique events. To investigate this idea, we used a novel behavioral approach inspired by a paradigm developed by our team to study episodic memory in a controlled and as ecological as possible way in humans. The participants freely explored three unique and rich laboratory episodes; each episode consisted of three unfamiliar odors (What positioned at three specific locations (Where within a visual context (Which context. During the retrieval test, which occurred 24 to 72 hours after the encoding, odors were used to trigger the retrieval of the complex episodes. The participants were proficient in recognizing the target odors among distractors and retrieving the visuospatial context in which they were encountered. The episodic nature of the task generated high and stable memory performances, which were accompanied by faster responses and slower and deeper breathing. Successful odor recognition and episodic memory were not related to differences in odor investigation at encoding. However, memory performances were influenced by the emotional content of the odors, regardless of odor valence, with both pleasant and unpleasant odors generating higher recognition and episodic retrieval than neutral odors. Finally, the present study also suggested that when the binding between the odors and the spatio-contextual features of the episode was successful, the odor recognition and the episodic retrieval collapsed into a unique memory process that began as soon as the participants smelled the odors.

  15. Recognition memory and the medial temporal lobe: from monkey research to human pathology.

    Science.gov (United States)

    Meunier, M; Barbeau, E

    2013-01-01

    This review provides a historical overview of decades of research on recognition memory, the process that allows both humans and animals to tell familiar from novel items. The emphasis is put on how monkey research improved our understanding of the medial temporal lobe (MTL) role and how tasks designed for monkeys influenced research in humans. The story starts in the early 1950s. Back then, memory was not a fashionable scientific topic. It was viewed as a function of the whole brain and not of specialized brain areas. All that changed in 1957-1958 when Brenda Milner, a neuropsychologist from Montreal, described patient H.M. He forgot all events as he lived them despite a fully preserved intelligence. He had received a MTL resection to relieve epilepsy. H.M. (1926-2008) would become the most influential patient in brain science. Which structures among those included in H.M.'s large lesion were important for recognition memory could not be evaluated in humans. It was gradually understood only after the successful development of a monkey model of human amnesia by Mishkin in 1978. Selective lesions and two behavioral tasks, delayed nonmatching-to-sample and visual paired comparison, were used to distinguish the contribution of the hippocampus from that of adjacent cortical areas. Driven by findings in non-human primates, human research on recognition memory is now trying to solve the question of whether the different structures composing MTL contributes to familiarity and recollection, the two possible forms taken by recognition. We described in particular two French patients, FRG and JMG, whose deficits support the currently dominant model attributing to the perirhinal cortex a critical role in recognition memory. Research on recognition memory has implications for the clinician as it may help understanding the cognitive deficits observed in different diseases. An illustration of such approach, linking basic and applied research, is provided for Alzheimer's disease.

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

    Science.gov (United States)

    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.

  17. Pre-stimulus BOLD-network activation modulates EEG spectral activity during working memory retention

    Directory of Open Access Journals (Sweden)

    Mara eKottlow

    2015-05-01

    Full Text Available Working memory (WM processes depend on our momentary mental state and therefore exhibit considerable fluctuations. Here, we investigate the interplay of task-preparatory and task-related brain activity as represented by pre-stimulus BOLD-fluctuations and spectral EEG from the retention periods of a visual WM task. Visual WM is used to maintain sensory information in the brain enabling the performance of cognitive operations and is associated with mental health.We tested 22 subjects simultaneously with EEG and fMRI while performing a visuo-verbal Sternberg task with two different loads, allowing for the temporal separation of preparation, encoding, retention and retrieval periods.Four temporally coherent networks - the default mode network (DMN, the dorsal attention, the right and the left WM network - were extracted from the continuous BOLD data by means of a group ICA. Subsequently, the modulatory effect of these networks’ pre-stimulus activation upon retention-related EEG activity in the theta, alpha and beta frequencies was analyzed. The obtained results are informative in the context of state-dependent information processing.We were able to replicate two well-known load-dependent effects: the frontal-midline theta increase during the task and the decrease of pre-stimulus DMN activity. As our main finding, these two measures seem to depend on each other as the significant negative correlations at frontal-midline channels suggested. Thus, suppressed pre-stimulus DMN levels facilitated later task related frontal midline theta increases. In general, based on previous findings that neuronal coupling in different frequency bands may underlie distinct functions in WM retention, our results suggest that processes reflected by spectral oscillations during retention seem not only to be online synchronized with activity in different attention-related networks but are also modulated by activity in these networks during preparation intervals.

  18. MEMORY MODULATION

    Science.gov (United States)

    Roozendaal, Benno; McGaugh, James L.

    2011-01-01

    Our memories are not all created equally strong: Some experiences are well remembered while others are remembered poorly, if at all. Research on memory modulation investigates the neurobiological processes and systems that contribute to such differences in the strength of our memories. Extensive evidence from both animal and human research indicates that emotionally significant experiences activate hormonal and brain systems that regulate the consolidation of newly acquired memories. These effects are integrated through noradrenergic activation of the basolateral amygdala which regulates memory consolidation via interactions with many other brain regions involved in consolidating memories of recent experiences. Modulatory systems not only influence neurobiological processes underlying the consolidation of new information, but also affect other mnemonic processes, including memory extinction, memory recall and working memory. In contrast to their enhancing effects on consolidation, adrenal stress hormones impair memory retrieval and working memory. Such effects, as with memory consolidation, require noradrenergic activation of the basolateral amygdala and interactions with other brain regions. PMID:22122145

  19. [Collective memories of women who have experienced maternal near miss: health needs and human rights].

    Science.gov (United States)

    Aguiar, Cláudia de Azevedo; Tanaka, Ana Cristina dʼAndretta

    2016-09-19

    The collective memories of women that have experienced maternal near miss can help elucidate serious obstetric events, like maternal death. Their experience is authentic and representative, with the construction of a common identity. This identity lends quality to a group's memory, and such memory is thus a social phenomenon. The study analyzed the experience of twelve women who nearly died during the gestational and postpartum cycle. The thematic oral history method was used, from the perspective of health needs and human rights. Six collective memories comprised the discourses: unmet health needs; healthcare deficiencies; denial of contact with the newborn child; violation of rights; absence of demand for rights; and compensation for unmet rights and needs. To understand these women's health needs is to acknowledge the women as bearers of rights and to individualize care, respecting their autonomy, guaranteeing access to technologies, and establishing an effective bond with health professionals.

  20. Robust Working Memory in an Asynchronously Spiking Neural Network Realized with Neuromorphic VLSI.

    Science.gov (United States)

    Giulioni, Massimiliano; Camilleri, Patrick; Mattia, Maurizio; Dante, Vittorio; Braun, Jochen; Del Giudice, Paolo

    2011-01-01

    We demonstrate bistable attractor dynamics in a spiking neural network implemented with neuromorphic VLSI hardware. The on-chip network consists of three interacting populations (two excitatory, one inhibitory) of leaky integrate-and-fire (LIF) neurons. One excitatory population is distinguished by strong synaptic self-excitation, which sustains meta-stable states of "high" and "low"-firing activity. Depending on the overall excitability, transitions to the "high" state may be evoked by external stimulation, or may occur spontaneously due to random activity fluctuations. In the former case, the "high" state retains a "working memory" of a stimulus until well after its release. In the latter case, "high" states remain stable for seconds, three orders of magnitude longer than the largest time-scale implemented in the circuitry. Evoked and spontaneous transitions form a continuum and may exhibit a wide range of latencies, depending on the strength of external stimulation and of recurrent synaptic excitation. In addition, we investigated "corrupted" "high" states comprising neurons of both excitatory populations. Within a "basin of attraction," the network dynamics "corrects" such states and re-establishes the prototypical "high" state. We conclude that, with effective theoretical guidance, full-fledged attractor dynamics can be realized with comparatively small populations of neuromorphic hardware neurons.

  1. Memory-induced mechanism for self-sustaining activity in networks

    Science.gov (United States)

    Allahverdyan, A. E.; Steeg, G. Ver; Galstyan, A.

    2015-12-01

    We study a mechanism of activity sustaining on networks inspired by a well-known model of neuronal dynamics. Our primary focus is the emergence of self-sustaining collective activity patterns, where no single node can stay active by itself, but the activity provided initially is sustained within the collective of interacting agents. In contrast to existing models of self-sustaining activity that are caused by (long) loops present in the network, here we focus on treelike structures and examine activation mechanisms that are due to temporal memory of the nodes. This approach is motivated by applications in social media, where long network loops are rare or absent. Our results suggest that under a weak behavioral noise, the nodes robustly split into several clusters, with partial synchronization of nodes within each cluster. We also study the randomly weighted version of the models where the nodes are allowed to change their connection strength (this can model attention redistribution) and show that it does facilitate the self-sustained activity.

  2. Professional development and human resources management in networks

    OpenAIRE

    Evgeniy Rudnev

    2016-01-01

    Social networks occupy more places in development of people and organizations. Confidence in institutions and social networking are different and based on referentiality in Internet. For communication in network persons choose a different strategies and behavior in LinkedIn, resources of whom may be in different degree are interesting in Human Resources Management for organizations. Members of different social groups and cultures demonstrate some differences in interaction with Russian identi...

  3. Effects of acute methamphetamine on emotional memory formation in humans: encoding vs consolidation.

    Science.gov (United States)

    Ballard, Michael E; Weafer, Jessica; Gallo, David A; de Wit, Harriet

    2015-01-01

    Understanding how stimulant drugs affect memory is important for understanding their addictive potential. Here we examined the effects of acute d-methamphetamine (METH), administered either before (encoding phase) or immediately after (consolidation phase) study on memory for emotional and neutral images in healthy humans. Young adult volunteers (N = 60) were randomly assigned to either an encoding group (N = 29) or a consolidation group (N = 31). Across three experimental sessions, they received placebo and two doses of METH (10, 20 mg) either 45 min before (encoding) or immediately after (consolidation) viewing pictures of emotionally positive, neutral, and negative scenes. Memory for the pictures was tested two days later, under drug-free conditions. Half of the sample reported sleep disturbances following the high dose of METH, which affected their memory performance. Therefore, participants were classified as poor sleepers (less than 6 hours; n = 29) or adequate sleepers (6 or more hours; n = 31) prior to analyses. For adequate sleepers, METH (20 mg) administered before encoding significantly improved memory accuracy relative to placebo, especially for emotional (positive and negative), compared to neutral, stimuli. For poor sleepers in the encoding group, METH impaired memory. METH did not affect memory in the consolidation group regardless of sleep quality. These results extend previous findings showing that METH can enhance memory for salient emotional stimuli but only if it is present at the time of study, where it can affect both encoding and consolidation. METH does not appear to facilitate consolidation if administered after encoding. The study also demonstrates the important role of sleep in memory studies.

  4. Effects of acute methamphetamine on emotional memory formation in humans: encoding vs consolidation.

    Directory of Open Access Journals (Sweden)

    Michael E Ballard

    Full Text Available Understanding how stimulant drugs affect memory is important for understanding their addictive potential. Here we examined the effects of acute d-methamphetamine (METH, administered either before (encoding phase or immediately after (consolidation phase study on memory for emotional and neutral images in healthy humans. Young adult volunteers (N = 60 were randomly assigned to either an encoding group (N = 29 or a consolidation group (N = 31. Across three experimental sessions, they received placebo and two doses of METH (10, 20 mg either 45 min before (encoding or immediately after (consolidation viewing pictures of emotionally positive, neutral, and negative scenes. Memory for the pictures was tested two days later, under drug-free conditions. Half of the sample reported sleep disturbances following the high dose of METH, which affected their memory performance. Therefore, participants were classified as poor sleepers (less than 6 hours; n = 29 or adequate sleepers (6 or more hours; n = 31 prior to analyses. For adequate sleepers, METH (20 mg administered before encoding significantly improved memory accuracy relative to placebo, especially for emotional (positive and negative, compared to neutral, stimuli. For poor sleepers in the encoding group, METH impaired memory. METH did not affect memory in the consolidation group regardless of sleep quality. These results extend previous findings showing that METH can enhance memory for salient emotional stimuli but only if it is present at the time of study, where it can affect both encoding and consolidation. METH does not appear to facilitate consolidation if administered after encoding. The study also demonstrates the important role of sleep in memory studies.

  5. Dissociating memory networks in early Alzheimer's disease and frontotemporal lobar degeneration - a combined study of hypometabolism and atrophy.

    Directory of Open Access Journals (Sweden)

    Stefan Frisch

    Full Text Available INTRODUCTION: We aimed at dissociating the neural correlates of memory disorders in Alzheimer's disease (AD and frontotemporal lobar degeneration (FTLD. METHODS: We included patients with AD (n = 19, 11 female, mean age 61 years and FTLD (n = 11, 5 female, mean age 61 years in early stages of their diseases. Memory performance was assessed by means of verbal and visual memory subtests from the Wechsler Memory Scale (WMS-R, including forgetting rates. Brain glucose utilization was measured by [18F]fluorodeoxyglucose positron emission tomography (FDG-PET and brain atrophy by voxel-based morphometry (VBM of T1-weighted magnetic resonance imaging (MRI scans. Using a whole brain approach, correlations between test performance and imaging data were computed separately in each dementia group, including a group of control subjects (n = 13, 6 female, mean age 54 years in both analyses. The three groups did not differ with respect to education and gender. RESULTS: Patients in both dementia groups generally performed worse than controls, but AD and FTLD patients did not differ from each other in any of the test parameters. However, memory performance was associated with different brain regions in the patient groups, with respect to both hypometabolism and atrophy: Whereas in AD patients test performance was mainly correlated with changes in the parieto-mesial cortex, performance in FTLD patients was correlated with changes in frontal cortical as well as subcortical regions. There were practically no overlapping regions associated with memory disorders in AD and FTLD as revealed by a conjunction analysis. CONCLUSION: Memory test performance may not distinguish between both dementia syndromes. In clinical practice, this may lead to misdiagnosis of FTLD patients with poor memory performance. Nevertheless, memory problems are associated with almost completely different neural correlates in both dementia syndromes. Obviously, memory functions are

  6. Social networks and human development / Redes sociales y desarrollo humano

    Directory of Open Access Journals (Sweden)

    Sara Gallego Trijueque

    2011-10-01

    Full Text Available The aim of this work is a brief introduction to the concept of social networks and their importance in society. Social networks have been responsible over the centuries to preserve community values, in addition to being facilitators of social interaction in human development processes, through communication and relationships between individuals.

  7. Lifespan Development of the Human Brain Revealed by Large-Scale Network Eigen-Entropy

    Directory of Open Access Journals (Sweden)

    Yiming Fan

    2017-09-01

    Full Text Available Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying functional connectivity patterns of the developing and aging brain. Normal brain development is characterized by continuous and significant network evolution through infancy, childhood, and adolescence, following specific maturational patterns. Normal aging is related to some resting state brain networks disruption, which are associated with certain cognitive decline. It is a big challenge to design an integral metric to track connectome evolution patterns across the lifespan, which is to understand the principles of network organization in the human brain. In this study, we first defined a brain network eigen-entropy (NEE based on the energy probability (EP of each brain node. Next, we used the NEE to characterize the lifespan orderness trajectory of the whole-brain functional connectivity of 173 healthy individuals ranging in age from 7 to 85 years. The results revealed that during the lifespan, the whole-brain NEE exhibited a significant non-linear decrease and that the EP distribution shifted from concentration to wide dispersion, implying orderness enhancement of functional connectome over age. Furthermore, brain regions with significant EP changes from the flourishing (7–20 years to the youth period (23–38 years were mainly located in the right prefrontal cortex and basal ganglia, and were involved in emotion regulation and executive function in coordination with the action of the sensory system, implying that self-awareness and voluntary control performance significantly changed during neurodevelopment. However, the changes from the youth period to middle age (40–59 years were located in the mesial temporal lobe and caudate, which are associated with long-term memory, implying that the memory of the human brain begins to decline with age during this period. Overall, the findings suggested that the human connectome

  8. Memory: Pandora's hippocampus?

    Science.gov (United States)

    Gabrieli, John D E

    2004-01-01

    Greater knowledge of the human brain has enabled us to begin devising therapies to rescue or modify memory for the afflicted, such as Alzheimer's patients or post-traumatic stress disorder victims. This same knowledge could also allow us to alter how normal, healthy memory operates; we may become able to enhance memory and learning through biological intervention. But the brain consists of complex, interactive networks, and unintended consequences could easily occur. Moreover, memory is woven into our individuality. Altering our memory processes therefore risks altering us fundamentally. We may not be able to resist opening this neuroscientific Pandora's Box, John Gabrieli writes, but we must proceed with all the wisdom we can muster.

  9. Design and analysis of high-capacity associative memories based on a class of discrete-time recurrent neural networks.

    Science.gov (United States)

    Zeng, Zhigang; Wang, Jun

    2008-12-01

    This paper presents a design method for synthesizing associative memories based on discrete-time recurrent neural networks. The proposed procedure enables both hetero- and autoassociative memories to be synthesized with high storage capacity and assured global asymptotic stability. The stored patterns are retrieved by feeding probes via external inputs rather than initial conditions. As typical representatives, discrete-time cellular neural networks (CNNs) designed with space-invariant cloning templates are examined in detail. In particular, it is shown that procedure herein can determine the input matrix of any CNN based on a space-invariant cloning template which involves only a few design parameters. Two specific examples and many experimental results are included to demonstrate the characteristics and performance of the designed associative memories.

  10. Deficits in episodic memory retrieval reveal impaired default mode network connectivity in amnestic mild cognitive impairment

    Directory of Open Access Journals (Sweden)

    Cameron J. Dunn

    2014-01-01

    Full Text Available Amnestic mild cognitive impairment (aMCI is believed to represent a transitional stage between normal healthy ageing and the development of dementia. In particular, aMCI patients have been shown to have higher annual transition rates to Alzheimer's Disease (AD than individuals without cognitive impairment. Despite intensifying interest investigating the neuroanatomical basis of this transition, there remain a number of questions regarding the pathophysiological process underlying aMCI itself. A number of recent studies in aMCI have shown specific impairments in connectivity within the default mode network (DMN, which is a group of regions strongly related to episodic memory capacities. However to date, no study has investigated the integrity of the DMN between patients with aMCI and those with a non-amnestic pattern of MCI (naMCI, who have cognitive impairment, but intact memory storage systems. In this study, we contrasted the DMN connectivity in 24 aMCI and 33 naMCI patients using seed-based resting state fMRI. The two groups showed no statistical difference in their DMN intra-connectivity. However when connectivity was analysed according to performance on measures of episodic memory retrieval, the two groups were separable, with aMCI patients demonstrating impaired functional connectivity between the hippocampal formation and the posterior cingulate cortex. We provide evidence that this lack of connectivity is driven by impaired communication from the posterior cingulate hub and does not simply represent hippocampal atrophy, suggesting that posterior cingulate degeneration is the driving force behind impaired DMN connectivity in aMCI.

  11. Deficits in episodic memory retrieval reveal impaired default mode network connectivity in amnestic mild cognitive impairment

    Science.gov (United States)

    Dunn, Cameron J.; Duffy, Shantel L; Hickie, Ian B; Lagopoulos, Jim; Lewis, Simon J.G.; Naismith, Sharon L.; Shine, James M.

    2014-01-01

    Amnestic mild cognitive impairment (aMCI) is believed to represent a transitional stage between normal healthy ageing and the development of dementia. In particular, aMCI patients have been shown to have higher annual transition rates to Alzheimer's Disease (AD) than individuals without cognitive impairment. Despite intensifying interest investigating the neuroanatomical basis of this transition, there remain a number of questions regarding the pathophysiological process underlying aMCI itself. A number of recent studies in aMCI have shown specific impairments in connectivity within the default mode network (DMN), which is a group of regions strongly related to episodic memory capacities. However to date, no study has investigated the integrity of the DMN between patients with aMCI and those with a non-amnestic pattern of MCI (naMCI), who have cognitive impairment, but intact memory storage systems. In this study, we contrasted the DMN connectivity in 24 aMCI and 33 naMCI patients using seed-based resting state fMRI. The two groups showed no statistical difference in their DMN intra-connectivity. However when connectivity was analysed according to performance on measures of episodic memory retrieval, the two groups were separable, with aMCI patients demonstrating impaired functional connectivity between the hippocampal formation and the posterior cingulate cortex. We provide evidence that this lack of connectivity is driven by impaired communication from the posterior cingulate hub and does not simply represent hippocampal atrophy, suggesting that posterior cingulate degeneration is the driving force behind impaired DMN connectivity in aMCI. PMID:24634833

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

    Science.gov (United States)

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

    2016-01-01

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

  13. Effects of Network Structure, Competition and Memory Time on Social Spreading Phenomena

    Science.gov (United States)

    Gleeson, James P.; O'Sullivan, Kevin P.; Baños, Raquel A.; Moreno, Yamir

    2016-04-01

    Online social media has greatly affected the way in which we communicate with each other. However, little is known about what fundamental mechanisms drive dynamical information flow in online social systems. Here, we introduce a generative model for online sharing behavior that is analytically tractable and that can reproduce several characteristics of empirical micro-blogging data on hashtag usage, such as (time-dependent) heavy-tailed distributions of meme popularity. The presented framework constitutes a null model for social spreading phenomena that, in contrast to purely empirical studies or simulation-based models, clearly distinguishes the roles of two distinct factors affecting meme popularity: the memory time of users and the connectivity structure of the social network.

  14. Effects of Network Structure, Competition and Memory Time on Social Spreading Phenomena

    Directory of Open Access Journals (Sweden)

    James P. Gleeson

    2016-05-01

    Full Text Available Online social media has greatly affected the way in which we communicate with each other. However, little is known about what fundamental mechanisms drive dynamical information flow in online social systems. Here, we introduce a generative model for online sharing behavior that is analytically tractable and that can reproduce several characteristics of empirical micro-blogging data on hashtag usage, such as (time-dependent heavy-tailed distributions of meme popularity. The presented framework constitutes a null model for social spreading phenomena that, in contrast to purely empirical studies or simulation-based models, clearly distinguishes the roles of two distinct factors affecting meme popularity: the memory time of users and the connectivity structure of the social network.

  15. Comparison between sparsely distributed memory and Hopfield-type neural network models

    Science.gov (United States)

    Keeler, James D.

    1986-01-01

    The Sparsely Distributed Memory (SDM) model (Kanerva, 1984) is compared to Hopfield-type neural-network models. A mathematical framework for comparing the two is developed, and the capacity of each model is investigated. The capacity of the SDM can be increased independently of the dimension of the stored vectors, whereas the Hopfield capacity is limited to a fraction of this dimension. However, the total number of stored bits per matrix element is the same in the two models, as well as for extended models with higher order interactions. The models are also compared in their ability to store sequences of patterns. The SDM is extended to include time delays so that contextual information can be used to cover sequences. Finally, it is shown how a generalization of the SDM allows storage of correlated input pattern vectors.

  16. ECG processing techniques based on neural networks and bidirectional associative memories.

    Science.gov (United States)

    Maglaveras, N; Stamkopoulos, T; Pappas, C; Strintzis, M

    1998-01-01

    Two ECG processing techniques are described for the classification of QRSs, PVCs and normal and ischaemic beats. The techniques use neural network (NN) technology in two ways. The first technique, uses nonlinear ECG mapping preprocessing and subsequently for classification uses a shrinking algorithm based on NNs. This technique is applied to the QRS/PVC problem with good result. The second technique is based on the Bidirectional Associative Memory (BAM) NN and is used to distinguish normal from ischaemic beats. In this technique the ECG beat is treated as a digitized image which is then transformed into a bipolar vector suitable for input in the BAM. The results show that this method, if properly calibrated, can result in a fast and reliable ischaemic beat detection algorithm.

  17. Early learning shapes the memory networks for arithmetic: evidence from brain potentials in bilinguals.

    Science.gov (United States)

    Salillas, Elena; Wicha, Nicole Y Y

    2012-07-01

    Language and math are intertwined during children's learning of arithmetic concepts, but the importance of language in adult arithmetic processing is less clear. To determine whether early learning plays a critical role in the math-language connection in adults, we tested retrieval of simple multiplication in adult bilinguals who learned arithmetic in only one language. We measured electrophysiological and behavioral responses during correctness judgments for problems presented as digits or as number words in Spanish or English. Problems presented in the language in which participants learned arithmetic elicited larger, more graded, and qualitatively different brain responses than did problems presented in participants' other language, and these responses more closely resembled responses for digits, even when participants' other language was more dominant. These findings suggest that the memory networks for simple multiplication are established when arithmetic concepts are first learned and are independent of language dominance in adulthood.

  18. Photoresponsive Liquid Crystalline Epoxy Networks with Shape Memory Behavior and Dynamic Ester Bonds.

    Science.gov (United States)

    Li, Yuzhan; Rios, Orlando; Keum, Jong K; Chen, Jihua; Kessler, Michael R

    2016-06-22

    Functional polymers are intelligent materials that can respond to a variety of external stimuli. However, these materials have not yet found widespread real world applications because of the difficulties in fabrication and the limited number of functional building blocks that can be incorporated into a material. Here, we demonstrate a simple route to incorporate three functional building blocks (azobenzene chromophores, liquid crystals, and dynamic covalent bonds) into an epoxy-based liquid crystalline network (LCN), in which an azobenzene-based epoxy monomer is polymerized with an aliphatic dicarboxylic acid to create exchangeable ester bonds that can be thermally activated. All three functional building blocks exhibited good compatibility, and the resulting materials exhibits various photomechanical, shape memory, and self-healing properties because of the azobenzene molecules, liquid crystals, and dynamic ester bonds, respectively.

  19. Beta and gamma oscillatory activities associated with olfactory memory tasks: Different rhythms for different functional networks?

    Directory of Open Access Journals (Sweden)

    Claire eMartin

    2014-06-01

    Full Text Available Olfactory processing in behaving animals, even at early stages, is inextricable from top down influences associated with odor perception. The anatomy of the olfactory network (olfactory bulb, piriform and entorhinal cortices and its unique direct access to the limbic system makes it particularly attractive to study how sensory processing could be modulated by learning and memory. Moreover, olfactory structures have been early reported to exhibit oscillatory population activities easy to capture through local field potential recordings. An attractive hypothesis is that neuronal oscillations would serve to ‘bind’ distant structures to reach a unified and coherent perception. In relation to this hypothesis, we will assess the functional relevance of different types of oscillatory activity observed in the olfactory system of behaving animals. This review will focus primarily on two types of oscillatory activities: beta (15-40 Hz and gamma (60-100 Hz. While gamma oscillations are dominant in the olfactory system in the absence of odorant, both beta and gamma rhythms have been reported to be modulated depending on the nature of the olfactory task. Studies from the authors of the present review and other groups brought evidence for a link between these oscillations and behavioral changes induced by olfactory learning. However, differences in studies led to divergent interpretations concerning the respective role of these oscillations in olfactory processing. Based on a critical reexamination of those data, we propose hypotheses on the functional involvement of beta and gamma oscillations for odor perception and memory.

  20. Enhanced human memory consolidation with post-learning stress: interaction with the degree of arousal at encoding.

    Science.gov (United States)

    Cahill, Larry; Gorski, Lukasz; Le, Kathryn

    2003-01-01

    Abundant evidence indicates that endogenous stress hormones such as epinephrine and corticosterone modulate memory consolidation in animals. We recently provided the first demonstration that an endogenous stress hormone (epinephrine) can enhance human memory consolidation. However, these findings also suggested that post-learning stress hormone activation does not uniformly enhance memory for all recently acquired information; rather, that it interacts with the degree of arousal at initial encoding of material in modulating memory for the material. Here we tested this hypothesis by administering cold pressor stress (CPS) or a control procedure to subjects after they viewed slides of varying emotional content, and assessing memory for the slides 1 wk later. CPS, which significantly elevated salivary cortisol levels, enhanced memory for emotionally arousing slides compared with the controls, but did not affect memory for relatively neutral slides. These findings further support the view that post-learning stress hormone-related activity interacts with arousal at initial encoding to modulate memory consolidation.

  1. Global adaptation in networks of selfish components: emergent associative memory at the system scale.

    Science.gov (United States)

    Watson, Richard A; Mills, Rob; Buckley, C L

    2011-01-01

    In some circumstances complex adaptive systems composed of numerous self-interested agents can self-organize into structures that enhance global adaptation, efficiency, or function. However, the general conditions for such an outcome are poorly understood and present a fundamental open question for domains as varied as ecology, sociology, economics, organismic biology, and technological infrastructure design. In contrast, sufficient conditions for artificial neural networks to form structures that perform collective computational processes such as associative memory/recall, classification, generalization, and optimization are well understood. Such global functions within a single agent or organism are not wholly surprising, since the mechanisms (e.g., Hebbian learning) that create these neural organizations may be selected for this purpose; but agents in a multi-agent system have no obvious reason to adhere to such a structuring protocol or produce such global behaviors when acting from individual self-interest. However, Hebbian learning is actually a very simple and fully distributed habituation or positive feedback principle. Here we show that when self-interested agents can modify how they are affected by other agents (e.g., when they can influence which other agents they interact with), then, in adapting these inter-agent relationships to maximize their own utility, they will necessarily alter them in a manner homologous with Hebbian learning. Multi-agent systems with adaptable relationships will thereby exhibit the same system-level behaviors as neural networks under Hebbian learning. For example, improved global efficiency in multi-agent systems can be explained by the inherent ability of associative memory to generalize by idealizing stored patterns and/or creating new combinations of subpatterns. Thus distributed multi-agent systems can spontaneously exhibit adaptive global behaviors in the same sense, and by the same mechanism, as with the organizational

  2. Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation.

    Science.gov (United States)

    Li, Xiang; Peng, Ling; Yao, Xiaojing; Cui, Shaolong; Hu, Yuan; You, Chengzeng; Chi, Tianhe

    2017-09-08

    Air pollutant concentration forecasting is an effective method of protecting public health by providing an early warning against harmful air pollutants. However, existing methods of air pollutant concentration prediction fail to effectively model long-term dependencies, and most neglect spatial correlations. In this paper, a novel long short-term memory neural network extended (LSTME) model that inherently considers spatiotemporal correlations is proposed for air pollutant concentration prediction. Long short-term memory (LSTM) layers were used to automatically extract inherent useful features from historical air pollutant data, and auxiliary data, including meteorological data and time stamp data, were merged into the proposed model to enhance the performance. Hourly PM2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm) concentration data collected at 12 air quality monitoring stations in Beijing City from Jan/01/2014 to May/28/2016 were used to validate the effectiveness of the proposed LSTME model. Experiments were performed using the spatiotemporal deep learning (STDL) model, the time delay neural network (TDNN) model, the autoregressive moving average (ARMA) model, the support vector regression (SVR) model, and the traditional LSTM NN model, and a comparison of the results demonstrated that the LSTME model is superior to the other statistics-based models. Additionally, the use of auxiliary data improved model performance. For the one-hour prediction tasks, the proposed model performed well and exhibited a mean absolute percentage error (MAPE) of 11.93%. In addition, we conducted multiscale predictions over different time spans and achieved satisfactory performance, even for 13-24 h prediction tasks (MAPE = 31.47%). Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Conditioning and time representation in long short-term memory networks.

    Science.gov (United States)

    Rivest, Francois; Kalaska, John F; Bengio, Yoshua

    2014-02-01

    Dopaminergic models based on the temporal-difference learning algorithm usually do not differentiate trace from delay conditioning. Instead, they use a fixed temporal representation of elapsed time since conditioned stimulus onset. Recently, a new model was proposed in which timing is learned within a long short-term memory (LSTM) artificial neural network representing the cerebral cortex (Rivest et al. in J Comput Neurosci 28(1):107-130, 2010). In this paper, that model's ability to reproduce and explain relevant data, as well as its ability to make interesting new predictions, are evaluated. The model reveals a strikingly different temporal representation between trace and delay conditioning since trace conditioning requires working memory to remember the past conditioned stimulus while delay conditioning does not. On the other hand, the model predicts no important difference in DA responses between those two conditions when trained on one conditioning paradigm and tested on the other. The model predicts that in trace conditioning, animal timing starts with the conditioned stimulus offset as opposed to its onset. In classical conditioning, it predicts that if the conditioned stimulus does not disappear after the reward, the animal may expect a second reward. Finally, the last simulation reveals that the buildup of activity of some units in the networks can adapt to new delays by adjusting their rate of integration. Most importantly, the paper shows that it is possible, with the proposed architecture, to acquire discharge patterns similar to those observed in dopaminergic neurons and in the cerebral cortex on those tasks simply by minimizing a predictive cost function.

  4. Functional evolution of new and expanded attention networks in humans.

    Science.gov (United States)

    Patel, Gaurav H; Yang, Danica; Jamerson, Emery C; Snyder, Lawrence H; Corbetta, Maurizio; Ferrera, Vincent P

    2015-07-28

    Macaques are often used as a model system for invasive investigations of the neural substrates of cognition. However, 25 million years of evolution separate humans and macaques from their last common ancestor, and this has likely substantially impacted the function of the cortical networks underlying cognitive processes, such as attention. We examined the homology of frontoparietal networks underlying attention by comparing functional MRI data from macaques and humans performing the same visual search task. Although there are broad similarities, we found fundamental differences between the species. First, humans have more dorsal attention network areas than macaques, indicating that in the course of evolution the human attention system has expanded compared with macaques. Second, potentially homologous areas in the dorsal attention network have markedly different biases toward representing the contralateral hemifield, indicating that the underlying neural architecture of these areas may differ in the most basic of properties, such as receptive field distribution. Third, despite clear evidence of the temporoparietal junction node of the ventral attention network in humans as elicited by this visual search task, we did not find functional evidence of a temporoparietal junction in macaques. None of these differences were the result of differences in training, experimental power, or anatomical variability between the two species. The results of this study indicate that macaque data should be applied to human models of cognition cautiously, and demonstrate how evolution may shape cortical networks.

  5. Conceptualization and measurement of integrated human service networks for evaluation

    Directory of Open Access Journals (Sweden)

    Gina Browne

    2007-12-01

    Full Text Available Introduction: Integration has been advanced as a strategy for the delivery of a number of human services that have traditionally been delivered by autonomous agencies with independent processes and funding sources. However, measurement of the dimensions of integration has been hampered by numerous factors, including a lack of definitional and conceptual clarity of integration, and the use of measurement tools with atheoretical foundations and limited psychometric testing. Theory/methods: Based on a review of integration measurement approaches, a comprehensive approach to the measure of multiple dimensions of integrated human service networks was conceptualized. The combination of concepts was derived from existing theoretical, policy, and measurement approaches in order to establish the content validity and comprehensiveness of the proposed measure. Results: The dimensions of human service integration measures are: (1 Observed (current and expected structural inputs, or the mix of agencies that comprise the network (e.g. extent, scope, depth, congruence within an agency, and reciprocity between agencies. (2 Functioning of the network both in terms of the quality of the network or partnership functioning and ingredients of the integration of the networks' working arrangements and range of human services provided. (3 Network outputs in terms of network capacity (e.g. what is accomplished, for how many and how quickly given the local demand measured from dual perspectives of the agency and the family. Conclusion: This newly developed measure unites multiple perspectives in a comprehensive approach to the measurement of integration of human service networks. Content validity has been established. Future work should focus on further refinement of this instrument through psychometric evaluation (e.g. construct validity in diverse networks and relating these measures of network integration to client and system outcomes.

  6. The organization of room geometry and object layout geometry in human memory.

    Science.gov (United States)

    Sluzenski, Julia; McNamara, Timothy P

    2011-08-01

    Research with humans and with nonhuman species has suggested a special role of room geometry in spatial memory functioning. In two experiments, participants learned the configuration of a room with four corners, along with the configuration of four objects within the room, while standing in a fixed position at the room's periphery. The configurations were either rectangular (Experiment 1) or irregular (Experiment 2). Room geometry was not recalled better than object layout geometry, and memories for both configurations were orientation dependent. These results suggest that room geometry and object layout geometry are represented similarly in human memory, at least in situations that promote long-term learning of object locations. There were also some differences between corners and objects in orientation dependence, suggesting that the two sources of information are represented in similar but separate spatial reference systems. [corrected

  7. Effects of overnight fasting on working memory-related brain network: an fMRI study.

    Science.gov (United States)

    Chechko, Natalia; Vocke, Sebastian; Habel, Ute; Toygar, Timur; Kuckartz, Lisa; Berthold-Losleben, Mark; Laoutidis, Zacharias G; Orfanos, Stelios; Wassenberg, Annette; Karges, Wölfram; Schneider, Frank; Kohn, Nils

    2015-03-01

    Glucose metabolism serves as the central source of energy for the human brain. Little is known about the effects of blood glucose level (BGL) on higher-order cognitive functions within a physiological range (e.g., after overnight fasting). In this randomized, placebo-controlled, double blind study, we assessed the impact of overnight fasting (14 h) on brain activation during a working memory task. We sought to mimic BGLs that occur naturally in healthy humans after overnight fasting. After standardized periods of food restriction, 40 (20 male) healthy participants were randomly assigned to receive either glucagon to balance the BGL or placebo (NaCl). A parametric fMRI paradigm, including 2-back and 0-back tasks, was used. Subclinically low BGL following overnight fasting was found to be linked to reduced involvement of the bilateral dorsal midline thalamus and the bilateral basal ganglia, suggesting high sensitivity of those regions to minimal changes in BGLs. Our results indicate that overnight fasting leads to physiologically low levels of glucose, impacting brain activation during working memory tasks even when there are no differences in cognitive performance.

  8. Mapping human whole-brain structural networks with diffusion MRI.

    Directory of Open Access Journals (Sweden)

    Patric Hagmann

    Full Text Available Understanding the large-scale structural network formed by neurons is a major challenge in system neuroscience. A detailed connectivity map covering the entire brain would therefore be of great value. Based on diffusion MRI, we propose an efficient methodology to generate large, comprehensive and individual white matter connectional datasets of the living or dead, human or animal brain. This non-invasive tool enables us to study the basic and potentially complex network properties of the entire brain. For two human subjects we find that their individual brain networks have an exponential node degree distribution and that their global organization is in the form of a small world.

  9. Prefrontal and parietal cortex in human episodic memory: an interference study by repetitive transcranial magnetic stimulation.

    Science.gov (United States)

    Rossi, Simone; Pasqualetti, Patrizio; Zito, Giancarlo; Vecchio, Fabrizio; Cappa, Stefano F; Miniussi, Carlo; Babiloni, Claudio; Rossini, Paolo M

    2006-02-01

    Neuroimaging findings, including repetitive transcranial magnetic stimulation (rTMS) interference, point to an engagement of prefrontal cortex (PFC) in learning and memory. Whether parietal cortex (PC) activity is causally linked to successful episodic encoding and retrieval is still uncertain. We compared the effects of event-related active or sham rTMS (a rapid-rate train coincident to the very first phases of memoranda presentation) to the left or right intraparietal sulcus, during a standardized episodic memory task of visual scenes, with those obtained in a fully matched sample of subjects who received rTMS on left or right dorsolateral PFC during the same task. In these subjects, specific hemispheric effects of rTMS included interference with encoding after left stimulation and disruption of retrieval after right stimulation. The interference of PC-rTMS on encoding/retrieval performance was negligible, lacking specificity even when higher intensities of stimulation were applied. However, right PC-rTMS of the same intensity lengthened reaction times in the context of a purely attentive visuospatial task. These results suggest that the activity of intraparietal sulci shown in several functional magnetic resonance studies on memory, unlike that of the dorsolateral PFC, is not causally engaged to a useful degree in memory encoding and retrieval of visual scenes. The parietal activations accompanying the memorization processes could reflect the engagement of a widespread brain attentional network, in which interference on a single 'node' is insufficient for an overt disruption of memory performance.

  10. Modelling Human Cortical Network in Real Brain Space

    Institute of Scientific and Technical Information of China (English)

    ZHAO Qing-Bai; FENG Hong-Bo; TANG Yi-Yuan

    2007-01-01

    Highly specific structural organization is of great significance in the topology of cortical networks.We introduce a human cortical network model.taking the specific cortical structure into account,in which nodes are brain sites placed in the actual positions of cerebral cortex and the establishment of edges depends on the spatial path length rather than the linear distance.The resulting network exhibits the essential features of cortical connectivity,properties of small-world networks and multiple clusters structure.Additionally.assortative mixing is also found in this roodel.All of these findings may be attributed to the spedtic cortical architecture.

  11. Inactivation of the anterior cingulate reveals enhanced reliance on cortical networks for remote spatial memory retrieval after sequential memory processing.

    Directory of Open Access Journals (Sweden)

    Brianne C Wartman

    Full Text Available One system consolidation model suggests that as time passes, ensembles of cortical neurons form strong connections to represent remote memories. In this model, the anterior cingulate cortex (ACC serves as a cortical region that represents remote memories. However, there is debate as to whether remote spatial memories go through this systems consolidation process and come to rely on the ACC. The present experiment examined whether increasing the processing demand on the hippocampus, by sequential training on two spatial tasks, would more fully engage the ACC during retrieval of a remote spatial memory. In this scenario, inactivation of the ACC at a remote time point was hypothesized to produce a severe memory deficit if rats had been trained on two, sequential spatial tasks. Rats were trained on a water maze (WM task only or a WM task followed by a radial arm maze task. A WM probe test was given recently or remotely to all rats. Prior to the probe test, rats received an injection of saline or muscimol into the ACC. A subtle deficit in probe performance was found at the remote time point in the group trained on only one spatial task and treated with muscimol. In the group trained on two spatial tasks and treated with muscimol, a subtle deficit in probe performance was noted at the recent time point and a substantial deficit in probe performance was observed at the remote time point. c-Fos labeling in the hippocampus revealed more labeling in the CA1 region in all remotely tested groups than recently tested groups. Findings suggest that spatial remote memories come to rely more fully on the ACC when hippocampal processing requirements are increased. Results also suggest continued involvement of the hippocampus in spatial memory retrieval along with a progressive strengthening of cortical connections as time progresses.

  12. Inactivation of the anterior cingulate reveals enhanced reliance on cortical networks for remote spatial memory retrieval after sequential memory processing.

    Science.gov (United States)

    Wartman, Brianne C; Gabel, Jennifer; Holahan, Matthew R

    2014-01-01

    One system consolidation model suggests that as time passes, ensembles of cortical neurons form strong connections to represent remote memories. In this model, the anterior cingulate cortex (ACC) serves as a cortical region that represents remote memories. However, there is debate as to whether remote spatial memories go through this systems consolidation process and come to rely on the ACC. The present experiment examined whether increasing the processing demand on the hippocampus, by sequential training on two spatial tasks, would more fully engage the ACC during retrieval of a remote spatial memory. In this scenario, inactivation of the ACC at a remote time point was hypothesized to produce a severe memory deficit if rats had been trained on two, sequential spatial tasks. Rats were trained on a water maze (WM) task only or a WM task followed by a radial arm maze task. A WM probe test was given recently or remotely to all rats. Prior to the probe test, rats received an injection of saline or muscimol into the ACC. A subtle deficit in probe performance was found at the remote time point in the group trained on only one spatial task and treated with muscimol. In the group trained on two spatial tasks and treated with muscimol, a subtle deficit in probe performance was noted at the recent time point and a substantial deficit in probe performance was observed at the remote time point. c-Fos labeling in the hippocampus revealed more labeling in the CA1 region in all remotely tested groups than recently tested groups. Findings suggest that spatial remote memories come to rely more fully on the ACC when hippocampal processing requirements are increased. Results also suggest continued involvement of the hippocampus in spatial memory retrieval along with a progressive strengthening of cortical connections as time progresses.

  13. Predicting errors from reconfiguration patterns in human brain networks.

    Science.gov (United States)

    Ekman, Matthias; Derrfuss, Jan; Tittgemeyer, Marc; Fiebach, Christian J

    2012-10-09

    Task preparation is a complex cognitive process that implements anticipatory adjustments to facilitate future task performance. Little is known about quantitative network parameters governing this process in humans. Using functional magnetic resonance imaging (fMRI) and functional connectivity measurements, we show that the large-scale topology of the brain network involved in task preparation shows a pattern of dynamic reconfigurations that guides optimal behavior. This network could be decomposed into two distinct topological structures, an error-resilient core acting as a major hub that integrates most of the network's communication and a predominantly sensory periphery showing more flexible network adaptations. During task preparation, core-periphery interactions were dynamically adjusted. Task-relevant visual areas showed a higher topological proximity to the network core and an enhancement in their local centrality and interconnectivity. Failure to reconfigure the network topology was predictive for errors, indicating that anticipatory network reconfigurations are crucial for successful task performance. On the basis of a unique network decoding approach, we also develop a general framework for the identification of characteristic patterns in complex networks, which is applicable to other fields in neuroscience that relate dynamic network properties to behavior.

  14. Brain and Social Networks: Fundamental Building Blocks of Human Experience.

    Science.gov (United States)

    Falk, Emily B; Bassett, Danielle S

    2017-09-01

    How do brains shape social networks, and how do social ties shape the brain? Social networks are complex webs by which ideas spread among people. Brains comprise webs by which information is processed and transmitted among neural units. While brain activity and structure offer biological mechanisms for human behaviors, social networks offer external inducers or modulators of those behaviors. Together, these two axes represent fundamental contributors to human experience. Integrating foundational knowledge from social and developmental psychology and sociology on how individuals function within dyads, groups, and societies with recent advances in network neuroscience can offer new insights into both domains. Here, we use the example of how ideas and behaviors spread to illustrate the potential of multilayer network models. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Gene transcriptional networks integrate microenvironmental signals in human breast cancer.

    Science.gov (United States)

    Xu, Ren; Mao, Jian-Hua

    2011-04-01

    A significant amount of evidence shows that microenvironmental signals generated from extracellular matrix (ECM) molecules, soluble factors, and cell-cell adhesion complexes cooperate at the extra- and intracellular level. This synergetic action of microenvironmental cues is crucial for normal mammary gland development and breast malignancy. To explore how the microenvironmental genes coordinate in human breast cancer at the genome level, we have performed gene co-expression network analysis in three independent microarray datasets and identified two microenvironment networks in human breast cancer tissues. Network I represents crosstalk and cooperation of ECM microenvironment and soluble factors during breast malignancy. The correlated expression of cytokines, chemokines, and cell adhesion proteins in Network II implicates the coordinated action of these molecules in modulating the immune response in breast cancer tissues. These results suggest that microenvironmental cues are integrated with gene transcriptional networks to promote breast cancer development.

  16. Low Proliferation and Differentiation Capacities of Adult Hippocampal Stem Cells Correlate with Memory Dysfunction in Humans

    Science.gov (United States)

    Coras, Roland; Siebzehnrubl, Florian A.; Pauli, Elisabeth; Huttner, Hagen B.; Njunting, Marleisje; Kobow, Katja; Villmann, Carmen; Hahnen, Eric; Neuhuber, Winfried; Weigel, Daniel; Buchfelder, Michael; Stefan, Hermann; Beck, Heinz; Steindler, Dennis A.; Blumcke, Ingmar

    2010-01-01

    The hippocampal dentate gyrus maintains its capacity to generate new neurons throughout life. In animal models, hippocampal neurogenesis is increased by cognitive tasks, and experimental ablation of neurogenesis disrupts specific modalities of learning and memory. In humans, the impact of neurogenesis on cognition remains unclear. Here, we…

  17. EFFECTS OF MAGNESIUM PEMOLINE UPON HUMAN LEARNING, MEMORY, AND PERFORMANCE TESTS.

    Science.gov (United States)

    SMITH, RONALD G.

    THIS STUDY WAS CONDUCTED DURING 1966 TO DETERMINE THE EFFECTS OF MAGNESIUM PEMOLINE (A COMBINATION OF 2-IMINO-5-PHENYL-4-OXAZOLIDINONE AND MAGNESIUM HYDROXIDE) ON A VARIETY OF HUMAN LEARNING, MEMORY, AND PERFORMANCE TASKS. MAGNESIUM PEMOLINE (25 OR 37.5 MG) OR A PLACEBO WAS ADMINISTERED ORALLY ON A DOUBLE-BLIND BASIS TO INTELLIGENCE-MATCHED GROUPS…

  18. Functional network organization of the human brain.

    Science.gov (United States)

    Power, Jonathan D; Cohen, Alexander L; Nelson, Steven M; Wig, Gagan S; Barnes, Kelly Anne; Church, Jessica A; Vogel, Alecia C; Laumann, Timothy O; Miezin, Fran M; Schlaggar, Bradley L; Petersen, Steven E

    2011-11-17

    Real-world complex systems may be mathematically modeled as graphs, revealing properties of the system. Here we study graphs of functional brain organization in healthy adults using resting state functional connectivity MRI. We propose two novel brain-wide graphs, one of 264 putative functional areas, the other a modification of voxelwise networks that eliminates potentially artificial short-distance relationships. These graphs contain many subgraphs in good agreement with known functional brain systems. Other subgraphs lack established functional identities; we suggest possible functional characteristics for these subgraphs. Further, graph measures of the areal network indicate that the default mode subgraph shares network properties with sensory and motor subgraphs: it is internally integrated but isolated from other subgraphs, much like a "processing" system. The modified voxelwise graph also reveals spatial motifs in the patterning of systems across the cortex.

  19. Language Identification in Short Utterances Using Long Short-Term Memory (LSTM) Recurrent Neural Networks.

    Science.gov (United States)

    Zazo, Ruben; Lozano-Diez, Alicia; Gonzalez-Dominguez, Javier; Toledano, Doroteo T; Gonzalez-Rodriguez, Joaquin

    2016-01-01

    Long Short Term Memory (LSTM) Recurrent Neural Networks (RNNs) have recently outperformed other state-of-the-art approaches, such as i-vector and Deep Neural Networks (DNNs), in automatic Language Identification (LID), particularly when dealing with very short utterances (∼3s). In this contribution we present an open-source, end-to-end, LSTM RNN system running on limited computational resources (a single GPU) that outperforms a reference i-vector system on a subset of the NIST Language Recognition Evaluation (8 target languages, 3s task) by up to a 26%. This result is in line with previously published research using proprietary LSTM implementations and huge computational resources, which made these former results hardly reproducible. Further, we extend those previous experiments modeling unseen languages (out of set, OOS, modeling), which is crucial in real applications. Results show that a LSTM RNN with OOS modeling is able to detect these languages and generalizes robustly to unseen OOS languages. Finally, we also analyze the effect of even more limited test data (from 2.25s to 0.1s) proving that with as little as 0.5s an accuracy of over 50% can be achieved.

  20. Language Identification in Short Utterances Using Long Short-Term Memory (LSTM Recurrent Neural Networks.

    Directory of Open Access Journals (Sweden)

    Ruben Zazo

    Full Text Available Long Short Term Memory (LSTM Recurrent Neural Networks (RNNs have recently outperformed other state-of-the-art approaches, such as i-vector and Deep Neural Networks (DNNs, in automatic Language Identification (LID, particularly when dealing with very short utterances (∼3s. In this contribution we present an open-source, end-to-end, LSTM RNN system running on limited computational resources (a single GPU that outperforms a reference i-vector system on a subset of the NIST Language Recognition Evaluation (8 target languages, 3s task by up to a 26%. This result is in line with previously published research using proprietary LSTM implementations and huge computational resources, which made these former results hardly reproducible. Further, we extend those previous experiments modeling unseen languages (out of set, OOS, modeling, which is crucial in real applications. Results show that a LSTM RNN with OOS modeling is able to detect these languages and generalizes robustly to unseen OOS languages. Finally, we also analyze the effect of even more limited test data (from 2.25s to 0.1s proving that with as little as 0.5s an accuracy of over 50% can be achieved.

  1. Cross-frequency synchronization connects networks of fast and slow oscillations during visual working memory maintenance

    Science.gov (United States)

    Siebenhühner, Felix; Wang, Sheng H; Palva, J Matias; Palva, Satu

    2016-01-01

    Neuronal activity in sensory and fronto-parietal (FP) areas underlies the representation and attentional control, respectively, of sensory information maintained in visual working memory (VWM). Within these regions, beta/gamma phase-synchronization supports the integration of sensory functions, while synchronization in theta/alpha bands supports the regulation of attentional functions. A key challenge is to understand which mechanisms integrate neuronal processing across these distinct frequencies and thereby the sensory and attentional functions. We investigated whether such integration could be achieved by cross-frequency phase synchrony (CFS). Using concurrent magneto- and electroencephalography, we found that CFS was load-dependently enhanced between theta and alpha–gamma and between alpha and beta-gamma oscillations during VWM maintenance among visual, FP, and dorsal attention (DA) systems. CFS also connected the hubs of within-frequency-synchronized networks and its strength predicted individual VWM capacity. We propose that CFS integrates processing among synchronized neuronal networks from theta to gamma frequencies to link sensory and attentional functions. DOI: http://dx.doi.org/10.7554/eLife.13451.001 PMID:27669146

  2. Human Face Recognition Using Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Răzvan-Daniel Albu

    2009-10-01

    Full Text Available In this paper, I present a novel hybrid face recognition approach based on a convolutional neural architecture, designed to robustly detect highly variable face patterns. The convolutional network extracts successively larger features in a hierarchical set of layers. With the weights of the trained neural networks there are created kernel windows used for feature extraction in a 3-stage algorithm. I present experimental results illustrating the efficiency of the proposed approach. I use a database of 796 images of 159 individuals from Reims University which contains quite a high degree of variability in expression, pose, and facial details.

  3. Digital Humanities and networked digital media

    OpenAIRE

    Finnemann, Niels Ole

    2014-01-01

    This article discusses digital humanities and the growing diversity of digital media, digital materials and digital methods. The first section describes the humanities computing tradition formed around the interpretation of computation as a rule-based process connected to a concept of digital materials centred on the digitisation of non-digital, finite works, corpora and oeuvres. The second section discusses “the big tent” of contemporary digital humanities. It is argued that there can be no ...

  4. Cortical network from human embryonic stem cells

    OpenAIRE

    2010-01-01

    Abstract The connection of embryonic stem cell technology and developmental biology provides valuable tools to decipher the mechanisms underlying human brain development and diseases, especially among neuronal populations, that are not readily available in primary cultures. It is obviously the case of neurons forming the human cerebral cortex. In the images that are presented, the neurons were generated in vitro from human embryonic stem cells via forebrain-like progenitors. Maintained in cul...

  5. Influence of oxytocin on human memory processes: validation by a control study.

    Science.gov (United States)

    Kennett, D J; Devlin, M C; Ferrier, B M

    1982-07-19

    An earlier report (1) of an adverse effect of high doses of oxytocin on human memory included results of studies on women receiving oxytocin as part of the treatment to induce 2nd trimester therapeutic abortion. These women served as their own controls. We have now been able to study a group of women who have been treated in all ways like the original group, with the exception that they did not receive oxytocin. The results from this external control corroborate the finding that oxytocin affected memory.

  6. Digital Humanities and networked digital media

    DEFF Research Database (Denmark)

    Finnemann, Niels Ole

    2014-01-01

    This article discusses digital humanities and the growing diversity of digital media, digital materials and digital methods. The first section describes the humanities computing tradition formed around the interpretation of computation as a rule-based process connected to a concept of digital...... materials centred on the digitisation of non-digital, finite works, corpora and oeuvres. The second section discusses “the big tent” of contemporary digital humanities. It is argued that there can be no unifying interpretation of digital humanities above the level of studying digital materials with the help...

  7. Dopamine in the medial amygdala network mediates human bonding

    Science.gov (United States)

    Touroutoglou, Alexandra; Rudy, Tali; Salcedo, Stephanie; Feldman, Ruth; Hooker, Jacob M.; Dickerson, Bradford C.; Catana, Ciprian; Barrett, Lisa Feldman

    2017-01-01

    Research in humans and nonhuman animals indicates that social affiliation, and particularly maternal bonding, depends on reward circuitry. Although numerous mechanistic studies in rodents demonstrated that maternal bonding depends on striatal dopamine transmission, the neurochemistry supporting maternal behavior in humans has not been described so far. In this study, we tested the role of central dopamine in human bonding. We applied a combined functional MRI-PET scanner to simultaneously probe mothers’ dopamine responses to their infants and the connectivity between the nucleus accumbens (NAcc), the amygdala, and the medial prefrontal cortex (mPFC), which form an intrinsic network (referred to as the “medial amygdala network”) that supports social functioning. We also measured the mothers’ behavioral synchrony with their infants and plasma oxytocin. The results of this study suggest that synchronous maternal behavior is associated with increased dopamine responses to the mother’s infant and stronger intrinsic connectivity within the medial amygdala network. Moreover, stronger network connectivity is associated with increased dopamine responses within the network and decreased plasma oxytocin. Together, these data indicate that dopamine is involved in human bonding. Compared with other mammals, humans have an unusually complex social life. The complexity of human bonding cannot be fully captured in nonhuman animal models, particularly in pathological bonding, such as that in autistic spectrum disorder or postpartum depression. Thus, investigations of the neurochemistry of social bonding in humans, for which this study provides initial evidence, are warranted. PMID:28193868

  8. Emotion and Autobiographical Memory

    Directory of Open Access Journals (Sweden)

    Nuray Sarp

    2011-09-01

    Full Text Available Self and mind are constituted with the cumulative effects of significant life events. This description is regarded as a given explicitly or implicitly in vari-ous theories of personality. Such an acknowledgment inevitably brings together these theories on two basic concepts. The first one is the emotions that give meaning to experiences and the second one is the memory which is related to the storage of these experiences. The part of the memory which is responsible for the storage and retrieval of life events is the autobiographical memory. Besides the development of personality, emotions and autobiographical memory are important in the development of and maintenance of psychopathology. Therefore, these two concepts have both longitudinal and cross-sectional functions in understanding human beings. In case of psychopathology, understanding emotions and autobiographical memory developmentally, aids in understanding the internal susceptibility factors. In addition, understanding how these two structures work and influence each other in an acute event would help to understand the etiological mechanisms of mental disorders. In the literature, theories that include both of these structures and that have clinical implications, are inconclusive. Theories on memory generally focus on cognitive and semantic structures while neglecting emotions, whereas theories on emotions generally neglect memory and its organization. There are only a few theories that cover both of these two concepts. In the present article, these theories that include both emotions and autobiographical memory in the same framework (i.e. Self Memory System, Associative Network Theory, Structural and Contextual theories and Affect Regulation Theory were discussed to see the full picture. Taken together, these theories seem to have the potential to suggest data-driven models in understanding and explaining symptoms such as flashbacks, dissociation, amnesia, over general memory seen in

  9. Age-dependent effects of the 5-hydroxytryptamine-2a-receptor polymorphism (His452Tyr) on human memory.

    Science.gov (United States)

    Papassotiropoulos, Andreas; Henke, Katharina; Aerni, Amanda; Coluccia, Daniel; Garcia, Esmeralda; Wollmer, Marc A; Huynh, Kim-Dung; Monsch, Andreas U; Stähelin, Hannes B; Hock, Christoph; Nitsch, Roger M; de Quervain, Dominique J-F

    2005-05-31

    A polymorphism (His452Tyr) of the 5-hydroxytryptamine (5-HT)2a receptor is associated with episodic memory in healthy young humans. Because 5-HT2a-receptor density decreases with increasing age, we tested whether the 5-HT2a receptor genotype effect on memory is influenced by age. We investigated the association of the His452Tyr genotype with memory performance in 622 healthy study participants aged from 18 to 90 years. In young to middle-aged participants, age significantly influenced genotype effects on episodic memory: the His452Tyr genotype exerted a significant influence on memory only in young participants. In the group of elderly cognitively healthy participants, the His452Tyr genotype did not affect memory performance. We conclude that age strongly modulates the effect of the 5-HT2a receptor polymorphism at residue 452 on episodic memory.

  10. Early-life stress impairs recognition memory and perturbs the functional maturation of prefrontal-hippocampal-perirhinal networks

    Science.gov (United States)

    Reincke, Samuel A. J.; Hanganu-Opatz, Ileana L.

    2017-01-01

    Early life exposure to stressful situations impairs cognitive performance of adults and contributes to the etiology of several psychiatric disorders. Most of affected cognitive abilities rely on coupling by synchrony within complex neuronal networks, including prefrontal cortex (PFC), hippocampus (HP), and perirhinal cortex (PRH). Yet it remains poorly understood how early life stress (ELS) induces dysfunction within these networks during the course of development. Here we used intermittent maternal separation during the first 2 postnatal weeks to mimic ELS and monitored the recognition memory and functional coupling within prefrontal-hippocampal-perirhinal circuits in juvenile rats. While maternally-separated female rats showed largely normal behavior, male rats experiencing this form of ELS had poorer location and recency recognition memory. Simultaneous multi-site extracellular recordings of network oscillations and neuronal spiking from PFC, HP, and PRH in vivo revealed corresponding decrease of oscillatory activity in theta and beta frequency bands in the PFC of male but not female rats experiencing maternal separation. This deficit was accompanied by weaker cross-frequency coupling within juvenile prefrontal-hippocampal networks. These results indicate that already at juvenile age ELS mimicked by maternal separation induces sex-specific deficits in recognition memory that might have as underlying mechanism a disturbed communication between PFC and HP. PMID:28169319

  11. Assessing reliable human mobility patterns from higher-order memory in mobile communications

    CERN Document Server

    De Domenico, Manlio; Arenas, Alex

    2016-01-01

    Understanding how people move within a geographic area, e.g. a city, a country or the whole world, is fundamental in several applications, from predicting the spatio-temporal evolution of an epidemics to inferring migration patterns. Mobile phone records provide an excellent proxy of human mobility, showing that movements exhibit a high level of memory. However, the precise role of memory in widely adopted proxies of mobility, as mobile phone records, is unknown. Here we use 560 millions of call detail records from Senegal to show that standard Markovian approaches, including higher-order ones, fail in capturing real mobility patterns and introduce spurious movements never observed in reality. We introduce an adaptive memory-driven approach to overcome such issues. At variance with Markovian models, it is able to realistically model conditional waiting times, i.e. the probability to stay in a specific area depending on individual's historical movements. Our results demonstrate that in standard mobility models...

  12. Sparse generalized volterra model of human hippocampal spike train transformation for memory prostheses.

    Science.gov (United States)

    Song, Dong; Robinson, Brian S; Hampson, Robert E; Marmarelis, Vasilis Z; Deadwyler, Sam A; Berger, Theodore W

    2015-01-01

    In order to build hippocampal prostheses for restoring memory functions, we build multi-input, multi-output (MIMO) nonlinear dynamical models of the human hippocampus. Spike trains are recorded from the hippocampal CA3 and CA1 regions of epileptic patients performing a memory-dependent delayed match-to-sample task. Using CA3 and CA1 spike trains as inputs and outputs respectively, second-order sparse generalized Laguerre-Volterra models are estimated with group lasso and local coordinate descent methods to capture the nonlinear dynamics underlying the spike train transformations. These models can accurately predict the CA1 spike trains based on the ongoing CA3 spike trains and thus will serve as the computational basis of the hippocampal memory prosthesis.

  13. Caffeine impact on working memory-related network activation patterns in early stages of cognitive decline

    Energy Technology Data Exchange (ETDEWEB)

    Haller, Sven [Affidea Centre de Diagnostic Radiologique de Carouge CDRC, Geneva (Switzerland); Uppsala University, Department of Surgical Sciences, Radiology, Uppsala (Sweden); Montandon, Marie-Louise; Rodriguez, Cristelle; Moser, Dominik; Toma, Simona; Hofmeister, Jeremy; Giannakopoulos, Panteleimon [University Hospitals of Geneva, Department of Psychiatry, Faculty of Medicine, Medical Direction, Geneva (Switzerland)

    2017-04-15

    Recent evidence indicates that caffeine may have a beneficial effect on cognitive decline and dementia. The current investigation assessed the effect of acute caffeine administration on working memory during the earliest stage of cognitive decline in elderly participants. The study includes consecutive 45 elderly controls and 18 individuals with mild cognitive impairment (MCI, 71.6 ± 4.7 years, 7 females). During neuropsychological follow-up at 18 months, 24 controls remained stable (sCON, 70.0 ± 4.3 years, 11 women), while the remaining 21 showed subtle cognitive deterioration (dCON, 73.4 ± 5.9 years, 14 women). All participants underwent an established 2-back working task in a crossover design of 200 mg caffeine versus placebo. Data analysis included task-related general linear model and functional connectivity tensorial independent component analysis. Working memory behavioral performances did not differ between sCON and dCON, while MCI was slower and less accurate than both control groups (p < 0.05). The dCON group had a less pronounced effect of acute caffeine administration essentially restricted to the right hemisphere (p < 0.05 corrected) and reduced default mode network (DMN) deactivation compared to sCON (p < 0.01 corrected). dCON cases are characterized by decreased sensitivity to caffeine effects on brain activation and DMN deactivation. These complex fMRI patterns possibly reflect the instable status of these cases with intact behavioral performances despite already existing functional alterations in neocortical circuits. (orig.)

  14. Enhanced structural connectivity within a brain sub-network supporting working memory and engagement processes after cognitive training.

    Science.gov (United States)

    Román, Francisco J; Iturria-Medina, Yasser; Martínez, Kenia; Karama, Sherif; Burgaleta, Miguel; Evans, Alan C; Jaeggi, Susanne M; Colom, Roberto

    2017-05-01

    The structural connectome provides relevant information about experience and training-related changes in the brain. Here, we used network-based statistics (NBS) and graph theoretical analyses to study structural changes in the brain as a function of cognitive training. Fifty-six young women were divided in two groups (experimental and control). We assessed their cognitive function before and after completing a working memory intervention using a comprehensive battery that included fluid and crystallized abilities, working memory and attention control, and we also obtained structural MRI images. We acquired and analyzed diffusion-weighted images to reconstruct the anatomical connectome and we computed standardized changes in connectivity as well as group differences across time using NBS. We also compared group differences relying on a variety of graph-theory indices (clustering, characteristic path length, global and local efficiency and strength) for the whole network as well as for the sub-network derived from NBS analyses. Finally, we calculated correlations between these graph indices and training performance as well as the behavioral changes in cognitive function. Our results revealed enhanced connectivity for the training group within one specific network comprised of nodes/regions supporting cognitive processes required by the training (working memory, interference resolution, inhibition, and task engagement). Significant group differences were also observed for strength and global efficiency indices in the sub-network detected by NBS. Therefore, the connectome approach is a valuable method for tracking the effects of cognitive training interventions across specific sub-networks. Moreover, this approach allowsfor the computation of graph theoretical network metricstoquantifythetopological architecture of the brain networkdetected. The observed structural brain changes support the behavioral results reported earlier (see Colom, Román, et al., 2013

  15. Shape-Memory Hydrogels: Evolution of Structural Principles To Enable Shape Switching of Hydrophilic Polymer Networks.

    Science.gov (United States)

    Löwenberg, Candy; Balk, Maria; Wischke, Christian; Behl, Marc; Lendlein, Andreas

    2017-02-15

    The ability of hydrophilic chain segments in polymer networks to strongly interact with water allows the volumetric expansion of the material and formation of a hydrogel. When polymer chain segments undergo reversible hydration depending on environmental conditions, smart hydrogels can be realized, which are able to shrink/swell and thus alter their volume on demand. In contrast, implementing the capacity of hydrogels to switch their shape rather than volume demands more sophisticated chemical approaches and structural concepts. In this Account, the principles of hydrogel network design, incorporation of molecular switches, and hydrogel microstructures are summarized that enable a spatially directed actuation of hydrogels by a shape-memory effect (SME) without major volume alteration. The SME involves an elastic deformation (programming) of samples, which are temporarily fixed by reversible covalent or physical cross-links resulting in a temporary shape. The material can reverse to the original shape when these molecular switches are affected by application of a suitable stimulus. Hydrophobic shape-memory polymers (SMPs), which are established with complex functions including multiple or reversible shape-switching, may provide inspiration for the molecular architecture of shape-memory hydrogels (SMHs), but cannot be identically copied in the world of hydrophilic soft materials. For instance, fixation of the temporary shape requires cross-links to be formed also in an aqueous environment, which may not be realized, for example, by crystalline domains from the hydrophilic main chains as these may dissolve in presence of water. Accordingly, dual-shape hydrogels have evolved, where, for example, hydrophobic crystallizable side chains have been linked into hydrophilic polymer networks to act as temperature-sensitive temporary cross-links. By incorporating a second type of such side chains, triple-shape hydrogels can be realized. Considering the typically given light

  16. High Accuracy Human Activity Monitoring using Neural network

    CERN Document Server

    Sharma, Annapurna; Chung, Wan-Young

    2011-01-01

    This paper presents the designing of a neural network for the classification of Human activity. A Triaxial accelerometer sensor, housed in a chest worn sensor unit, has been used for capturing the acceleration of the movements associated. All the three axis acceleration data were collected at a base station PC via a CC2420 2.4GHz ISM band radio (zigbee wireless compliant), processed and classified using MATLAB. A neural network approach for classification was used with an eye on theoretical and empirical facts. The work shows a detailed description of the designing steps for the classification of human body acceleration data. A 4-layer back propagation neural network, with Levenberg-marquardt algorithm for training, showed best performance among the other neural network training algorithms.

  17. Integrated Network Architecture for Sustained Human and Robotic Exploration

    Science.gov (United States)

    Noreen, Gary; Cesarone, Robert; Deutsch, Leslie; Edwards, Charles; Soloff, Jason; Ely, Todd; Cook, Brian; Morabito, David; Hemmati, Hamid; Piazolla, Sabino; hide

    2005-01-01

    The National Aeronautics and Space Administration (NASA) Exploration Systems Enterprise is planning a series of human and robotic missions to the Earth's moon and to Mars. These missions will require communication and navigation services. This paper1 sets forth presumed requirements for such services and concepts for lunar and Mars telecommunications network architectures to satisfy the presumed requirements. The paper suggests that an inexpensive ground network would suffice for missions to the near-side of the moon. A constellation of three Lunar Telecommunications Orbiters connected to an inexpensive ground network could provide continuous redundant links to a polar lunar base and its vicinity. For human and robotic missions to Mars, a pair of areostationary satellites could provide continuous redundant links between Earth and a mid-latitude Mars base in conjunction with the Deep Space Network augmented by large arrays of 12-m antennas on Earth.

  18. Age and gender-related differences in a spatial memory task in humans.

    Science.gov (United States)

    León, Irene; Tascón, Laura; Cimadevilla, José Manuel

    2016-06-01

    Cognitive skills decline with age. Our ability to keep oriented in our surrounding environment was demonstrated to be influenced by factors like age and gender. Introduction of virtual reality based tasks improved assessment of spatial memory in humans. In this study, spatial orientation was assessed in a virtual memory task in order to determine the effect of aging and gender on navigational skills. Subjects from 45 to 74 years of age were organized in three groups (45-54, 55-64, 65-74 years old). Two levels of difficulty were considered. Results showed that males outperformed females in 65-74 years-old group. In addition to this, females showed a more noticeable poor performance in spatial memory than males, since memory differences appeared between all age groups. On the other hand, 65-74 year-old males showed an impaired performance in comparison with 45-54 year-old group. These results support that spatial memory becomes less accurate as we age and gender is an important factor influencing spatial orientation skills.

  19. Memória humana e teatro Human memory and theater

    Directory of Open Access Journals (Sweden)

    Edna de Souza Alves

    2001-01-01

    Full Text Available A memória humana é essencial para a atividade teatral. Isso por um motivo óbvio: é ela que possibilita aos atores gravarem suas falas e ao público compreender a mensagem passada pela peça. Neste trabalho, investigamos as noções de memória propostas por Descartes, Hume e Kohonen. Para eles, a memória é imprescindível na obtenção e desenvolvimento do conhecimento. A nosso ver, o estudo da memória é de grande importância para o teatro, à medida que este não seria possível sem aquela.The human memory plays an essential role in theatrical activity because it makes it possible that the actors record their lines and the public understands the message transmitted in the play. In this work, the notion of memory proposed by Descartes, Hume and Kohonen are investigated. For those thinkers, memory is indispensable to obtain and develop knowledge. In our opinion, the study of memory is of great importance for the theater, because the theater doesn't exist without memory.

  20. An association between human hippocampal volume and topographical memory in healthy young adults.

    Directory of Open Access Journals (Sweden)

    Tom eHartley

    2012-12-01

    Full Text Available The association between human hippocampal structure and topographical memory was investigated in healthy adults (N=30. Structural MR images were acquired, and voxel-based morphometry (VBM was used to estimate local gray matter volume throughout the brain. A complementary automated mesh-based segmentation approach was used to independently isolate and measure specified structures including the hippocampus. Topographical memory was assessed using a version of the Four Mountains Task, a short test designed to target hippocampal spatial function. Each item requires subjects to briefly study a landscape scene before recognizing the depicted place from a novel viewpoint and under altered non-spatial conditions when presented amongst similar alternative scenes. Positive correlations between topographical memory performance and hippocampal volume were observed in both VBM and segmentation-based analyses. Score on the topographical memory task was also correlated with the volume of some subcortical structures, extra-hippocampal gray matter and total brain volume, with the most robust and extensive covariation seen in circumscribed neocortical regions in the insula and anterior temporal lobes. Taken together with earlier findings, the results suggest that global variations in brain morphology affect the volume of the hippocampus and its specific contribution to topographical memory. We speculate that behavioral variation might arise directly through the impact of resource constraints on spatial representations in the hippocampal formation and its inputs, and perhaps indirectly through an increased reliance on non-allocentric strategies.

  1. Reproducibility of graph metrics of human brain functional networks.

    Science.gov (United States)

    Deuker, Lorena; Bullmore, Edward T; Smith, Marie; Christensen, Soren; Nathan, Pradeep J; Rockstroh, Brigitte; Bassett, Danielle S

    2009-10-01

    Graph theory provides many metrics of complex network organization that can be applied to analysis of brain networks derived from neuroimaging data. Here we investigated the test-retest reliability of graph metrics of functional networks derived from magnetoencephalography (MEG) data recorded in two sessions from 16 healthy volunteers who were studied at rest and during performance of the n-back working memory task in each session. For each subject's data at each session, we used a wavelet filter to estimate the mutual information (MI) between each pair of MEG sensors in each of the classical frequency intervals from gamma to low delta in the overall range 1-60 Hz. Undirected binary graphs were generated by thresholding the MI matrix and 8 global network metrics were estimated: the clustering coefficient, path length, small-worldness, efficiency, cost-efficiency, assortativity, hierarchy, and synchronizability. Reliability of each graph metric was assessed using the intraclass correlation (ICC). Good reliability was demonstrated for most metrics applied to the n-back data (mean ICC=0.62). Reliability was greater for metrics in lower frequency networks. Higher frequency gamma- and beta-band networks were less reliable at a global level but demonstrated high reliability of nodal metrics in frontal and parietal regions. Performance of the n-back task was associated with greater reliability than measurements on resting state data. Task practice was also associated with greater reliability. Collectively these results suggest that graph metrics are sufficiently reliable to be considered for future longitudinal studies of functional brain network changes.

  2. Reassembling the Social Environment: A Network Approack to Human Behavior

    OpenAIRE

    Dhrubodhi Mukherjee

    2007-01-01

    This paper critically examines the influence of the structural elements of human behavior that are often neglected in social work literature (Robbins et al., 1998). It incorporates a new multi-theoretical framework that critically examines the significance of a network approach in analyzing social, ideological, and economic structures and their influence on individual actors. This paper discusses two interrelated theories: social network theory and social capital theory, and critiques their r...

  3. Network effects in a human capital based economic growth model

    Science.gov (United States)

    Vaz Martins, Teresa; Araújo, Tanya; Augusta Santos, Maria; St Aubyn, Miguel

    2009-06-01

    We revisit a recently introduced agent model [ACS, 11, 99 (2008)], where economic growth is a consequence of education (human capital formation) and innovation, and investigate the influence of the agents’ social network, both on an agent’s decision to pursue education and on the output of new ideas. Regular and random networks are considered. The results are compared with the predictions of a mean field (representative agent) model.

  4. Digital Humanities and networked digital media

    DEFF Research Database (Denmark)

    Finnemann, Niels Ole

    2014-01-01

    This article discusses digital humanities and the growing diversity of digital media, digital materials and digital methods. The first section describes the humanities computing tradition formed around the interpretation of computation as a rule-based process connected to a concept of digital...... of software-supported methods. This is so, in part, because of the complexity of the world and, in part, because digital media remain open to the projection of new epistemologies onto the functional architecture of these media. The third section discusses the heterogeneous character of digital materials...... materials centred on the digitisation of non-digital, finite works, corpora and oeuvres. The second section discusses “the big tent” of contemporary digital humanities. It is argued that there can be no unifying interpretation of digital humanities above the level of studying digital materials with the help...

  5. MicroRNA-138 is a potential regulator of memory performance in humans

    Directory of Open Access Journals (Sweden)

    Julia eSchröder

    2014-07-01

    Full Text Available Genetic factors underlie a substantial proportion of individual differences in cognitive functions in humans, including processes related to episodic and working memory. While genetic association studies have proposed several candidate memory genes, these currently explain only a minor fraction of the phenotypic variance. Here, we performed genome-wide screening on 13 episodic and working memory phenotypes in 1,318 participants of the Berlin Aging Study II aged 60 years or older. The analyses highlight a number of novel single nucleotide polymorphisms (SNPs associated with memory performance, including one located in a putative regulatory region of microRNA (miRNA hsa-mir-138-5p (rs9882688, P-value = 7.8x10-9. Expression quantitative trait locus analyses on next-generation RNA-sequencing data revealed that rs9882688 genotypes show a significant correlation with the expression levels of this miRNA in 309 human lymphoblastoid cell lines (P-value = 5x10-4. In silico modeling of other top-ranking GWAS signals identified an additional memory-associated SNP in the 3' untranslated region (3'UTR of DCP1B, a gene encoding a core component of the mRNA decapping complex in humans, predicted to interfere with hsa-mir-138-5p binding. This prediction was confirmed in vitro by luciferase assays showing differential binding of hsa-mir-138-5p to 3'UTR reporter constructs in two human cell lines (HEK293: P-value = 0.0470; SH-SY5Y: P-value = 0.0866. Finally, expression profiling of hsa-mir-138-5p and DCP1B mRNA in human post-mortem brain tissue revealed that both molecules are expressed simultaneously in frontal cortex and hippocampus, suggesting that the proposed interaction between hsa-mir-138-5p and DCP1B may also take place in vivo. In summary, by combining unbiased genome-wide screening with extensive in silico modeling, in vitro functional assays, and gene expression profiling, our study identified miRNA-138 as a potential molecular regulator of human memory

  6. MicroRNA-138 is a potential regulator of memory performance in humans

    Science.gov (United States)

    Schröder, Julia; Ansaloni, Sara; Schilling, Marcel; Liu, Tian; Radke, Josefine; Jaedicke, Marian; Schjeide, Brit-Maren M.; Mashychev, Andriy; Tegeler, Christina; Radbruch, Helena; Papenberg, Goran; Düzel, Sandra; Demuth, Ilja; Bucholtz, Nina; Lindenberger, Ulman; Li, Shu-Chen; Steinhagen-Thiessen, Elisabeth; Lill, Christina M.; Bertram, Lars

    2014-01-01

    Genetic factors underlie a substantial proportion of individual differences in cognitive functions in humans, including processes related to episodic and working memory. While genetic association studies have proposed several candidate “memory genes,” these currently explain only a minor fraction of the phenotypic variance. Here, we performed genome-wide screening on 13 episodic and working memory phenotypes in 1318 participants of the Berlin Aging Study II aged 60 years or older. The analyses highlight a number of novel single nucleotide polymorphisms (SNPs) associated with memory performance, including one located in a putative regulatory region of microRNA (miRNA) hsa-mir-138-5p (rs9882688, P-value = 7.8 × 10−9). Expression quantitative trait locus analyses on next-generation RNA-sequencing data revealed that rs9882688 genotypes show a significant correlation with the expression levels of this miRNA in 309 human lymphoblastoid cell lines (P-value = 5 × 10−4). In silico modeling of other top-ranking GWAS signals identified an additional memory-associated SNP in the 3′ untranslated region (3′ UTR) of DCP1B, a gene encoding a core component of the mRNA decapping complex in humans, predicted to interfere with hsa-mir-138-5p binding. This prediction was confirmed in vitro by luciferase assays showing differential binding of hsa-mir-138-5p to 3′ UTR reporter constructs in two human cell lines (HEK293: P-value = 0.0470; SH-SY5Y: P-value = 0.0866). Finally, expression profiling of hsa-mir-138-5p and DCP1B mRNA in human post-mortem brain tissue revealed that both molecules are expressed simultaneously in frontal cortex and hippocampus, suggesting that the proposed interaction between hsa-mir-138-5p and DCP1B may also take place in vivo. In summary, by combining unbiased genome-wide screening with extensive in silico modeling, in vitro functional assays, and gene expression profiling, our study identified miRNA-138 as a potential molecular regulator of

  7. Modeling human dynamics of face-to-face interaction networks

    CERN Document Server

    Starnini, Michele; Pastor-Satorras, Romualdo

    2013-01-01

    Face-to-face interaction networks describe social interactions in human gatherings, and are the substrate for processes such as epidemic spreading and gossip propagation. The bursty nature of human behavior characterizes many aspects of empirical data, such as the distribution of conversation lengths, of conversations per person, or of inter-conversation times. Despite several recent attempts, a general theoretical understanding of the global picture emerging from data is still lacking. Here we present a simple model that reproduces quantitatively most of the relevant features of empirical face-to-face interaction networks. The model describes agents which perform a random walk in a two dimensional space and are characterized by an attractiveness whose effect is to slow down the motion of people around them. The proposed framework sheds light on the dynamics of human interactions and can improve the modeling of dynamical processes taking place on the ensuing dynamical social networks.

  8. Temporal networks of face-to-face human interactions

    CERN Document Server

    Barrat, Alain

    2013-01-01

    The ever increasing adoption of mobile technologies and ubiquitous services allows to sense human behavior at unprecedented levels of details and scale. Wearable sensors are opening up a new window on human mobility and proximity at the finest resolution of face-to-face proximity. As a consequence, empirical data describing social and behavioral networks are acquiring a longitudinal dimension that brings forth new challenges for analysis and modeling. Here we review recent work on the representation and analysis of temporal networks of face-to-face human proximity, based on large-scale datasets collected in the context of the SocioPatterns collaboration. We show that the raw behavioral data can be studied at various levels of coarse-graining, which turn out to be complementary to one another, with each level exposing different features of the underlying system. We briefly review a generative model of temporal contact networks that reproduces some statistical observables. Then, we shift our focus from surface ...

  9. DIFFERENCE FEATURE NEURAL NETWORK IN RECOGNITION OF HUMAN FACES

    Institute of Scientific and Technical Information of China (English)

    Chen Gang; Qi Feihu

    2001-01-01

    This article discusses vision recognition process and finds out that human recognizes objects not by their isolated features, but by their main difference features which people get by contrasting them. According to the resolving character of difference features for vision recognition, the difference feature neural network(DFNN) which is the improved auto-associative neural network is proposed.Using ORL database, the comparative experiment for face recognition with face images and the ones added Gaussian noise is performed, and the result shows that DFNN is better than the auto-associative neural network and it proves DFNN is more efficient.

  10. Flow distributions and spatial correlations in human brain capillary networks

    Science.gov (United States)

    Lorthois, Sylvie; Peyrounette, Myriam; Larue, Anne; Le Borgne, Tanguy

    2015-11-01

    The vascular system of the human brain cortex is composed of a space filling mesh-like capillary network connected upstream and downstream to branched quasi-fractal arterioles and venules. The distribution of blood flow rates in these networks may affect the efficiency of oxygen transfer processes. Here, we investigate the distribution and correlation properties of blood flow velocities from numerical simulations in large 3D human intra-cortical vascular network (10000 segments) obtained from an anatomical database. In each segment, flow is solved from a 1D non-linear model taking account of the complex rheological properties of blood flow in microcirculation to deduce blood pressure, blood flow and red blood cell volume fraction distributions throughout the network. The network structural complexity is found to impart broad and spatially correlated Lagrangian velocity distributions, leading to power law transit time distributions. The origins of this behavior (existence of velocity correlations in capillary networks, influence of the coupling with the feeding arterioles and draining veins, topological disorder, complex blood rheology) are studied by comparison with results obtained in various model capillary networks of controlled disorder. ERC BrainMicroFlow GA615102, ERC ReactiveFronts GA648377.

  11. Synergistic Effects of Human Milk Nutrients in the Support of Infant Recognition Memory: An Observational Study.

    Science.gov (United States)

    Cheatham, Carol L; Sheppard, Kelly Will

    2015-11-03

    The aim was to explore the relation of human milk lutein; choline; and docosahexaenoic acid (DHA) with recognition memory abilities of six-month-olds. Milk samples obtained three to four months postpartum were analyzed for fatty acids, lutein, and choline. At six months, participants were invited to an electrophysiology session. Recognition memory was tested with a 70-30 oddball paradigm in a high-density 128-lead event-related potential (ERP) paradigm. Complete data were available for 55 participants. Data were averaged at six groupings (Frontal Right; Frontal Central; Frontal Left; Central; Midline; and Parietal) for latency to peak, peak amplitude, and mean amplitude. Difference scores were calculated as familiar minus novel. Final regression models revealed the lutein X free choline interaction was significant for the difference in latency scores at frontal and central areas (p memory. The DHA X free choline interaction was also significant for the difference in latency scores at frontal, central, and midline areas (p memory. Interactions between human milk nutrients appear important in predicting infant cognition, and there may be a benefit to specific nutrient combinations.

  12. Synergistic Effects of Human Milk Nutrients in the Support of Infant Recognition Memory: An Observational Study

    Directory of Open Access Journals (Sweden)

    Carol L. Cheatham

    2015-11-01

    Full Text Available The aim was to explore the relation of human milk lutein; choline; and docosahexaenoic acid (DHA with recognition memory abilities of six-month-olds. Milk samples obtained three to four months postpartum were analyzed for fatty acids, lutein, and choline. At six months, participants were invited to an electrophysiology session. Recognition memory was tested with a 70–30 oddball paradigm in a high-density 128-lead event-related potential (ERP paradigm. Complete data were available for 55 participants. Data were averaged at six groupings (Frontal Right; Frontal Central; Frontal Left; Central; Midline; and Parietal for latency to peak, peak amplitude, and mean amplitude. Difference scores were calculated as familiar minus novel. Final regression models revealed the lutein X free choline interaction was significant for the difference in latency scores at frontal and central areas (p < 0.05 and p < 0.001; respectively. Higher choline levels with higher lutein levels were related to better recognition memory. The DHA X free choline interaction was also significant for the difference in latency scores at frontal, central, and midline areas (p < 0.01; p < 0.001; p < 0.05 respectively. Higher choline with higher DHA was related to better recognition memory. Interactions between human milk nutrients appear important in predicting infant cognition, and there may be a benefit to specific nutrient combinations.

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

    Science.gov (United States)

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

    2008-03-01

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

  14. Development of human brain structural networks through infancy and childhood.

    Science.gov (United States)

    Huang, Hao; Shu, Ni; Mishra, Virendra; Jeon, Tina; Chalak, Lina; Wang, Zhiyue J; Rollins, Nancy; Gong, Gaolang; Cheng, Hua; Peng, Yun; Dong, Qi; He, Yong

    2015-05-01

    During human brain development through infancy and childhood, microstructural and macrostructural changes take place to reshape the brain's structural networks and better adapt them to sophisticated functional and cognitive requirements. However, structural topological configuration of the human brain during this specific development period is not well understood. In this study, diffusion magnetic resonance image (dMRI) of 25 neonates, 13 toddlers, and 25 preadolescents were acquired to characterize network dynamics at these 3 landmark cross-sectional ages during early childhood. dMRI tractography was used to construct human brain structural networks, and the underlying topological properties were quantified by graph-theory approaches. Modular organization and small-world attributes are evident at birth with several important topological metrics increasing monotonically during development. Most significant increases of regional nodes occur in the posterior cingulate cortex, which plays a pivotal role in the functional default mode network. Positive correlations exist between nodal efficiencies and fractional anisotropy of the white matter traced from these nodes, while correlation slopes vary among the brain regions. These results reveal substantial topological reorganization of human brain structural networks through infancy and childhood, which is likely to be the outcome of both heterogeneous strengthening of the major white matter tracts and pruning of other axonal fibers. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

    Science.gov (United States)

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

    2015-03-01

    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.

  16. Gambiense human african trypanosomiasis and immunological memory: effect on phenotypic lymphocyte profiles and humoral immunity.

    Science.gov (United States)

    Lejon, Veerle; Mumba Ngoyi, Dieudonné; Kestens, Luc; Boel, Luc; Barbé, Barbara; Kande Betu, Victor; van Griensven, Johan; Bottieau, Emmanuel; Muyembe Tamfum, Jean-Jacques; Jacobs, Jan; Büscher, Philippe

    2014-03-01

    In mice, experimental infection with Trypanosoma brucei causes decreased bone marrow B-cell development, abolished splenic B-cell maturation and loss of antibody mediated protection including vaccine induced memory responses. Nothing is known about this phenomenon in human African trypanosomiasis (HAT), but if occurring, it would imply the need of revaccination of HAT patients after therapy and abolish hope for a HAT vaccine. The effect of gambiense HAT on peripheral blood memory T- and B-cells and on innate and vaccine induced antibody levels was examined. The percentage of memory B- and T-cells was quantified in peripheral blood, prospectively collected in DR Congo from 117 Trypanosoma brucei gambiense infected HAT patients before and six months after treatment and 117 controls at the same time points. Antibodies against carbohydrate antigens on red blood cells and against measles were quantified. Before treatment, significantly higher percentages of memory B-cells, mainly T-independent memory B-cells, were observed in HAT patients compared to controls (CD20+CD27+IgM+, 13.0% versus 2.0%, p<0.001). The percentage of memory T-cells, mainly early effector/memory T-cells, was higher in HAT (CD3+CD45RO+CD27+, 19.4% versus 16.7%, p = 0.003). After treatment, the percentage of memory T-cells normalized, the percentage of memory B-cells did not. The median anti-red blood cell carbohydrate IgM level was one titer lower in HAT patients than in controls (p<0.004), and partially normalized after treatment. Anti-measles antibody concentrations were lower in HAT patients than in controls (medians of 1500 versus 2250 mIU/ml, p = 0.02), and remained so after treatment, but were above the cut-off level assumed to provide protection in 94.8% of HAT patients, before and after treatment (versus 98.3% of controls, p = 0.3). Although functionality of the B-cells was not verified, the results suggest that immunity was conserved in T.b. gambiense infected HAT patients and

  17. A real-time in-memory discovery service leveraging hierarchical packaging information in a unique identifier network to retrieve track and trace information

    CERN Document Server

    Müller, Jürgen

    2014-01-01

    This book examines how to efficiently retrieve track and trace information for an item that took a certain path through a complex network of manufacturers, wholesalers, retailers and consumers. It includes valuable tips on in-memory data management.

  18. Acute and Non-acute Effects of Cannabis on Human Memory Function: A Critical Review of Neuroimaging Studies

    NARCIS (Netherlands)

    Bossong, M.G.; Jager, G.; Bhattacharyya, S.; Allen, P.

    2014-01-01

    Smoking cannabis produces a diverse range of effects, including impairments in learning and memory. These effects are exerted through action on the endocannabinoid system, which suggests involvement of this system in human cognition. Learning and memory deficits are core symptoms of psychiatric and

  19. Effects of ¿9-Tetrahydrocannabinol Administration on human encoding and recall memory function: a pharmacological fMRI study

    NARCIS (Netherlands)

    Bossong, M.G.; Jager, G.; Hell, van H.H.; Zuurman, L.; Jansma, J.M.; Mehta, M.A.; Gerven, van J.; Kahn, R.S.; Ramsey, N.F.

    2012-01-01

    Deficits in memory function are an incapacitating aspect of various psychiatric and neurological disorders. Animal studies have recently provided strong evidence for involvement of the endocannabinoid (eCB) system in memory function. Neuropsychological studies in humans have shown less convincing

  20. Effects of ¿9-Tetrahydrocannabinol Administration on human encoding and recall memory function: a pharmacological fMRI study

    NARCIS (Netherlands)

    Bossong, M.G.; Jager, G.; Hell, van H.H.; Zuurman, L.; Jansma, J.M.; Mehta, M.A.; Gerven, van J.; Kahn, R.S.; Ramsey, N.F.

    2012-01-01

    Deficits in memory function are an incapacitating aspect of various psychiatric and neurological disorders. Animal studies have recently provided strong evidence for involvement of the endocannabinoid (eCB) system in memory function. Neuropsychological studies in humans have shown less convincing ev

  1. Acute and Non-acute Effects of Cannabis on Human Memory Function: A Critical Review of Neuroimaging Studies

    NARCIS (Netherlands)

    Bossong, M.G.; Jager, G.; Bhattacharyya, S.; Allen, P.

    2014-01-01

    Smoking cannabis produces a diverse range of effects, including impairments in learning and memory. These effects are exerted through action on the endocannabinoid system, which suggests involvement of this system in human cognition. Learning and memory deficits are core symptoms of psychiatric and

  2. Effects of ¿9-Tetrahydrocannabinol Administration on human encoding and recall memory function: a pharmacological fMRI study

    NARCIS (Netherlands)

    Bossong, M.G.; Jager, G.; Hell, van H.H.; Zuurman, L.; Jansma, J.M.; Mehta, M.A.; Gerven, van J.; Kahn, R.S.; Ramsey, N.F.

    2012-01-01

    Deficits in memory function are an incapacitating aspect of various psychiatric and neurological disorders. Animal studies have recently provided strong evidence for involvement of the endocannabinoid (eCB) system in memory function. Neuropsychological studies in humans have shown less convincing ev

  3. Context-dependent encoding of fear and extinction memories in a large-scale network model of the basal amygdala.

    OpenAIRE

    Ioannis Vlachos; Cyril Herry; Andreas Lüthi; Ad Aertsen; Arvind Kumar

    2011-01-01

    International audience; The basal nucleus of the amygdala (BA) is involved in the formation of context-dependent conditioned fear and extinction memories. To understand the underlying neural mechanisms we developed a large-scale neuron network model of the BA, composed of excitatory and inhibitory leaky-integrate-and-fire neurons. Excitatory BA neurons received conditioned stimulus (CS)-related input from the adjacent lateral nucleus (LA) and contextual input from the hippocampus or medial pr...

  4. Altered short-term plasticity within the working memory neural network: Is it neuroticism or is it depression?

    Science.gov (United States)

    Bianchi, Renzo; Laurent, Eric

    2016-04-01

    In the present article, we discuss (1) the importance of assessing and statistically considering both clinical and subclinical forms of depression when examining the relationship between neuroticism and short-term plasticity within the working memory neural network, and (2) the hypothesis of an antagonism between neuroticism and conscientiousness in personality research. We suggest that (1) neuroticism and depression should be examined in a relational manner, and (2) neuroticism and conscientiousness should not be antagonized.

  5. Analyzing, Modeling, and Simulation for Human Dynamics in Social Network

    Directory of Open Access Journals (Sweden)

    Yunpeng Xiao

    2012-01-01

    Full Text Available This paper studies the human behavior in the top-one social network system in China (Sina Microblog system. By analyzing real-life data at a large scale, we find that the message releasing interval (intermessage time obeys power law distribution both at individual level and at group level. Statistical analysis also reveals that human behavior in social network is mainly driven by four basic elements: social pressure, social identity, social participation, and social relation between individuals. Empirical results present the four elements' impact on the human behavior and the relation between these elements. To further understand the mechanism of such dynamic phenomena, a hybrid human dynamic model which combines “interest” of individual and “interaction” among people is introduced, incorporating the four elements simultaneously. To provide a solid evaluation, we simulate both two-agent and multiagent interactions with real-life social network topology. We achieve the consistent results between empirical studies and the simulations. The model can provide a good understanding of human dynamics in social network.

  6. Security Implications of Human-Trafficking Networks

    Science.gov (United States)

    2007-06-15

    to those security concerns. Background How is Human Trafficking Carried Out? While trafficking victims are often found in sweatshops , domestic...labor. This type of trafficking is often found in agricultural labor, the production of goods (typically called sweatshops ) and construction labor

  7. Identification of a Typical CSTR Using Optimal Focused Time Lagged Recurrent Neural Network Model with Gamma Memory Filter

    Directory of Open Access Journals (Sweden)

    S. N. Naikwad

    2009-01-01

    Full Text Available A focused time lagged recurrent neural network (FTLR NN with gamma memory filter is designed to learn the subtle complex dynamics of a typical CSTR process. Continuous stirred tank reactor exhibits complex nonlinear operations where reaction is exothermic. It is noticed from literature review that process control of CSTR using neuro-fuzzy systems was attempted by many, but optimal neural network model for identification of CSTR process is not yet available. As CSTR process includes temporal relationship in the input-output mappings, time lagged recurrent neural network is particularly used for identification purpose. The standard back propagation algorithm with momentum term has been proposed in this model. The various parameters like number of processing elements, number of hidden layers, training and testing percentage, learning rule and transfer function in hidden and output layer are investigated on the basis of performance measures like MSE, NMSE, and correlation coefficient on testing data set. Finally effects of different norms are tested along with variation in gamma memory filter. It is demonstrated that dynamic NN model has a remarkable system identification capability for the problems considered in this paper. Thus FTLR NN with gamma memory filter can be used to learn underlying highly nonlinear dynamics of the system, which is a major contribution of this paper.

  8. Acting bodies and social networks a bridge between technology and working memory

    CERN Document Server

    Pirani, Bianca Maria

    2009-01-01

    Acting Bodies and Social Networks analyzes the complex interactions of body, mind and microelectronic technologies. Internationally renowned scholars look into the nature of the mind - a combination of thought, perception, emotion, will and imagination - as well as the ever-increasing impact and complexity of microelectronic technologies. The proliferation of these technologies facilitates a profound change in the boundaries between bodies and technologies. These technologies expand the temporal and spatial existence of humans; today, people can instantly communicate all over the world and ove

  9. Human-specific transcriptional networks in the brain.

    Science.gov (United States)

    Konopka, Genevieve; Friedrich, Tara; Davis-Turak, Jeremy; Winden, Kellen; Oldham, Michael C; Gao, Fuying; Chen, Leslie; Wang, Guang-Zhong; Luo, Rui; Preuss, Todd M; Geschwind, Daniel H

    2012-08-23

    Understanding human-specific patterns of brain gene expression and regulation can provide key insights into human brain evolution and speciation. Here, we use next-generation sequencing, and Illumina and Affymetrix microarray platforms, to compare the transcriptome of human, chimpanzee, and macaque telencephalon. Our analysis reveals a predominance of genes differentially expressed within human frontal lobe and a striking increase in transcriptional complexity specific to the human lineage in the frontal lobe. In contrast, caudate nucleus gene expression is highly conserved. We also identify gene coexpression signatures related to either neuronal processes or neuropsychiatric diseases, including a human-specific module with CLOCK as its hub gene and another module enriched for neuronal morphological processes and genes coexpressed with FOXP2, a gene important for language evolution. These data demonstrate that transcriptional networks have undergone evolutionary remodeling even within a given brain region, providing a window through which to view the foundation of uniquely human cognitive capacities.

  10. Molecular networks and the evolution of human cognitive specializations.

    Science.gov (United States)

    Fontenot, Miles; Konopka, Genevieve

    2014-12-01

    Inroads into elucidating the origins of human cognitive specializations have taken many forms, including genetic, genomic, anatomical, and behavioral assays that typically compare humans to non-human primates. While the integration of all of these approaches is essential for ultimately understanding human cognition, here, we review the usefulness of coexpression network analysis for specifically addressing this question. An increasing number of studies have incorporated coexpression networks into brain expression studies comparing species, disease versus control tissue, brain regions, or developmental time periods. A clearer picture has emerged of the key genes driving brain evolution, as well as the developmental and regional contributions of gene expression patterns important for normal brain development and those misregulated in cognitive diseases. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Development of Spatial and Verbal Working Memory Capacity in the Human Brain

    Science.gov (United States)

    Thomason, Moriah E.; Race, Elizabeth; Burrows, Brittany; Whitfield-Gabrieli, Susan; Glover, Gary H.; Gabrieli, John D. E.

    2009-01-01

    A core aspect of working memory (WM) is the capacity to maintain goal-relevant information in mind, but little is known about how this capacity develops in the human brain. We compared brain activation, via fMRI, between children (ages 7-12 years) and adults (ages 20-29 years) performing tests of verbal and spatial WM with varying amounts (loads)…

  12. Development of Spatial and Verbal Working Memory Capacity in the Human Brain

    Science.gov (United States)

    Thomason, Moriah E.; Race, Elizabeth; Burrows, Brittany; Whitfield-Gabrieli, Susan; Glover, Gary H.; Gabrieli, John D. E.

    2009-01-01

    A core aspect of working memory (WM) is the capacity to maintain goal-relevant information in mind, but little is known about how this capacity develops in the human brain. We compared brain activation, via fMRI, between children (ages 7-12 years) and adults (ages 20-29 years) performing tests of verbal and spatial WM with varying amounts (loads)…

  13. Human behavior understanding in networked sensing theory and applications of networks of sensors

    CERN Document Server

    Spagnolo, Paolo; Distante, Cosimo

    2014-01-01

    This unique text/reference provides a broad overview of both the technical challenges in sensor network development, and the real-world applications of distributed sensing. Important aspects of distributed computing in large-scale networked sensor systems are analyzed in the context of human behavior understanding, including such topics as systems design tools and techniques, in-network signals, and information processing. Additionally, the book examines a varied range of application scenarios, covering surveillance, indexing and retrieval, patient care, industrial safety, social and ambient

  14. The role of awareness and working memory in human transitive inference.

    Science.gov (United States)

    Libben, M; Titone, D

    2008-01-01

    The human ability to perform transitive inference (TI) is an area of debate from a neurocognitive standpoint. Some studies emphasize a stimulus driven medial-temporal lobe process [Preston, A.R., Shrager, Y., Dudukovic, N.M., Gabrieli, J.D., 2004. Hippocampal contribution to the novel use of relational information in declarative memory. Hippocampus 14, 148-152; Titone, D., Ditman, T., Holzman, P., Eichenbaum, H., Levy, D., 2004. A transitive inference test of relational memory in schizophrenia. Schizophr. Res. 68, 235-247; Van Elzakker, M., O'Reilley, R., Rudy, J., 2003. Transivity, flexibility, conjenctive representation and the hippocampus: an empirical analysis. Hippocampus 13, 334-340] while others emphasize a higher-level frontal lobe strategy that requires the flexible maintenance of information in working memory [Waltz, J., Knowlton, B., Holyoak, K., Boone, K., Mishkin, F., de Menedezes Santos, M., Thomas, C., Miller, B., 1999. A system for relational reasoning in human prefrontal cortex. Psychol. Sci. 10, 119-125]. In two experiments we investigated when and how adults employ different cognitive strategies during TI by evaluating the interaction between task instructions and individual differences in working memory capacity. Participants engaged in a paired discrimination task involving a 6-unit TI hierarchy and were either prior aware, prior unaware or serendipitously aware of the hierarchical relationship among stimulus items. Both prior aware participants and serendipitously aware participants were more likely to engage in a logic-based strategy compared to unaware participants who relied upon stimulus-driven strategies. Individual differences in working memory were associated with the acquisition of awareness in the serendipitously aware group and with the maintenance of awareness in the prior aware group. These findings suggest that the capacity for TI may be supported by multiple neurocognitive strategies, and that the specific strategy employed is

  15. Studying frequency processing of the brain to enhance long-term memory and develop a human brain protocol.

    Science.gov (United States)

    Friedrich, Wernher; Du, Shengzhi; Balt, Karlien

    2015-01-01

    The temporal lobe in conjunction with the hippocampus is responsible for memory processing. The gamma wave is involved with this process. To develop a human brain protocol, a better understanding of the relationship between gamma and long-term memory is vital. A more comprehensive understanding of the human brain and specific analogue waves it uses will support the development of a human brain protocol. Fifty-eight participants aged between 6 and 60 years participated in long-term memory experiments. It is envisaged that the brain could be stimulated through binaural beats (sound frequency) at 40 Hz (gamma) to enhance long-term memory capacity. EEG recordings have been transformed to sound and then to an information standard, namely ASCII. Statistical analysis showed a proportional relationship between long-term memory and gamma activity. Results from EEG recordings indicate a pattern. The pattern was obtained through the de-codification of an EEG recording to sound and then to ASCII. Stimulation of gamma should enhance long term memory capacity. More research is required to unlock the human brains' protocol key. This key will enable the processing of information directly to and from human memory via gamma, the hippocampus and the temporal lobe.

  16. Novelty detection and encoding for declarative memory within the human hippocampus.

    Science.gov (United States)

    Grunwald, Thomas; Kurthen, Martin

    2006-10-01

    Intracranial recordings of cognitive potentials within the human hippocampal system have identified N400 potentials in the anterior mesial temporal lobe (AMTL-N400) that correlate with verbal memory performance and are associated with novelty detection. Their amplitudes to "new" but not "old" words in a verbal recognition task correlate with the neuronal density of the hippocampal CA1-region and can be reduced selectively by the NMDA-receptor blocker ketamine. Moreover, it could be shown that NMDA-receptor dependent long-term potentiation (LTP), a form of synaptic plasticity with Hebbian characteristics, can be readily induced in human hippocampal slices but not in patients with hippocampal sclerosis. In these latter patients, we also found a reduction of AMTL-N400 amplitudes similar to the one induced by ketamine. In addition, we could show that hippocampal novelty detection is associated with successful encoding for declarative memory. Together, our findings suggest that successful encoding for declarative memory is at least in part mediated by NMDA-receptor dependent novelty detection within the human hippocampal system.

  17. Network structure dependence on unconstrained isothermal-recovery processes for shape-memory thiol-epoxy "click" systems

    Science.gov (United States)

    Belmonte, Alberto; Fernández-Francos, Xavier; De la Flor, Silvia; Serra, Àngels

    2016-07-01

    The shape-memory response (SMR) of "click" thiol-epoxy polymers produced using latent catalysts, with different network structure and thermo-mechanical properties, was tested on unconstrained shape-recovery processes under isothermal conditions. Experiments at several programming temperatures ( T_{prog}) and isothermal-recovery temperatures ( T_{iso}) were carried out, and the shape-memory stability was analyzed through various consecutive shape-memory cycles. The temperature profile during the isothermal-recovery experiments was monitored, and it showed that the shape-recovery process takes place while the sample is becoming thermally stable and before stable isothermal temperature conditions are eventually reached. The shape-recovery process takes place in two different stages regardless of T_{iso}: a slow initial stage until the process is triggered at a temperature strongly related with the beginning of network relaxation, followed by the typical exponential decay of the relaxation processes until completion at a temperature below or very close to Tg. The shape-recovery process is slower in materials with more densely crosslinked and hindered network structures. The shape-recovery time ( t_{sr}) is significantly reduced when the isothermal-recovery temperature T_{iso} increases from below to above Tg because the network relaxation dynamics accelerates. However, the temperature range from the beginning to the end of the recovery process is hardly affected by T_{iso}; at higher T_{iso} it is only slightly shifted to higher temperatures. These results suggest that the shape-recovery process can be controlled by changing the network structure and working at T_{iso} < Tg to maximize the effect of the structure and/or by increasing T_{iso} to minimize the effect but increasing the shape-recovery rate.

  18. Noninvasively decoding the contents of visual working memory in the human prefrontal cortex within high-gamma oscillatory patterns.

    Science.gov (United States)

    Polanía, Rafael; Paulus, Walter; Nitsche, Michael A

    2012-02-01

    The temporal maintenance and subsequent retrieval of information that no longer exists in the environment is called working memory. It is believed that this type of memory is controlled by the persistent activity of neuronal populations, including the prefrontal, temporal, and parietal cortex. For a long time, it has been controversially discussed whether, in working memory, the PFC stores past sensory events or, instead, its activation is an extramnemonic source of top-down control over posterior regions. Recent animal studies suggest that specific information about the contents of working memory can be decoded from population activity in prefrontal areas. However, it has not been shown whether the contents of working memory during the delay periods can be decoded from EEG recordings in the human brain. We show that by analyzing the nonlinear dynamics of EEG oscillatory patterns it is possible to noninvasively decode with high accuracy, during encoding and maintenance periods, the contents of visual working memory information within high-gamma oscillations in the human PFC. These results are thus in favor of an active storage function of the human PFC in working memory; this, without ruling out the role of PFC in top-down processes. The ability to noninvasively decode the contents of working memory is promising in applications such as brain computer interfaces, together with computation of value function during planning and decision making processes.

  19. Modules of human micro-RNA co-target network

    Science.gov (United States)

    Basu, Mahashweta; Bhattacharyya, Nitai P.; Mohanty, P. K.

    2011-05-01

    Human micro RNAs (miRNAs) target about 90% of the coding genes and form a complex regulatory network. We study the community structure of the miRNA co-target network considering miRNAs as the nodes which are connected by weighted links. The weight of link that connects a pair of miRNAs denote the total number of common transcripts targeted by that pair. We argue that the network consists of about 74 modules, quite similar to the components (or clusters) obtained earlier [Online J Bioinformatics, 10,280], indicating that the components of the miRNA co-target network are self organized in a way to maximize the modularity.