WorldWideScience

Sample records for human memory network

  1. The working memory networks of the human brain.

    Science.gov (United States)

    Linden, David E J

    2007-06-01

    Working memory and short-term memory are closely related in their cognitive architecture, capacity limitations, and functional neuroanatomy, which only partly overlap with those of long-term memory. The author reviews the functional neuroimaging literature on the commonalities and differences between working memory and short-term memory and the interplay of areas with modality-specific and supramodal representations in the brain networks supporting these fundamental cognitive processes. Sensory stores in the visual, auditory, and somatosensory cortex play a role in short-term memory, but supramodal parietal and frontal areas are often recruited as well. Classical working memory operations such as manipulation, protection against interference, or updating almost certainly require at least some degree of prefrontal support, but many pure maintenance tasks involve these areas as well. Although it seems that activity shifts from more posterior regions during encoding to more anterior regions during delay, some studies reported sustained delay activity in sensory areas as well. This spatiotemporal complexity of the short-term memory/working memory networks is mirrored in the activation patterns that may explain capacity constraints, which, although most prominent in the parietal cortex, seem to be pervasive across sensory and premotor areas. Finally, the author highlights open questions for cognitive neuroscience research of working memory, such as that of the mechanisms for integrating different types of content (binding) or those providing the link to long-term memory.

  2. Context-dependent human extinction memory is mediated by a ventromedial prefrontal and hippocampal network.

    Science.gov (United States)

    Kalisch, Raffael; Korenfeld, Elian; Stephan, Klaas E; Weiskopf, Nikolaus; Seymour, Ben; Dolan, Raymond J

    2006-09-13

    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 with theoretical predictions derived from animal studies, we show that, after extinction, a CS-evoked engagement of human ventromedial prefrontal cortex (VMPFC) and hippocampus is context dependent, being expressed in an extinction, but not a conditioning, context. Likewise, a positive correlation between VMPFC and hippocampal activity is extinction context dependent. Thus, a VMPFC-hippocampal network provides for context-dependent recall of human extinction memory, consistent with a view that hippocampus confers context dependence on VMPFC.

  3. Statistical modelling of networked human-automation performance using working memory capacity.

    Science.gov (United States)

    Ahmed, Nisar; de Visser, Ewart; Shaw, Tyler; Mohamed-Ameen, Amira; Campbell, Mark; Parasuraman, Raja

    2014-01-01

    This study examines the challenging problem of modelling the interaction between individual attentional limitations and decision-making performance in networked human-automation system tasks. Analysis of real experimental data from a task involving networked supervision of multiple unmanned aerial vehicles by human participants shows that both task load and network message quality affect performance, but that these effects are modulated by individual differences in working memory (WM) capacity. These insights were used to assess three statistical approaches for modelling and making predictions with real experimental networked supervisory performance data: classical linear regression, non-parametric Gaussian processes and probabilistic Bayesian networks. It is shown that each of these approaches can help designers of networked human-automated systems cope with various uncertainties in order to accommodate future users by linking expected operating conditions and performance from real experimental data to observable cognitive traits like WM capacity. Practitioner Summary: Working memory (WM) capacity helps account for inter-individual variability in operator performance in networked unmanned aerial vehicle supervisory tasks. This is useful for reliable performance prediction near experimental conditions via linear models; robust statistical prediction beyond experimental conditions via Gaussian process models and probabilistic inference about unknown task conditions/WM capacities via Bayesian network models.

  4. 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.

  5. Alternating Dynamics of Segregation and Integration in Human EEG Functional Networks During Working-memory Task.

    Science.gov (United States)

    Zippo, Antonio G; Della Rosa, Pasquale A; Castiglioni, Isabella; Biella, Gabriele E M

    2018-02-10

    Brain functional networks show high variability in short time windows but mechanisms governing these transient dynamics remain unknown. In this work, we studied the temporal evolution of functional brain networks involved in a working memory (WM) task while recording high-density electroencephalography (EEG) in human normal subjects. We found that functional brain networks showed an initial phase characterized by an increase of the functional segregation index followed by a second phase where the functional segregation faded after the prevailing the functional integration. Notably, wrong trials were associated with different or disrupted sequences of the segregation-integration profiles and measures of network centrality and modularity were able to identify crucial aspects of the oscillatory network dynamics. Additionally, computational investigations further supported the experimental results. The brain functional organization may respond to the information processing demand of a WM task following a 2-step atomic scheme wherein segregation and integration alternately dominate the functional configurations. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  6. 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.

  7. Neural networks engaged in short-term memory rehearsal are disrupted by irrelevant speech in human subjects.

    Science.gov (United States)

    Kopp, Franziska; Schröger, Erich; Lipka, Sigrid

    2004-01-02

    Rehearsal mechanisms in human short-term memory are increasingly understood in the light of both behavioural and neuroanatomical findings. However, little is known about the cooperation of participating brain structures and how such cooperations are affected when memory performance is disrupted. In this paper we use EEG coherence as a measure of synchronization to investigate rehearsal processes and their disruption by irrelevant speech in a delayed serial recall paradigm. Fronto-central and fronto-parietal theta (4-7.5 Hz), beta (13-20 Hz), and gamma (35-47 Hz) synchronizations are shown to be involved in our short-term memory task. Moreover, the impairment in serial recall due to irrelevant speech was preceded by a reduction of gamma band coherence. Results suggest that the irrelevant speech effect has its neural basis in the disruption of left-lateralized fronto-central networks. This stresses the importance of gamma band activity for short-term memory operations.

  8. 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…

  9. 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

  10. 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.

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

    OpenAIRE

    Kalisch, Raffael; Korenfeld, Elian; Stephan, Klaas E.; Weiskopf, Nikolaus; Seymour, Ben; Dolan, Raymond 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...

  12. Episodic memory in aspects of large-scale brain networks

    Science.gov (United States)

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

    2015-01-01

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

  13. Episodic memory in aspects of large-scale brain networks

    Directory of Open Access Journals (Sweden)

    Woorim eJeong

    2015-08-01

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

  14. Spatial and Temporal Episodic Memory Retrieval Recruit Dissociable Functional Networks in the Human Brain

    Science.gov (United States)

    Ekstrom, Arne D.; Bookheimer, Susan Y.

    2007-01-01

    Imaging, electrophysiological studies, and lesion work have shown that the medial temporal lobe (MTL) is important for episodic memory; however, it is unclear whether different MTL regions support the spatial, temporal, and item elements of episodic memory. In this study we used fMRI to examine retrieval performance emphasizing different aspects…

  15. The increase in medial prefrontal glutamate/glutamine concentration during memory encoding is associated with better memory performance and stronger functional connectivity in the human medial prefrontal-thalamus-hippocampus network.

    Science.gov (United States)

    Thielen, Jan-Willem; Hong, Donghyun; Rohani Rankouhi, Seyedmorteza; Wiltfang, Jens; Fernández, Guillén; Norris, David G; Tendolkar, Indira

    2018-06-01

    The classical model of the declarative memory system describes the hippocampus and its interactions with representational brain areas in posterior neocortex as being essential for the formation of long-term episodic memories. However, new evidence suggests an extension of this classical model by assigning the medial prefrontal cortex (mPFC) a specific, yet not fully defined role in episodic memory. In this study, we utilized 1H magnetic resonance spectroscopy (MRS) and psychophysiological interaction (PPI) analysis to lend further support for the idea of a mnemonic role of the mPFC in humans. By using MRS, we measured mPFC γ-aminobutyric acid (GABA) and glutamate/glutamine (GLx) concentrations before and after volunteers memorized face-name association. We demonstrate that mPFC GLx but not GABA levels increased during the memory task, which appeared to be related to memory performance. Regarding functional connectivity, we used the subsequent memory paradigm and found that the GLx increase was associated with stronger mPFC connectivity to thalamus and hippocampus for associations subsequently recognized with high confidence as opposed to subsequently recognized with low confidence/forgotten. Taken together, we provide new evidence for an mPFC involvement in episodic memory by showing a memory-related increase in mPFC excitatory neurotransmitter levels that was associated with better memory and stronger memory-related functional connectivity in a medial prefrontal-thalamus-hippocampus network. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

  16. The neurobiology of the human memory.

    Science.gov (United States)

    Fietta, Pierluigi; Fietta, Pieranna

    2011-01-01

    Memory can be defined as the ability to acquire, process, store, and retrieve information. Memory is indispensable for learning, adaptation, and survival of every living organism. In humans, the remembering process has acquired great flexibility and complexity, reaching close links with other mental functions, such as thinking and emotions. Changes in synaptic connectivity and interactions among multiple neural networks provide the neurobiological substrates for memory encoding, retention, and consolidation. Memory may be categorized as short-term and long-term memory (according to the storage temporal duration), as implicit and explicit memory (with respect to the consciousness of remembering), as declarative (knowing that [fact]) and procedural (knowing how [skill]) memory, or as sensory (echoic, iconic and haptil), semantic, and episodic memory (according to the various remembering domains). Significant advances have been obtained in understanding memory neurobiology, but much remains to be learned in its cognitive, psychological, and phenomenological aspects.

  17. Carrying the past to the future: Distinct brain networks underlie individual differences in human spatial working memory capacity.

    Science.gov (United States)

    Liu, Siwei; Poh, Jia-Hou; Koh, Hui Li; Ng, Kwun Kei; Loke, Yng Miin; Lim, Joseph Kai Wei; Chong, Joanna Su Xian; Zhou, Juan

    2018-08-01

    Spatial working memory (SWM) relies on the interplay of anatomically separated and interconnected large-scale brain networks. EEG studies often observe load-associated sustained negative activity during SWM retention. Yet, whether and how such sustained negative activity in retention relates to network-specific functional activation/deactivation and relates to individual differences in SWM capacity remain to be elucidated. To cover these gaps, we recorded concurrent EEG-fMRI data in 70 healthy young adults during the Sternberg delayed-match-to-sample SWM task with three memory load levels. To a subset of participants (N = 28) that performed the task properly and had artefact-free fMRI and EEG data, we employed a novel temporo-spatial principal component analysis to derive load-dependent negative slow wave (NSW) from retention-related event-related potentials. The associations between NSW responses with SWM capacity were divergent in the higher (N = 14) and lower (N = 14) SWM capacity groups. Specifically, larger load-related increase in NSW amplitude was associated with greater SWM capacity for the higher capacity group but lower SWM capacity for the lower capacity group. Furthermore, for the higher capacity group, larger NSW amplitude was related to greater activation in bilateral parietal areas of the fronto-parietal network (FPN) and greater deactivation in medial frontal gyrus and posterior mid-cingulate cortex of the default mode network (DMN) during retention. In contrast, the lower capacity group did not show similar pattern. Instead, greater NSW was linked to higher deactivation in right posterior middle temporal gyrus. Our findings shed light on the possible differential EEG-informed neural network mechanism during memory maintenance underlying individual differences in SWM capacity. Copyright © 2018 Elsevier Inc. All rights reserved.

  18. Short term memory in echo state networks

    OpenAIRE

    Jaeger, H.

    2001-01-01

    The report investigates the short-term memory capacity of echo state recurrent neural networks. A quantitative measure MC of short-term memory capacity is introduced. The main result is that MC 5 N for networks with linear Output units and i.i.d. input, where N is network size. Conditions under which these maximal memory capacities are realized are described. Several theoretical and practical examples demonstrate how the short-term memory capacities of echo state networks can be exploited for...

  19. Network resiliency through memory health monitoring and proactive management

    Science.gov (United States)

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

    2017-11-21

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

  20. 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.

  1. 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.

  2. Properties of a memory network in psychology

    International Nuclear Information System (INIS)

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

    2007-01-01

    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

  3. A nap to recap or how reward regulates hippocampal-prefrontal memory networks during daytime sleep in humans.

    Science.gov (United States)

    Igloi, Kinga; Gaggioni, Giulia; Sterpenich, Virginie; Schwartz, Sophie

    2015-10-16

    Sleep plays a crucial role in the consolidation of newly acquired memories. Yet, how our brain selects the noteworthy information that will be consolidated during sleep remains largely unknown. Here we show that post-learning sleep favors the selectivity of long-term consolidation: when tested three months after initial encoding, the most important (i.e., rewarded, strongly encoded) memories are better retained, and also remembered with higher subjective confidence. Our brain imaging data reveals that the functional interplay between dopaminergic reward regions, the prefrontal cortex and the hippocampus contributes to the integration of rewarded associative memories. We further show that sleep spindles strengthen memory representations based on reward values, suggesting a privileged replay of information yielding positive outcomes. These findings demonstrate that post-learning sleep determines the neural fate of motivationally-relevant memories and promotes a value-based stratification of long-term memory stores.

  4. Reward disrupts reactivated human skill memory

    OpenAIRE

    Dayan, Eran; Laor-Maayany, Rony; Censor, Nitzan

    2016-01-01

    Accumulating evidence across species and memory domains shows that when an existing memory is reactivated, it becomes susceptible to modifications. However, the potential role of reward signals in these mechanisms underlying human memory dynamics is unknown. Leaning on a wealth of findings on the role of reward in reinforcing memory, we tested the impact of reinforcing a skill memory trace with monetary reward following memory reactivation, on strengthening of the memory trace. Reinforcing re...

  5. Evolving spiking networks with variable resistive memories.

    Science.gov (United States)

    Howard, Gerard; Bull, Larry; de Lacy Costello, Ben; Gale, Ella; Adamatzky, Andrew

    2014-01-01

    Neuromorphic computing is a brainlike information processing paradigm that requires adaptive learning mechanisms. A spiking neuro-evolutionary system is used for this purpose; plastic resistive memories are implemented as synapses in spiking neural networks. The evolutionary design process exploits parameter self-adaptation and allows the topology and synaptic weights to be evolved for each network in an autonomous manner. Variable resistive memories are the focus of this research; each synapse has its own conductance profile which modifies the plastic behaviour of the device and may be altered during evolution. These variable resistive networks are evaluated on a noisy robotic dynamic-reward scenario against two static resistive memories and a system containing standard connections only. The results indicate that the extra behavioural degrees of freedom available to the networks incorporating variable resistive memories enable them to outperform the comparative synapse types.

  6. A short-term neural network memory

    Energy Technology Data Exchange (ETDEWEB)

    Morris, R.J.T.; Wong, W.S.

    1988-12-01

    Neural network memories with storage prescriptions based on Hebb's rule are known to collapse as more words are stored. By requiring that the most recently stored word be remembered precisely, a new simple short-term neutral network memory is obtained and its steady state capacity analyzed and simulated. Comparisons are drawn with Hopfield's method, the delta method of Widrow and Hoff, and the revised marginalist model of Mezard, Nadal, and Toulouse.

  7. A Memory Efficient Network Encryption Scheme

    Science.gov (United States)

    El-Fotouh, Mohamed Abo; Diepold, Klaus

    In this paper, we studied the two widely used encryption schemes in network applications. Shortcomings have been found in both schemes, as these schemes consume either more memory to gain high throughput or low memory with low throughput. The need has aroused for a scheme that has low memory requirements and in the same time possesses high speed, as the number of the internet users increases each day. We used the SSM model [1], to construct an encryption scheme based on the AES. The proposed scheme possesses high throughput together with low memory requirements.

  8. 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. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. Multistability in bidirectional associative memory neural networks

    International Nuclear Information System (INIS)

    Huang Gan; Cao Jinde

    2008-01-01

    In this Letter, the multistability issue is studied for Bidirectional Associative Memory (BAM) neural networks. Based on the existence and stability analysis of the neural networks with or without delay, it is found that the 2n-dimensional networks can have 3 n equilibria and 2 n equilibria of them are locally exponentially stable, where each layer of the BAM network has n neurons. Furthermore, the results has been extended to (n+m)-dimensional BAM neural networks, where there are n and m neurons on the two layers respectively. Finally, two numerical examples are presented to illustrate the validity of our results

  10. Multistability in bidirectional associative memory neural networks

    Science.gov (United States)

    Huang, Gan; Cao, Jinde

    2008-04-01

    In this Letter, the multistability issue is studied for Bidirectional Associative Memory (BAM) neural networks. Based on the existence and stability analysis of the neural networks with or without delay, it is found that the 2 n-dimensional networks can have 3 equilibria and 2 equilibria of them are locally exponentially stable, where each layer of the BAM network has n neurons. Furthermore, the results has been extended to (n+m)-dimensional BAM neural networks, where there are n and m neurons on the two layers respectively. Finally, two numerical examples are presented to illustrate the validity of our results.

  11. 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.

  12. Reward disrupts reactivated human skill memory.

    Science.gov (United States)

    Dayan, Eran; Laor-Maayany, Rony; Censor, Nitzan

    2016-06-16

    Accumulating evidence across species and memory domains shows that when an existing memory is reactivated, it becomes susceptible to modifications. However, the potential role of reward signals in these mechanisms underlying human memory dynamics is unknown. Leaning on a wealth of findings on the role of reward in reinforcing memory, we tested the impact of reinforcing a skill memory trace with monetary reward following memory reactivation, on strengthening of the memory trace. Reinforcing reactivated memories did not strengthen the memory, but rather led to disruption of the memory trace, breaking down the link between memory reactivation and subsequent memory strength. Statistical modeling further revealed a strong mediating role for memory reactivation in linking between memory encoding and subsequent memory strength only when the memory was replayed without reinforcement. We suggest that, rather than reinforcing the existing memory trace, reward creates a competing memory trace, impairing expression of the original reward-free memory. This mechanism sheds light on the processes underlying skill acquisition, having wide translational implications.

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

    Science.gov (United States)

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

    2015-01-01

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

  14. Automated Commonsense Reasoning About Human Memory

    National Research Council Canada - National Science Library

    Swanson, Reid; Gordon, Andrew S

    2005-01-01

    .... In this paper we evaluate the inferential competency of an existing formal theory of commonsense human memory by attempting to use it to validate the appropriateness of a commonsense memory strategy...

  15. Sequence memory based on coherent spin-interaction neural networks.

    Science.gov (United States)

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

    2014-12-01

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

  16. 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. Published by Oxford University Press 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

  17. Neural Networks for Time Perception and Working Memory

    Science.gov (United States)

    Üstün, Sertaç; Kale, Emre H.; Çiçek, Metehan

    2017-01-01

    Time is an important concept which determines most human behaviors, however questions remain about how time is perceived and which areas of the brain are responsible for time perception. The aim of this study was to evaluate the relationship between time perception and working memory in healthy adults. Functional magnetic resonance imaging (fMRI) was used during the application of a visual paradigm. In all of the conditions, the participants were presented with a moving black rectangle on a gray screen. The rectangle was obstructed by a black bar for a time period and then reappeared again. During different conditions, participants (n = 15, eight male) responded according to the instructions they were given, including details about time and the working memory or dual task requirements. The results showed activations in right dorsolateral prefrontal and right intraparietal cortical networks, together with the anterior cingulate cortex (ACC), anterior insula and basal ganglia (BG) during time perception. On the other hand, working memory engaged the left prefrontal cortex, ACC, left superior parietal cortex, BG and cerebellum activity. Both time perception and working memory were related to a strong peristriate cortical activity. On the other hand, the interaction of time and memory showed activity in the intraparietal sulcus (IPS) and posterior cingulate cortex (PCC). These results support a distributed neural network based model for time perception and that the intraparietal and posterior cingulate areas might play a role in the interface of memory and timing. PMID:28286475

  18. Social Working Memory: Neurocognitive networks and plasticity

    OpenAIRE

    Meyer, Meghan Leigh

    2014-01-01

    The social world is incredibly complex and the ability to keep track of various pieces of social information at once is imperative for success as a social species. Yet, how humans manage social information in mind has to date remained a mystery. On the one hand, psychological models of working memory, or the ability to maintain and manipulate information in mind, suggest that managing social information in mind would rely on generic working memory processes. However, recent research in social...

  19. Memory in cultured cortical networks

    NARCIS (Netherlands)

    le Feber, Jakob; Witteveen, T.; Stoyanova, Irina; Rutten, Wim

    2012-01-01

    Tetanic stimulation was applied to affect network connectivity, as assessed by conditional firing probabilities. We showed that the first period(s) of titanic stimulation at a certain electrode significantly alters functional connectivity, but subsequent, identical stimuli do not. These findings

  20. 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...... and their disease relationships from the reported TDDB database. The resulting human EDN takes into consideration the level of evidence of the toxicant-disease relationships allowing including some degrees of significance in the disease-disease associations. Such network can be used to identify uncharacterized...

  1. 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

  2. Critical dynamics in associative memory networks

    Directory of Open Access Journals (Sweden)

    Maximilian eUhlig

    2013-07-01

    Full Text Available Critical behavior in neural networks is characterized by scale-free avalanche size distributions and can be explained by self-regulatory mechanisms. Theoretical and experimental evidence indicates that information storage capacity reaches its maximum in the critical regime. We study the effect of structural connectivity formed by Hebbian learning on the criticality of network dynamics. The network endowed with Hebbian learning only does not allow for simultaneous information storage and criticality. However, the critical regime is can be stabilized by short-term synaptic dynamics in the form of synaptic depression and facilitation or, alternatively, by homeostatic adaptation of the synaptic weights. We show that a heterogeneous distribution of maximal synaptic strengths does not preclude criticality if the Hebbian learning is alternated with periods of critical dynamics recovery. We discuss the relevance of these findings for the flexibility of memory in aging and with respect to the recent theory of synaptic plasticity.

  3. Short-Term Memory in Orthogonal Neural Networks

    Science.gov (United States)

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

    2004-04-01

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

  4. Short-term memory in orthogonal neural networks

    International Nuclear Information System (INIS)

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

    2004-01-01

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

  5. Attention-based Memory Selection Recurrent Network for Language Modeling

    OpenAIRE

    Liu, Da-Rong; Chuang, Shun-Po; Lee, Hung-yi

    2016-01-01

    Recurrent neural networks (RNNs) have achieved great success in language modeling. However, since the RNNs have fixed size of memory, their memory cannot store all the information about the words it have seen before in the sentence, and thus the useful long-term information may be ignored when predicting the next words. In this paper, we propose Attention-based Memory Selection Recurrent Network (AMSRN), in which the model can review the information stored in the memory at each previous time ...

  6. Scaling properties in time-varying networks with memory

    Science.gov (United States)

    Kim, Hyewon; Ha, Meesoon; Jeong, Hawoong

    2015-12-01

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

  7. Parallel structures in human and computer memory

    Science.gov (United States)

    Kanerva, Pentti

    1986-08-01

    If we think of our experiences as being recorded continuously on film, then human memory can be compared to a film library that is indexed by the contents of the film strips stored in it. Moreover, approximate retrieval cues suffice to retrieve information stored in this library: We recognize a familiar person in a fuzzy photograph or a familiar tune played on a strange instrument. This paper is about how to construct a computer memory that would allow a computer to recognize patterns and to recall sequences the way humans do. Such a memory is remarkably similar in structure to a conventional computer memory and also to the neural circuits in the cortex of the cerebellum of the human brain. The paper concludes that the frame problem of artificial intelligence could be solved by the use of such a memory if we were able to encode information about the world properly.

  8. Human Memory Organization for Computer Programs.

    Science.gov (United States)

    Norcio, A. F.; Kerst, Stephen M.

    1983-01-01

    Results of study investigating human memory organization in processing of computer programming languages indicate that algorithmic logic segments form a cognitive organizational structure in memory for programs. Statement indentation and internal program documentation did not enhance organizational process of recall of statements in five Fortran…

  9. Circadian Rhythms in Human Memory.

    Science.gov (United States)

    Folkard, Simon; Monk, Timothy H.

    1980-01-01

    Two experiments are described that examined the influence of time-of-day of presentation on immediate and delayed retention and its potential effects on retrieval from long-term memory. Time of presentation was found to influence both immediate and delayed (28 day) retention, but not retrieval from long-term memory. (Author/SJL)

  10. Application of reflective memory network in Tokamak fast controller

    International Nuclear Information System (INIS)

    Weng Chuqiao; Zhang Ming; Liu Rui; Zheng Wei; Zhuang Ge

    2014-01-01

    A specific application of reflective memory network in Tokamak fast controller was introduced in this paper. The PMC-5565 reflective memory card and ACC-5565 network hub were used to build a reflective memory real-time network to test its real- time function. The real-time, rapidity and determinacy of the time delay for fast controller controlling power device under the reflective memory network were tested in the LabVIEW RT real-time operation system. Depending on the reflective memory technology, the data in several fast controllers were synchronized, and multiple control tasks using a single control task were finished. The experiment results show that the reflective memory network can meet the real-time requirements for fast controller to perform the feedback control over devices. (authors)

  11. 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.

  12. Music Learning with Long Short Term Memory Networks

    OpenAIRE

    Colombo, Florian François

    2015-01-01

    Humans are able to learn and compose complex, yet beautiful, pieces of music as seen in e.g. the highly complicated works of J.S. Bach. However, how our brain is able to store and produce these very long temporal sequences is still an open question. Long short-term memory (LSTM) artificial neural networks have been shown to be efficient in sequence learning tasks thanks to their inherent ability to bridge long time lags between input events and their target signals. Here, I investigate the po...

  13. 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.

  14. Dopamine D1 signaling organizes network dynamics underlying working memory.

    Science.gov (United States)

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

    2016-06-01

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

  15. A New Conceptualization of Human Visual Sensory-Memory

    OpenAIRE

    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. Wh...

  16. 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...

  17. Memory replay in balanced recurrent networks.

    Directory of Open Access Journals (Sweden)

    Nikolay Chenkov

    2017-01-01

    Full Text Available Complex patterns of neural activity appear during up-states in the neocortex and sharp waves in the hippocampus, including sequences that resemble those during prior behavioral experience. The mechanisms underlying this replay are not well understood. How can small synaptic footprints engraved by experience control large-scale network activity during memory retrieval and consolidation? We hypothesize that sparse and weak synaptic connectivity between Hebbian assemblies are boosted by pre-existing recurrent connectivity within them. To investigate this idea, we connect sequences of assemblies in randomly connected spiking neuronal networks with a balance of excitation and inhibition. Simulations and analytical calculations show that recurrent connections within assemblies allow for a fast amplification of signals that indeed reduces the required number of inter-assembly connections. Replay can be evoked by small sensory-like cues or emerge spontaneously by activity fluctuations. Global-potentially neuromodulatory-alterations of neuronal excitability can switch between network states that favor retrieval and consolidation.

  18. Shape Memory of Human Red Blood Cells

    OpenAIRE

    Fischer, Thomas M.

    2004-01-01

    The human red cell can be deformed by external forces but returns to the biconcave resting shape after removal of the forces. If after such shape excursions the rim is always formed by the same part of the membrane, the cell is said to have a memory of its biconcave shape. If the rim can form anywhere on the membrane, the cell would have no shape memory. The shape memory was probed by an experiment called go-and-stop. Locations on the membrane were marked by spontaneously adhering latex spher...

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

    Science.gov (United States)

    2017-01-01

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

  20. 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.

  1. 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.

  2. Dynamical behaviour of neuronal networks iterated with memory

    International Nuclear Information System (INIS)

    Melatagia, P.M.; Ndoundam, R.; Tchuente, M.

    2005-11-01

    We study memory iteration where the updating consider a longer history of each site and the set of interaction matrices is palindromic. We analyze two different ways of updating the networks: parallel iteration with memory and sequential iteration with memory that we introduce in this paper. For parallel iteration, we define Lyapunov functional which permits us to characterize the periods behaviour and explicitly bounds the transient lengths of neural networks iterated with memory. For sequential iteration, we use an algebraic invariant to characterize the periods behaviour of the studied model of neural computation. (author)

  3. Biological Networks Entropies: Examples in Neural Memory Networks, Genetic Regulation Networks and Social Epidemic Networks

    Directory of Open Access Journals (Sweden)

    Jacques Demongeot

    2018-01-01

    Full Text Available Networks used in biological applications at different scales (molecule, cell and population are of different types: neuronal, genetic, and social, but they share the same dynamical concepts, in their continuous differential versions (e.g., non-linear Wilson-Cowan system as well as in their discrete Boolean versions (e.g., non-linear Hopfield system; in both cases, the notion of interaction graph G(J associated to its Jacobian matrix J, and also the concepts of frustrated nodes, positive or negative circuits of G(J, kinetic energy, entropy, attractors, structural stability, etc., are relevant and useful for studying the dynamics and the robustness of these systems. We will give some general results available for both continuous and discrete biological networks, and then study some specific applications of three new notions of entropy: (i attractor entropy, (ii isochronal entropy and (iii entropy centrality; in three domains: a neural network involved in the memory evocation, a genetic network responsible of the iron control and a social network accounting for the obesity spread in high school environment.

  4. Two-Layer Feedback Neural Networks with Associative Memories

    International Nuclear Information System (INIS)

    Gui-Kun, Wu; Hong, Zhao

    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. (general)

  5. Differential neural network configuration during human path integration

    Science.gov (United States)

    Arnold, Aiden E. G. F; Burles, Ford; Bray, Signe; Levy, Richard M.; Iaria, Giuseppe

    2014-01-01

    Path integration is a fundamental skill for navigation in both humans and animals. Despite recent advances in unraveling the neural basis of path integration in animal models, relatively little is known about how path integration operates at a neural level in humans. Previous attempts to characterize the neural mechanisms used by humans to visually path integrate have suggested a central role of the hippocampus in allowing accurate performance, broadly resembling results from animal data. However, in recent years both the central role of the hippocampus and the perspective that animals and humans share similar neural mechanisms for path integration has come into question. The present study uses a data driven analysis to investigate the neural systems engaged during visual path integration in humans, allowing for an unbiased estimate of neural activity across the entire brain. Our results suggest that humans employ common task control, attention and spatial working memory systems across a frontoparietal network during path integration. However, individuals differed in how these systems are configured into functional networks. High performing individuals were found to more broadly express spatial working memory systems in prefrontal cortex, while low performing individuals engaged an allocentric memory system based primarily in the medial occipito-temporal region. These findings suggest that visual path integration in humans over short distances can operate through a spatial working memory system engaging primarily the prefrontal cortex and that the differential configuration of memory systems recruited by task control networks may help explain individual biases in spatial learning strategies. PMID:24808849

  6. Topology influences performance in the associative memory neural networks

    International Nuclear Information System (INIS)

    Lu Jianquan; He Juan; Cao Jinde; Gao Zhiqiang

    2006-01-01

    To explore how topology affects performance within Hopfield-type associative memory neural networks (AMNNs), we studied the computational performance of the neural networks with regular lattice, random, small-world, and scale-free structures. In this Letter, we found that the memory performance of neural networks obtained through asynchronous updating from 'larger' nodes to 'smaller' nodes are better than asynchronous updating in random order, especially for the scale-free topology. The computational performance of associative memory neural networks linked by the above-mentioned network topologies with the same amounts of nodes (neurons) and edges (synapses) were studied respectively. Along with topologies becoming more random and less locally disordered, we will see that the performance of associative memory neural network is quite improved. By comparing, we show that the regular lattice and random network form two extremes in terms of patterns stability and retrievability. For a network, its patterns stability and retrievability can be largely enhanced by adding a random component or some shortcuts to its structured component. According to the conclusions of this Letter, we can design the associative memory neural networks with high performance and minimal interconnect requirements

  7. Two Distinct Scene-Processing Networks Connecting Vision and Memory.

    Science.gov (United States)

    Baldassano, Christopher; Esteva, Andre; Fei-Fei, Li; Beck, Diane M

    2016-01-01

    A number of regions in the human brain are known to be involved in processing natural scenes, but the field has lacked a unifying framework for understanding how these different regions are organized and interact. We provide evidence from functional connectivity and meta-analyses for a new organizational principle, in which scene processing relies upon two distinct networks that split the classically defined parahippocampal place area (PPA). The first network of strongly connected regions consists of the occipital place area/transverse occipital sulcus and posterior PPA, which contain retinotopic maps and are not strongly coupled to the hippocampus at rest. The second network consists of the caudal inferior parietal lobule, retrosplenial complex, and anterior PPA, which connect to the hippocampus (especially anterior hippocampus), and are implicated in both visual and nonvisual tasks, including episodic memory and navigation. We propose that these two distinct networks capture the primary functional division among scene-processing regions, between those that process visual features from the current view of a scene and those that connect information from a current scene view with a much broader temporal and spatial context. This new framework for understanding the neural substrates of scene-processing bridges results from many lines of research, and makes specific functional predictions.

  8. Studies of Human Memory and Language Processing.

    Science.gov (United States)

    Collins, Allan M.

    The purposes of this study were to determine the nature of human semantic memory and to obtain knowledge usable in the future development of computer systems that can converse with people. The work was based on a computer model which is designed to comprehend English text, relating the text to information stored in a semantic data base that is…

  9. 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.

  10. 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

  11. 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

  12. 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.

  13. Shape memory of human red blood cells.

    Science.gov (United States)

    Fischer, Thomas M

    2004-05-01

    The human red cell can be deformed by external forces but returns to the biconcave resting shape after removal of the forces. If after such shape excursions the rim is always formed by the same part of the membrane, the cell is said to have a memory of its biconcave shape. If the rim can form anywhere on the membrane, the cell would have no shape memory. The shape memory was probed by an experiment called go-and-stop. Locations on the membrane were marked by spontaneously adhering latex spheres. Shape excursions were induced by shear flow. In virtually all red cells, a shape memory was found. After stop of flow and during the return of the latex spheres to the original location, the red cell shape was biconcave. The return occurred by a tank-tread motion of the membrane. The memory could not be eliminated by deforming the red cells in shear flow up to 4 h at room temperature as well as at 37 degrees C. It is suggested that 1). the characteristic time of stress relaxation is >80 min and 2). red cells in vivo also have a shape memory.

  14. 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...

  15. Aplikasi Bidirectional Assosiatif Memori (BAM) Network pada Pengenalan Model

    OpenAIRE

    Iskandar, Iskhaq

    2001-01-01

    Penelitian ini bertujuan untuk menyusun suatu simulasi komputer yang dapat dipergunakan untuk menguji kemampuan memori komputer dalam mengenali suatu model tertentu berdasarkan algoritma Bidirectional Assosiatif Memori Neural Network. Model yang digunakan dalam penelitian dalam penelitian ini adalah huruf-huruf abjad yang dinyatakan dalam kode polar –1 dan +1 dalam bentuk matrik [5x3]. Hasil yang didapat dalam penelitian ini menunjukkan bahwa rancangan network yang disusun mampu mengenali mod...

  16. Single-item memory, associative memory, and the human hippocampus

    OpenAIRE

    Gold, Jeffrey J.; Hopkins, Ramona O.; Squire, Larry R.

    2006-01-01

    We tested recognition memory for items and associations in memory-impaired patients with bilateral lesions thought to be limited to the hippocampal region. In Experiment 1 (Combined memory test), participants studied words and then took a memory test in which studied words, new words, studied word pairs, and recombined word pairs were presented in a mixed order. In Experiment 2 (Separated memory test), participants studied single words and then took a memory test involving studied word and ne...

  17. vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design

    OpenAIRE

    Rhu, Minsoo; Gimelshein, Natalia; Clemons, Jason; Zulfiqar, Arslan; Keckler, Stephen W.

    2016-01-01

    The most widely used machine learning frameworks require users to carefully tune their memory usage so that the deep neural network (DNN) fits into the DRAM capacity of a GPU. This restriction hampers a researcher's flexibility to study different machine learning algorithms, forcing them to either use a less desirable network architecture or parallelize the processing across multiple GPUs. We propose a runtime memory manager that virtualizes the memory usage of DNNs such that both GPU and CPU...

  18. Social working memory: neurocognitive networks and directions for future research.

    Science.gov (United States)

    Meyer, Meghan L; Lieberman, Matthew D

    2012-01-01

    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 (SWM). 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 SWM and that both the mentalizing and canonical working memory neurocognitive networks support SWM. 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.

  19. 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...

  20. Estimating Memory Deterioration Rates Following Neurodegeneration and Traumatic Brain Injuries in a Hopfield Network Model

    Directory of Open Access Journals (Sweden)

    Melanie Weber

    2017-11-01

    Full Text Available Neurodegenerative diseases and traumatic brain injuries (TBI are among the main causes of cognitive dysfunction in humans. At a neuronal network level, they both extensively exhibit focal axonal swellings (FAS, which in turn, compromise the information encoded in spike trains and lead to potentially severe functional deficits. There are currently no satisfactory quantitative predictors of decline in memory-encoding neuronal networks based on the impact and statistics of FAS. Some of the challenges of this translational approach include our inability to access small scale injuries with non-invasive methods, the overall complexity of neuronal pathologies, and our limited knowledge of how networks process biological signals. The purpose of this computational study is three-fold: (i to extend Hopfield's model for associative memory to account for the effects of FAS, (ii to calibrate FAS parameters from biophysical observations of their statistical distribution and size, and (iii to systematically evaluate deterioration rates for different memory-recall tasks as a function of FAS injury. We calculate deterioration rates for a face-recognition task to account for highly correlated memories and also for a discrimination task of random, uncorrelated memories with a size at the capacity limit of the Hopfield network. While it is expected that the performance of any injured network should decrease with injury, our results link, for the first time, the memory recall ability to observed FAS statistics. This allows for plausible estimates of cognitive decline for different stages of brain disorders within neuronal networks, bridging experimental observations following neurodegeneration and TBI with compromised memory recall. The work lends new insights to help close the gap between theory and experiment on how biological signals are processed in damaged, high-dimensional functional networks, and towards positing new diagnostic tools to measure cognitive

  1. Estimating Memory Deterioration Rates Following Neurodegeneration and Traumatic Brain Injuries in a Hopfield Network Model

    Science.gov (United States)

    Weber, Melanie; Maia, Pedro D.; Kutz, J. Nathan

    2017-01-01

    Neurodegenerative diseases and traumatic brain injuries (TBI) are among the main causes of cognitive dysfunction in humans. At a neuronal network level, they both extensively exhibit focal axonal swellings (FAS), which in turn, compromise the information encoded in spike trains and lead to potentially severe functional deficits. There are currently no satisfactory quantitative predictors of decline in memory-encoding neuronal networks based on the impact and statistics of FAS. Some of the challenges of this translational approach include our inability to access small scale injuries with non-invasive methods, the overall complexity of neuronal pathologies, and our limited knowledge of how networks process biological signals. The purpose of this computational study is three-fold: (i) to extend Hopfield's model for associative memory to account for the effects of FAS, (ii) to calibrate FAS parameters from biophysical observations of their statistical distribution and size, and (iii) to systematically evaluate deterioration rates for different memory-recall tasks as a function of FAS injury. We calculate deterioration rates for a face-recognition task to account for highly correlated memories and also for a discrimination task of random, uncorrelated memories with a size at the capacity limit of the Hopfield network. While it is expected that the performance of any injured network should decrease with injury, our results link, for the first time, the memory recall ability to observed FAS statistics. This allows for plausible estimates of cognitive decline for different stages of brain disorders within neuronal networks, bridging experimental observations following neurodegeneration and TBI with compromised memory recall. The work lends new insights to help close the gap between theory and experiment on how biological signals are processed in damaged, high-dimensional functional networks, and towards positing new diagnostic tools to measure cognitive deficits. PMID

  2. Neural network modeling of associative memory: Beyond the Hopfield model

    Science.gov (United States)

    Dasgupta, Chandan

    1992-07-01

    A number of neural network models, in which fixed-point and limit-cycle attractors of the underlying dynamics are used to store and associatively recall information, are described. In the first class of models, a hierarchical structure is used to store an exponentially large number of strongly correlated memories. The second class of models uses limit cycles to store and retrieve individual memories. A neurobiologically plausible network that generates low-amplitude periodic variations of activity, similar to the oscillations observed in electroencephalographic recordings, is also described. Results obtained from analytic and numerical studies of the properties of these networks are discussed.

  3. 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.

  4. Bridging humans via agent networks

    International Nuclear Information System (INIS)

    Ishida, Toru

    1994-01-01

    Recent drastic advance in telecommunication networks enabled the human organization of new class, teleorganization, which differ from any existing organization in that the organization which is easy to create by using telecommunication networks is virtual and remote, that people can join multiple organizations simultaneously, and that the organization can involve people who may not know each other. In order to enjoy the recent advance in telecommunication, the agent networks to help people organize themselves are needed. In this paper, an architecture of agent networks, in which each agent learns the preference or the utility functioin of the owner, and acts on behalf of the owner in maintaining the organization, is proposed. When an agent networks supports a human organization, the conventional human interface is divided into personal and social interfaces. The functionalities of the social interface in teleconferencing and telelearning were investigated. In both cases, the existence of B-ISDN is assumed, and the extension to the business meeting scheduling using personal handy phone (PHS) networks with personal digital assistant (PDA) terminals is expected. These circumstances are described. Mutual selection protocols (MSP) and their dynamic properties are explained. (K.I.)

  5. Limitations of Human Visual Working Memory

    OpenAIRE

    Wesenick, Maria-Barbara

    2004-01-01

    The present empirical study investigates limitations of human visual working memory (VWM). The experiments of the present work involve the experimental paradigm of change detection using simple geometrical objects in the form of rectangles of different colour, length, and orientation. It can be shown, that a limited performance in the temporary storage of visual information has multiple sources. Limitations of VWM can be attributed to a limited capacity or a limited duration, but also to limi...

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

    Science.gov (United States)

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

    2016-01-01

    Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during an n-back working-memory task) and positron emission tomography using the radiotracer [11C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. SIGNIFICANCE

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

    Science.gov (United States)

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

    2016-04-13

    Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during ann-back working-memory task) and positron emission tomography using the radiotracer [(11)C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. It is unclear

  8. 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.

  9. Thalamic control of human attention driven by memory and learning.

    Science.gov (United States)

    de Bourbon-Teles, José; Bentley, Paul; Koshino, Saori; Shah, Kushal; Dutta, Agneish; Malhotra, Paresh; Egner, Tobias; Husain, Masud; Soto, David

    2014-05-05

    The role of the thalamus in high-level cognition-attention, working memory (WM), rule-based learning, and decision making-remains poorly understood, especially in comparison to that of cortical frontoparietal networks [1-3]. Studies of visual thalamus have revealed important roles for pulvinar and lateral geniculate nucleus in visuospatial perception and attention [4-10] and for mediodorsal thalamus in oculomotor control [11]. Ventrolateral thalamus contains subdivisions devoted to action control as part of a circuit involving the basal ganglia [12, 13] and motor, premotor, and prefrontal cortices [14], whereas anterior thalamus forms a memory network in connection with the hippocampus [15]. This connectivity profile suggests that ventrolateral and anterior thalamus may represent a nexus between mnemonic and control functions, such as action or attentional selection. Here, we characterize the role of thalamus in the interplay between memory and visual attention. We show that ventrolateral lesions impair the influence of WM representations on attentional deployment. A subsequent fMRI study in healthy volunteers demonstrates involvement of ventrolateral and, notably, anterior thalamus in biasing attention through WM contents. To further characterize the memory types used by the thalamus to bias attention, we performed a second fMRI study that involved learning of stimulus-stimulus associations and their retrieval from long-term memory to optimize attention in search. Responses in ventrolateral and anterior thalamic nuclei tracked learning of the predictiveness of these abstract associations and their use in directing attention. These findings demonstrate a key role for human thalamus in higher-level cognition, notably, in mnemonic biasing of attention. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  10. 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.

  11. 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

  12. 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.

  13. The Cognitive Neuroscience of Human Memory Since H.M

    OpenAIRE

    Squire, Larry R.; Wixted, John T.

    2011-01-01

    Work with patient H.M., beginning in the 1950s, established key principles about the organization of memory that inspired decades of experimental work. Since H.M., the study of human memory and its disorders has continued to yield new insights and to improve understanding of the structure and organization of memory. Here we review this work with emphasis on the neuroanatomy of medial temporal lobe and diencephalic structures important for memory, multiple memory systems, visual perception, im...

  14. Cerebrocerebellar networks during articulatory rehearsal and verbal working memory tasks.

    Science.gov (United States)

    Chen, S H Annabel; Desmond, John E

    2005-01-15

    Converging evidence has implicated the cerebellum in verbal working memory. The current fMRI study sought to further characterize cerebrocerebellar participation in this cognitive process by revealing regions of activation common to a verbal working task and an articulatory control task, as well as regions that are uniquely activated by working memory. Consistent with our model's predictions, load-dependent activations were observed in Broca's area (BA 44/6) and the superior cerebellar hemisphere (VI/CrusI) for both working memory and motoric rehearsal. In contrast, activations unique to verbal working memory were found in the inferior parietal lobule (BA 40) and the right inferior cerebellum hemisphere (VIIB). These findings provide evidence for two cerebrocerebellar networks for verbal working memory: a frontal/superior cerebellar articulatory control system and a parietal/inferior cerebellar phonological storage system.

  15. 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.

  16. 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.

  17. Hidden long evolutionary memory in a model biochemical network

    Science.gov (United States)

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

    2018-04-01

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

  18. Is Cooperative Memory Special? The Role of Costly Errors, Context, and Social Network Size When Remembering Cooperative Actions

    Directory of Open Access Journals (Sweden)

    Tim Winke

    2017-10-01

    Full Text Available Theoretical studies of cooperative behavior have focused on decision strategies, such as tit-for-tat, that depend on remembering a partner’s last choices. Yet, an empirical study by Stevens et al. (2011 demonstrated that human memory may not meet the requirements that needed to use these strategies. When asked to recall the previous behavior of simulated partners in a cooperative memory task, participants performed poorly, making errors in 10–24% of the trials. However, we do not know the extent to which this task taps specialized cognition for cooperation. It may be possible to engage participants in more cooperative, strategic thinking, which may improve memory. On the other hand, compared with other situations, a cooperative context may already engage improved memory via cheater detection mechanisms. This study investigated the specificity of memory in cooperative contexts by varying (1 the costs of errors in memory by making forgetting defection more costly and (2 whether the recall situation is framed as a cooperative or neutral context. Also, we investigated whether variation in participants’ social network size could account for individual differences observed in memory accuracy. We found that neither including differential costs for misremembering defection nor removing the cooperative context influenced memory accuracy for cooperation. Combined, these results suggest that memory accuracy is robust to differences in the cooperative context: Adding more strategic components does not help accuracy, and removing cooperative components does not hurt accuracy. Social network size, however, did correlate with memory accuracy: People with larger networks remembered the events better. These findings suggest that cooperative memory does not seem to be special compared with other forms of memory, which aligns with previous work demonstrating the domain generality of memory. However, the demands of interacting in a large social network may

  19. 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.

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

    Science.gov (United States)

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

    2017-03-29

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

  1. A Gamma Memory Neural Network for System Identification

    Science.gov (United States)

    Motter, Mark A.; Principe, Jose C.

    1992-01-01

    A gamma neural network topology is investigated for a system identification application. A discrete gamma memory structure is used in the input layer, providing delayed values of both the control inputs and the network output to the input layer. The discrete gamma memory structure implements a tapped dispersive delay line, with the amount of dispersion regulated by a single, adaptable parameter. The network is trained using static back propagation, but captures significant features of the system dynamics. The system dynamics identified with the network are the Mach number dynamics of the 16 Foot Transonic Tunnel at NASA Langley Research Center, Hampton, Virginia. The training data spans an operating range of Mach numbers from 0.4 to 1.3.

  2. Memory in Neural Networks and Glasses

    NARCIS (Netherlands)

    Heerema, M.

    2000-01-01

    The thesis tries and models a neural network in a way which, at essential points, is biologically realistic. In a biological context, the changes of the synapses of the neural network are most often described by what is called `Hebb's learning rule'. On careful analysis it is, in fact, nothing but a

  3. Memory functions reveal structural properties of gene regulatory networks

    Science.gov (United States)

    Perez-Carrasco, Ruben

    2018-01-01

    Gene regulatory networks (GRNs) control cellular function and decision making during tissue development and homeostasis. Mathematical tools based on dynamical systems theory are often used to model these networks, but the size and complexity of these models mean that their behaviour is not always intuitive and the underlying mechanisms can be difficult to decipher. For this reason, methods that simplify and aid exploration of complex networks are necessary. To this end we develop a broadly applicable form of the Zwanzig-Mori projection. By first converting a thermodynamic state ensemble model of gene regulation into mass action reactions we derive a general method that produces a set of time evolution equations for a subset of components of a network. The influence of the rest of the network, the bulk, is captured by memory functions that describe how the subnetwork reacts to its own past state via components in the bulk. These memory functions provide probes of near-steady state dynamics, revealing information not easily accessible otherwise. We illustrate the method on a simple cross-repressive transcriptional motif to show that memory functions not only simplify the analysis of the subnetwork but also have a natural interpretation. We then apply the approach to a GRN from the vertebrate neural tube, a well characterised developmental transcriptional network composed of four interacting transcription factors. The memory functions reveal the function of specific links within the neural tube network and identify features of the regulatory structure that specifically increase the robustness of the network to initial conditions. Taken together, the study provides evidence that Zwanzig-Mori projections offer powerful and effective tools for simplifying and exploring the behaviour of GRNs. PMID:29470492

  4. Coherent oscillatory networks supporting short-term memory retention.

    Science.gov (United States)

    Payne, Lisa; Kounios, John

    2009-01-09

    Accumulating evidence suggests that top-down processes, reflected by frontal-midline theta-band (4-8 Hz) electroencephalogram (EEG) oscillations, strengthen the activation of a memory set during short-term memory (STM) retention. In addition, the amplitude of posterior alpha-band (8-13 Hz) oscillations during STM retention is thought to reflect a mechanism that protects fragile STM activations from interference by gating bottom-up sensory inputs. The present study addressed two important questions about these phenomena. First, why have previous studies not consistently found memory set-size effects on frontal-midline theta? Second, how does posterior alpha participate in STM retention? To answer these questions, large-scale network connectivity during STM retention was examined by computing EEG wavelet coherence during the retention period of a modified Sternberg task using visually-presented letters as stimuli. The results showed (a) increasing theta-band coherence between frontal-midline and left temporal-parietal sites with increasing memory load, and (b) increasing alpha-band coherence between midline parietal and left temporal/parietal sites with increasing memory load. These findings support the view that theta-band coherence, rather than amplitude, is the key factor in selective top-down strengthening of the memory set and demonstrate that posterior alpha-band oscillations associated with sensory gating are involved in STM retention by participating in the STM network.

  5. Mechanisms of memory storage in a model perirhinal network.

    Science.gov (United States)

    Samarth, Pranit; Ball, John M; Unal, Gunes; Paré, Denis; Nair, Satish S

    2017-01-01

    The perirhinal cortex supports recognition and associative memory. Prior unit recording studies revealed that recognition memory involves a reduced responsiveness of perirhinal cells to familiar stimuli whereas associative memory formation is linked to increasing perirhinal responses to paired stimuli. Both effects are thought to depend on perirhinal plasticity but it is unclear how the same network could support these opposite forms of plasticity. However, a recent study showed that when neocortical inputs are repeatedly activated, depression or potentiation could develop, depending on the extent to which the stimulated neocortical activity recruited intrinsic longitudinal connections. We developed a biophysically realistic perirhinal model that reproduced these phenomena and used it to investigate perirhinal mechanisms of associative memory. These analyzes revealed that associative plasticity is critically dependent on a specific subset of neurons, termed conjunctive cells (CCs). When the model network was trained with spatially distributed but coincident neocortical inputs, CCs acquired excitatory responses to the paired inputs and conveyed them to distributed perirhinal sites via longitudinal projections. CC ablation during recall abolished expression of the associative memory. However, CC ablation during training did not prevent memory formation because new CCs emerged, revealing that competitive synaptic interactions governs the formation of CC assemblies.

  6. 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. Copyright 2009 Elsevier Inc. All rights reserved.

  7. Memory in cultured cortical networks: experiment and modeling

    NARCIS (Netherlands)

    Witteveen, Tim; van Veenendaal, Tamar; le Feber, Jakob; Sergeev, A.

    The mechanism behind memory is one of the mysteries in neuroscience. Here we unravel part of the mechanism by showing that cultured neuronal networks develop an activity connectivity balance. External inputs disturb this balance and induce connectivity changes. The new connectivity is no longer

  8. The Structure of Human Memory. Technical Report No. 321.

    Science.gov (United States)

    Brewer, William F.; Pani, John R.

    The four sections of this paper provide an analysis of the structure of human memory. The first section, intended to provide a clear example of personal memory, examines a hypothetical episode in the life of an undergraduate student, and shows how one episode can give rise to three different forms of memory: personal, semantic, and rote…

  9. Kinetics and clonality of immunological memory in humans.

    Science.gov (United States)

    Beverley, Peter C L

    2004-10-01

    T-cell immunological memory consists largely of clones of proliferating lymphocytes maintained by antigenic stimulation and the survival and proliferative effects of cytokines. The duration of survival of memory clones in humans is determine by the Hayflick limit on the number of cell divisions, the rate of cycling of memory cells and factors that control erosion of telomeres, including mechanisms that control telomerase.

  10. Default network connectivity during a working memory task.

    Science.gov (United States)

    Bluhm, Robyn L; Clark, C Richard; McFarlane, Alexander C; Moores, Kathryn A; Shaw, Marnie E; Lanius, Ruth A

    2011-07-01

    The default network exhibits correlated activity at rest and has shown decreased activation during performance of cognitive tasks. There has been little investigation of changes in connectivity of this network during task performance. In this study, we examined task-related modulation of connectivity between two seed regions from the default network posterior cingulated cortex (PCC) and medial prefrontal cortex (mPFC) and the rest of the brain in 12 healthy adults. The purpose was to determine (1) whether connectivity within the default network differs between a resting state and performance of a cognitive (working memory) task and (2) whether connectivity differs between these nodes of the default network and other brain regions, particularly those implicated in cognitive tasks. There was little change in connectivity with the other main areas of the default network for either seed region, but moderate task-related changes in connectivity occurred between seed regions and regions outside the default network. For example, connectivity of the mPFC with the right insula and the right superior frontal gyrus decreased during task performance. Increased connectivity during the working memory task occurred between the PCC and bilateral inferior frontal gyri, and between the mPFC and the left inferior frontal gyrus, cuneus, superior parietal lobule, middle temporal gyrus and cerebellum. Overall, the areas showing greater correlation with the default network seed regions during task than at rest have been previously implicated in working memory tasks. These changes may reflect a decrease in the negative correlations occurring between the default and task-positive networks at rest. Copyright © 2010 Wiley-Liss, Inc.

  11. The Cognitive Neuroscience of Human Memory Since H.M

    Science.gov (United States)

    Squire, Larry R.; Wixted, John T.

    2011-01-01

    Work with patient H.M., beginning in the 1950s, established key principles about the organization of memory that inspired decades of experimental work. Since H.M., the study of human memory and its disorders has continued to yield new insights and to improve understanding of the structure and organization of memory. Here we review this work with emphasis on the neuroanatomy of medial temporal lobe and diencephalic structures important for memory, multiple memory systems, visual perception, immediate memory, memory consolidation, the locus of long-term memory storage, the concepts of recollection and familiarity, and the question of how different medial temporal lobe structures may contribute differently to memory functions. PMID:21456960

  12. 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.

  13. The human hippocampus: cognitive maps or relational memory?

    Science.gov (United States)

    Kumaran, Dharshan; Maguire, Eleanor A

    2005-08-03

    The hippocampus is widely accepted to play a pivotal role in memory. Two influential theories offer competing accounts of its fundamental operating mechanism. The cognitive map theory posits a special role in mapping large-scale space, whereas the relational theory argues it supports amodal relational processing. Here, we pit the two theories against each other using a novel paradigm in which the relational processing involved in navigating in a city was matched with similar navigational and relational processing demands in a nonspatial (social) domain. During functional magnetic resonance imaging, participants determined the optimal route either between friends' homes or between the friends themselves using social connections. Separate brain networks were engaged preferentially during the two tasks, with hippocampal activation driven only by spatial relational processing. We conclude that the human hippocampus appears to have a bias toward the processing of spatial relationships, in accordance with the cognitive map theory. Our results both advance our understanding of the nature of the hippocampal contribution to memory and provide insights into how social networks are instantiated at the neural level.

  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. Fast mapping rapidly integrates information into existing memory networks.

    Science.gov (United States)

    Coutanche, Marc N; Thompson-Schill, Sharon L

    2014-12-01

    Successful learning involves integrating new material into existing memory networks. A learning procedure known as fast mapping (FM), thought to simulate the word-learning environment of children, has recently been linked to distinct neuroanatomical substrates in adults. This idea has suggested the (never-before tested) hypothesis that FM may promote rapid incorporation into cortical memory networks. We test this hypothesis here in 2 experiments. In our 1st experiment, we introduced 50 participants to 16 unfamiliar animals and names through FM or explicit encoding (EE) and tested participants on the training day, and again after sleep. Learning through EE produced strong declarative memories, without immediate lexical competition, as expected from slow-consolidation models. Learning through FM, however, led to almost immediate lexical competition, which continued to the next day. Additionally, the learned words began to prime related concepts on the day following FM (but not EE) training. In a 2nd experiment, we replicated the lexical integration results and determined that presenting an already-known item during learning was crucial for rapid integration through FM. The findings presented here indicate that learned items can be integrated into cortical memory networks at an accelerated rate through fast mapping. The retrieval of a related known concept, in order to infer the target of the FM question, is critical for this effect. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  16. 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.

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

    Science.gov (United States)

    Jablonski, Piotr; Poe, Gina; Zochowski, Michal

    2007-03-01

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

  18. Synthetic vision and memory for autonomous virtual humans

    OpenAIRE

    PETERS, CHRISTOPHER; O'SULLIVAN, CAROL ANN

    2002-01-01

    PUBLISHED A memory model based on ?stage theory?, an influential concept of memory from the field of cognitive psychology, is presented for application to autonomous virtual humans. The virtual human senses external stimuli through a synthetic vision system. The vision system incorporates multiple modes of vision in order to accommodate a perceptual attention approach. The memory model is used to store perceived and attended object information at different stages in a filtering...

  19. Post-study caffeine administration enhances memory consolidation in humans.

    Science.gov (United States)

    Borota, Daniel; Murray, Elizabeth; Keceli, Gizem; Chang, Allen; Watabe, Joseph M; Ly, Maria; Toscano, John P; Yassa, Michael A

    2014-02-01

    It is currently not known whether caffeine has an enhancing effect on long-term memory in humans. We used post-study caffeine administration to test its effect on memory consolidation using a behavioral discrimination task. Caffeine enhanced performance 24 h after administration according to an inverted U-shaped dose-response curve; this effect was specific to consolidation and not retrieval. We conclude that caffeine enhanced consolidation of long-term memories in humans.

  20. A simplified memory network model based on pattern formations

    Science.gov (United States)

    Xu, Kesheng; Zhang, Xiyun; Wang, Chaoqing; Liu, Zonghua

    2014-12-01

    Many experiments have evidenced the transition with different time scales from short-term memory (STM) to long-term memory (LTM) in mammalian brains, while its theoretical understanding is still under debate. To understand its underlying mechanism, it has recently been shown that it is possible to have a long-period rhythmic synchronous firing in a scale-free network, provided the existence of both the high-degree hubs and the loops formed by low-degree nodes. We here present a simplified memory network model to show that the self-sustained synchronous firing can be observed even without these two necessary conditions. This simplified network consists of two loops of coupled excitable neurons with different synaptic conductance and with one node being the sensory neuron to receive an external stimulus signal. This model can be further used to show how the diversity of firing patterns can be selectively formed by varying the signal frequency, duration of the stimulus and network topology, which corresponds to the patterns of STM and LTM with different time scales. A theoretical analysis is presented to explain the underlying mechanism of firing patterns.

  1. The Human Dimension of Networks

    Science.gov (United States)

    2008-06-01

    Networking Organizational Issues Authors: Bruce J. West Ph.D. Army Research Office Elizabeth K. Bowman Ph.D. Army Research Laboratory – Human...Contact: Elizabeth K.Bowman AMSRD-ARL-HR Bulding 459, Aberdeen Proving Ground, MD 21005 410-278-5924 EBowman@arl.army.mil 1 Report Documentation Page...L.E. Brus , Nature 383, 802 (1996); M. Kuno, D.P. Fromim, s.R. Hohmson, A. Gallagher and D.J. Nesbitt, Phys. Rev. B 67, 125304 (2003); K.R. Shimizu

  2. Synthetic vision and memory model for virtual human - biomed 2010.

    Science.gov (United States)

    Zhao, Yue; Kang, Jinsheng; Wright, David

    2010-01-01

    This paper describes the methods and case studies of a novel synthetic vision and memory model for virtual human. The synthetic vision module simulates the biological / optical abilities and limitations of the human vision. The module is based on a series of collision detection between the boundary of virtual humans field of vision (FOV) volume and the surface of objects in a recreated 3D environment. The memory module simulates a short-term memory capability by employing a simplified memory structure (first-in-first-out stack). The synthetic vision and memory model has been integrated into a virtual human modelling project, Intelligent Virtual Modelling. The project aimed to improve the realism and autonomy of virtual humans.

  3. 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.

  4. 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.

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

    Science.gov (United States)

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

    2016-10-01

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

  6. False memory and the associative network of happiness.

    Science.gov (United States)

    Koo, Minkyung; Oishi, Shigehiro

    2009-02-01

    This research examines the relationship between individuals' levels of life satisfaction and their associative networks of happiness. Study 1 measured European Americans' degree of false memory of happiness using the Deese-Roediger-McDermott paradigm. Scores on the Satisfaction With Life Scale predicted the likelihood of false memory of happiness but not of other lure words such as sleep . In Study 2, European American participants completed an association-judgment task in which they judged the extent to which happiness and each of 15 positive emotion terms were associated with each other. Consistent with Study 1's findings, chronically satisfied individuals exhibited stronger associations between happiness and other positive emotion terms than did unsatisfied individuals. However, Koreans and Asian Americans did not exhibit such a pattern regarding their chronic level of life satisfaction (Study 3). In combination, results suggest that there are important individual and cultural differences in the cognitive structure and associative network of happiness.

  7. Associative memory in an analog iterated-map neural network

    Science.gov (United States)

    Marcus, C. M.; Waugh, F. R.; Westervelt, R. M.

    1990-03-01

    The behavior of an analog neural network with parallel dynamics is studied analytically and numerically for two associative-memory learning algorithms, the Hebb rule and the pseudoinverse rule. Phase diagrams in the parameter space of analog gain β and storage ratio α are presented. For both learning rules, the networks have large ``recall'' phases in which retrieval states exist and convergence to a fixed point is guaranteed by a global stability criterion. We also demonstrate numerically that using a reduced analog gain increases the probability of recall starting from a random initial state. This phenomenon is comparable to thermal annealing used to escape local minima but has the advantage of being deterministic, and therefore easily implemented in electronic hardware. Similarities and differences between analog neural networks and networks with two-state neurons at finite temperature are also discussed.

  8. Periodic bidirectional associative memory neural networks with distributed delays

    Science.gov (United States)

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

    2006-05-01

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

  9. Transfer of an unknown quantum state, quantum networks, and memory

    International Nuclear Information System (INIS)

    Biswas, Asoka; Agarwal, G.S.

    2004-01-01

    We present a protocol for transfer of an unknown quantum state. The protocol is based on a two-mode cavity interacting dispersively in a sequential manner with three-level atoms in the Λ configuration. We propose a scheme for quantum networking using an atomic channel. We investigate the effect of cavity decoherence in the entire process. Further, we demonstrate the possibility of an efficient quantum memory for arbitrary superposition of two modes of a cavity containing one photon

  10. Memory under stress: from single systems to network changes.

    Science.gov (United States)

    Schwabe, Lars

    2017-02-01

    Stressful events have profound effects on learning and memory. These effects are mainly mediated by catecholamines and glucocorticoid hormones released from the adrenals during stressful encounters. It has been known for long that both catecholamines and glucocorticoids influence the functioning of the hippocampus, a critical hub for episodic memory. However, areas implicated in other forms of memory, such as the insula or the dorsal striatum, can be affected by stress as well. Beyond changes in single memory systems, acute stress triggers the reconfiguration of large scale neural networks which sets the stage for a shift from thoughtful, 'cognitive' control of learning and memory toward more reflexive, 'habitual' processes. Stress-related alterations in amygdala connectivity with the hippocampus, dorsal striatum, and prefrontal cortex seem to play a key role in this shift. The bias toward systems proficient in threat processing and the implementation of well-established routines may facilitate coping with an acute stressor. Overreliance on these reflexive systems or the inability to shift flexibly between them, however, may represent a risk factor for psychopathology in the long-run. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  11. Synaptic plasticity, memory and the hippocampus: a neural network approach to causality.

    Science.gov (United States)

    Neves, Guilherme; Cooke, Sam F; Bliss, Tim V P

    2008-01-01

    Two facts about the hippocampus have been common currency among neuroscientists for several decades. First, lesions of the hippocampus in humans prevent the acquisition of new episodic memories; second, activity-dependent synaptic plasticity is a prominent feature of hippocampal synapses. Given this background, the hypothesis that hippocampus-dependent memory is mediated, at least in part, by hippocampal synaptic plasticity has seemed as cogent in theory as it has been difficult to prove in practice. Here we argue that the recent development of transgenic molecular devices will encourage a shift from mechanistic investigations of synaptic plasticity in single neurons towards an analysis of how networks of neurons encode and represent memory, and we suggest ways in which this might be achieved. In the process, the hypothesis that synaptic plasticity is necessary and sufficient for information storage in the brain may finally be validated.

  12. 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.

  13. 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.

  14. Reactivation in Working Memory: An Attractor Network Model of Free Recall

    Science.gov (United States)

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

    2013-01-01

    The dynamic nature of human working memory, the general-purpose system for processing continuous input, while keeping no longer externally available information active in the background, is well captured in immediate free recall of supraspan word-lists. Free recall tasks produce several benchmark memory phenomena, like the U-shaped serial position curve, reflecting enhanced memory for early and late list items. To account for empirical data, including primacy and recency as well as contiguity effects, we propose here a neurobiologically based neural network model that unifies short- and long-term forms of memory and challenges both the standard view of working memory as persistent activity and dual-store accounts of free recall. Rapidly expressed and volatile synaptic plasticity, modulated intrinsic excitability, and spike-frequency adaptation are suggested as key cellular mechanisms underlying working memory encoding, reactivation and recall. Recent findings on the synaptic and molecular mechanisms behind early LTP and on spiking activity during delayed-match-to-sample tasks support this view. PMID:24023690

  15. How the amygdala affects emotional memory by altering brain network properties.

    Science.gov (United States)

    Hermans, Erno J; Battaglia, Francesco P; Atsak, Piray; de Voogd, Lycia D; Fernández, Guillén; Roozendaal, Benno

    2014-07-01

    The amygdala has long been known to play a key role in supporting memory for emotionally arousing experiences. For example, classical fear conditioning depends on neural plasticity within this anterior medial temporal lobe region. Beneficial effects of emotional arousal on memory, however, are not restricted to simple associative learning. Our recollection of emotional experiences often includes rich representations of, e.g., spatiotemporal context, visceral states, and stimulus-response associations. Critically, such memory features are known to bear heavily on regions elsewhere in the brain. These observations led to the modulation account of amygdala function, which postulates that amygdala activation enhances memory consolidation by facilitating neural plasticity and information storage processes in its target regions. Rodent work in past decades has identified the most important brain regions and neurochemical processes involved in these modulatory actions, and neuropsychological and neuroimaging work in humans has produced a large body of convergent data. Importantly, recent methodological developments make it increasingly realistic to monitor neural interactions underlying such modulatory effects as they unfold. For instance, functional connectivity network modeling in humans has demonstrated how information exchanges between the amygdala and specific target regions occur within the context of large-scale neural network interactions. Furthermore, electrophysiological and optogenetic techniques in rodents are beginning to make it possible to quantify and even manipulate such interactions with millisecond precision. In this paper we will discuss that these developments will likely lead to an updated view of the amygdala as a critical nexus within large-scale networks supporting different aspects of memory processing for emotionally arousing experiences. Copyright © 2014 Elsevier Inc. All rights reserved.

  16. Neuroanatomic organization of sound memory in humans.

    Science.gov (United States)

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

    2006-11-01

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

  17. Awake reactivation predicts memory in humans

    OpenAIRE

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

    2013-01-01

    How is new information converted into a memory trace? Here, we used functional neuroimaging to assess what happens to representations of new events after we first experience them. We found that a particular part of the medial temporal lobe, a brain region known to be critical for intact memory, spontaneously reactivates these events even when we are engaged in unrelated activities. Indeed, the extent to which such automatic reactivation occurs seems directly related to later memory performanc...

  18. The organization and neural substrates of human memory.

    Science.gov (United States)

    Squire, L R

    The neurology of memory has been illuminated by parallel studies of patients with circumscribed memory impairment and animal models of human amnesia. Human amnesia can occur as an isolated cognitive deficit that impairs the ability to learn new facts and episodes. In addition, memory can be affected for material learned many years prior to the onset of amnesia. The finding that some memory abilities are intact in amnesia (e.g., skill learning, word priming, and adaptation-level effects) has suggested that memory can be divided into two or more separate processes. Declarative memory affords the ability to store information explicitly and to retrieve it later as a conscious recollection. This form of memory depends on the integrity of the structures damaged in amnesia. Other, non-declarative kinds of memory afford the ability to change as the result of experience, but the information is available only through performance. Recent studies of a favorable human case provided strong evidence that the hippocampus is a critical component of the declarative memory system. Extensive convergent and divergent projections link the hippocampus to many areas of neocortex where processing and storage of new information is likely to occur. It is perhaps by way of these connections that the hippocampus operates upon and participates in declarative representations.

  19. 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.

  20. The effects of working memory training on functional brain network efficiency.

    Science.gov (United States)

    Langer, Nicolas; von Bastian, Claudia C; Wirz, Helen; Oberauer, Klaus; Jäncke, Lutz

    2013-10-01

    The human brain is a highly interconnected network. Recent studies have shown that the functional and anatomical features of this network are organized in an efficient small-world manner that confers high efficiency of information processing at relatively low connection cost. However, it has been unclear how the architecture of functional brain networks is related to performance in working memory (WM) tasks and if these networks can be modified by WM training. Therefore, we conducted a double-blind training study enrolling 66 young adults. Half of the subjects practiced three WM tasks and were compared to an active control group practicing three tasks with low WM demand. High-density resting-state electroencephalography (EEG) was recorded before and after training to analyze graph-theoretical functional network characteristics at an intracortical level. WM performance was uniquely correlated with power in the theta frequency, and theta power was increased by WM training. Moreover, the better a person's WM performance, the more their network exhibited small-world topology. WM training shifted network characteristics in the direction of high performers, showing increased small-worldness within a distributed fronto-parietal network. Taken together, this is the first longitudinal study that provides evidence for the plasticity of the functional brain network underlying WM. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. Homologous mechanisms of visuospatial working memory maintenance in macaque and human: Properties and sources

    Science.gov (United States)

    Reinhart, Robert M.G.; Heitz, Richard P.; Purcell, Braden A.; Weigand, Pauline K.; Schall, Jeffrey D.; Woodman, Geoffrey F.

    2012-01-01

    Although areas of frontal cortex are thought to be critical for maintaining information in visuospatial working memory, the event-related potential (ERP) index of maintenance is found over posterior cortex in humans. In the present study, we reconcile these seemingly contradictory findings. Here we show that macaque monkeys and humans exhibit the same posterior ERP signature of working memory maintenance that predicts the precision of the memory-based behavioral responses. In addition, we show that the specific pattern of rhythmic oscillations in the alpha band, recently demonstrated to underlie the human visual working memory ERP component, is also present in monkeys. Next, we concurrently recorded intracranial local field potentials from two prefrontal and another frontal cortical area to determine their contribution to the surface potential indexing maintenance. The local fields in the two prefrontal areas, but not the cortex immediately posterior, exhibited amplitude modulations, timing, and relationships to behavior indicating that they contribute to the generation of the surface ERP component measured from the distal posterior electrodes. Rhythmic neural activity in the theta and gamma bands during maintenance provided converging support for the engagement of the same brain regions. These findings demonstrate that nonhuman primates have homologous electrophysiological signatures of visuospatial working memory to those of humans and that a distributed neural network, including frontal areas, underlies the posterior ERP index of visuospatial working memory maintenance. PMID:22649249

  2. A second look at the structure of human olfactory memory.

    Science.gov (United States)

    White, Theresa L

    2009-07-01

    How do we remember olfactory information? Is the architecture of human olfactory memory unique compared with that of memory for other types of stimuli? Ten years ago, a review article evaluated these questions, as well as the distinction between long- and short-term olfactory memory, with three lines of evidence: capacity differences, coding differences, and neuropsychological evidence, though serial position effects were also considered. From the data available at the time, the article preliminarily suggested that olfactory memory was a two-component system that was not qualitatively different from memory systems for other types of stimuli. The decade that has elapsed since then has ushered in considerable changes in theories of memory structure and provided huge advances in neuroscience capabilities. Not only have many studies exploring various aspects of olfactory memory been published, but a model of olfactory perception that includes an integral unitary memory system also has been presented. Consequently, the structure of olfactory memory is reevaluated in the light of further information currently available with the same theoretical lines of evidence previously considered. This evaluation finds that the preponderance of evidence suggests that, as in memory for other types of sensory stimuli, the short-term-long-term distinction remains a valuable dissociation for conceptualizing olfactory memory, though perhaps not as architecturally separate systems.

  3. Enhanced memory performance thanks to neural network assortativity

    International Nuclear Information System (INIS)

    Franciscis, S. de; Johnson, S.; Torres, J. J.

    2011-01-01

    The behaviour of many complex dynamical systems has been found to depend crucially on the structure of the underlying networks of interactions. An intriguing feature of empirical networks is their assortativity--i.e., the extent to which the degrees of neighbouring nodes are correlated. However, until very recently it was difficult to take this property into account analytically, most work being exclusively numerical. We get round this problem by considering ensembles of equally correlated graphs and apply this novel technique to the case of attractor neural networks. Assortativity turns out to be a key feature for memory performance in these systems - so much so that for sufficiently correlated topologies the critical temperature diverges. We predict that artificial and biological neural systems could significantly enhance their robustness to noise by developing positive correlations.

  4. Iconic memory and parietofrontal network: fMRI study using temporal integration.

    Science.gov (United States)

    Saneyoshi, Ayako; Niimi, Ryosuke; Suetsugu, Tomoko; Kaminaga, Tatsuro; Yokosawa, Kazuhiko

    2011-08-03

    We investigated the neural basis of iconic memory using functional magnetic resonance imaging. The parietofrontal network of selective attention is reportedly relevant to readout from iconic memory. We adopted a temporal integration task that requires iconic memory but not selective attention. The results showed that the task activated the parietofrontal network, confirming that the network is involved in readout from iconic memory. We further tested a condition in which temporal integration was performed by visual short-term memory but not by iconic memory. However, no brain region revealed higher activation for temporal integration by iconic memory than for temporal integration by visual short-term memory. This result suggested that there is no localized brain region specialized for iconic memory per se.

  5. 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. PMID:27375519

  6. Verbal working memory-related neural network communication in schizophrenia.

    Science.gov (United States)

    Kustermann, Thomas; Popov, Tzvetan; Miller, Gregory A; Rockstroh, Brigitte

    2018-04-19

    Impaired working memory (WM) in schizophrenia is associated with reduced hemodynamic and electromagnetic activity and altered network connectivity within and between memory-associated neural networks. The present study sought to determine whether schizophrenia involves disruption of a frontal-parietal network normally supporting WM and/or involvement of another brain network. Nineteen schizophrenia patients (SZ) and 19 healthy comparison subjects (HC) participated in a cued visual-verbal Sternberg task while dense-array EEG was recorded. A pair of item arrays each consisting of 2-4 consonants was presented bilaterally for 200 ms with a prior cue signaling the hemifield of the task-relevant WM set. A central probe letter 2,000 ms later prompted a choice reaction time decision about match/mismatch with the target WM set. Group and WM load effects on time domain and time-frequency domain 11-15 Hz alpha power were assessed for the cue-to-probe time window, and posterior 11-15 Hz alpha power and frontal 4-8 Hz theta power were assessed during the retention period. Directional connectivity was estimated via Granger causality, evaluating group differences in communication. SZ showed slower responding, lower accuracy, smaller overall time-domain alpha power increase, and less load-dependent alpha power increase. Midline frontal theta power increases did not vary by group or load. Network communication in SZ was characterized by temporal-to-posterior information flow, in contrast to bidirectional temporal-posterior communication in HC. Results indicate aberrant WM network activity supporting WM in SZ that might facilitate normal load-dependent and only marginally less accurate task performance, despite generally slower responding. © 2018 Society for Psychophysiological Research.

  7. Social Transmission of False Memory in Small Groups and Large Networks.

    Science.gov (United States)

    Maswood, Raeya; Rajaram, Suparna

    2018-05-21

    Sharing information and memories is a key feature of social interactions, making social contexts important for developing and transmitting accurate memories and also false memories. False memory transmission can have wide-ranging effects, including shaping personal memories of individuals as well as collective memories of a network of people. This paper reviews a collection of key findings and explanations in cognitive research on the transmission of false memories in small groups. It also reviews the emerging experimental work on larger networks and collective false memories. Given the reconstructive nature of memory, the abundance of misinformation in everyday life, and the variety of social structures in which people interact, an understanding of transmission of false memories has both scientific and societal implications. © 2018 Cognitive Science Society, Inc.

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

    Science.gov (United States)

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

    2013-10-01

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

  9. Is functional integration of resting state brain networks an unspecific biomarker for working memory performance?

    Science.gov (United States)

    Alavash, Mohsen; Doebler, Philipp; Holling, Heinz; Thiel, Christiane M; Gießing, Carsten

    2015-03-01

    Is there one optimal topology of functional brain networks at rest from which our cognitive performance would profit? Previous studies suggest that functional integration of resting state brain networks is an important biomarker for cognitive performance. However, it is still unknown whether higher network integration is an unspecific predictor for good cognitive performance or, alternatively, whether specific network organization during rest predicts only specific cognitive abilities. Here, we investigated the relationship between network integration at rest and cognitive performance using two tasks that measured different aspects of working memory; one task assessed visual-spatial and the other numerical working memory. Network clustering, modularity and efficiency were computed to capture network integration on different levels of network organization, and to statistically compare their correlations with the performance in each working memory test. The results revealed that each working memory aspect profits from a different resting state topology, and the tests showed significantly different correlations with each of the measures of network integration. While higher global network integration and modularity predicted significantly better performance in visual-spatial working memory, both measures showed no significant correlation with numerical working memory performance. In contrast, numerical working memory was superior in subjects with highly clustered brain networks, predominantly in the intraparietal sulcus, a core brain region of the working memory network. Our findings suggest that a specific balance between local and global functional integration of resting state brain networks facilitates special aspects of cognitive performance. In the context of working memory, while visual-spatial performance is facilitated by globally integrated functional resting state brain networks, numerical working memory profits from increased capacities for local processing

  10. Cognitive memory.

    Science.gov (United States)

    Widrow, Bernard; Aragon, Juan Carlos

    2013-05-01

    Regarding the workings of the human mind, memory and pattern recognition seem to be intertwined. You generally do not have one without the other. Taking inspiration from life experience, a new form of computer memory has been devised. Certain conjectures about human memory are keys to the central idea. The design of a practical and useful "cognitive" memory system is contemplated, a memory system that may also serve as a model for many aspects of human memory. The new memory does not function like a computer memory where specific data is stored in specific numbered registers and retrieval is done by reading the contents of the specified memory register, or done by matching key words as with a document search. Incoming sensory data would be stored at the next available empty memory location, and indeed could be stored redundantly at several empty locations. The stored sensory data would neither have key words nor would it be located in known or specified memory locations. Sensory inputs concerning a single object or subject are stored together as patterns in a single "file folder" or "memory folder". When the contents of the folder are retrieved, sights, sounds, tactile feel, smell, etc., are obtained all at the same time. Retrieval would be initiated by a query or a prompt signal from a current set of sensory inputs or patterns. A search through the memory would be made to locate stored data that correlates with or relates to the prompt input. The search would be done by a retrieval system whose first stage makes use of autoassociative artificial neural networks and whose second stage relies on exhaustive search. Applications of cognitive memory systems have been made to visual aircraft identification, aircraft navigation, and human facial recognition. Concerning human memory, reasons are given why it is unlikely that long-term memory is stored in the synapses of the brain's neural networks. Reasons are given suggesting that long-term memory is stored in DNA or RNA

  11. Capacity of oscillatory associative-memory networks with error-free retrieval

    International Nuclear Information System (INIS)

    Nishikawa, Takashi; Lai Yingcheng; Hoppensteadt, Frank C.

    2004-01-01

    Networks of coupled periodic oscillators (similar to the Kuramoto model) have been proposed as models of associative memory. However, error-free retrieval states of such oscillatory networks are typically unstable, resulting in a near zero capacity. This puts the networks at disadvantage as compared with the classical Hopfield network. Here we propose a simple remedy for this undesirable property and show rigorously that the error-free capacity of our oscillatory, associative-memory networks can be made as high as that of the Hopfield network. They can thus not only provide insights into the origin of biological memory, but can also be potentially useful for applications in information science and engineering

  12. Human short-term spatial memory: precision predicts capacity.

    Science.gov (United States)

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

    2015-03-01

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

  13. 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.

  14. What does the functional organization of cortico-hippocampal networks tell us about the functional organization of memory?

    Science.gov (United States)

    Reagh, Zachariah M; Ranganath, Charan

    2018-04-25

    Historically, research on the cognitive processes that support human memory proceeded, to a large extent, independently of research on the neural basis of memory. Accumulating evidence from neuroimaging, however, has enabled the field to develop a broader and more integrative perspective. Here, we briefly outline how advances in cognitive neuroscience can potentially shed light on concepts and controversies in human memory research. We argue that research on the functional properties of cortico-hippocampal networks informs us about how memories might be organized in the brain, which, in turn, helps to reconcile seemingly disparate perspectives in cognitive psychology. Finally, we discuss several open questions and directions for future research. Copyright © 2018. Published by Elsevier B.V.

  15. 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...

  16. 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...

  17. The ultrametric organization of memories in a neural network

    International Nuclear Information System (INIS)

    Parga, N.; Virasoro, M.A.

    1985-08-01

    In Hopfield's model of human memory the words to be stored must be orthogonal. From the point of view of human psychology this feature is unacceptable unless we reinterpret these words as primordial categories. But then one has to complete the model so as to be able to store a full hierarchical tree of categories embodying subcategories and so on. We use recent results on the spin glass mean field theories to show that this complementation can be done in a natural way with a minimal modification of Hebb's rule for learning. Categorization emerges naturally from an encoding stage structured in layers. (author)

  18. 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).

  19. A specific role for the human amygdala in olfactory memory.

    Science.gov (United States)

    Buchanan, Tony W; Tranel, Daniel; Adolphs, Ralph

    2003-01-01

    The medial temporal lobe is known to play a role in the processing of olfaction and memory. The specific contribution of the human amygdala to memory for odors has not been addressed, however. The role of this region in memory for odors was assessed in patients with unilateral amygdala damage due to temporal lobectomy (n = 20; 11 left, 9 right), one patient with selective bilateral amygdala damage, and in 20 age-matched normal controls. Fifteen odors were presented, followed 1 h later by an odor-name matching test and an odor-odor recognition test. Signal detection analyses showed that both unilateral groups were impaired in their memory for matching odors with names, these patients were not significantly impaired on odor-odor recognition. Bilateral amygdala damage resulted in severe impairment in both odor-name matching as well as in odor-odor recognition memory. Importantly, none of the patients were impaired on an auditory verbal learning task, suggesting that these findings reflect a specific impairment in olfactory memory, and not merely a more general memory deficit. Taken together, the data provide neuropsychological evidence that the human amygdala is essential for olfactory memory.

  20. Human tracking over camera networks: a review

    Science.gov (United States)

    Hou, Li; Wan, Wanggen; Hwang, Jenq-Neng; Muhammad, Rizwan; Yang, Mingyang; Han, Kang

    2017-12-01

    In recent years, automated human tracking over camera networks is getting essential for video surveillance. The tasks of tracking human over camera networks are not only inherently challenging due to changing human appearance, but also have enormous potentials for a wide range of practical applications, ranging from security surveillance to retail and health care. This review paper surveys the most widely used techniques and recent advances for human tracking over camera networks. Two important functional modules for the human tracking over camera networks are addressed, including human tracking within a camera and human tracking across non-overlapping cameras. The core techniques of human tracking within a camera are discussed based on two aspects, i.e., generative trackers and discriminative trackers. The core techniques of human tracking across non-overlapping cameras are then discussed based on the aspects of human re-identification, camera-link model-based tracking and graph model-based tracking. Our survey aims to address existing problems, challenges, and future research directions based on the analyses of the current progress made toward human tracking techniques over camera networks.

  1. Plastic modulation of episodic memory networks in the aging brain with cognitive decline.

    Science.gov (United States)

    Bai, Feng; Yuan, Yonggui; Yu, Hui; Zhang, Zhijun

    2016-07-15

    Social-cognitive processing has been posited to underlie general functions such as episodic memory. Episodic memory impairment is a recognized hallmark of amnestic mild cognitive impairment (aMCI) who is at a high risk for dementia. Three canonical networks, self-referential processing, executive control processing and salience processing, have distinct roles in episodic memory retrieval processing. It remains unclear whether and how these sub-networks of the episodic memory retrieval system would be affected in aMCI. This task-state fMRI study constructed systems-level episodic memory retrieval sub-networks in 28 aMCI and 23 controls using two computational approaches: a multiple region-of-interest based approach and a voxel-level functional connectivity-based approach, respectively. These approaches produced the remarkably similar findings that the self-referential processing network made critical contributions to episodic memory retrieval in aMCI. More conspicuous alterations in self-referential processing of the episodic memory retrieval network were identified in aMCI. In order to complete a given episodic memory retrieval task, increases in cooperation between the self-referential processing network and other sub-networks were mobilized in aMCI. Self-referential processing mediate the cooperation of the episodic memory retrieval sub-networks as it may help to achieve neural plasticity and may contribute to the prevention and treatment of dementia. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Memory and learning in a class of neural network models

    International Nuclear Information System (INIS)

    Wallace, D.J.

    1986-01-01

    The author discusses memory and learning properties of the neural network model now identified with Hopfield's work. The model, how it attempts to abstract some key features of the nervous system, and the sense in which learning and memory are identified in the model are described. A brief report is presented on the important role of phase transitions in the model and their implications for memory capacity. The results of numerical simulations obtained using the ICL Distributed Array Processors at Edinburgh are presented. A summary is presented on how the fraction of images which are perfectly stored, depends on the number of nodes and the number of nominal images which one attempts to store using the prescription in Hopfield's paper. Results are presented on the second phase transition in the model, which corresponds to almost total loss of storage capacity as the number of nominal images is increased. Results are given on the performance of a new iterative algorithm for exact storage of up to N images in an N node model

  3. Repeated labilization-reconsolidation processes strengthen declarative memory in humans.

    Directory of Open Access Journals (Sweden)

    Cecilia Forcato

    Full Text Available The idea that memories are immutable after consolidation has been challenged. Several reports have shown that after the presentation of a specific reminder, reactivated old memories become labile and again susceptible to amnesic agents. Such vulnerability diminishes with the progress of time and implies a re-stabilization phase, usually referred to as reconsolidation. To date, the main findings describe the mechanisms associated with the labilization-reconsolidation process, but little is known about its functionality from a biological standpoint. Indeed, two functions have been proposed. One suggests that destabilization of the original memory after the reminder allows the integration of new information into the background of the original memory (memory updating, and the other suggests that the labilization-reconsolidation process strengthens the original memory (memory strengthening. We have previously reported the reconsolidation of human declarative memories, demonstrating memory updating in the framework of reconsolidation. Here we deal with the strengthening function attributed to the reconsolidation process. We triggered labilization-reconsolidation processes successively by repeated presentations of the proper reminder. Participants learned an association between five cue-syllables and their respective response-syllables. Twenty-four hours later, the paired-associate verbal memory was labilized by exposing the subjects to one, two or four reminders. The List-memory was evaluated on Day 3 showing that the memory was improved when at least a second reminder was presented in the time window of the first labilization-reconsolidation process prompted by the earlier reminder. However, the improvement effect was revealed on Day 3, only when at least two reminders were presented on Day 2 and not as a consequence of only retrieval. Therefore, we propose central concepts for the reconsolidation process, emphasizing its biological role and the

  4. Repeated Labilization-Reconsolidation Processes Strengthen Declarative Memory in Humans

    Science.gov (United States)

    Forcato, Cecilia; Rodríguez, María L. C.; Pedreira, María E.

    2011-01-01

    The idea that memories are immutable after consolidation has been challenged. Several reports have shown that after the presentation of a specific reminder, reactivated old memories become labile and again susceptible to amnesic agents. Such vulnerability diminishes with the progress of time and implies a re-stabilization phase, usually referred to as reconsolidation. To date, the main findings describe the mechanisms associated with the labilization-reconsolidation process, but little is known about its functionality from a biological standpoint. Indeed, two functions have been proposed. One suggests that destabilization of the original memory after the reminder allows the integration of new information into the background of the original memory (memory updating), and the other suggests that the labilization-reconsolidation process strengthens the original memory (memory strengthening). We have previously reported the reconsolidation of human declarative memories, demonstrating memory updating in the framework of reconsolidation. Here we deal with the strengthening function attributed to the reconsolidation process. We triggered labilization-reconsolidation processes successively by repeated presentations of the proper reminder. Participants learned an association between five cue-syllables and their respective response-syllables. Twenty-four hours later, the paired-associate verbal memory was labilized by exposing the subjects to one, two or four reminders. The List-memory was evaluated on Day 3 showing that the memory was improved when at least a second reminder was presented in the time window of the first labilization-reconsolidation process prompted by the earlier reminder. However, the improvement effect was revealed on Day 3, only when at least two reminders were presented on Day2 and not as a consequence of only retrieval. Therefore, we propose central concepts for the reconsolidation process, emphasizing its biological role and the parametrical constrains

  5. 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

  6. EDUCATIONAL NETWORKING: HUMAN VIEW TO CYBER DEFENSE

    OpenAIRE

    Oleksandr Yu. Burov

    2016-01-01

    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 corr...

  7. 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.

  8. Not only … but also: REM sleep creates and NREM Stage 2 instantiates landmark junctions in cortical memory networks.

    Science.gov (United States)

    Llewellyn, Sue; Hobson, J Allan

    2015-07-01

    This article argues both rapid eye movement (REM) and non-rapid eye movement (NREM) sleep contribute to overnight episodic memory processes but their roles differ. Episodic memory may have evolved from memory for spatial navigation in animals and humans. Equally, mnemonic navigation in world and mental space may rely on fundamentally equivalent processes. Consequently, the basic spatial network characteristics of pathways which meet at omnidirectional nodes or junctions may be conserved in episodic brain networks. A pathway is formally identified with the unidirectional, sequential phases of an episodic memory. In contrast, the function of omnidirectional junctions is not well understood. In evolutionary terms, both animals and early humans undertook tours to a series of landmark junctions, to take advantage of resources (food, water and shelter), whilst trying to avoid predators. Such tours required memory for emotionally significant landmark resource-place-danger associations and the spatial relationships amongst these landmarks. In consequence, these tours may have driven the evolution of both spatial and episodic memory. The environment is dynamic. Resource-place associations are liable to shift and new resource-rich landmarks may be discovered, these changes may require re-wiring in neural networks. To realise these changes, REM may perform an associative, emotional encoding function between memory networks, engendering an omnidirectional landmark junction which is instantiated in the cortex during NREM Stage 2. In sum, REM may preplay associated elements of past episodes (rather than replay individual episodes), to engender an unconscious representation which can be used by the animal on approach to a landmark junction in wake. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. 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.

  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. Richness of information about novel words influences how episodic and semantic memory networks interact during lexicalization

    NARCIS (Netherlands)

    Takashima, A.; Bakker, I.; Hell, J.G. van; Janzen, G.; McQueen, J.M.

    2014-01-01

    The complementary learning systems account of declarative memory suggests two distinct memory networks, a fast-mapping, episodic system involving the hippocampus, and a slower semantic memory system distributed across the neocortex in which new information is gradually integrated with existing

  12. The role of sleep in human declarative memory consolidation.

    Science.gov (United States)

    Alger, Sara E; Chambers, Alexis M; Cunningham, Tony; Payne, Jessica D

    2015-01-01

    Through a variety of methods, researchers have begun unraveling the mystery of why humans spend one-third of their lives asleep. Though sleep likely serves multiple functions, it has become clear that the sleeping brain offers an ideal environment for solidifying newly learned information in the brain. Sleep , which comprises a complex collection of brain states, supports the consolidation of many different types of information. It not only promotes learning and memory stabilization, but also memory reorganization that can lead to various forms of insightful behavior. As this chapter will describe, research provides ample support for these crucial cognitive functions of sleep . Focusing on the declarative memory system in humans, we review the literature regarding the benefits of sleep for both neutral and emotionally salient declarative memory. Finally, we discuss the literature regarding the impact of sleep on emotion regulation.

  13. Formation and suppression of acoustic memories during human sleep.

    Science.gov (United States)

    Andrillon, Thomas; Pressnitzer, Daniel; Léger, Damien; Kouider, Sid

    2017-08-08

    Sleep and memory are deeply related, but the nature of the neuroplastic processes induced by sleep remains unclear. Here, we report that memory traces can be both formed or suppressed during sleep, depending on sleep phase. We played samples of acoustic noise to sleeping human listeners. Repeated exposure to a novel noise during Rapid Eye Movements (REM) or light non-REM (NREM) sleep leads to improvements in behavioral performance upon awakening. Strikingly, the same exposure during deep NREM sleep leads to impaired performance upon awakening. Electroencephalographic markers of learning extracted during sleep confirm a dissociation between sleep facilitating memory formation (light NREM and REM sleep) and sleep suppressing learning (deep NREM sleep). We can trace these neural changes back to transient sleep events, such as spindles for memory facilitation and slow waves for suppression. Thus, highly selective memory processes are active during human sleep, with intertwined episodes of facilitative and suppressive plasticity.Though memory and sleep are related, it is still unclear whether new memories can be formed during sleep. Here, authors show that people could learn new sounds during REM or light non-REM sleep, but that learning was suppressed when sounds were played during deep NREM sleep.

  14. 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

  15. Human Temporal Cortical Single Neuron Activity During Working Memory Maintenance

    Science.gov (United States)

    Zamora, Leona; Corina, David; Ojemann, George

    2016-01-01

    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

  16. 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.

  17. Network Sampling with Memory: A proposal for more efficient sampling from social networks

    Science.gov (United States)

    Mouw, Ted; Verdery, Ashton M.

    2013-01-01

    Techniques for sampling from networks have grown into an important area of research across several fields. For sociologists, the possibility of sampling from a network is appealing for two reasons: (1) A network sample can yield substantively interesting data about network structures and social interactions, and (2) it is useful in situations where study populations are difficult or impossible to survey with traditional sampling approaches because of the lack of a sampling frame. Despite its appeal, methodological concerns about the precision and accuracy of network-based sampling methods remain. In particular, recent research has shown that sampling from a network using a random walk based approach such as Respondent Driven Sampling (RDS) can result in high design effects (DE)—the ratio of the sampling variance to the sampling variance of simple random sampling (SRS). A high design effect means that more cases must be collected to achieve the same level of precision as SRS. In this paper we propose an alternative strategy, Network Sampling with Memory (NSM), which collects network data from respondents in order to reduce design effects and, correspondingly, the number of interviews needed to achieve a given level of statistical power. NSM combines a “List” mode, where all individuals on the revealed network list are sampled with the same cumulative probability, with a “Search” mode, which gives priority to bridge nodes connecting the current sample to unexplored parts of the network. We test the relative efficiency of NSM compared to RDS and SRS on 162 school and university networks from Add Health and Facebook that range in size from 110 to 16,278 nodes. The results show that the average design effect for NSM on these 162 networks is 1.16, which is very close to the efficiency of a simple random sample (DE=1), and 98.5% lower than the average DE we observed for RDS. PMID:24159246

  18. 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.

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

    Science.gov (United States)

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

    2018-05-01

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

  20. Concept typicality responses in the semantic memory network.

    Science.gov (United States)

    Santi, Andrea; Raposo, Ana; Frade, Sofia; Marques, J Frederico

    2016-12-01

    For decades concept typicality has been recognized as critical to structuring conceptual knowledge, but only recently has typicality been applied in better understanding the processes engaged by the neurological network underlying semantic memory. This previous work has focused on one region within the network - the Anterior Temporal Lobe (ATL). The ATL responds negatively to concept typicality (i.e., the more atypical the item, the greater the activation in the ATL). To better understand the role of typicality in the entire network, we ran an fMRI study using a category verification task in which concept typicality was manipulated parametrically. We argue that typicality is relevant to both amodal feature integration centers as well as category-specific regions. Both the Inferior Frontal Gyrus (IFG) and ATL demonstrated a negative correlation with typicality, whereas inferior parietal regions showed positive effects. We interpret this in light of functional theories of these regions. Interactions between category and typicality were not observed in regions classically recognized as category-specific, thus, providing an argument against category specific regions, at least with fMRI. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Pre-stimulus thalamic theta power predicts human memory formation.

    Science.gov (United States)

    Sweeney-Reed, Catherine M; Zaehle, Tino; Voges, Jürgen; Schmitt, Friedhelm C; Buentjen, Lars; Kopitzki, Klaus; Richardson-Klavehn, Alan; Hinrichs, Hermann; Heinze, Hans-Jochen; Knight, Robert T; Rugg, Michael D

    2016-09-01

    Pre-stimulus theta (4-8Hz) power in the hippocampus and neocortex predicts whether a memory for a subsequent event will be formed. Anatomical studies reveal thalamus-hippocampal connectivity, and lesion, neuroimaging, and electrophysiological studies show that memory processing involves the dorsomedial (DMTN) and anterior thalamic nuclei (ATN). The small size and deep location of these nuclei have limited real-time study of their activity, however, and it is unknown whether pre-stimulus theta power predictive of successful memory formation is also found in these subcortical structures. We recorded human electrophysiological data from the DMTN and ATN of 7 patients receiving deep brain stimulation for refractory epilepsy. We found that greater pre-stimulus theta power in the right DMTN was associated with successful memory encoding, predicting both behavioral outcome and post-stimulus correlates of successful memory formation. In particular, significant correlations were observed between right DMTN theta power and both frontal theta and right ATN gamma (32-50Hz) phase alignment, and frontal-ATN theta-gamma cross-frequency coupling. We draw the following primary conclusions. Our results provide direct electrophysiological evidence in humans of a role for the DMTN as well as the ATN in memory formation. Furthermore, prediction of subsequent memory performance by pre-stimulus thalamic oscillations provides evidence that post-stimulus differences in thalamic activity that index successful and unsuccessful encoding reflect brain processes specifically underpinning memory formation. Finally, the findings broaden the understanding of brain states that facilitate memory encoding to include subcortical as well as cortical structures. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. 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.

  3. Shape memory and actuation behavior of semicrystalline polymer networks

    International Nuclear Information System (INIS)

    Bothe, Martin

    2014-01-01

    Shape memory polymers (SMPs) can change their shape on application of a suitable stimulus. To enable such behavior, a 'programming' procedure fixes a deformation, yielding a stable temporary shape. In thermoresponsive SMPs, subsequent heating triggers entropy-elastic recovery of the initial shape. An additional shape change on cooling, i.e. thermoreversible two-way actuation, can be stimulated by a crystallization phenomenon. In this thesis, cyclic thermomechanical measurements systematically determined (1) the shape memory and (2) the actuation behavior under constant load as well as under stress-free conditions. Chemically cross-linked, star-shaped polyhedral oligomeric silsesquioxane polyurethane (SPOSS-PU) hybrid polymer networks and physically cross-linked poly(ester urethane) (PEU) block copolymers were investigated around the melting and crystallization temperatures of their polyester soft segments. (1) The SPOSS-PUs showed excellent shape fixities and recoverabilities of almost 100% at high cross-linking density, while PEUs exhibited pronounced shape memory properties at increased soft segment content. Furthermore, two-fold programmed SPOSS-PU specimens were able to recover their initial shape in two thermally separated events. Even a neck, which formed during deformation of SPOSS-PUs with high soft segment content, was reversed. (2) In PEUs, globally oriented crystallization on cooling drove expansion of the sample, in particular at high soft segment content and after application of a strong deformation. Melting reversed that orientation; the PEU sample contracted and thereby completed the thermoreversible actuation cycle. Under load, multiple polymorphic phase transitions enabled two successive expansion and contraction steps, while under stress-free conditions various geometric shape changes, including the increase and decrease of PEU sample length and thickness as well as twisting and untwisting could be experimentally witnessed. Such actuation

  4. Shape memory and actuation behavior of semicrystalline polymer networks

    Energy Technology Data Exchange (ETDEWEB)

    Bothe, Martin

    2014-07-01

    Shape memory polymers (SMPs) can change their shape on application of a suitable stimulus. To enable such behavior, a 'programming' procedure fixes a deformation, yielding a stable temporary shape. In thermoresponsive SMPs, subsequent heating triggers entropy-elastic recovery of the initial shape. An additional shape change on cooling, i.e. thermoreversible two-way actuation, can be stimulated by a crystallization phenomenon. In this thesis, cyclic thermomechanical measurements systematically determined (1) the shape memory and (2) the actuation behavior under constant load as well as under stress-free conditions. Chemically cross-linked, star-shaped polyhedral oligomeric silsesquioxane polyurethane (SPOSS-PU) hybrid polymer networks and physically cross-linked poly(ester urethane) (PEU) block copolymers were investigated around the melting and crystallization temperatures of their polyester soft segments. (1) The SPOSS-PUs showed excellent shape fixities and recoverabilities of almost 100% at high cross-linking density, while PEUs exhibited pronounced shape memory properties at increased soft segment content. Furthermore, two-fold programmed SPOSS-PU specimens were able to recover their initial shape in two thermally separated events. Even a neck, which formed during deformation of SPOSS-PUs with high soft segment content, was reversed. (2) In PEUs, globally oriented crystallization on cooling drove expansion of the sample, in particular at high soft segment content and after application of a strong deformation. Melting reversed that orientation; the PEU sample contracted and thereby completed the thermoreversible actuation cycle. Under load, multiple polymorphic phase transitions enabled two successive expansion and contraction steps, while under stress-free conditions various geometric shape changes, including the increase and decrease of PEU sample length and thickness as well as twisting and untwisting could be experimentally witnessed. Such

  5. 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.

  6. Centralized Networks to Generate Human Body Motions.

    Science.gov (United States)

    Vakulenko, Sergei; Radulescu, Ovidiu; Morozov, Ivan; Weber, Andres

    2017-12-14

    We consider continuous-time recurrent neural networks as dynamical models for the simulation of human body motions. These networks consist of a few centers and many satellites connected to them. The centers evolve in time as periodical oscillators with different frequencies. The center states define the satellite neurons' states by a radial basis function (RBF) network. To simulate different motions, we adjust the parameters of the RBF networks. Our network includes a switching module that allows for turning from one motion to another. Simulations show that this model allows us to simulate complicated motions consisting of many different dynamical primitives. We also use the model for learning human body motion from markers' trajectories. We find that center frequencies can be learned from a small number of markers and can be transferred to other markers, such that our technique seems to be capable of correcting for missing information resulting from sparse control marker settings.

  7. Neuroanatomy of episodic and semantic memory in humans: a brief review of neuroimaging studies.

    Science.gov (United States)

    García-Lázaro, Haydée G; Ramirez-Carmona, Rocio; Lara-Romero, Ruben; Roldan-Valadez, Ernesto

    2012-01-01

    One of the most basic functions in every individual and species is memory. Memory is the process by which information is saved as knowledge and retained for further use as needed. Learning is a neurobiological phenomenon by which we acquire certain information from the outside world and is a precursor to memory. Memory consists of the capacity to encode, store, consolidate, and retrieve information. Recently, memory has been defined as a network of connections whose function is primarily to facilitate the long-lasting persistence of learned environmental cues. In this review, we present a brief description of the current classifications of memory networks with a focus on episodic memory and its anatomical substrate. We also present a brief review of the anatomical basis of memory systems and the most commonly used neuroimaging methods to assess memory, illustrated with magnetic resonance imaging images depicting the hippocampus, temporal lobe, and hippocampal formation, which are the main brain structures participating in memory networks.

  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. The parietal memory network activates similarly for true and associative false recognition elicited via the DRM procedure.

    Science.gov (United States)

    McDermott, Kathleen B; Gilmore, Adrian W; Nelson, Steven M; Watson, Jason M; Ojemann, Jeffrey G

    2017-02-01

    Neuroimaging investigations of human memory encoding and retrieval have revealed that multiple regions of parietal cortex contribute to memory. Recently, a sparse network of regions within parietal cortex has been identified using resting state functional connectivity (MRI techniques). The regions within this network exhibit consistent task-related responses during memory formation and retrieval, leading to its being called the parietal memory network (PMN). Among its signature patterns are: deactivation during initial experience with an item (e.g., encoding); activation during subsequent repetitions (e.g., at retrieval); greater activation for successfully retrieved familiar words than novel words (e.g., hits relative to correctly-rejected lures). The question of interest here is whether novel words that are subjectively experienced as having been recently studied would elicit PMN activation similar to that of hits. That is, we compared old items correctly recognized to two types of novel items on a recognition test: those correctly identified as new and those incorrectly labeled as old due to their strong associative relation to the studied words (in the DRM false memory protocol). Subjective oldness plays a strong role in driving activation, as hits and false alarms activated similarly (and greater than correctly-rejected lures). Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. 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.

  11. Measuring dynamic process of working memory training with functional brain networks

    Directory of Open Access Journals (Sweden)

    Hong Wang

    2015-12-01

    Full Text Available In this paper, we proposed the functional brain networks and graphic theory method to measure the effect of working memory training on the neural activities. 12 subjects were recruited in this study, and they did the same working memory task before they had been trained and after training. We architected functional brain networks based on EEG coherence and calculated properties of brain networks to measure the neural co-activities and the working memory level of subjects. As the result, the internal connections in frontal region decreased after working memory training, but the connection between frontal region and top region increased. And the more small-world feature was observed after training. The features observed above were in alpha (8-13 Hz and beta (13-30 Hz bands. The functional brain networks based on EEG coherence proposed in this paper can be used as the indicator of working memory level.

  12. 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.

  13. Glucose enhancement of human memory: a comprehensive research review of the glucose memory facilitation effect.

    Science.gov (United States)

    Smith, Michael A; Riby, Leigh M; Eekelen, J Anke M van; Foster, Jonathan K

    2011-01-01

    The brain relies upon glucose as its primary fuel. In recent years, a rich literature has developed from both human and animal studies indicating that increases in circulating blood glucose can facilitate cognitive functioning. This phenomenon has been termed the 'glucose memory facilitation effect'. The purpose of this review is to discuss a number of salient studies which have investigated the influence of glucose ingestion on neurocognitive performance in individuals with (a) compromised neurocognitive capacity, as well as (b) normally functioning individuals (with a focus on research conducted with human participants). The proposed neurocognitive mechanisms purported to underlie the modulatory effect of glucose on neurocognitive performance will also be considered. Many theories have focussed upon the hippocampus, given that this brain region is heavily implicated in learning and memory. Further, it will be suggested that glucose is a possible mechanism underlying the phenomenon that enhanced memory performance is typically observed for emotionally laden stimuli. Copyright © 2010 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    Michelmann, Sebastian; Bowman, Howard; Hanslmayr, Simon

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Sebastian Michelmann

    2016-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Sergio Verduzco-Flores

    2009-08-01

    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.

  17. The impact of auditory working memory training on the fronto-parietal working memory network

    OpenAIRE

    Schneiders, Julia A.; Opitz, Bertram; Tang, Huijun; Deng, Yuan; Xie, Chaoxiang; Li, Hong; Mecklinger, Axel

    2012-01-01

    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 ...

  18. Visual question answering using hierarchical dynamic memory networks

    Science.gov (United States)

    Shang, Jiayu; Li, Shiren; Duan, Zhikui; Huang, Junwei

    2018-04-01

    Visual Question Answering (VQA) is one of the most popular research fields in machine learning which aims to let the computer learn to answer natural language questions with images. In this paper, we propose a new method called hierarchical dynamic memory networks (HDMN), which takes both question attention and visual attention into consideration impressed by Co-Attention method, which is the best (or among the best) algorithm for now. Additionally, we use bi-directional LSTMs, which have a better capability to remain more information from the question and image, to replace the old unit so that we can capture information from both past and future sentences to be used. Then we rebuild the hierarchical architecture for not only question attention but also visual attention. What's more, we accelerate the algorithm via a new technic called Batch Normalization which helps the network converge more quickly than other algorithms. The experimental result shows that our model improves the state of the art on the large COCO-QA dataset, compared with other methods.

  19. Expression of human PQBP-1 in Drosophila impairs long-term memory and induces abnormal courtship.

    Science.gov (United States)

    Yoshimura, Natsue; Horiuchi, Daisuke; Shibata, Masao; Saitoe, Minoru; Qi, Mei-Ling; Okazawa, Hitoshi

    2006-04-17

    Frame shift mutations of the polyglutamine binding protein-1 (PQBP1) gene lead to total or partial truncation of the C-terminal domain (CTD) and cause mental retardation in human patients. Interestingly, normal Drosophila homologue of PQBP-1 lacks CTD. As a model to analyze the molecular network of PQBP-1 affecting intelligence, we generated transgenic flies expressing human PQBP-1 with CTD. Pavlovian olfactory conditioning revealed that the transgenic flies showed disturbance of long-term memory. In addition, they showed abnormal courtship that male flies follow male flies. Abnormal functions of PQBP-1 or its binding partner might be linked to these symptoms.

  20. Thalamic Control of Human Attention Driven by Memory and Learning

    OpenAIRE

    de Bourbon-Teles, José; Bentley, Paul; Koshino, Saori; Shah, Kushal; Dutta, Agneish; Malhotra, Paresh; Egner, Tobias; Husain, Masud; Soto, David

    2014-01-01

    Summary The role of the thalamus in high-level cognition—attention, working memory (WM), rule-based learning, and decision making—remains poorly understood, especially in comparison to that of cortical frontoparietal networks [1–3]. Studies of visual thalamus have revealed important roles for pulvinar and lateral geniculate nucleus in visuospatial perception and attention [4–10] and for mediodorsal thalamus in oculomotor control [11]. Ventrolateral thalamus contains subdivisions devoted to ac...

  1. Adaptive changes in human memory: a literature review

    Directory of Open Access Journals (Sweden)

    Agnieszka Laura Sabiniewicz

    2017-07-01

    Full Text Available The paper contains a review of the literature concerning memory abilities and human senses performance under different environmental circumstances. A number of studies indicated that environment has a significant impact on human senses functioning. It can affect it in a mechanical way, by a chronic exposure to potentially harmful substances or processes in different work environments. Also, some cognitive abilities that have evolved to perform evolutionary essential functions lost their importance because of the change of environment impact. Moreover, training can be a source of improvement of both human senses and cognitive abilities, as well. That might suggest that, while using, under different environmental circumstances different cognitive abilities develop. We take into a particular consideration human memory and its role, show current studies in this field and suggest new research directions.

  2. Functional connectivity pattern during rest within the episodic memory network in association with episodic memory performance in bipolar disorder.

    Science.gov (United States)

    Oertel-Knöchel, Viola; Reinke, Britta; Matura, Silke; Prvulovic, David; Linden, David E J; van de Ven, Vincent

    2015-02-28

    In this study, we sought to examine the intrinsic functional organization of the episodic memory network during rest in bipolar disorder (BD). The previous work suggests that deficits in intrinsic functional connectivity may account for impaired memory performance. We hypothesized that regions involved in episodic memory processing would reveal aberrant functional connectivity in patients with bipolar disorder. We examined 21 patients with BD and 21 healthy matched controls who underwent functional magnetic resonance imaging (fMRI) during a resting condition. We did a seed-based functional connectivity analysis (SBA), using the regions of the episodic memory network that showed a significantly different activation pattern during task-related fMRI as seeds. The functional connectivity scores (FC) were further correlated with episodic memory task performance. Our results revealed decreased FC scores within frontal areas and between frontal and temporal/hippocampal/limbic regions in BD patients in comparison with controls. We observed higher FC in BD patients compared with controls between frontal and limbic regions. The decrease in fronto-frontal functional connectivity in BD patients showed a significant positive association with episodic memory performance. The association between task-independent dysfunctional frontal-limbic FC and episodic memory performance may be relevant for current pathophysiological models of the disease. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  3. Heider balance in human networks

    Science.gov (United States)

    Gawroński, P.; Kułakowski, K.

    2005-07-01

    Recently, a continuous dynamics was proposed to simulate dynamics of interpersonal relations in a society represented by a fully connected graph. The final state of such a society was found to be identical with the so-called Heider balance (HB), where the society is divided into two mutually hostile groups. In the continuous model, a polarization of opinions was found in HB. Here we demonstrate that the polarization occurs also in Barabási-Albert networks, where the Heider balance is not necessarily present. In the second part of this work we demonstrate the results of our formalism, when applied to reference examples: the Southern women and the Zachary club.

  4. 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.

  5. A Larger Social Network Enhances Novel Object Location Memory and Reduces Hippocampal Microgliosis in Aged Mice

    Science.gov (United States)

    Smith, Bryon M.; Yao, Xinyue; Chen, Kelly S.; Kirby, Elizabeth D.

    2018-01-01

    The mammalian hippocampus shows marked decline in function with aging across many species, including humans and laboratory rodent models. This decline frequently manifests in memory impairments that occur even in the absence of dementia pathology. In humans, a number of factors correlate with preserved hippocampal memory in aging, such as exercise, cognitive stimulation and number of social ties. While interventional studies and animal models clearly indicate that exercise and cognitive stimulation lead to hippocampal preservation, there is relatively little research on whether a decline in social ties leads to cognitive decline or vice versa. Even in animal studies of environmental enrichment in aging, the focus typically falls on physical enrichment such as a rotating cast of toys, rather than the role of social interactions. The present studies investigated the hypothesis that a greater number of social ties in aging mice would lead to improved hippocampal function. Aged, female C57/Bl6 mice were housed for 3 months in pairs or large groups (7 mice per cage). Group-housed mice showed greater novel object location memory and stronger preference for a spatial navigation strategy in the Barnes maze, though no difference in escape latency, compared to pair-housed mice. Group-housed mice did not differ from pair-housed mice in basal corticosterone levels or adult hippocampal neurogenesis. Group-housed mice did, however, show reduced numbers of Iba1/CD68+ microglia in the hippocampus. These findings suggest that group housing led to better memory function and reduced markers of neuroinflammation in aged mice. More broadly, they support a causative link between social ties and hippocampal function, suggesting that merely having a larger social network can positively influence the aging brain. Future research should address the molecular mechanisms by which a greater number of social ties alters hippocampal function. PMID:29904345

  6. 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.

  7. 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

  8. Integrating Data and Networks: Human Factors

    Science.gov (United States)

    Chen, R. S.

    2012-12-01

    The development of technical linkages and interoperability between scientific networks is a necessary but not sufficient step towards integrated use and application of networked data and information for scientific and societal benefit. A range of "human factors" must also be addressed to ensure the long-term integration, sustainability, and utility of both the interoperable networks themselves and the scientific data and information to which they provide access. These human factors encompass the behavior of both individual humans and human institutions, and include system governance, a common framework for intellectual property rights and data sharing, consensus on terminology, metadata, and quality control processes, agreement on key system metrics and milestones, the compatibility of "business models" in the short and long term, harmonization of incentives for cooperation, and minimization of disincentives. Experience with several national and international initiatives and research programs such as the International Polar Year, the Group on Earth Observations, the NASA Earth Observing Data and Information System, the U.S. National Spatial Data Infrastructure, the Global Earthquake Model, and the United Nations Spatial Data Infrastructure provide a range of lessons regarding these human factors. Ongoing changes in science, technology, institutions, relationships, and even culture are creating both opportunities and challenges for expanded interoperability of scientific networks and significant improvement in data integration to advance science and the use of scientific data and information to achieve benefits for society as a whole.

  9. Distinct Hippocampal versus Frontoparietal Network Contributions to Retrieval and Memory-guided Exploration.

    Science.gov (United States)

    Bridge, Donna J; Cohen, Neal J; Voss, Joel L

    2017-08-01

    Memory can profoundly influence new learning, presumably because memory optimizes exploration of to-be-learned material. Although hippocampus and frontoparietal networks have been implicated in memory-guided exploration, their specific and interactive roles have not been identified. We examined eye movements during fMRI scanning to identify neural correlates of the influences of memory retrieval on exploration and learning. After retrieval of one object in a multiobject array, viewing was strategically directed away from the retrieved object toward nonretrieved objects, such that exploration was directed toward to-be-learned content. Retrieved objects later served as optimal reminder cues, indicating that exploration caused memory to become structured around the retrieved content. Hippocampal activity was associated with memory retrieval, whereas frontoparietal activity varied with strategic viewing patterns deployed after retrieval, thus providing spatiotemporal dissociation of memory retrieval from memory-guided learning strategies. Time-lagged fMRI connectivity analyses indicated that hippocampal activity predicted frontoparietal activity to a greater extent for a condition in which retrieval guided exploration occurred than for a passive control condition in which exploration was not influenced by retrieval. This demonstrates network-level interaction effects specific to influences of memory on strategic exploration. These findings show how memory guides behavior during learning and demonstrate distinct yet interactive hippocampal-frontoparietal roles in implementing strategic exploration behaviors that determine the fate of evolving memory representations.

  10. Distinct hippocampal versus frontoparietal-network contributions to retrieval and memory-guided exploration

    Science.gov (United States)

    Bridge, Donna J.; Cohen, Neal J.; Voss, Joel L.

    2017-01-01

    Memory can profoundly influence new learning, presumably because memory optimizes exploration of to-be-learned material. Although hippocampus and frontoparietal networks have been implicated in memory-guided exploration, their specific and interactive roles have not been identified. We examined eye movements during fMRI scanning to identify neural correlates of the influences of memory retrieval on exploration and learning. Following retrieval of one object in a multi-object array, viewing was strategically directed away from the retrieved object toward non-retrieved objects, such that exploration was directed towards to-be-learned content. Retrieved objects later served as optimal reminder cues, indicating that exploration caused memory to become structured around the retrieved content. Hippocampal activity was associated with memory retrieval whereas frontoparietal activity varied with strategic viewing patterns deployed following retrieval, thus providing spatiotemporal dissociation of memory retrieval from memory-guided learning strategies. Time-lagged fMRI connectivity analyses indicated that hippocampal activity predicted frontoparietal activity to a greater extent for a condition in which retrieval guided exploration than for a passive control condition in which exploration was not influenced by retrieval. This demonstrates network-level interaction effects specific to influences of memory on strategic exploration. These findings show how memory guides behavior during learning and demonstrate distinct yet interactive hippocampal-frontoparietal roles in implementing strategic exploration behaviors that determine the fate of evolving memory representations. PMID:28471729

  11. 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

    2017-03-14

    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.

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

    OpenAIRE

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

    2014-01-01

    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 ...

  13. Evidence for anomalous network connectivity during working memory encoding in schizophrenia: an ICA based analysis.

    Directory of Open Access Journals (Sweden)

    Shashwath A Meda

    2009-11-01

    Full Text Available Numerous neuroimaging studies report abnormal regional brain activity during working memory performance in schizophrenia, but few have examined brain network integration as determined by "functional connectivity" analyses.We used independent component analysis (ICA to identify and characterize dysfunctional spatiotemporal networks in schizophrenia engaged during the different stages (encoding and recognition of a Sternberg working memory fMRI paradigm. 37 chronic schizophrenia and 54 healthy age/gender-matched participants performed a modified Sternberg Item Recognition fMRI task. Time series images preprocessed with SPM2 were analyzed using ICA. Schizophrenia patients showed relatively less engagement of several distinct "normal" encoding-related working memory networks compared to controls. These encoding networks comprised 1 left posterior parietal-left dorsal/ventrolateral prefrontal cortex, cingulate, basal ganglia, 2 right posterior parietal, right dorsolateral prefrontal cortex and 3 default mode network. In addition, the left fronto-parietal network demonstrated a load-dependent functional response during encoding. Network engagement that differed between groups during recognition comprised the posterior cingulate, cuneus and hippocampus/parahippocampus. As expected, working memory task accuracy differed between groups (p<0.0001 and was associated with degree of network engagement. Functional connectivity within all three encoding-associated functional networks correlated significantly with task accuracy, which further underscores the relevance of abnormal network integration to well-described schizophrenia working memory impairment. No network was significantly associated with task accuracy during the recognition phase.This study extends the results of numerous previous schizophrenia studies that identified isolated dysfunctional brain regions by providing evidence of disrupted schizophrenia functional connectivity using ICA within

  14. Multiple spatial frequency channels in human visual perceptual memory.

    Science.gov (United States)

    Nemes, V A; Whitaker, D; Heron, J; McKeefry, D J

    2011-12-08

    Current models of short-term visual perceptual memory invoke mechanisms that are closely allied to low-level perceptual discrimination mechanisms. The purpose of this study was to investigate the extent to which human visual perceptual memory for spatial frequency is based upon multiple, spatially tuned channels similar to those found in the earliest stages of visual processing. To this end we measured how performance on a delayed spatial frequency discrimination paradigm was affected by the introduction of interfering or 'memory masking' stimuli of variable spatial frequency during the delay period. Masking stimuli were shown to induce shifts in the points of subjective equality (PSE) when their spatial frequencies were within a bandwidth of 1.2 octaves of the reference spatial frequency. When mask spatial frequencies differed by more than this value, there was no change in the PSE from baseline levels. This selective pattern of masking was observed for different spatial frequencies and demonstrates the existence of multiple, spatially tuned mechanisms in visual perceptual memory. Memory masking effects were also found to occur for horizontal separations of up to 6 deg between the masking and test stimuli and lacked any orientation selectivity. These findings add further support to the view that low-level sensory processing mechanisms form the basis for the retention of spatial frequency information in perceptual memory. However, the broad range of transfer of memory masking effects across spatial location and other dimensions indicates more long range, long duration interactions between spatial frequency channels that are likely to rely contributions from neural processes located in higher visual areas. Copyright © 2011 Elsevier Ltd. All rights reserved.

  15. 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…

  16. Short-term memory in olfactory network dynamics

    Science.gov (United States)

    Stopfer, Mark; Laurent, Gilles

    1999-12-01

    Neural assemblies in a number of animal species display self-organized, synchronized oscillations in response to sensory stimuli in a variety of brain areas.. In the olfactory system of insects, odour-evoked oscillatory synchronization of antennal lobe projection neurons (PNs) is superimposed on slower and stimulus-specific temporal activity patterns. Hence, each odour activates a specific and dynamic projection neuron assembly whose evolution during a stimulus is locked to the oscillation clock. Here we examine, using locusts, the changes in population dynamics of projection-neuron assemblies over repeated odour stimulations, as would occur when an animal first encounters and then repeatedly samples an odour for identification or localization. We find that the responses of these assemblies rapidly decrease in intensity, while they show a marked increase in spike time precision and inter-neuronal oscillatory coherence. Once established, this enhanced precision in the representation endures for several minutes. This change is stimulus-specific, and depends on events within the antennal lobe circuits, independent of olfactory receptor adaptation: it may thus constitute a form of sensory memory. Our results suggest that this progressive change in olfactory network dynamics serves to converge, over repeated odour samplings, on a more precise and readily classifiable odour representation, using relational information contained across neural assemblies.

  17. 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.

  18. 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

    2014-10-01

    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 toward 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 reward-guided 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. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. Is a Responsive Default Mode Network Required for Successful Working Memory Task Performance?

    Science.gov (United States)

    Čeko, Marta; Gracely, John L; Fitzcharles, Mary-Ann; Seminowicz, David A; Schweinhardt, Petra; Bushnell, M Catherine

    2015-08-19

    In studies of cognitive processing using tasks with externally directed attention, regions showing increased (external-task-positive) and decreased or "negative" [default-mode network (DMN)] fMRI responses during task performance are dynamically responsive to increasing task difficulty. Responsiveness (modulation of fMRI signal by increasing load) has been linked directly to successful cognitive task performance in external-task-positive regions but not in DMN regions. To investigate whether a responsive DMN is required for successful cognitive performance, we compared healthy human subjects (n = 23) with individuals shown to have decreased DMN engagement (chronic pain patients, n = 28). Subjects performed a multilevel working-memory task (N-back) during fMRI. If a responsive DMN is required for successful performance, patients having reduced DMN responsiveness should show worsened performance; if performance is not reduced, their brains should show compensatory activation in external-task-positive regions or elsewhere. All subjects showed decreased accuracy and increased reaction times with increasing task level, with no significant group differences on either measure at any level. Patients had significantly reduced negative fMRI response (deactivation) of DMN regions (posterior cingulate/precuneus, medial prefrontal cortex). Controls showed expected modulation of DMN deactivation with increasing task difficulty. Patients showed significantly reduced modulation of DMN deactivation by task difficulty, despite their successful task performance. We found no evidence of compensatory neural recruitment in external-task-positive regions or elsewhere. Individual responsiveness of the external-task-positive ventrolateral prefrontal cortex, but not of DMN regions, correlated with task accuracy. These findings suggest that a responsive DMN may not be required for successful cognitive performance; a responsive external-task-positive network may be sufficient. We studied the

  20. An architecture for human-network interfaces

    DEFF Research Database (Denmark)

    Sonnenwald, Diane H.

    1990-01-01

    Some of the issues (and their consequences) that arise when human-network interfaces (HNIs) are viewed from the perspective of people who use and develop them are examined. Target attributes of HNI architecture are presented. A high-level architecture model that supports the attributes is discussed...

  1. Finite-Time Stability for Fractional-Order Bidirectional Associative Memory Neural Networks with Time Delays

    International Nuclear Information System (INIS)

    Xu Chang-Jin; Li Pei-Luan; Pang Yi-Cheng

    2017-01-01

    This paper is concerned with fractional-order bidirectional associative memory (BAM) neural networks with time delays. Applying Laplace transform, the generalized Gronwall inequality and estimates of Mittag–Leffler functions, some sufficient conditions which ensure the finite-time stability of fractional-order bidirectional associative memory neural networks with time delays are obtained. Two examples with their simulations are given to illustrate the theoretical findings. Our results are new and complement previously known results. (paper)

  2. Deep Recurrent Neural Networks for Human Activity Recognition

    Directory of Open Access Journals (Sweden)

    Abdulmajid Murad

    2017-11-01

    Full Text Available Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM and k-nearest neighbors (KNN. Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs and CNNs.

  3. Deep Recurrent Neural Networks for Human Activity Recognition.

    Science.gov (United States)

    Murad, Abdulmajid; Pyun, Jae-Young

    2017-11-06

    Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs.

  4. SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks

    OpenAIRE

    Wang, Linnan; Ye, Jinmian; Zhao, Yiyang; Wu, Wei; Li, Ang; Song, Shuaiwen Leon; Xu, Zenglin; Kraska, Tim

    2018-01-01

    Going deeper and wider in neural architectures improves the accuracy, while the limited GPU DRAM places an undesired restriction on the network design domain. Deep Learning (DL) practitioners either need change to less desired network architectures, or nontrivially dissect a network across multiGPUs. These distract DL practitioners from concentrating on their original machine learning tasks. We present SuperNeurons: a dynamic GPU memory scheduling runtime to enable the network training far be...

  5. 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.

  6. The Time Course of Task-Specific Memory Consolidation Effects in Resting State Networks

    Science.gov (United States)

    Sami, Saber; Robertson, Edwin M.

    2014-01-01

    Previous studies have reported functionally localized changes in resting-state brain activity following a short period of motor learning, but their relationship with memory consolidation and their dependence on the form of learning is unclear. We investigate these questions with implicit or explicit variants of the serial reaction time task (SRTT). fMRI resting-state functional connectivity was measured in human subjects before the tasks, and 0.1, 0.5, and 6 h after learning. There was significant improvement in procedural skill in both groups, with the group learning under explicit conditions showing stronger initial acquisition, and greater improvement at the 6 h retest. Immediately following acquisition, this group showed enhanced functional connectivity in networks including frontal and cerebellar areas and in the visual cortex. Thirty minutes later, enhanced connectivity was observed between cerebellar nuclei, thalamus, and basal ganglia, whereas at 6 h there was enhanced connectivity in a sensory-motor cortical network. In contrast, immediately after acquisition under implicit conditions, there was increased connectivity in a network including precentral and sensory-motor areas, whereas after 30 min a similar cerebello-thalamo-basal ganglionic network was seen as in explicit learning. Finally, 6 h after implicit learning, we found increased connectivity in medial temporal cortex, but reduction in precentral and sensory-motor areas. Our findings are consistent with predictions that two variants of the SRTT task engage dissociable functional networks, although there are also networks in common. We also show a converging and diverging pattern of flux between prefrontal, sensory-motor, and parietal areas, and subcortical circuits across a 6 h consolidation period. PMID:24623776

  7. On the effect of memory in one-dimensional K=4 automata on networks

    Science.gov (United States)

    Alonso-Sanz, Ramón; Cárdenas, Juan Pablo

    2008-12-01

    The effect of implementing memory in cells of one-dimensional CA, and on nodes of various types of automata on networks with increasing degrees of random rewiring is studied in this article, paying particular attention to the case of four inputs. As a rule, memory induces a moderation in the rate of changing nodes and in the damage spreading, albeit in the latter case memory turns out to be ineffective in the control of the damage as the wiring network moves away from the ordered structure that features proper one-dimensional CA. This article complements the previous work done in the two-dimensional context.

  8. Hierarchical modularity in human brain functional networks

    Directory of Open Access Journals (Sweden)

    David Meunier

    2009-10-01

    Full Text Available 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 the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions.

  9. Single unit approaches to human vision and memory.

    Science.gov (United States)

    Kreiman, Gabriel

    2007-08-01

    Research on the visual system focuses on using electrophysiology, pharmacology and other invasive tools in animal models. Non-invasive tools such as scalp electroencephalography and imaging allow examining humans but show a much lower spatial and/or temporal resolution. Under special clinical conditions, it is possible to monitor single-unit activity in humans when invasive procedures are required due to particular pathological conditions including epilepsy and Parkinson's disease. We review our knowledge about the visual system and visual memories in the human brain at the single neuron level. The properties of the human brain seem to be broadly compatible with the knowledge derived from animal models. The possibility of examining high-resolution brain activity in conscious human subjects allows investigators to ask novel questions that are challenging to address in animal models.

  10. 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.

  11. Memory and neural networks on the basis of color centers in solids.

    Science.gov (United States)

    Winnacker, Albrecht; Osvet, Andres

    2009-11-01

    Optical data recording is one of the most widely used and efficient systems of memory in the non-living world. The application of color centers in this context offers not only systems of high speed in writing and read-out due to a high degree of parallelism in data handling but also a possibility to set up models of neural networks. In this way, systems with a high potential for image processing, pattern recognition and logical operations can be constructed. A limitation to storage density is given by the diffraction limit of optical data recording. It is shown that this limitation can at least in principle be overcome by the principle of spectral hole burning, which results in systems of storage capacities close to the human brain system.

  12. Is a Responsive Default Mode Network Required for Successful Working Memory Task Performance?

    Science.gov (United States)

    Čeko, Marta; Gracely, John L.; Fitzcharles, Mary-Ann; Seminowicz, David A.; Schweinhardt, Petra

    2015-01-01

    In studies of cognitive processing using tasks with externally directed attention, regions showing increased (external-task-positive) and decreased or “negative” [default-mode network (DMN)] fMRI responses during task performance are dynamically responsive to increasing task difficulty. Responsiveness (modulation of fMRI signal by increasing load) has been linked directly to successful cognitive task performance in external-task-positive regions but not in DMN regions. To investigate whether a responsive DMN is required for successful cognitive performance, we compared healthy human subjects (n = 23) with individuals shown to have decreased DMN engagement (chronic pain patients, n = 28). Subjects performed a multilevel working-memory task (N-back) during fMRI. If a responsive DMN is required for successful performance, patients having reduced DMN responsiveness should show worsened performance; if performance is not reduced, their brains should show compensatory activation in external-task-positive regions or elsewhere. All subjects showed decreased accuracy and increased reaction times with increasing task level, with no significant group differences on either measure at any level. Patients had significantly reduced negative fMRI response (deactivation) of DMN regions (posterior cingulate/precuneus, medial prefrontal cortex). Controls showed expected modulation of DMN deactivation with increasing task difficulty. Patients showed significantly reduced modulation of DMN deactivation by task difficulty, despite their successful task performance. We found no evidence of compensatory neural recruitment in external-task-positive regions or elsewhere. Individual responsiveness of the external-task-positive ventrolateral prefrontal cortex, but not of DMN regions, correlated with task accuracy. These findings suggest that a responsive DMN may not be required for successful cognitive performance; a responsive external-task-positive network may be sufficient

  13. New Perspectives on the Brain Lesion Approach - Implications for Theoretical Models of Human Memory.

    Science.gov (United States)

    Irish, Muireann; van Kesteren, Marlieke T R

    2018-03-15

    Human lesion studies represent the cornerstone of modern day neuropsychology and provide an important adjunct to functional neuroimaging methods. The study of human lesion groups with damage to distinct regions of the brain permits the identification of underlying mechanisms and structures not only associated with, but essential for, complex cognitive processes. Here, we consider a recent review by McCormick et al., 2018 in which the power of the lesion model approach is elegantly presented with respect to a host of sophisticated cognitive endeavors, including autobiographical memory, future thinking, spatial navigation, and decision-making. By comparing profiles of loss and sparing in hippocampal (HC) and ventromedial prefrontal cortex (vmPFC) lesion groups, the authors provide new insights into the underlying neuroarchitecture of these diverse cognitive functions. Building on this framework, we consider how vmPFC and HC degeneration, in the context of large-scale network dysfunction in dementia, impacts discrete facets of memory and social cognition. Notably, we find remarkable concordance between the available evidence in dementia and that of the HC and vmPFC lesion literature. We further assess the role of the prefrontal cortex in modulating aspects of spatial navigation and discuss the role of schema-related processing in the service of memory more broadly. Far from being obsolete, we contend that human lesion work occupies a crucial position in cognitive neuroscience and offers an array of exciting areas for future study within this field. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

  14. Episodic memory for human-like agents and human-like agents for episodic memory

    Czech Academy of Sciences Publication Activity Database

    Brom, C.; Lukavský, Jiří; Kadlec, R.

    2010-01-01

    Roč. 2, č. 2 (2010), s. 227-244 ISSN 1793-8473 Institutional research plan: CEZ:AV0Z70250504 Keywords : episodic memory * virtual agent * modelling Subject RIV: AN - Psychology http://www.worldscinet.com/ijmc/02/0202/S1793843010000461.html

  15. 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.

  16. 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.

  17. 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. PMID:22952608

  18. Long Short-Term Memory Neural Networks for Online Disturbance Detection in Satellite Image Time Series

    Directory of Open Access Journals (Sweden)

    Yun-Long Kong

    2018-03-01

    Full Text Available A satellite image time series (SITS contains a significant amount of temporal information. By analysing this type of data, the pattern of the changes in the object of concern can be explored. The natural change in the Earth’s surface is relatively slow and exhibits a pronounced pattern. Some natural events (for example, fires, floods, plant diseases, and insect pests and human activities (for example, deforestation and urbanisation will disturb this pattern and cause a relatively profound change on the Earth’s surface. These events are usually referred to as disturbances. However, disturbances in ecosystems are not easy to detect from SITS data, because SITS contain combined information on disturbances, phenological variations and noise in remote sensing data. In this paper, a novel framework is proposed for online disturbance detection from SITS. The framework is based on long short-term memory (LSTM networks. First, LSTM networks are trained by historical SITS. The trained LSTM networks are then used to predict new time series data. Last, the predicted data are compared with real data, and the noticeable deviations reveal disturbances. Experimental results using 16-day compositions of the moderate resolution imaging spectroradiometer (MOD13Q1 illustrate the effectiveness and stability of the proposed approach for online disturbance detection.

  19. Fronto-parietal network oscillations reveal relationship between working memory capacity and cognitive control

    Directory of Open Access Journals (Sweden)

    Rasa eGulbinaite

    2014-09-01

    Full Text Available Executive-attention theory proposes a close relationship between working memory capacity (WMC and cognitive control abilities. However, conflicting results are documented in the literature, with some studies reporting that individual variations in WMC predict differences in cognitive control and trial-to-trial control adjustments (operationalized as the size of the congruency effect and congruency sequence effects, respectively, while others report no WMC-related differences. We hypothesized that brain network dynamics might be a more sensitive measure of WMC-related differences in cognitive control abilities. Thus, in the present study, we measured human EEG during the Simon task to characterize WMC-related differences in the neural dynamics of conflict processing and adaptation to conflict. Although high- and low-WMC individuals did not differ behaviorally, there were substantial WMC-related differences in theta (4-8 Hz and delta (1-3 Hz connectivity in fronto-parietal networks. Group differences in local theta and delta power were relatively less pronounced. These results suggest that the relationship between WMC and cognitive control abilities is more strongly reflected in large-scale oscillatory network dynamics than in spatially localized activity or in behavioral task performance.

  20. Factors affecting reorganisation of memory encoding networks in temporal lobe epilepsy

    Science.gov (United States)

    Sidhu, M.K.; Stretton, J.; Winston, G.P.; Symms, M.; Thompson, P.J.; Koepp, M.J.; Duncan, J.S.

    2015-01-01

    Summary Aims In temporal lobe epilepsy (TLE) due to hippocampal sclerosis reorganisation in the memory encoding network has been consistently described. Distinct areas of reorganisation have been shown to be efficient when associated with successful subsequent memory formation or inefficient when not associated with successful subsequent memory. We investigated the effect of clinical parameters that modulate memory functions: age at onset of epilepsy, epilepsy duration and seizure frequency in a large cohort of patients. Methods We studied 53 patients with unilateral TLE and hippocampal sclerosis (29 left). All participants performed a functional magnetic resonance imaging memory encoding paradigm of faces and words. A continuous regression analysis was used to investigate the effects of age at onset of epilepsy, epilepsy duration and seizure frequency on the activation patterns in the memory encoding network. Results Earlier age at onset of epilepsy was associated with left posterior hippocampus activations that were involved in successful subsequent memory formation in left hippocampal sclerosis patients. No association of age at onset of epilepsy was seen with face encoding in right hippocampal sclerosis patients. In both left hippocampal sclerosis patients during word encoding and right hippocampal sclerosis patients during face encoding, shorter duration of epilepsy and lower seizure frequency were associated with medial temporal lobe activations that were involved in successful memory formation. Longer epilepsy duration and higher seizure frequency were associated with contralateral extra-temporal activations that were not associated with successful memory formation. Conclusion Age at onset of epilepsy influenced verbal memory encoding in patients with TLE due to hippocampal sclerosis in the speech-dominant hemisphere. Shorter duration of epilepsy and lower seizure frequency were associated with less disruption of the efficient memory encoding network whilst

  1. Wind Power Forecasting Based on Echo State Networks and Long Short-Term Memory

    DEFF Research Database (Denmark)

    López, Erick; Allende, Héctor; Gil, Esteban

    2018-01-01

    involved. In particular, two types of RNN, Long Short-Term Memory (LSTM) and Echo State Network (ESN), have shown good results in time series forecasting. In this work, we present an LSTM+ESN architecture that combines the characteristics of both networks. An architecture similar to an ESN is proposed...

  2. Convergence analysis of stochastic hybrid bidirectional associative memory neural networks with delays

    International Nuclear Information System (INIS)

    Wan Li; Zhou Qinghua

    2007-01-01

    The stability property of stochastic hybrid bidirectional associate memory (BAM) neural networks with discrete delays is considered. Without assuming the symmetry of synaptic connection weights and the monotonicity and differentiability of activation functions, the delay-independent sufficient conditions to guarantee the exponential stability of the equilibrium solution for such networks are given by using the nonnegative semimartingale convergence theorem

  3. Convergence analysis of stochastic hybrid bidirectional associative memory neural networks with delays

    Science.gov (United States)

    Wan, Li; Zhou, Qinghua

    2007-10-01

    The stability property of stochastic hybrid bidirectional associate memory (BAM) neural networks with discrete delays is considered. Without assuming the symmetry of synaptic connection weights and the monotonicity and differentiability of activation functions, the delay-independent sufficient conditions to guarantee the exponential stability of the equilibrium solution for such networks are given by using the nonnegative semimartingale convergence theorem.

  4. Temporal stability in human interaction networks

    Science.gov (United States)

    Fabbri, Renato; Fabbri, Ricardo; Antunes, Deborah Christina; Pisani, Marilia Mello; de Oliveira, Osvaldo Novais

    2017-11-01

    This paper reports on stable (or invariant) properties of human interaction networks, with benchmarks derived from public email lists. Activity, recognized through messages sent, along time and topology were observed in snapshots in a timeline, and at different scales. Our analysis shows that activity is practically the same for all networks across timescales ranging from seconds to months. The principal components of the participants in the topological metrics space remain practically unchanged as different sets of messages are considered. The activity of participants follows the expected scale-free trace, thus yielding the hub, intermediary and peripheral classes of vertices by comparison against the Erdös-Rényi model. The relative sizes of these three sectors are essentially the same for all email lists and the same along time. Typically, 45% are peripheral vertices. Similar results for the distribution of participants in the three sectors and for the relative importance of the topological metrics were obtained for 12 additional networks from Facebook, Twitter and ParticipaBR. These properties are consistent with the literature and may be general for human interaction networks, which has important implications for establishing a typology of participants based on quantitative criteria.

  5. Continual and One-Shot Learning Through Neural Networks with Dynamic External Memory

    DEFF Research Database (Denmark)

    Lüders, Benno; Schläger, Mikkel; Korach, Aleksandra

    2017-01-01

    it easier to find unused memory location and therefor facilitates the evolution of continual learning networks. Our results suggest that augmenting evolving networks with an external memory component is not only a viable mechanism for adaptive behaviors in neuroevolution but also allows these networks...... a new task is learned. This paper takes a step in overcoming this limitation by building on the recently proposed Evolving Neural Turing Machine (ENTM) approach. In the ENTM, neural networks are augmented with an external memory component that they can write to and read from, which allows them to store...... associations quickly and over long periods of time. The results in this paper demonstrate that the ENTM is able to perform one-shot learning in reinforcement learning tasks without catastrophic forgetting of previously stored associations. Additionally, we introduce a new ENTM default jump mechanism that makes...

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

    NARCIS (Netherlands)

    Kroes, Marijn C. W.; Tendolkar, Indira; van Wingen, Guido A.; van Waarde, Jeroen A.; Strange, Bryan A.; Fernández, Guillén

    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

  7. Distributed memory in a heterogeneous network, as used in the CERN-PS complex timing system

    CERN Document Server

    Kovaltsov, V I

    1995-01-01

    The Distributed Table Manager (DTM) is a fast and efficient utility for distributing named binary data structures called Tables, of arbitrary size and structure, around a heterogeneous network of computers to a set of registered clients. The Tables are transmitted over a UDP network between DTM servers in network format, where the servers perform the conversions to and from host format for local clients. The servers provide clients with synchronization mechanisms, a choice of network data flows, and table options such as keeping table disc copies, shared memory or heap memory table allocation, table read/write permissions, and table subnet broadcasting. DTM has been designed to be easily maintainable, and to automatically recover from the type of errors typically encountered in a large control system network. The DTM system is based on a three level server daemon hierarchy, in which an inter daemon protocol handles network failures, and incorporates recovery procedures which will guarantee table consistency w...

  8. Neural correlates of heat-evoked pain memory in humans.

    Science.gov (United States)

    Wang, Liping; Gui, Peng; Li, Lei; Ku, Yixuan; Bodner, Mark; Fan, Gaojie; Zhou, Yong-Di; Dong, Xiao-Wei

    2016-03-01

    The neural processes underlying pain memory are not well understood. To explore these processes, contact heat-evoked potentials (CHEPs) were recorded in humans with electroencephalography (EEG) technique during a delayed matching-to-sample task, a working memory task involving presentations of two successive painful heat stimuli (S-1 and S-2) with different intensities separated by a 2-s interval (the memorization period). At the end of the task, the subject was required to discriminate the stimuli by indicating which (S-1 or S-2) induced more pain. A control task was used, in which no active discrimination was required between stimuli. All event-related potential (ERP) analysis was aligned to the onset of S-1. EEG activity exhibited two successive CHEPs: an N2-P2 complex (∼400 ms after onset of S-1) and an ultralate component (ULC, ∼900 ms). The amplitude of the N2-P2 at vertex, but not the ULC, was significantly correlated with stimulus intensity in these two tasks, suggesting that the N2-P2 represents neural coding of pain intensity. A late negative component (LNC) in the frontal recording region was observed only in the memory task during a 500-ms period before onset of S-2. LNC amplitude differed between stimulus intensities and exhibited significant correlations with the N2-P2 complex. These indicate that the frontal LNC is involved in maintenance of intensity of pain in working memory. Furthermore, alpha-band oscillations observed in parietal recording regions during the late delay displayed significant power differences between tasks. This study provides in the temporal domain previously unidentified neural evidence showing the neural processes involved in working memory of painful stimuli. Copyright © 2016 the American Physiological Society.

  9. Associative memory for online learning in noisy environments using self-organizing incremental neural network.

    Science.gov (United States)

    Sudo, Akihito; Sato, Akihiro; Hasegawa, Osamu

    2009-06-01

    Associative memory operating in a real environment must perform well in online incremental learning and be robust to noisy data because noisy associative patterns are presented sequentially in a real environment. We propose a novel associative memory that satisfies these requirements. Using the proposed method, new associative pairs that are presented sequentially can be learned accurately without forgetting previously learned patterns. The memory size of the proposed method increases adaptively with learning patterns. Therefore, it suffers neither redundancy nor insufficiency of memory size, even in an environment in which the maximum number of associative pairs to be presented is unknown before learning. Noisy inputs in real environments are classifiable into two types: noise-added original patterns and faultily presented random patterns. The proposed method deals with two types of noise. To our knowledge, no conventional associative memory addresses noise of both types. The proposed associative memory performs as a bidirectional one-to-many or many-to-one associative memory and deals not only with bipolar data, but also with real-valued data. Results demonstrate that the proposed method's features are important for application to an intelligent robot operating in a real environment. The originality of our work consists of two points: employing a growing self-organizing network for an associative memory, and discussing what features are necessary for an associative memory for an intelligent robot and proposing an associative memory that satisfies those requirements.

  10. 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.

  11. Reactivation in Working Memory : An Attractor Network Model of Free Recall

    OpenAIRE

    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...

  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

    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.

  14. 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.

  15. Apolipoprotein E4 causes early olfactory network abnormalities and short-term olfactory memory impairments.

    Science.gov (United States)

    Peng, Katherine Y; Mathews, Paul M; Levy, Efrat; Wilson, Donald A

    2017-02-20

    While apolipoprotein (Apo) E4 is linked to increased incidence of Alzheimer's disease (AD), there is growing evidence that it plays a role in functional brain irregularities that are independent of AD pathology. However, ApoE4-driven functional differences within olfactory processing regions have yet to be examined. Utilizing knock-in mice humanized to ApoE4 versus the more common ApoE3, we examined a simple olfactory perceptual memory that relies on the transfer of information from the olfactory bulb (OB) to the piriform cortex (PCX), the primary cortical region involved in higher order olfaction. In addition, we have recorded in vivo resting and odor-evoked local field potentials (LPF) from both brain regions and measured corresponding odor response magnitudes in anesthetized young (6-month-old) and middle-aged (12-month-old) ApoE mice. Young ApoE4 compared to ApoE3 mice exhibited a behavioral olfactory deficit coinciding with hyperactive odor-evoked response magnitudes within the OB that were not observed in older ApoE4 mice. Meanwhile, middle-aged ApoE4 compared to ApoE3 mice exhibited heightened response magnitudes in the PCX without a corresponding olfactory deficit, suggesting a shift with aging in ApoE4-driven effects from OB to PCX. Interestingly, the increased ApoE4-specific response in the PCX at middle-age was primarily due to a dampening of baseline spontaneous activity rather than an increase in evoked response power. Our findings indicate that early ApoE4-driven olfactory memory impairments and OB network abnormalities may be a precursor to later network dysfunction in the PCX, a region that not only is targeted early in AD, but may be selectively vulnerable to ApoE4 genotype. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

  16. Structure of the human chromosome interaction network.

    Directory of Open Access Journals (Sweden)

    Sergio Sarnataro

    Full Text Available New Hi-C technologies have revealed that chromosomes have a complex network of spatial contacts in the cell nucleus of higher organisms, whose organisation is only partially understood. Here, we investigate the structure of such a network in human GM12878 cells, to derive a large scale picture of nuclear architecture. We find that the intensity of intra-chromosomal interactions is power-law distributed. Inter-chromosomal interactions are two orders of magnitude weaker and exponentially distributed, yet they are not randomly arranged along the genomic sequence. Intra-chromosomal contacts broadly occur between epigenomically homologous regions, whereas inter-chromosomal contacts are especially associated with regions rich in highly expressed genes. Overall, genomic contacts in the nucleus appear to be structured as a network of networks where a set of strongly individual chromosomal units, as envisaged in the 'chromosomal territory' scenario derived from microscopy, interact with each other via on average weaker, yet far from random and functionally important interactions.

  17. The impact of auditory working memory training on the fronto-parietal working memory network.

    Science.gov (United States)

    Schneiders, Julia A; Opitz, Bertram; Tang, Huijun; Deng, Yuan; Xie, Chaoxiang; Li, Hong; Mecklinger, Axel

    2012-01-01

    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 a (across-modal) visual working memory task. We used 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 transfer task. Training-induced activation decreases in the auditory transfer task were found in two regions in the right inferior frontal gyrus. These effects confirm our previous findings in the visual modality and extents intra-modal effects in the prefrontal cortex to the auditory modality. As the right inferior frontal gyrus is frequently found in maintaining modality-specific auditory information, these results might reflect increased neural efficiency in auditory working memory processes. Furthermore, task-unspecific (amodal) activation decreases in the visual and auditory transfer task were found in the right inferior parietal lobule and the superior portion of the right middle frontal gyrus reflecting less demand on general attentional control processes. These data are in good agreement with amodal activation decreases within the same brain regions on a visual transfer task reported previously.

  18. The impact of auditory working memory training on the fronto-parietal working memory network

    Science.gov (United States)

    Schneiders, Julia A.; Opitz, Bertram; Tang, Huijun; Deng, Yuan; Xie, Chaoxiang; Li, Hong; Mecklinger, Axel

    2012-01-01

    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 a (across-modal) visual working memory task. We used 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 transfer task. Training-induced activation decreases in the auditory transfer task were found in two regions in the right inferior frontal gyrus. These effects confirm our previous findings in the visual modality and extents intra-modal effects in the prefrontal cortex to the auditory modality. As the right inferior frontal gyrus is frequently found in maintaining modality-specific auditory information, these results might reflect increased neural efficiency in auditory working memory processes. Furthermore, task-unspecific (amodal) activation decreases in the visual and auditory transfer task were found in the right inferior parietal lobule and the superior portion of the right middle frontal gyrus reflecting less demand on general attentional control processes. These data are in good agreement with amodal activation decreases within the same brain regions on a visual transfer task reported previously. PMID:22701418

  19. 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.

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

    Science.gov (United States)

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

    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 sclerosis (24 left) and 26 healthy control subjects. All participants performed a functional magnetic resonance imaging memory encoding paradigm of faces and words with subsequent out-of-scanner recognition assessments. A blocked analysis was used to investigate activations during encoding and neural correlates of subsequent memory were investigated using an event-related analysis. Event-related activations were then correlated with out-of-scanner verbal and visual memory scores. During word encoding, control subjects activated the left prefrontal cortex and left hippocampus whereas patients with left hippocampal sclerosis showed significant additional right temporal and extra-temporal activations. Control subjects displayed subsequent verbal memory effects within left parahippocampal gyrus, left orbitofrontal cortex and fusiform gyrus whereas patients with left hippocampal sclerosis activated only right posterior hippocampus, parahippocampus and fusiform gyrus. Correlational analysis showed that patients with left hippocampal sclerosis with better verbal memory additionally activated left orbitofrontal cortex, anterior cingulate cortex and left posterior hippocampus. During face encoding, control subjects showed right lateralized prefrontal cortex and bilateral hippocampal activations. Patients with right hippocampal sclerosis showed increased temporal activations within the superior temporal gyri bilaterally and no increased extra-temporal areas of activation compared with

  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. Dynamics of continuous-time bidirectional associative memory neural networks with impulses and their discrete counterparts

    International Nuclear Information System (INIS)

    Huo Haifeng; Li Wantong

    2009-01-01

    This paper is concerned with the global stability characteristics of a system of equations modelling the dynamics of continuous-time bidirectional associative memory neural networks with impulses. Sufficient conditions which guarantee the existence of a unique equilibrium and its exponential stability of the networks are obtained. For the goal of computation, discrete-time analogues of the corresponding continuous-time bidirectional associative memory neural networks with impulses are also formulated and studied. Our results show that the above continuous-time and discrete-time systems with impulses preserve the dynamics of the networks without impulses when we make some modifications and impose some additional conditions on the systems, the convergence characteristics dynamics of the networks are preserved by both continuous-time and discrete-time systems with some restriction imposed on the impulse effect.

  3. Memory traces of long-range coordinated oscillations in the sleeping human brain.

    Science.gov (United States)

    Piantoni, Giovanni; Van Der Werf, Ysbrand D; Jensen, Ole; Van Someren, Eus J W

    2015-01-01

    Cognition involves coordinated activity across distributed neuronal networks. Neuronal activity during learning triggers cortical plasticity that allows for reorganization of the neuronal network and integration of new information. Animal studies have shown post-learning reactivation of learning-elicited neuronal network activity during subsequent sleep, supporting consolidation of the reorganization. However, no previous studies, to our knowledge, have demonstrated reactivation of specific learning-elicited long-range functional connectivity during sleep in humans. We here show reactivation of learning-induced long-range synchronization of magnetoencephalography power fluctuations in human sleep. Visuomotor learning elicited a specific profile of long-range cortico-cortical synchronization of slow (0.1 Hz) fluctuations in beta band (12-30 Hz) power. The parieto-occipital part of this synchronization profile reappeared in delta band (1-3.5 Hz) power fluctuations during subsequent sleep, but not during the intervening wakefulness period. Individual differences in the reactivated synchronization predicted postsleep performance improvement. The presleep resting-state synchronization profile was not reactivated during sleep. The findings demonstrate reactivation of long-range coordination of neuronal activity in humans, more specifically of reactivation of coupling of infra-slow fluctuations in oscillatory power. The spatiotemporal profile of delta power fluctuations during sleep may subserve memory consolidation by echoing coordinated activation elicited by prior learning. © 2014 Wiley Periodicals, Inc.

  4. Richness of information about novel words influences how episodic and semantic memory networks interact during lexicalization.

    Science.gov (United States)

    Takashima, Atsuko; Bakker, Iske; van Hell, Janet G; Janzen, Gabriele; McQueen, James M

    2014-01-01

    The complementary learning systems account of declarative memory suggests two distinct memory networks, a fast-mapping, episodic system involving the hippocampus, and a slower semantic memory system distributed across the neocortex in which new information is gradually integrated with existing representations. In this study, we investigated the extent to which these two networks are involved in the integration of novel words into the lexicon after extensive learning, and how the involvement of these networks changes after 24h. In particular, we explored whether having richer information at encoding influences the lexicalization trajectory. We trained participants with two sets of novel words, one where exposure was only to the words' phonological forms (the form-only condition), and one where pictures of unfamiliar objects were associated with the words' phonological forms (the picture-associated condition). A behavioral measure of lexical competition (indexing lexicalization) indicated stronger competition effects for the form-only words. Imaging (fMRI) results revealed greater involvement of phonological lexical processing areas immediately after training in the form-only condition, suggesting that tight connections were formed between novel words and existing lexical entries already at encoding. Retrieval of picture-associated novel words involved the episodic/hippocampal memory system more extensively. Although lexicalization was weaker in the picture-associated condition, overall memory strength was greater when tested after a 24hour delay, probably due to the availability of both episodic and lexical memory networks to aid retrieval. It appears that, during lexicalization of a novel word, the relative involvement of different memory networks differs according to the richness of the information about that word available at encoding. © 2013.

  5. Determination of memory performance

    International Nuclear Information System (INIS)

    Gopych, P.M.

    1999-01-01

    Within the scope of testing statistical hypotheses theory a model definition and a computer method for model calculation of widely used in neuropsychology human memory performance (free recall, cued recall, and recognition probabilities), a model definition and a computer method for model calculation of intensities of cues used in experiments for testing human memory quality are proposed. Models for active and passive traces of memory and their relations are found. It was shown that autoassociative memory unit in the form of short two-layer artificial neural network with (or without) damages can be used for model description of memory performance in subjects with (or without) local brain lesions

  6. 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.

  7. 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. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. 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. Copyright © 2015 Elsevier B.V. All rights reserved.

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

    International Nuclear Information System (INIS)

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

    2016-01-01

    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 (T g ), could be tunable by varying the constituents and T g 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. (paper)

  10. Optical waveguides with memory effect using photochromic material for neural network

    Science.gov (United States)

    Tanimoto, Keisuke; Amemiya, Yoshiteru; Yokoyama, Shin

    2018-04-01

    An optical neural network using a waveguide with a memory effect, a photodiode, CMOS circuits and LEDs was proposed. To realize the neural network, optical waveguides with a memory effect were fabricated using a cladding layer containing the photochromic material “diarylethene”. The transmittance of green light was decreased by UV light irradiation and recovered by the passage of green light through the waveguide. It was confirmed that the transmittance versus total energy of the green light that passed through the waveguide well fit the universal exponential curve.

  11. A novel network of chaotic elements and its application in multi-valued associative memory

    International Nuclear Information System (INIS)

    Xiu Chunbo; Liu Xiangdong; Tang Yunyu; Zhang Yuhe

    2004-01-01

    We give a novel chaotic element model whose activation function composed of Gauss and Sigmoid function. It is shown that the model may exhibit a complex dynamic behavior. The most significant bifurcation processes, leading to chaos, are investigated through the computation of the Lyapunov exponents. Based on this model, we propose a novel network of chaotic elements, which can be applied in associative memory, and then investigate its dynamic behavior. It is worth noting that multi-valued associative memory can also be realized by this network

  12. Stationary oscillation for nonautonomous bidirectional associative memory neural networks with impulse

    International Nuclear Information System (INIS)

    Zhang Yinping

    2009-01-01

    In this paper, we study the existence, uniqueness and global stability of periodic solution (i.e. stationary oscillation) for general bidirectional associative memory neural networks with impulses. Some sufficient conditions are obtained for stationary oscillation of the nonautonomous bidirectional associative memory neural networks with impulses. It is derived by using a new method which is different from those of previous literatures, and a assumption in previous results does not required. The model considered is more general and some previous results are extended and improved. An illustrative example is given to demonstrate the effectiveness and less conservativeness of the obtained results.

  13. Computational Model-Based Prediction of Human Episodic Memory Performance Based on Eye Movements

    Science.gov (United States)

    Sato, Naoyuki; Yamaguchi, Yoko

    Subjects' episodic memory performance is not simply reflected by eye movements. We use a ‘theta phase coding’ model of the hippocampus to predict subjects' memory performance from their eye movements. Results demonstrate the ability of the model to predict subjects' memory performance. These studies provide a novel approach to computational modeling in the human-machine interface.

  14. Network dynamics of human face perception.

    Directory of Open Access Journals (Sweden)

    Cihan Mehmet Kadipasaoglu

    Full Text Available Prevailing theories suggests that cortical regions responsible for face perception operate in a serial, feed-forward fashion. Here, we utilize invasive human electrophysiology to evaluate serial models of face-processing via measurements of cortical activation, functional connectivity, and cortico-cortical evoked potentials. We find that task-dependent changes in functional connectivity between face-selective regions in the inferior occipital (f-IOG and fusiform gyrus (f-FG are bidirectional, not feed-forward, and emerge following feed-forward input from early visual cortex (EVC to both of these regions. Cortico-cortical evoked potentials similarly reveal independent signal propagations between EVC and both f-IOG and f-FG. These findings are incompatible with serial models, and support a parallel, distributed network underpinning face perception in humans.

  15. 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. Copyright © 2014 the authors 0270-6474/14/3416662-09$15.00/0.

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    Sarah I Gimbel

    Full Text Available 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.

  18. Using Hierarchical Temporal Memory for Detecting Anomalous Network Activity

    Science.gov (United States)

    2008-03-01

    warfare, computer network operations, psychological operations, military deception, and operations security, in concert with specified supporting and...you up short—you were subconsciously predicting something else and were surprised by the mismatch” [3]. Notable neurobiologist Horace Barlow of the...malicious network activity is flagged as abnormal . That is, test data should present the N-HTM network with spatial-temporal patterns that do not match 46

  19. Complex human mobility dynamics on a network

    International Nuclear Information System (INIS)

    Szell, M.

    2010-01-01

    Massive multiplayer online games provide a fascinating new way of observing hundreds of thousands of simultaneously interacting individuals engaged in virtual socio-economic activities. We have compiled a data set consisting of practically all actions of all players over a period of four years from an online game played by over 350,000 people. The universe of this online world is a lattice-like network on which players move in order to interact with other players. We focus on the mobility of human players on this network over a time-period of 500 days. We take a number of mobility measurements and compare them with measures of simulated random walkers on the same topology. Mobility of players is sub-diffusive - the mean squared displacement follows a power law with exponent 0.4 - and significantly deviates from mobility patterns of random walkers. Mean first passage times and transition counts relate via a power-law with slope -1/3. We compare our results with studies where human mobility was measured via mobile phone data and find striking similarities. (author)

  20. Direct Electrical Stimulation of the Human Entorhinal Region and Hippocampus Impairs Memory.

    Science.gov (United States)

    Jacobs, Joshua; Miller, Jonathan; Lee, Sang Ah; Coffey, Tom; Watrous, Andrew J; Sperling, Michael R; Sharan, Ashwini; Worrell, Gregory; Berry, Brent; Lega, Bradley; Jobst, Barbara C; Davis, Kathryn; Gross, Robert E; Sheth, Sameer A; Ezzyat, Youssef; Das, Sandhitsu R; Stein, Joel; Gorniak, Richard; Kahana, Michael J; Rizzuto, Daniel S

    2016-12-07

    Deep brain stimulation (DBS) has shown promise for treating a range of brain disorders and neurological conditions. One recent study showed that DBS in the entorhinal region improved the accuracy of human spatial memory. Based on this line of work, we performed a series of experiments to more fully characterize the effects of DBS in the medial temporal lobe on human memory. Neurosurgical patients with implanted electrodes performed spatial and verbal-episodic memory tasks. During the encoding periods of both tasks, subjects received electrical stimulation at 50 Hz. In contrast to earlier work, electrical stimulation impaired memory performance significantly in both spatial and verbal tasks. Stimulation in both the entorhinal region and hippocampus caused decreased memory performance. These findings indicate that the entorhinal region and hippocampus are causally involved in human memory and suggest that refined methods are needed to use DBS in these regions to improve memory. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. 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.

  2. 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.

  3. System level mechanisms of adaptation, learning, memory formation and evolvability: the role of chaperone and other networks.

    Science.gov (United States)

    Gyurko, David M; Soti, Csaba; Stetak, Attila; Csermely, Peter

    2014-05-01

    During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here, we describe first the protein structure networks of molecular chaperones, then characterize chaperone containing sub-networks of interactomes called as chaperone-networks or chaperomes. We review the role of molecular chaperones in short-term adaptation of cellular networks in response to stress, and in long-term adaptation discussing their putative functions in the regulation of evolvability. We provide a general overview of possible network mechanisms of adaptation, learning and memory formation. We propose that changes of network rigidity play a key role in learning and memory formation processes. Flexible network topology provides ' learning-competent' state. Here, networks may have much less modular boundaries than locally rigid, highly modular networks, where the learnt information has already been consolidated in a memory formation process. Since modular boundaries are efficient filters of information, in the 'learning-competent' state information filtering may be much smaller, than after memory formation. This mechanism restricts high information transfer to the 'learning competent' state. After memory formation, modular boundary-induced segregation and information filtering protect the stored information. The flexible networks of young organisms are generally in a 'learning competent' state. On the contrary, locally rigid networks of old organisms have lost their 'learning competent' state, but store and protect their learnt information efficiently. We anticipate that the above mechanism may operate at the level of both protein-protein interaction and neuronal networks.

  4. Skeleton-Based Human Action Recognition With Global Context-Aware Attention LSTM Networks

    Science.gov (United States)

    Liu, Jun; Wang, Gang; Duan, Ling-Yu; Abdiyeva, Kamila; Kot, Alex C.

    2018-04-01

    Human action recognition in 3D skeleton sequences has attracted a lot of research attention. Recently, Long Short-Term Memory (LSTM) networks have shown promising performance in this task due to their strengths in modeling the dependencies and dynamics in sequential data. As not all skeletal joints are informative for action recognition, and the irrelevant joints often bring noise which can degrade the performance, we need to pay more attention to the informative ones. However, the original LSTM network does not have explicit attention ability. In this paper, we propose a new class of LSTM network, Global Context-Aware Attention LSTM (GCA-LSTM), for skeleton based action recognition. This network is capable of selectively focusing on the informative joints in each frame of each skeleton sequence by using a global context memory cell. To further improve the attention capability of our network, we also introduce a recurrent attention mechanism, with which the attention performance of the network can be enhanced progressively. Moreover, we propose a stepwise training scheme in order to train our network effectively. Our approach achieves state-of-the-art performance on five challenging benchmark datasets for skeleton based action recognition.

  5. Dynamic analysis of stochastic bidirectional associative memory neural networks with delays

    International Nuclear Information System (INIS)

    Zhao Hongyong; Ding Nan

    2007-01-01

    In this paper, stochastic bidirectional associative memory neural networks model with delays is considered. By constructing Lyapunov functionals, and using stochastic analysis method and inequality technique, we give some sufficient criteria ensuring almost sure exponential stability, pth exponential stability and mean value exponential stability. The obtained criteria can be used as theoretic guidance to stabilize neural networks in practical applications when stochastic noise is taken into consideration

  6. Global asymptotic stability of hybrid bidirectional associative memory neural networks with time delays

    International Nuclear Information System (INIS)

    Arik, Sabri

    2006-01-01

    This Letter presents a sufficient condition for the existence, uniqueness and global asymptotic stability of the equilibrium point for bidirectional associative memory (BAM) neural networks with distributed time delays. The results impose constraint conditions on the network parameters of neural system independently of the delay parameter, and they are applicable to all bounded continuous non-monotonic neuron activation functions. The results are also compared with the previous results derived in the literature

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

    Science.gov (United States)

    Senan, Sibel; Arik, Sabri

    2007-10-01

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

  8. Global asymptotic stability of hybrid bidirectional associative memory neural networks with time delays

    Science.gov (United States)

    Arik, Sabri

    2006-02-01

    This Letter presents a sufficient condition for the existence, uniqueness and global asymptotic stability of the equilibrium point for bidirectional associative memory (BAM) neural networks with distributed time delays. The results impose constraint conditions on the network parameters of neural system independently of the delay parameter, and they are applicable to all bounded continuous non-monotonic neuron activation functions. The results are also compared with the previous results derived in the literature.

  9. 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 ...

  10. The role of autobiographical memory networks in the experience of negative emotions: how our remembered past elicits our current feelings.

    Science.gov (United States)

    Philippe, Frederick L; Koestner, Richard; Lecours, Serge; Beaulieu-Pelletier, Genevieve; Bois, Katy

    2011-12-01

    The present research examined the role of autobiographical memory networks on negative emotional experiences. Results from 2 studies found support for an active but also discriminant role of autobiographical memories and their related networked memories on negative emotions. In addition, in line with self-determination theory, thwarting of the psychological needs for competence, autonomy, and relatedness was found to be the critical component of autobiographical memory affecting negative emotional experiences. Study 1 revealed that need thwarting in a specific autobiographical memory network related to the theme of loss was positively associated with depressive negative emotions, but not with other negative emotions. Study 2 showed within a prospective design a differential predictive validity between 2 autobiographical memory networks (an anger-related vs. a guilt-related memory) on situational anger reactivity with respect to unfair treatment. All of these results held after controlling for neuroticism (Studies 1 and 2), self-control (Study 2), and for the valence (Study 1) and emotions (Study 2) found in the measured autobiographical memory network. These findings highlight the ongoing emotional significance of representations of need thwarting in autobiographical memory networks. (c) 2011 APA, all rights reserved.

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

    Science.gov (United States)

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

    2018-01-01

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

  12. 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.

  13. Memory networks supporting retrieval effort and retrieval success under conditions of full and divided attention.

    Science.gov (United States)

    Skinner, Erin I; Fernandes, Myra A; Grady, Cheryl L

    2009-01-01

    We used a multivariate analysis technique, partial least squares (PLS), to identify distributed patterns of brain activity associated with retrieval effort and retrieval success. Participants performed a recognition memory task under full attention (FA) or two different divided attention (DA) conditions during retrieval. Behaviorally, recognition was disrupted when a word, but not digit-based distracting task, was performed concurrently with retrieval. PLS was used to identify patterns of brain activation that together covaried with the three memory conditions and which were functionally connected with activity in the right hippocampus to produce successful memory performance. Results indicate that activity in the right dorsolateral frontal cortex increases during conditions of DA at retrieval, and that successful memory performance in the DA-digit condition is associated with activation of the same network of brain regions functionally connected to the right hippocampus, as under FA, which increases with increasing memory performance. Finally, DA conditions that disrupt successful memory performance (DA-word) interfere with recruitment of both retrieval-effort and retrieval-success networks.

  14. Human Memory B Cells in Healthy Gingiva, Gingivitis, and Periodontitis.

    Science.gov (United States)

    Mahanonda, Rangsini; Champaiboon, Chantrakorn; Subbalekha, Keskanya; Sa-Ard-Iam, Noppadol; Rattanathammatada, Warattaya; Thawanaphong, Saranya; Rerkyen, Pimprapa; Yoshimura, Fuminobu; Nagano, Keiji; Lang, Niklaus P; Pichyangkul, Sathit

    2016-08-01

    The presence of inflammatory infiltrates with B cells, specifically plasma cells, is the hallmark of periodontitis lesions. The composition of these infiltrates in various stages of homeostasis and disease development is not well documented. Human tissue biopsies from sites with gingival health (n = 29), gingivitis (n = 8), and periodontitis (n = 21) as well as gingival tissue after treated periodontitis (n = 6) were obtained and analyzed for their composition of B cell subsets. Ag specificity, Ig secretion, and expression of receptor activator of NF-κB ligand and granzyme B were performed. Although most of the B cell subsets in healthy gingiva and gingivitis tissues were CD19(+)CD27(+)CD38(-) memory B cells, the major B cell component in periodontitis was CD19(+)CD27(+)CD38(+)CD138(+)HLA-DR(low) plasma cells, not plasmablasts. Plasma cell aggregates were observed at the base of the periodontal pocket and scattered throughout the gingiva, especially apically toward the advancing front of the lesion. High expression of CXCL12, a proliferation-inducing ligand, B cell-activating factor, IL-10, IL-6, and IL-21 molecules involved in local B cell responses was detected in both gingivitis and periodontitis tissues. Periodontitis tissue plasma cells mainly secreted IgG specific to periodontal pathogens and also expressed receptor activator of NF-κB ligand, a bone resorption cytokine. Memory B cells resided in the connective tissue subjacent to the junctional epithelium in healthy gingiva. This suggested a role of memory B cells in maintaining periodontal homeostasis. Copyright © 2016 by The American Association of Immunologists, Inc.

  15. In search of memory tests equivalent for experiments on animals and humans.

    Science.gov (United States)

    Brodziak, Andrzej; Kołat, Estera; Różyk-Myrta, Alicja

    2014-12-19

    Older people often exhibit memory impairments. Contemporary demographic trends cause aging of the society. In this situation, it is important to conduct clinical trials of drugs and use training methods to improve memory capacity. Development of new memory tests requires experiments on animals and then clinical trials in humans. Therefore, we decided to review the assessment methods and search for tests that evaluate analogous cognitive processes in animals and humans. This review has enabled us to propose 2 pairs of tests of the efficiency of working memory capacity in animals and humans. We propose a basic set of methods for complex clinical trials of drugs and training methods to improve memory, consisting of 2 pairs of tests: 1) the Novel Object Recognition Test - Sternberg Item Recognition Test and 2) the Object-Location Test - Visuospatial Memory Test. We postulate that further investigations of methods that are equivalent in animals experiments and observations performed on humans are necessary.

  16. Multi-stimulus-responsive shape-memory polymer nanocomposite network cross-linked by cellulose nanocrystals.

    Science.gov (United States)

    Liu, Ye; Li, Ying; Yang, Guang; Zheng, Xiaotong; Zhou, Shaobing

    2015-02-25

    In this study, we developed a thermoresponsive and water-responsive shape-memory polymer nanocomposite network by chemically cross-linking cellulose nanocrystals (CNCs) with polycaprolactone (PCL) and polyethylene glycol (PEG). The nanocomposite network was fully characterized, including the microstructure, cross-link density, water contact angle, water uptake, crystallinity, thermal properties, and static and dynamic mechanical properties. We found that the PEG[60]-PCL[40]-CNC[10] nanocomposite exhibited excellent thermo-induced and water-induced shape-memory effects in water at 37 °C (close to body temperature), and the introduction of CNC clearly improved the mechanical properties of the mixture of both PEG and PCL polymers with low molecular weights. In addition, Alamar blue assays based on osteoblasts indicated that the nanocomposites possessed good cytocompatibility. Therefore, this thermoresponsive and water-responsive shape-memory nanocomposite could be potentially developed into a new smart biomaterial.

  17. 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...

  18. 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.

  19. Episodic memory and the role of the brain’s default-mode network

    NARCIS (Netherlands)

    Huijbers, W.

    2010-01-01

    This thesis provides a number of new insights into episodic memory and the role of the default-mode network. First, it provides the first direct evidence for the contrasting role of DMN during encoding and retrieval. Secondly, the experimental findings eliminate several possible explanations for the

  20. Interaction of language, auditory and memory brain networks in auditory verbal hallucinations

    NARCIS (Netherlands)

    Curcic-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, Andre

    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

  1. Robust stability of bidirectional associative memory neural networks with time delays

    Science.gov (United States)

    Park, Ju H.

    2006-01-01

    Based on the Lyapunov Krasovskii functionals combined with linear matrix inequality approach, a novel stability criterion is proposed for asymptotic stability of bidirectional associative memory neural networks with time delays. A novel delay-dependent stability criterion is given in terms of linear matrix inequalities, which can be solved easily by various optimization algorithms.

  2. Robust stability of bidirectional associative memory neural networks with time delays

    International Nuclear Information System (INIS)

    Park, Ju H.

    2006-01-01

    Based on the Lyapunov-Krasovskii functionals combined with linear matrix inequality approach, a novel stability criterion is proposed for asymptotic stability of bidirectional associative memory neural networks with time delays. A novel delay-dependent stability criterion is given in terms of linear matrix inequalities, which can be solved easily by various optimization algorithms

  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. 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.

  5. Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall

    Science.gov (United States)

    Hampson, Robert E.; Song, Dong; Robinson, Brian S.; Fetterhoff, Dustin; Dakos, Alexander S.; Roeder, Brent M.; She, Xiwei; Wicks, Robert T.; Witcher, Mark R.; Couture, Daniel E.; Laxton, Adrian W.; Munger-Clary, Heidi; Popli, Gautam; Sollman, Myriam J.; Whitlow, Christopher T.; Marmarelis, Vasilis Z.; Berger, Theodore W.; Deadwyler, Sam A.

    2018-06-01

    Objective. We demonstrate here the first successful implementation in humans of a proof-of-concept system for restoring and improving memory function via facilitation of memory encoding using the patient’s own hippocampal spatiotemporal neural codes for memory. Memory in humans is subject to disruption by drugs, disease and brain injury, yet previous attempts to restore or rescue memory function in humans typically involved only nonspecific, modulation of brain areas and neural systems related to memory retrieval. Approach. We have constructed a model of processes by which the hippocampus encodes memory items via spatiotemporal firing of neural ensembles that underlie the successful encoding of short-term memory. A nonlinear multi-input, multi-output (MIMO) model of hippocampal CA3 and CA1 neural firing is computed that predicts activation patterns of CA1 neurons during the encoding (sample) phase of a delayed match-to-sample (DMS) human short-term memory task. Main results. MIMO model-derived electrical stimulation delivered to the same CA1 locations during the sample phase of DMS trials facilitated short-term/working memory by 37% during the task. Longer term memory retention was also tested in the same human subjects with a delayed recognition (DR) task that utilized images from the DMS task, along with images that were not from the task. Across the subjects, the stimulated trials exhibited significant improvement (35%) in both short-term and long-term retention of visual information. Significance. These results demonstrate the facilitation of memory encoding which is an important feature for the construction of an implantable neural prosthetic to improve human memory.

  6. Artificial neural network detects human uncertainty

    Science.gov (United States)

    Hramov, Alexander E.; Frolov, Nikita S.; Maksimenko, Vladimir A.; Makarov, Vladimir V.; Koronovskii, Alexey A.; Garcia-Prieto, Juan; Antón-Toro, Luis Fernando; Maestú, Fernando; Pisarchik, Alexander N.

    2018-03-01

    Artificial neural networks (ANNs) are known to be a powerful tool for data analysis. They are used in social science, robotics, and neurophysiology for solving tasks of classification, forecasting, pattern recognition, etc. In neuroscience, ANNs allow the recognition of specific forms of brain activity from multichannel EEG or MEG data. This makes the ANN an efficient computational core for brain-machine systems. However, despite significant achievements of artificial intelligence in recognition and classification of well-reproducible patterns of neural activity, the use of ANNs for recognition and classification of patterns in neural networks still requires additional attention, especially in ambiguous situations. According to this, in this research, we demonstrate the efficiency of application of the ANN for classification of human MEG trials corresponding to the perception of bistable visual stimuli with different degrees of ambiguity. We show that along with classification of brain states associated with multistable image interpretations, in the case of significant ambiguity, the ANN can detect an uncertain state when the observer doubts about the image interpretation. With the obtained results, we describe the possible application of ANNs for detection of bistable brain activity associated with difficulties in the decision-making process.

  7. Global asymptotic stability analysis of bidirectional associative memory neural networks with distributed delays and impulse

    International Nuclear Information System (INIS)

    Huang Zaitang; Luo Xiaoshu; Yang Qigui

    2007-01-01

    Many systems existing in physics, chemistry, biology, engineering and information science can be characterized by impulsive dynamics caused by abrupt jumps at certain instants during the process. These complex dynamical behaviors can be model by impulsive differential system or impulsive neural networks. This paper formulates and studies a new model of impulsive bidirectional associative memory (BAM) networks with finite distributed delays. Several fundamental issues, such as global asymptotic stability and existence and uniqueness of such BAM neural networks with impulse and distributed delays, are established

  8. Periodic oscillation of higher-order bidirectional associative memory neural networks with periodic coefficients and delays

    Science.gov (United States)

    Ren, Fengli; Cao, Jinde

    2007-03-01

    In this paper, several sufficient conditions are obtained ensuring existence, global attractivity and global asymptotic stability of the periodic solution for the higher-order bidirectional associative memory neural networks with periodic coefficients and delays by using the continuation theorem of Mawhin's coincidence degree theory, the Lyapunov functional and the non-singular M-matrix. Two examples are exploited to illustrate the effectiveness of the proposed criteria. These results are more effective than the ones in the literature for some neural networks, and can be applied to the design of globally attractive or globally asymptotically stable networks and thus have important significance in both theory and applications.

  9. Exponential stability of continuous-time and discrete-time bidirectional associative memory networks with delays

    International Nuclear Information System (INIS)

    Liang Jinling; Cao Jinde

    2004-01-01

    First, convergence of continuous-time Bidirectional Associative Memory (BAM) neural networks are studied. By using Lyapunov functionals and some analysis technique, the delay-independent sufficient conditions are obtained for the networks to converge exponentially toward the equilibrium associated with the constant input sources. Second, discrete-time analogues of the continuous-time BAM networks are formulated and studied. It is shown that the convergence characteristics of the continuous-time systems are preserved by the discrete-time analogues without any restriction imposed on the uniform discretionary step size. An illustrative example is given to demonstrate the effectiveness of the obtained results

  10. A Mechanistic Model of Human Recall of Social Network Structure and Relationship Affect.

    Science.gov (United States)

    Omodei, Elisa; Brashears, Matthew E; Arenas, Alex

    2017-12-07

    The social brain hypothesis argues that the need to deal with social challenges was key to our evolution of high intelligence. Research with non-human primates as well as experimental and fMRI studies in humans produce results consistent with this claim, leading to an estimate that human primary groups should consist of roughly 150 individuals. Gaps between this prediction and empirical observations can be partially accounted for using "compression heuristics", or schemata that simplify the encoding and recall of social information. However, little is known about the specific algorithmic processes used by humans to store and recall social information. We describe a mechanistic model of human network recall and demonstrate its sufficiency for capturing human recall behavior observed in experimental contexts. We find that human recall is predicated on accurate recall of a small number of high degree network nodes and the application of heuristics for both structural and affective information. This provides new insight into human memory, social network evolution, and demonstrates a novel approach to uncovering human cognitive operations.

  11. Stochastic Wilson–Cowan models of neuronal network dynamics with memory and delay

    International Nuclear Information System (INIS)

    Goychuk, Igor; Goychuk, Andriy

    2015-01-01

    We consider a simple Markovian class of the stochastic Wilson–Cowan type models of neuronal network dynamics, which incorporates stochastic delay caused by the existence of a refractory period of neurons. From the point of view of the dynamics of the individual elements, we are dealing with a network of non-Markovian stochastic two-state oscillators with memory, which are coupled globally in a mean-field fashion. This interrelation of a higher-dimensional Markovian and lower-dimensional non-Markovian dynamics is discussed in its relevance to the general problem of the network dynamics of complex elements possessing memory. The simplest model of this class is provided by a three-state Markovian neuron with one refractory state, which causes firing delay with an exponentially decaying memory within the two-state reduced model. This basic model is used to study critical avalanche dynamics (the noise sustained criticality) in a balanced feedforward network consisting of the excitatory and inhibitory neurons. Such avalanches emerge due to the network size dependent noise (mesoscopic noise). Numerical simulations reveal an intermediate power law in the distribution of avalanche sizes with the critical exponent around −1.16. We show that this power law is robust upon a variation of the refractory time over several orders of magnitude. However, the avalanche time distribution is biexponential. It does not reflect any genuine power law dependence. (paper)

  12. 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

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

    Science.gov (United States)

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

    2015-02-01

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

  14. 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.

  15. Cognitive reserve moderates the association between functional network anti-correlations and memory in MCI.

    Science.gov (United States)

    Franzmeier, Nicolai; Buerger, Katharina; Teipel, Stefan; Stern, Yaakov; Dichgans, Martin; Ewers, Michael

    2017-02-01

    Cognitive reserve (CR) shows protective effects on cognitive function in older adults. Here, we focused on the effects of CR at the functional network level. We assessed in patients with amnestic mild cognitive impairment (aMCI) whether higher CR moderates the association between low internetwork cross-talk on memory performance. In 2 independent aMCI samples (n = 76 and 93) and healthy controls (HC, n = 36), CR was assessed via years of education and intelligence (IQ). We focused on the anti-correlation between the dorsal attention network (DAN) and an anterior and posterior default mode network (DMN), assessed via sliding time window analysis of resting-state functional magnetic resonance imaging (fMRI). The DMN-DAN anti-correlation was numerically but not significantly lower in aMCI compared to HC. However, in aMCI, lower anterior DMN-DAN anti-correlation was associated with lower memory performance. This association was moderated by CR proxies, where the association between the internetwork anti-correlation and memory performance was alleviated at higher levels of education or IQ. In conclusion, lower DAN-DMN cross-talk is associated with lower memory in aMCI, where such effects are buffered by higher CR. Copyright © 2016 Elsevier Inc. All rights reserved.

  16. Unraveling Network-induced Memory Contention: Deeper Insights with Machine Learning

    International Nuclear Information System (INIS)

    Groves, Taylor Liles; Grant, Ryan; Gonzales, Aaron; Arnold, Dorian

    2017-01-01

    Remote Direct Memory Access (RDMA) is expected to be an integral communication mechanism for future exascale systems enabling asynchronous data transfers, so that applications may fully utilize CPU resources while simultaneously sharing data amongst remote nodes. We examine Network-induced Memory Contention (NiMC) on Infiniband networks. We expose the interactions between RDMA, main-memory and cache, when applications and out-of-band services compete for memory resources. We then explore NiMCs resulting impact on application-level performance. For a range of hardware technologies and HPC workloads, we quantify NiMC and show that NiMCs impact grows with scale resulting in up to 3X performance degradation at scales as small as 8K processes even in applications that previously have been shown to be performance resilient in the presence of noise. In addition, this work examines the problem of predicting NiMC's impact on applications by leveraging machine learning and easily accessible performance counters. This approach provides additional insights about the root cause of NiMC and facilitates dynamic selection of potential solutions. Finally, we evaluated three potential techniques to reduce NiMCs impact, namely hardware offloading, core reservation and network throttling.

  17. Memory and pattern storage in neural networks with activity dependent synapses

    Science.gov (United States)

    Mejias, J. F.; Torres, J. J.

    2009-01-01

    We present recently obtained results on the influence of the interplay between several activity dependent synaptic mechanisms, such as short-term depression and facilitation, on the maximum memory storage capacity in an attractor neural network [1]. In contrast with the case of synaptic depression, which drastically reduces the capacity of the network to store and retrieve activity patterns [2], synaptic facilitation is able to enhance the memory capacity in different situations. In particular, we find that a convenient balance between depression and facilitation can enhance the memory capacity, reaching maximal values similar to those obtained with static synapses, that is, without activity-dependent processes. We also argue, employing simple arguments, that this level of balance is compatible with experimental data recorded from some cortical areas, where depression and facilitation may play an important role for both memory-oriented tasks and information processing. We conclude that depressing synapses with a certain level of facilitation allow to recover the good retrieval properties of networks with static synapses while maintaining the nonlinear properties of dynamic synapses, convenient for information processing and coding.

  18. Contrasting Networks for Recognition Memory and Recency Memory Revealed by Immediate-Early Gene Imaging in the Rat

    Science.gov (United States)

    2014-01-01

    The expression of the immediate-early gene c-fos was used to compare networks of activity associated with recency memory (temporal order memory) and recognition memory. In Experiment 1, rats were first familiarized with sets of objects and then given pairs of different, familiar objects to explore. For the recency test group, each object in a pair was separated by 110 min in the time between their previous presentations. For the recency control test, each object in a pair was separated by less than a 1 min between their prior presentations. Temporal discrimination of the objects correlated with c-fos activity in the recency test group in several sites, including area Te2, the perirhinal cortex, lateral entorhinal cortex, as well as the dentate gyrus, hippocampal fields CA3 and CA1. For both the test and control conditions, network models were derived using structural equation modeling. The recency test model emphasized serial connections from the perirhinal cortex to lateral entorhinal cortex and then to the CA1 subfield. The recency control condition involved more parallel pathways, but again highlighted CA1 within the hippocampus. Both models contrasted with those derived from tests of object recognition (Experiment 2), because stimulus novelty was associated with pathways from the perirhinal cortex to lateral entorhinal cortex that then involved both the dentate gyrus (and CA3) and CA1 in parallel. The present findings implicate CA1 for the processing of familiar stimuli, including recency discriminations, while the dentate gyrus and CA3 pathways are recruited when the perirhinal cortex signals novel stimuli. PMID:24933661

  19. 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.

    2015-01-01

    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. PMID:26261317

  20. 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.

  1. 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

  2. Top-down and bottom-up attention-to-memory: mapping functional connectivity in two distinct networks that underlie cued and uncued recognition memory.

    Science.gov (United States)

    Burianová, Hana; Ciaramelli, Elisa; Grady, Cheryl L; Moscovitch, Morris

    2012-11-15

    The objective of this study was to examine the functional connectivity of brain regions active during cued and uncued recognition memory to test the idea that distinct networks would underlie these memory processes, as predicted by the attention-to-memory (AtoM) hypothesis. The AtoM hypothesis suggests that dorsal parietal cortex (DPC) allocates effortful top-down attention to memory retrieval during cued retrieval, whereas ventral parietal cortex (VPC) mediates spontaneous bottom-up capture of attention by memory during uncued retrieval. To identify networks associated with these two processes, we conducted a functional connectivity analysis of a left DPC and a left VPC region, both identified by a previous analysis of task-related regional activations. We hypothesized that the two parietal regions would be functionally connected with distinct neural networks, reflecting their engagement in the differential mnemonic processes. We found two spatially dissociated networks that overlapped only in the precuneus. During cued trials, DPC was functionally connected with dorsal attention areas, including the superior parietal lobules, right precuneus, and premotor cortex, as well as relevant memory areas, such as the left hippocampus and the middle frontal gyri. During uncued trials, VPC was functionally connected with ventral attention areas, including the supramarginal gyrus, cuneus, and right fusiform gyrus, as well as the parahippocampal gyrus. In addition, activity in the DPC network was associated with faster response times for cued retrieval. This is the first study to show a dissociation of the functional connectivity of posterior parietal regions during episodic memory retrieval, characterized by a top-down AtoM network involving DPC and a bottom-up AtoM network involving VPC. Copyright © 2012 Elsevier Inc. All rights reserved.

  3. 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.

  4. 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.

  5. Recurrent Neural Network For Forecasting Time Series With Long Memory Pattern

    Science.gov (United States)

    Walid; Alamsyah

    2017-04-01

    Recurrent Neural Network as one of the hybrid models are often used to predict and estimate the issues related to electricity, can be used to describe the cause of the swelling of electrical load which experienced by PLN. In this research will be developed RNN forecasting procedures at the time series with long memory patterns. Considering the application is the national electrical load which of course has a different trend with the condition of the electrical load in any country. This research produces the algorithm of time series forecasting which has long memory pattern using E-RNN after this referred to the algorithm of integrated fractional recurrent neural networks (FIRNN).The prediction results of long memory time series using models Fractional Integrated Recurrent Neural Network (FIRNN) showed that the model with the selection of data difference in the range of [-1,1] and the model of Fractional Integrated Recurrent Neural Network (FIRNN) (24,6,1) provides the smallest MSE value, which is 0.00149684.

  6. Synaptic potentiation facilitates memory-like attractor dynamics in cultured in vitro hippocampal networks.

    Directory of Open Access Journals (Sweden)

    Mark Niedringhaus

    Full Text Available Collective rhythmic dynamics from neurons is vital for cognitive functions such as memory formation but how neurons self-organize to produce such activity is not well understood. Attractor-based computational models have been successfully implemented as a theoretical framework for memory storage in networks of neurons. Additionally, activity-dependent modification of synaptic transmission is thought to be the physiological basis of learning and memory. The goal of this study is to demonstrate that using a pharmacological treatment that has been shown to increase synaptic strength within in vitro networks of hippocampal neurons follows the dynamical postulates theorized by attractor models. We use a grid of extracellular electrodes to study changes in network activity after this perturbation and show that there is a persistent increase in overall spiking and bursting activity after treatment. This increase in activity appears to recruit more "errant" spikes into bursts. Phase plots indicate a conserved activity pattern suggesting that a synaptic potentiation perturbation to the attractor leaves it unchanged. Lastly, we construct a computational model to demonstrate that these synaptic perturbations can account for the dynamical changes seen within the network.

  7. Gender differences in working memory networks: a BrainMap meta-analysis.

    Science.gov (United States)

    Hill, Ashley C; Laird, Angela R; Robinson, Jennifer L

    2014-10-01

    Gender differences in psychological processes have been of great interest in a variety of fields. While the majority of research in this area has focused on specific differences in relation to test performance, this study sought to determine the underlying neurofunctional differences observed during working memory, a pivotal cognitive process shown to be predictive of academic achievement and intelligence. Using the BrainMap database, we performed a meta-analysis and applied activation likelihood estimation to our search set. Our results demonstrate consistent working memory networks across genders, but also provide evidence for gender-specific networks whereby females consistently activate more limbic (e.g., amygdala and hippocampus) and prefrontal structures (e.g., right inferior frontal gyrus), and males activate a distributed network inclusive of more parietal regions. These data provide a framework for future investigations using functional or effective connectivity methods to elucidate the underpinnings of gender differences in neural network recruitment during working memory tasks. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. Default network activation during episodic and semantic memory retrieval: A selective meta-analytic comparison.

    Science.gov (United States)

    Kim, Hongkeun

    2016-01-08

    It remains unclear whether and to what extent the default network subregions involved in episodic memory (EM) and semantic memory (SM) processes overlap or are separated from one another. This study addresses this issue through a controlled meta-analysis of functional neuroimaging studies involving healthy participants. Various EM and SM task paradigms differ widely in the extent of default network involvement. Therefore, the issue at hand cannot be properly addressed without some control for this factor. In this regard, this study employs a two-stage analysis: a preliminary meta-analysis to select EM and SM task paradigms that recruit relatively extensive default network regions and a main analysis to compare the selected task paradigms. Based on a within-EM comparison, the default network contributed more to recollection/familiarity effects than to old/new effects, and based on a within-SM comparison, it contributed more to word/pseudoword effects than to semantic/phonological effects. According to a direct comparison of recollection/familiarity and word/pseudoword effects, each involving a range of default network regions, there were more overlaps than separations in default network subregions involved in these two effects. More specifically, overlaps included the bilateral posterior cingulate/retrosplenial cortex, left inferior parietal lobule, and left anteromedial prefrontal regions, whereas separations included only the hippocampal formation and the parahippocampal cortex region, which was unique to recollection/familiarity effects. These results indicate that EM and SM retrieval processes involving strong memory signals recruit extensive and largely overlapping default network regions and differ mainly in distinct contributions of hippocampus and parahippocampal regions to EM retrieval. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Finite Memory Walk and Its Application to Small-World Network

    Science.gov (United States)

    Oshima, Hiraku; Odagaki, Takashi

    2012-07-01

    In order to investigate the effects of cycles on the dynamical process on both regular lattices and complex networks, we introduce a finite memory walk (FMW) as an extension of the simple random walk (SRW), in which a walker is prohibited from moving to sites visited during m steps just before the current position. This walk interpolates the simple random walk (SRW), which has no memory (m = 0), and the self-avoiding walk (SAW), which has an infinite memory (m = ∞). We investigate the FMW on regular lattices and clarify the fundamental characteristics of the walk. We find that (1) the mean-square displacement (MSD) of the FMW shows a crossover from the SAW at a short time step to the SRW at a long time step, and the crossover time is approximately equivalent to the number of steps remembered, and that the MSD can be rescaled in terms of the time step and the size of memory; (2) the mean first-return time (MFRT) of the FMW changes significantly at the number of remembered steps that corresponds to the size of the smallest cycle in the regular lattice, where ``smallest'' indicates that the size of the cycle is the smallest in the network; (3) the relaxation time of the first-return time distribution (FRTD) decreases as the number of cycles increases. We also investigate the FMW on the Watts--Strogatz networks that can generate small-world networks, and show that the clustering coefficient of the Watts--Strogatz network is strongly related to the MFRT of the FMW that can remember two steps.

  10. Effects of Stress and Task Difficulty on Working Memory and Cortical Networking.

    Science.gov (United States)

    Kim, Yujin; Woo, Jihwan; Woo, Minjung

    2017-12-01

    This study investigated interactive effects of stress and task difficulty on working memory and cortico-cortical communication during memory encoding. Thirty-eight adolescent participants (mean age of 15.7 ± 1.5 years) completed easy and hard working memory tasks under low- and high-stress conditions. We analyzed the accuracy and reaction time (RT) of working memory performance and inter- and intrahemispheric electroencephalogram coherences during memory encoding. Working memory accuracy was higher, and RT shorter, in the easy versus the hard task. RT was shorter under the high-stress (TENS) versus low-stress (no-TENS) condition, while there was no difference in memory accuracy between the two stress conditions. For electroencephalogram coherence, we found higher interhemispheric coherence in all bands but only at frontal electrode sites in the easy versus the hard task. On the other hand, intrahemispheric coherence was higher in the left hemisphere in the easy (versus hard task) and higher in the right hemisphere (with one exception) in the hard (versus easy task). Inter- and intracoherences were higher in the low- versus high-stress condition. Significant interactions between task difficulty and stress condition were observed in coherences of the beta frequency band. The difference in coherence between low- and high-stress conditions was greater in the hard compared with the easy task, with lower coherence under the high-stress condition relative to the low-stress condition. Stress seemed to cause a decrease in cortical network communications between memory-relevant cortical areas as task difficulty increased.

  11. 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.

  12. 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.

  13. 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.

    2014-01-01

    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 an important role in the expression of extinction memory, has been shown to be functionally impaired after stress exposure. Further, recent research in rodents found that exposure to stress led 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 responses, 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, one day later participants in the stress group (n = 27) demonstrated significantly less

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

    Directory of Open Access Journals (Sweden)

    Florian eFiebig

    2014-07-01

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

  15. Aging and Network Properties: Stability Over Time and Links with Learning during Working Memory Training

    Directory of Open Access Journals (Sweden)

    Alexandru D. Iordan

    2018-01-01

    Full Text Available Growing evidence suggests that healthy aging affects the configuration of large-scale functional brain networks. This includes reducing network modularity and local efficiency. However, the stability of these effects over time and their potential role in learning remain poorly understood. The goal of the present study was to further clarify previously reported age effects on “resting-state” networks, to test their reliability over time, and to assess their relation to subsequent learning during training. Resting-state fMRI data from 23 young (YA and 20 older adults (OA were acquired in 2 sessions 2 weeks apart. Graph-theoretic analyses identified both consistencies in network structure and differences in module composition between YA and OA, suggesting topological changes and less stability of functional network configuration with aging. Brain-wide, OA showed lower modularity and local efficiency compared to YA, consistent with the idea of age-related functional dedifferentiation, and these effects were replicable over time. At the level of individual networks, OA consistently showed greater participation and lower local efficiency and within-network connectivity in the cingulo-opercular network, as well as lower intra-network connectivity in the default-mode network and greater participation of the somato-sensorimotor network, suggesting age-related differential effects at the level of specialized brain modules. Finally, brain-wide network properties showed associations, albeit limited, with learning rates, as assessed with 10 days of computerized working memory training administered after the resting-state sessions, suggesting that baseline network configuration may influence subsequent learning outcomes. Identification of neural mechanisms associated with learning-induced plasticity is important for further clarifying whether and how such changes predict the magnitude and maintenance of training gains, as well as the extent and limits of

  16. 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.

  17. The contribution of the human posterior parietal cortex to episodic memory

    OpenAIRE

    Sestieri, Carlo; Shulman, Gordon L.; Corbetta, Maurizio

    2017-01-01

    The posterior parietal cortex (PPC) is traditionally associated with attention, perceptual decision making and sensorimotor transformations, but more recent human neuroimaging studies support an additional role in episodic memory retrieval. In this Opinion article, we present a functional–anatomical model of the involvement of the PPC in memory retrieval. Parietal regions involved in perceptual attention and episodic memory are largely segregated and often show a push–pull relationship, poten...

  18. Dynamic reconfiguration of human brain functional networks through neurofeedback.

    Science.gov (United States)

    Haller, Sven; Kopel, Rotem; Jhooti, Permi; Haas, Tanja; Scharnowski, Frank; Lovblad, Karl-Olof; Scheffler, Klaus; Van De Ville, Dimitri

    2013-11-01

    Recent fMRI studies demonstrated that functional connectivity is altered following cognitive tasks (e.g., learning) or due to various neurological disorders. We tested whether real-time fMRI-based neurofeedback can be a tool to voluntarily reconfigure brain network interactions. To disentangle learning-related from regulation-related effects, we first trained participants to voluntarily regulate activity in the auditory cortex (training phase) and subsequently asked participants to exert learned voluntary self-regulation in the absence of feedback (transfer phase without learning). Using independent component analysis (ICA), we found network reconfigurations (increases in functional network connectivity) during the neurofeedback training phase between the auditory target region and (1) the auditory pathway; (2) visual regions related to visual feedback processing; (3) insula related to introspection and self-regulation and (4) working memory and high-level visual attention areas related to cognitive effort. Interestingly, the auditory target region was identified as the hub of the reconfigured functional networks without a-priori assumptions. During the transfer phase, we again found specific functional connectivity reconfiguration between auditory and attention network confirming the specific effect of self-regulation on functional connectivity. Functional connectivity to working memory related networks was no longer altered consistent with the absent demand on working memory. We demonstrate that neurofeedback learning is mediated by widespread changes in functional connectivity. In contrast, applying learned self-regulation involves more limited and specific network changes in an auditory setup intended as a model for tinnitus. Hence, neurofeedback training might be used to promote recovery from neurological disorders that are linked to abnormal patterns of brain connectivity. Copyright © 2013 Elsevier Inc. All rights reserved.

  19. Activation of the occipital cortex and deactivation of the default mode network during working memory in the early blind.

    Science.gov (United States)

    Park, Hae-Jeong; Chun, Ji-Won; Park, Bumhee; Park, Haeil; Kim, Joong Il; Lee, Jong Doo; Kim, Jae-Jin

    2011-05-01

    Although blind people heavily depend on working memory to manage daily life without visual information, it is not clear yet whether their working memory processing involves functional reorganization of the memory-related cortical network. To explore functional reorganization of the cortical network that supports various types of working memory processes in the early blind, we investigated activation differences between 2-back tasks and 0-back tasks using fMRI in 10 congenitally blind subjects and 10 sighted subjects. We used three types of stimulus sequences: words for a verbal task, pitches for a non-verbal task, and sound locations for a spatial task. When compared to the sighted, the blind showed additional activations in the occipital lobe for all types of stimulus sequences for working memory and more significant deactivation in the posterior cingulate cortex of the default mode network. The blind had increased effective connectivity from the default mode network to the left parieto-frontal network and from the occipital cortex to the right parieto-frontal network during the 2-back tasks than the 0-back tasks. These findings suggest not only cortical plasticity of the occipital cortex but also reorganization of the cortical network for the executive control of working memory.

  20. Non-equilibrium physics of neural networks for leaning, memory and decision making: landscape and flux perspectives

    Science.gov (United States)

    Wang, Jin

    Cognitive behaviors are determined by underlying neural networks. Many brain functions, such as learning and memory, can be described by attractor dynamics. We developed a theoretical framework for global dynamics by quantifying the landscape associated with the steady state probability distributions and steady state curl flux, measuring the degree of non-equilibrium through detailed balance breaking. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. Both landscape and flux determine the kinetic paths and speed of decision making. The kinetics and global stability of decision making are explored by quantifying the landscape topography through the barrier heights and the mean first passage time. The theoretical predictions are in agreement with experimental observations: more errors occur under time pressure. We quantitatively explored two mechanisms of the speed-accuracy tradeoff with speed emphasis and further uncovered the tradeoffs among speed, accuracy, and energy cost. Our results show an optimal balance among speed, accuracy, and the energy cost in decision making. We uncovered possible mechanisms of changes of mind and how mind changes improve performance in decision processes. Our landscape approach can help facilitate an understanding of the underlying physical mechanisms of cognitive processes and identify the key elements in neural networks.

  1. Effects of Intranasal Oxytocin on Long-Term Memory in Healthy Humans: A Systematic Review.

    Science.gov (United States)

    Brambilla, Michela; Manenti, Rosa; de Girolamo, Giovanni; Adenzato, Mauro; Bocchio-Chiavetto, Luisella; Cotelli, Maria

    2016-12-01

    Preclinical Research The neuropeptide oxytocin (Oxt) is implicated in complex emotional and social behaviors and appears to play an important role in learning and memory. Animal studies have shown that the effects of exogenous Oxt on memory vary according to the timing of administration, context, gender, and dose and may improve the memory of social, but not nonsocial stimuli. Oxt is intimately involved in a broad array of neuropsychiatric functions and may therefore be a pharmacological target for several psychiatric disorders. This review summarizes the potential effects of Oxt on long-term memory processes in healthy humans based on a PubMed search over the period 1980-2016. The effects of intranasal Oxt on human memory are controversial and the studies included in this review have applied a variety of learning paradigms, in turn producing variable outcomes. Specifically, data on the long-term memory of nonemotional stimuli found no effect or even worsening in memory, while studies using emotional stimuli showed an improvement of long-term memory performance. In conclusion, this review identified a link between long-term memory performance and exogenous intranasal Oxt in humans, although these results still warrant further confirmation in large, multicenter randomized controlled trials. Drug Dev Res 77 : 479-488, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  2. Aberrant neural networks for the recognition memory of socially relevant information in patients with schizophrenia.

    Science.gov (United States)

    Oh, Jooyoung; Chun, Ji-Won; Kim, Eunseong; Park, Hae-Jeong; Lee, Boreom; Kim, Jae-Jin

    2017-01-01

    Patients with schizophrenia exhibit several cognitive deficits, including memory impairment. Problems with recognition memory can hinder socially adaptive behavior. Previous investigations have suggested that altered activation of the frontotemporal area plays an important role in recognition memory impairment. However, the cerebral networks related to these deficits are not known. The aim of this study was to elucidate the brain networks required for recognizing socially relevant information in patients with schizophrenia performing an old-new recognition task. Sixteen patients with schizophrenia and 16 controls participated in this study. First, the subjects performed the theme-identification task during functional magnetic resonance imaging. In this task, pictures depicting social situations were presented with three words, and the subjects were asked to select the best theme word for each picture. The subjects then performed an old-new recognition task in which they were asked to discriminate whether the presented words were old or new. Task performance and neural responses in the old-new recognition task were compared between the subject groups. An independent component analysis of the functional connectivity was performed. The patients with schizophrenia exhibited decreased discriminability and increased activation of the right superior temporal gyrus compared with the controls during correct responses. Furthermore, aberrant network activities were found in the frontopolar and language comprehension networks in the patients. The functional connectivity analysis showed aberrant connectivity in the frontopolar and language comprehension networks in the patients with schizophrenia, and these aberrations possibly contribute to their low recognition performance and social dysfunction. These results suggest that the frontopolar and language comprehension networks are potential therapeutic targets in patients with schizophrenia.

  3. A One-Pass Real-Time Decoder Using Memory-Efficient State Network

    Science.gov (United States)

    Shao, Jian; Li, Ta; Zhang, Qingqing; Zhao, Qingwei; Yan, Yonghong

    This paper presents our developed decoder which adopts the idea of statically optimizing part of the knowledge sources while handling the others dynamically. The lexicon, phonetic contexts and acoustic model are statically integrated to form a memory-efficient state network, while the language model (LM) is dynamically incorporated on the fly by means of extended tokens. The novelties of our approach for constructing the state network are (1) introducing two layers of dummy nodes to cluster the cross-word (CW) context dependent fan-in and fan-out triphones, (2) introducing a so-called “WI layer” to store the word identities and putting the nodes of this layer in the non-shared mid-part of the network, (3) optimizing the network at state level by a sufficient forward and backward node-merge process. The state network is organized as a multi-layer structure for distinct token propagation at each layer. By exploiting the characteristics of the state network, several techniques including LM look-ahead, LM cache and beam pruning are specially designed for search efficiency. Especially in beam pruning, a layer-dependent pruning method is proposed to further reduce the search space. The layer-dependent pruning takes account of the neck-like characteristics of WI layer and the reduced variety of word endings, which enables tighter beam without introducing much search errors. In addition, other techniques including LM compression, lattice-based bookkeeping and lattice garbage collection are also employed to reduce the memory requirements. Experiments are carried out on a Mandarin spontaneous speech recognition task where the decoder involves a trigram LM and CW triphone models. A comparison with HDecode of HTK toolkits shows that, within 1% performance deviation, our decoder can run 5 times faster with half of the memory footprint.

  4. 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

  5. Association Between Sluggish Cognitive Tempo Symptoms and Attentional Network and Working Memory in Primary Schoolchildren.

    Science.gov (United States)

    Camprodon-Rosanas, E; Ribas-Fitó, N; Batlle, S; Persavento, C; Alvarez-Pedrerol, M; Sunyer, J; Forns, J

    2017-04-01

    Few consistent data are available in relation to the cognitive and neuropsychological processes involved in sluggish cognitive tempo (SCT) symptoms. The objective of this study was to determine the association of working memory and attentional networks with SCT symptoms in primary schoolchildren. The participants were schoolchildren aged 7 to 10 years ( n = 183) from primary schools in Catalonia (Spain). All the participants completed a working memory task (n-back) and an attentional network task (ANT). Their parents completed an SCT-Child Behavior Checklist self-report and a questionnaire concerning sociodemographic variables. Teachers of the participants provided information on ADHD symptoms and learning determinants. SCT symptoms were correlated with lower scores in both the n-back and ANT. In multivariate regression analysis, SCT symptoms were associated with slower hit reaction times from the ANT. Our results suggest that SCT symptoms are associated with a neuropsychological profile that is different from the classical ADHD profile and characterized by slower reaction times.

  6. Finite-Time Stability for Fractional-Order Bidirectional Associative Memory Neural Networks with Time Delays

    Science.gov (United States)

    Xu, Chang-Jin; Li, Pei-Luan; Pang, Yi-Cheng

    2017-02-01

    This paper is concerned with fractional-order bidirectional associative memory (BAM) neural networks with time delays. Applying Laplace transform, the generalized Gronwall inequality and estimates of Mittag-Leffler functions, some sufficient conditions which ensure the finite-time stability of fractional-order bidirectional associative memory neural networks with time delays are obtained. Two examples with their simulations are given to illustrate the theoretical findings. Our results are new and complement previously known results. Supported by National Natural Science Foundation of China under Grant Nos.~61673008, 11261010, 11101126, Project of High-Level Innovative Talents of Guizhou Province ([2016]5651), Natural Science and Technology Foundation of Guizhou Province (J[2015]2025 and J[2015]2026), 125 Special Major Science and Technology of Department of Education of Guizhou Province ([2012]011) and Natural Science Foundation of the Education Department of Guizhou Province (KY[2015]482)

  7. Prefrontal spatial working memory network predicts animal's decision making in a free choice saccade task.

    Science.gov (United States)

    Mochizuki, Kei; Funahashi, Shintaro

    2016-01-01

    While neurons in the lateral prefrontal cortex (PFC) encode spatial information during the performance of working memory tasks, they are also known to participate in subjective behavior such as spatial attention and action selection. In the present study, we analyzed the activity of primate PFC neurons during the performance of a free choice memory-guided saccade task in which the monkeys needed to choose a saccade direction by themselves. In trials when the receptive field location was subsequently chosen by the animal, PFC neurons with spatially selective visual response started to show greater activation before cue onset. This result suggests that the fluctuation of firing before cue presentation prematurely biased the representation of a certain spatial location and eventually encouraged the subsequent choice of that location. In addition, modulation of the activity by the animal's choice was observed only in neurons with high sustainability of activation and was also dependent on the spatial configuration of the visual cues. These findings were consistent with known characteristics of PFC neurons in information maintenance in spatial working memory function. These results suggest that precue fluctuation of spatial representation was shared and enhanced through the working memory network in the PFC and could finally influence the animal's free choice of saccade direction. The present study revealed that the PFC plays an important role in decision making in a free choice condition and that the dynamics of decision making are constrained by the network architecture embedded in this cortical area. Copyright © 2016 the American Physiological Society.

  8. Prefrontal spatial working memory network predicts animal's decision making in a free choice saccade task

    Science.gov (United States)

    Mochizuki, Kei

    2015-01-01

    While neurons in the lateral prefrontal cortex (PFC) encode spatial information during the performance of working memory tasks, they are also known to participate in subjective behavior such as spatial attention and action selection. In the present study, we analyzed the activity of primate PFC neurons during the performance of a free choice memory-guided saccade task in which the monkeys needed to choose a saccade direction by themselves. In trials when the receptive field location was subsequently chosen by the animal, PFC neurons with spatially selective visual response started to show greater activation before cue onset. This result suggests that the fluctuation of firing before cue presentation prematurely biased the representation of a certain spatial location and eventually encouraged the subsequent choice of that location. In addition, modulation of the activity by the animal's choice was observed only in neurons with high sustainability of activation and was also dependent on the spatial configuration of the visual cues. These findings were consistent with known characteristics of PFC neurons in information maintenance in spatial working memory function. These results suggest that precue fluctuation of spatial representation was shared and enhanced through the working memory network in the PFC and could finally influence the animal's free choice of saccade direction. The present study revealed that the PFC plays an important role in decision making in a free choice condition and that the dynamics of decision making are constrained by the network architecture embedded in this cortical area. PMID:26490287

  9. Zero-dynamics principle for perfect quantum memory in linear networks

    International Nuclear Information System (INIS)

    Yamamoto, Naoki; James, Matthew R

    2014-01-01

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

  10. Zero-dynamics principle for perfect quantum memory in linear networks

    Science.gov (United States)

    Yamamoto, Naoki; James, Matthew R.

    2014-07-01

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

  11. Discrete-time bidirectional associative memory neural networks with variable delays

    International Nuclear Information System (INIS)

    Liang Jinling; Cao Jinde; Ho, Daniel W.C.

    2005-01-01

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

  12. Global asymptotic stability analysis of bidirectional associative memory neural networks with time delays.

    Science.gov (United States)

    Arik, Sabri

    2005-05-01

    This paper presents a sufficient condition for the existence, uniqueness and global asymptotic stability of the equilibrium point for bidirectional associative memory (BAM) neural networks with distributed time delays. The results impose constraint conditions on the network parameters of neural system independently of the delay parameter, and they are applicable to all continuous nonmonotonic neuron activation functions. It is shown that in some special cases of the results, the stability criteria can be easily checked. Some examples are also given to compare the results with the previous results derived in the literature.

  13. Convergence dynamics of hybrid bidirectional associative memory neural networks with distributed delays

    International Nuclear Information System (INIS)

    Liao Xiaofeng; Wong, K.-W.; Yang Shizhong

    2003-01-01

    In this Letter, the characteristics of the convergence dynamics of hybrid bidirectional associative memory neural networks with distributed transmission delays are studied. Without assuming the symmetry of synaptic connection weights and the monotonicity and differentiability of activation functions, the Lyapunov functionals are constructed and the generalized Halanay-type inequalities are employed to derive the delay-independent sufficient conditions under which the networks converge exponentially to the equilibria associated with temporally uniform external inputs. Some examples are given to illustrate the correctness of our results

  14. Discrete-time bidirectional associative memory neural networks with variable delays

    Science.gov (United States)

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

    2005-02-01

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

  15. New results for global robust stability of bidirectional associative memory neural networks with multiple time delays

    International Nuclear Information System (INIS)

    Senan, Sibel; Arik, Sabri

    2009-01-01

    This paper presents some new sufficient conditions for the global robust asymptotic stability of the equilibrium point for bidirectional associative memory (BAM) neural networks with multiple time delays. The results we obtain impose constraint conditions on the network parameters of neural system independently of the delay parameter, and they are applicable to all bounded continuous non-monotonic neuron activation functions. We also give some numerical examples to demonstrate the applicability and effectiveness of our results, and compare the results with the previous robust stability results derived in the literature.

  16. Filtering and storage working memory networks in younger and older age.

    Science.gov (United States)

    Vellage, Anne-Katrin; Becke, Andreas; Strumpf, Hendrik; Baier, Bernhard; Schönfeld, Mircea Ariel; Hopf, Jens-Max; Müller, Notger G

    2016-11-01

    Working memory (WM) is a multi-component model that among others involves the two processes of filtering and storage. The first reflects the necessity to inhibit irrelevant information from entering memory, whereas the latter refers to the active maintenance of object representations in memory. In this study, we aimed at a) redefining the neuronal networks sustaining filtering and storage within visual working memory by avoiding shortcomings of prior studies, and b) assessing age-related changes in these networks. We designed a new paradigm that strictly controlled for perceptual load by presenting the same number of stimuli in each of three conditions. We calculated fMRI contrasts between a baseline condition (low filter and low storage load) and conditions that posed high demands on filtering and storage, respectively, in large samples of younger ( n  = 40) and elder ( n  = 38) participants. Our approach of comparing contrasts between groups revealed more extensive filter and storage WM networks than previous studies. In the younger group, filtering involved the bilateral insulae, the right occipital cortex, the right brainstem, and the right cerebellum. In the elder group, filtering was associated with the bilateral insulae, right precuneus, and bilateral ventromedial prefrontal cortex. An extensive neuronal network was also found during storage of information in the bilateral posterior parietal cortex, the left ventromedial prefrontal cortex, and the right precuneus in the younger participants. In addition to these brain regions, elder participants recruited the bilateral ventral prefrontal cortex, the superior, middle and inferior and temporal cortex, the left cingulum and the bilateral parahippocampal cortex. In general, elder participants recruited more brain regions in comparison to younger participants to reach similar accuracy levels. Furthermore, in elder participants one brain region emerged in both contrasts, namely the left ventromedial prefrontal

  17. 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...

  18. On exponential stability of bidirectional associative memory neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Park, Ju H.; Lee, S.M.; Kwon, O.M.

    2009-01-01

    For bidirectional associate memory neural networks with time-varying delays, the problems of determining the exponential stability and estimating the exponential convergence rate are investigated by employing the Lyapunov functional method and linear matrix inequality (LMI) technique. A novel criterion for the stability, which give information on the delay-dependent property, is derived. A numerical example is given to demonstrate the effectiveness of the obtained results.

  19. Statistical downscaling of precipitation using long short-term memory recurrent neural networks

    Science.gov (United States)

    Misra, Saptarshi; Sarkar, Sudeshna; Mitra, Pabitra

    2017-11-01

    Hydrological impacts of global climate change on regional scale are generally assessed by downscaling large-scale climatic variables, simulated by General Circulation Models (GCMs), to regional, small-scale hydrometeorological variables like precipitation, temperature, etc. In this study, we propose a new statistical downscaling model based on Recurrent Neural Network with Long Short-Term Memory which captures the spatio-temporal dependencies in local rainfall. The previous studies have used several other methods such as linear regression, quantile regression, kernel regression, beta regression, and artificial neural networks. Deep neural networks and recurrent neural networks have been shown to be highly promising in modeling complex and highly non-linear relationships between input and output variables in different domains and hence we investigated their performance in the task of statistical downscaling. We have tested this model on two datasets—one on precipitation in Mahanadi basin in India and the second on precipitation in Campbell River basin in Canada. Our autoencoder coupled long short-term memory recurrent neural network model performs the best compared to other existing methods on both the datasets with respect to temporal cross-correlation, mean squared error, and capturing the extremes.

  20. Neural Network with Local Memory for Nuclear Reactor Power Level Control

    International Nuclear Information System (INIS)

    Uluyol, Oender; Ragheb, Magdi; Tsoukalas, Lefteri

    2001-01-01

    A methodology is introduced for a neural network with local memory called a multilayered local output gamma feedback (LOGF) neural network within the paradigm of locally-recurrent globally-feedforward neural networks. It appears to be well-suited for the identification, prediction, and control tasks in highly dynamic systems; it allows for the presentation of different timescales through incorporation of a gamma memory. A learning algorithm based on the backpropagation-through-time approach is derived. The spatial and temporal weights of the network are iteratively optimized for a given problem using the derived learning algorithm. As a demonstration of the methodology, it is applied to the task of power level control of a nuclear reactor at different fuel cycle conditions. The results demonstrate that the LOGF neural network controller outperforms the classical as well as the state feedback-assisted classical controllers for reactor power level control by showing a better tracking of the demand power, improving the fuel and exit temperature responses, and by performing robustly in different fuel cycle and power level conditions

  1. Keeping and transmission of the memory. The memory duty for the human and the environment service

    International Nuclear Information System (INIS)

    2003-05-01

    Applied to the long-dated survey mission devoted to the ANDRA, the memory duty is a regulation necessity. They must realize the conservation and the transmission of the long-dated memory of stored radioactive wastes and their behavior in the future. A presentation of the interveners and their point of view during the conference are presented. (A.L.B.)

  2. 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.…

  3. 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…

  4. Attention supports verbal short-term memory via competition between dorsal and ventral attention networks.

    Science.gov (United States)

    Majerus, Steve; Attout, Lucie; D'Argembeau, Arnaud; Degueldre, Christian; Fias, Wim; Maquet, Pierre; Martinez Perez, Trecy; Stawarczyk, David; Salmon, Eric; Van der Linden, Martial; Phillips, Christophe; Balteau, Evelyne

    2012-05-01

    Interactions between the neural correlates of short-term memory (STM) and attention have been actively studied in the visual STM domain but much less in the verbal STM domain. Here we show that the same attention mechanisms that have been shown to shape the neural networks of visual STM also shape those of verbal STM. Based on previous research in visual STM, we contrasted the involvement of a dorsal attention network centered on the intraparietal sulcus supporting task-related attention and a ventral attention network centered on the temporoparietal junction supporting stimulus-related attention. We observed that, with increasing STM load, the dorsal attention network was activated while the ventral attention network was deactivated, especially during early maintenance. Importantly, activation in the ventral attention network increased in response to task-irrelevant stimuli briefly presented during the maintenance phase of the STM trials but only during low-load STM conditions, which were associated with the lowest levels of activity in the dorsal attention network during encoding and early maintenance. By demonstrating a trade-off between task-related and stimulus-related attention networks during verbal STM, this study highlights the dynamics of attentional processes involved in verbal STM.

  5. 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...

  6. 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…

  7. PIYAS-Proceeding to Intelligent Service Oriented Memory Allocation for Flash Based Data Centric Sensor Devices in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sanam Shahla Rizvi

    2009-12-01

    Full Text Available Flash memory has become a more widespread storage medium for modern wireless devices because of its effective characteristics like non-volatility, small size, light weight, fast access speed, shock resistance, high reliability and low power consumption. Sensor nodes are highly resource constrained in terms of limited processing speed, runtime memory, persistent storage, communication bandwidth and finite energy. Therefore, for wireless sensor networks supporting sense, store, merge and send schemes, an efficient and reliable file system is highly required with consideration of sensor node constraints. In this paper, we propose a novel log structured external NAND flash memory based file system, called Proceeding to Intelligent service oriented memorY Allocation for flash based data centric Sensor devices in wireless sensor networks (PIYAS. This is the extended version of our previously proposed PIYA [1]. The main goals of the PIYAS scheme are to achieve instant mounting and reduced SRAM space by keeping memory mapping information to a very low size of and to provide high query response throughput by allocation of memory to the sensor data by network business rules. The scheme intelligently samples and stores the raw data and provides high in-network data availability by keeping the aggregate data for a longer period of time than any other scheme has done before. We propose effective garbage collection and wear-leveling schemes as well. The experimental results show that PIYAS is an optimized memory management scheme allowing high performance for wireless sensor networks.

  8. PIYAS-proceeding to intelligent service oriented memory allocation for flash based data centric sensor devices in wireless sensor networks.

    Science.gov (United States)

    Rizvi, Sanam Shahla; Chung, Tae-Sun

    2010-01-01

    Flash memory has become a more widespread storage medium for modern wireless devices because of its effective characteristics like non-volatility, small size, light weight, fast access speed, shock resistance, high reliability and low power consumption. Sensor nodes are highly resource constrained in terms of limited processing speed, runtime memory, persistent storage, communication bandwidth and finite energy. Therefore, for wireless sensor networks supporting sense, store, merge and send schemes, an efficient and reliable file system is highly required with consideration of sensor node constraints. In this paper, we propose a novel log structured external NAND flash memory based file system, called Proceeding to Intelligent service oriented memorY Allocation for flash based data centric Sensor devices in wireless sensor networks (PIYAS). This is the extended version of our previously proposed PIYA [1]. The main goals of the PIYAS scheme are to achieve instant mounting and reduced SRAM space by keeping memory mapping information to a very low size of and to provide high query response throughput by allocation of memory to the sensor data by network business rules. The scheme intelligently samples and stores the raw data and provides high in-network data availability by keeping the aggregate data for a longer period of time than any other scheme has done before. We propose effective garbage collection and wear-leveling schemes as well. The experimental results show that PIYAS is an optimized memory management scheme allowing high performance for wireless sensor networks.

  9. Semantic and episodic memory of music are subserved by distinct neural networks.

    Science.gov (United States)

    Platel, Hervé; Baron, Jean-Claude; Desgranges, Béatrice; Bernard, Frédéric; Eustache, Francis

    2003-09-01

    Numerous functional imaging studies have shown that retrieval from semantic and episodic memory is subserved by distinct neural networks. However, these results were essentially obtained with verbal and visuospatial material. The aim of this work was to determine the neural substrates underlying the semantic and episodic components of music using familiar and nonfamiliar melodic tunes. To study musical semantic memory, we designed a task in which the instruction was to judge whether or not the musical extract was felt as "familiar." To study musical episodic memory, we constructed two delayed recognition tasks, one containing only familiar and the other only nonfamiliar items. For each recognition task, half of the extracts (targets) were presented in the prior semantic task. The episodic and semantic tasks were to be contrasted by a comparison to two perceptive control tasks and to one another. Cerebral blood flow was assessed by means of the oxygen-15-labeled water injection method, using high-resolution PET. Distinct patterns of activations were found. First, regarding the episodic memory condition, bilateral activations of the middle and superior frontal gyri and precuneus (more prominent on the right side) were observed. Second, the semantic memory condition disclosed extensive activations in the medial and orbital frontal cortex bilaterally, the left angular gyrus, and predominantly the left anterior part of the middle temporal gyri. The findings from this study are discussed in light of the available neuropsychological data obtained in brain-damaged subjects and functional neuroimaging studies.

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

    Science.gov (United States)

    Luhmann, Christian C; Rajaram, Suparna

    2015-12-01

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

  11. Modulation of network excitability by persistent activity: how working memory affects the response to incoming stimuli.

    Directory of Open Access Journals (Sweden)

    Elisa M Tartaglia

    2015-02-01

    Full Text Available Persistent activity and match effects are widely regarded as neuronal correlates of short-term storage and manipulation of information, with the first serving active maintenance and the latter supporting the comparison between memory contents and incoming sensory information. The mechanistic and functional relationship between these two basic neurophysiological signatures of working memory remains elusive. We propose that match signals are generated as a result of transient changes in local network excitability brought about by persistent activity. Neurons more active will be more excitable, and thus more responsive to external inputs. Accordingly, network responses are jointly determined by the incoming stimulus and the ongoing pattern of persistent activity. Using a spiking model network, we show that this mechanism is able to reproduce most of the experimental phenomenology of match effects as exposed by single-cell recordings during delayed-response tasks. The model provides a unified, parsimonious mechanistic account of the main neuronal correlates of working memory, makes several experimentally testable predictions, and demonstrates a new functional role for persistent activity.

  12. Inter-crosslinking network gels having both shape memory and high ductility

    Science.gov (United States)

    Amano, Yoshitaka; Hidema, Ruri; Furukawa, Hidemitsu

    2012-04-01

    Medical treatment for injuries should be easy and quick in many accidents. Plasters or bandages are frequently used to wrap and fix injured parts. If plasters or bandages have additional smart functions, such as cooling, removability and repeatability, they will be much more useful and effective. Here we propose innovative biocompatible materials, that is, nontoxic high-strength shape-memory gels as novel smart medical materials. These smart gels were prepared from two monomers (DMAAm and SA), a polymer (HPC), and an inter-crosslinking agent (Karenz-MOI). In the synthesis of the gels, 1) a shape-memory copolymer network is made from the DMAAm and the SA, and 2) the copolymer and the HPC are crosslinked by the Karenz-MOI. Thus the crosslinking points are connected only between the different polymers. This is our original technique of developing a new network structure of gels, named Inter-Crosslinking Network (ICN). The ICN gels achieve high ductility, going up to 700% strain in tensile tests, while the ICN gels contain about 44% water. Moreover the SA has temperature dependence due to its crystallization properties; thus the ICN gels obtain shape memory properties and are named ICN-SMG. While the Young's modulus of the ICN-SMG is large below their crystallization temperature and the gels behave like plastic materials, the modulus becomes smaller above the temperature and the gels turn back to their original shape.

  13. Preserved functional connectivity in the default mode and salience networks is associated with youthful memory in superaging

    OpenAIRE

    Barrett, Lisa; Zhang, Jiahe; Andreano, Joseph; Dickerson, Bradford; Touroutoglou, Alexandra

    2018-01-01

    'Superagers' are older adults who, despite their advanced age, maintain youthful memory. Previous morphometry studies revealed multiple default mode network (DMN) and salience network (SN) regions whose cortical thickness is preserved in superagers and correlates with memory performance. In this study, we examined the intrinsic functional connectivity within DMN and SN in 41 young (24.5 ± 3.6 years old) and 40 elderly adults (66.9 ± 5.5 years old). As in prior studies, superaging was defined ...

  14. 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.

  15. 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.

  16. 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.

  17. The contribution of the human posterior parietal cortex to episodic memory.

    Science.gov (United States)

    Sestieri, Carlo; Shulman, Gordon L; Corbetta, Maurizio

    2017-02-17

    The posterior parietal cortex (PPC) is traditionally associated with attention, perceptual decision making and sensorimotor transformations, but more recent human neuroimaging studies support an additional role in episodic memory retrieval. In this Opinion article, we present a functional-anatomical model of the involvement of the PPC in memory retrieval. Parietal regions involved in perceptual attention and episodic memory are largely segregated and often show a push-pull relationship, potentially mediated by prefrontal regions. Moreover, different PPC regions carry out specific functions during retrieval - for example, representing retrieved information, recoding this information based on task demands, or accumulating evidence for memory decisions.

  18. Losing memories overnight: a unique form of human amnesia.

    Science.gov (United States)

    Smith, Christine N; Frascino, Jennifer C; Kripke, Donald L; McHugh, Paul R; Treisman, Glenn J; Squire, Larry R

    2010-08-01

    Since an automobile accident in 2005, patient FL has reported difficulty retaining information from one day to the next. During the course of any given day, she describes her memory as normal. However, memory for each day disappears during a night of sleep. She reports good memory for events that occurred before the accident. Although this pattern of memory impairment is, to our knowledge, unique to the medical literature, it was depicted in the fictional film "50 First Dates". On formal testing, FL performed moderately well when trying to remember material that she had learned during the same day, but she exhibited no memory at all for material that she knew had been presented on a previous day. For some tests, unbeknownst to FL, material learned on the previous day was intermixed with material learned on the same day as the test. On these occasions, FL's memory was good. Thus, she was able to remember events from earlier days when memory was tested covertly. FL performed differently in a number of ways from individuals who were instructed to consciously feign her pattern of memory impairment. It was also the impression of those who worked with FL that she believed she had the memory impairment that she described and that she was not intentionally feigning amnesia. On the basis of her neuropsychological findings, together with a normal neurological exam, normal MRI findings, and psychiatric evaluation, we suggest that FL exhibits a unique form of functional amnesia and that its characterization may have been influenced by knowledge of how amnesia was depicted in a popular film. She subsequently improved (and began retaining day-to-day memory) at Johns Hopkins University where she was in a supportive in-patient environment and was shown how to take control of her condition by interrupting her sleep at 4-h intervals. Published by Elsevier Ltd.

  19. Evidence for a double dissociation of articulatory rehearsal and non-articulatory maintenance of phonological information in human verbal working memory.

    Science.gov (United States)

    Trost, Sarah; Gruber, Oliver

    2012-01-01

    Recent functional neuroimaging studies have provided evidence that human verbal working memory is represented by two complementary neural systems, a left lateralized premotor-parietal network implementing articulatory rehearsal and a presumably phylogenetically older bilateral anterior-prefrontal/inferior-parietal network subserving non-articulatory maintenance of phonological information. In order to corroborate these findings from functional neuroimaging, we performed a targeted behavioural study in patients with very selective and circumscribed brain lesions to key regions suggested to support these different subcomponents of human verbal working memory. Within a sample of over 500 neurological patients assessed with high-resolution structural magnetic resonance imaging, we identified 2 patients with corresponding brain lesions, one with an isolated lesion to Broca's area and the other with a selective lesion bilaterally to the anterior middle frontal gyrus. These 2 patients as well as groups of age-matched healthy controls performed two circuit-specific verbal working memory tasks. In this way, we systematically assessed the hypothesized selective behavioural effects of these brain lesions on the different subcomponents of verbal working memory in terms of a double dissociation. Confirming prior findings, the lesion to Broca's area led to reduced performance under articulatory rehearsal, whereas the non-articulatory maintenance of phonological information was unimpaired. Conversely, the bifrontopolar brain lesion was associated with impaired non-articulatory phonological working memory, whereas performance under articulatory rehearsal was unaffected. The present experimental neuropsychological study in patients with specific and circumscribed brain lesions confirms the hypothesized double dissociation of two complementary brain systems underlying verbal working memory in humans. In particular, the results demonstrate the functional relevance of the anterior

  20. 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

  1. 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.

  2. Human memory CD8 T cell effector potential is epigenetically preserved during in vivo homeostasis.

    Science.gov (United States)

    Abdelsamed, Hossam A; Moustaki, Ardiana; Fan, Yiping; Dogra, Pranay; Ghoneim, Hazem E; Zebley, Caitlin C; Triplett, Brandon M; Sekaly, Rafick-Pierre; Youngblood, Ben

    2017-06-05

    Antigen-independent homeostasis of memory CD8 T cells is vital for sustaining long-lived T cell-mediated immunity. In this study, we report that maintenance of human memory CD8 T cell effector potential during in vitro and in vivo homeostatic proliferation is coupled to preservation of acquired DNA methylation programs. Whole-genome bisulfite sequencing of primary human naive, short-lived effector memory (T EM ), and longer-lived central memory (T CM ) and stem cell memory (T SCM ) CD8 T cells identified effector molecules with demethylated promoters and poised for expression. Effector-loci demethylation was heritably preserved during IL-7- and IL-15-mediated in vitro cell proliferation. Conversely, cytokine-driven proliferation of T CM and T SCM memory cells resulted in phenotypic conversion into T EM cells and was coupled to increased methylation of the CCR7 and Tcf7 loci. Furthermore, haploidentical donor memory CD8 T cells undergoing in vivo proliferation in lymphodepleted recipients also maintained their effector-associated demethylated status but acquired T EM -associated programs. These data demonstrate that effector-associated epigenetic programs are preserved during cytokine-driven subset interconversion of human memory CD8 T cells. © 2017 Abdelsamed et al.

  3. A role for α-adducin (ADD-1) in nematode and human memory.

    Science.gov (United States)

    Vukojevic, Vanja; Gschwind, Leo; Vogler, Christian; Demougin, Philippe; de Quervain, Dominique J-F; Papassotiropoulos, Andreas; Stetak, Attila

    2012-03-21

    Identifying molecular mechanisms that underlie learning and memory is one of the major challenges in neuroscience. Taken the advantages of the nematode Caenorhabditis elegans, we investigated α-adducin (add-1) in aversive olfactory associative learning and memory. Loss of add-1 function selectively impaired short- and long-term memory without causing acquisition, sensory, or motor deficits. We showed that α-adducin is required for consolidation of synaptic plasticity, for sustained synaptic increase of AMPA-type glutamate receptor (GLR-1) content and altered GLR-1 turnover dynamics. ADD-1, in a splice-form- and tissue-specific manner, controlled the storage of memories presumably through actin-capping activity. In support of the C. elegans results, genetic variability of the human ADD1 gene was significantly associated with episodic memory performance in healthy young subjects. Finally, human ADD1 expression in nematodes restored loss of C. elegans add-1 gene function. Taken together, our findings support a role for α-adducin in memory from nematodes to humans. Studying the molecular and genetic underpinnings of memory across distinct species may be helpful in the development of novel strategies to treat memory-related diseases.

  4. 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.

  5. Human processor modelling language (HPML): Estimate working memory load through interaction

    OpenAIRE

    Geisler, J.; Scheben, C.

    2007-01-01

    To operate machines over their user interface may cause high load on human's working memory. This load can decrease performance in the working task significantly if this task is a cognitive challenging one, e. g. diagnosis. With the »Human Processor Modelling Language« (HPML) the interaction activity can be modelled with a directed graph. From such models a condensed indicator value for working memory load can be estimated. Thus different user interface solutions can get compared with respect...

  6. A human protein interaction network shows conservation of aging processes between human and invertebrate species.

    Directory of Open Access Journals (Sweden)

    Russell Bell

    2009-03-01

    Full Text Available We have mapped a protein interaction network of human homologs of proteins that modify longevity in invertebrate species. This network is derived from a proteome-scale human protein interaction Core Network generated through unbiased high-throughput yeast two-hybrid searches. The longevity network is composed of 175 human homologs of proteins known to confer increased longevity through loss of function in yeast, nematode, or fly, and 2,163 additional human proteins that interact with these homologs. Overall, the network consists of 3,271 binary interactions among 2,338 unique proteins. A comparison of the average node degree of the human longevity homologs with random sets of proteins in the Core Network indicates that human homologs of longevity proteins are highly connected hubs with a mean node degree of 18.8 partners. Shortest path length analysis shows that proteins in this network are significantly more connected than would be expected by chance. To examine the relationship of this network to human aging phenotypes, we compared the genes encoding longevity network proteins to genes known to be changed transcriptionally during aging in human muscle. In the case of both the longevity protein homologs and their interactors, we observed enrichments for differentially expressed genes in the network. To determine whether homologs of human longevity interacting proteins can modulate life span in invertebrates, homologs of 18 human FRAP1 interacting proteins showing significant changes in human aging muscle were tested for effects on nematode life span using RNAi. Of 18 genes tested, 33% extended life span when knocked-down in Caenorhabditis elegans. These observations indicate that a broad class of longevity genes identified in invertebrate models of aging have relevance to human aging. They also indicate that the longevity protein interaction network presented here is enriched for novel conserved longevity proteins.

  7. 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.

  8. Specific responses of human hippocampal neurons are associated with better memory.

    Science.gov (United States)

    Suthana, Nanthia A; Parikshak, Neelroop N; Ekstrom, Arne D; Ison, Matias J; Knowlton, Barbara J; Bookheimer, Susan Y; Fried, Itzhak

    2015-08-18

    A population of human hippocampal neurons has shown responses to individual concepts (e.g., Jennifer Aniston) that generalize to different instances of the concept. However, recordings from the rodent hippocampus suggest an important function of these neurons is their ability to discriminate overlapping representations, or pattern separate, a process that may facilitate discrimination of similar events for successful memory. In the current study, we explored whether human hippocampal neurons can also demonstrate the ability to discriminate between overlapping representations and whether this selectivity could be directly related to memory performance. We show that among medial temporal lobe (MTL) neurons, certain populations of neurons are selective for a previously studied (target) image in that they show a significant decrease in firing rate to very similar (lure) images. We found that a greater proportion of these neurons can be found in the hippocampus compared with other MTL regions, and that memory for individual items is correlated to the degree of selectivity of hippocampal neurons responsive to those items. Moreover, a greater proportion of hippocampal neurons showed selective firing for target images in good compared with poor performers, with overall memory performance correlated with hippocampal selectivity. In contrast, selectivity in other MTL regions was not associated with memory performance. These findings show that a substantial proportion of human hippocampal neurons encode specific memories that support the discrimination of overlapping representations. These results also provide previously unidentified evidence consistent with a unique role of the human hippocampus in orthogonalization of representations in declarative memory.

  9. Evidence for Human Fronto-Central Gamma Activity during Long-Term Memory Encoding of Word Sequences

    Science.gov (United States)

    Meeuwissen, Esther Berendina; Takashima, Atsuko; Fernández, Guillén; Jensen, Ole

    2011-01-01

    Although human gamma activity (30–80 Hz) associated with visual processing is often reported, it is not clear to what extend gamma activity can be reliably detected non-invasively from frontal areas during complex cognitive tasks such as long term memory (LTM) formation. We conducted a memory experiment composed of 35 blocks each having three parts: LTM encoding, working memory (WM) maintenance and LTM retrieval. In the LTM encoding and WM maintenance parts, participants had to respectively encode or maintain the order of three sequentially presented words. During LTM retrieval subjects had to reproduce these sequences. Using magnetoencephalography (MEG) we identified significant differences in the gamma and beta activity. Robust gamma activity (55–65 Hz) in left BA6 (supplementary motor area (SMA)/pre-SMA) was stronger during LTM rehearsal than during WM maintenance. The gamma activity was sustained throughout the 3.4 s rehearsal period during which a fixation cross was presented. Importantly, the difference in gamma band activity correlated with memory performance over subjects. Further we observed a weak gamma power difference in left BA6 during the first half of the LTM rehearsal interval larger for successfully than unsuccessfully reproduced word triplets. In the beta band, we found a power decrease in left anterior regions during LTM rehearsal compared to WM maintenance. Also this suppression of beta power correlated with memory performance over subjects. Our findings show that an extended network of brain areas, characterized by oscillatory activity in different frequency bands, supports the encoding of word sequences in LTM. Gamma band activity in BA6 possibly reflects memory processes associated with language and timing, and suppression of beta activity at left frontal sensors is likely to reflect the release of inhibition directly associated with the engagement of language functions. PMID:21738641

  10. Evidence for human fronto-central gamma activity during long-term memory encoding of word sequences.

    Directory of Open Access Journals (Sweden)

    Esther Berendina Meeuwissen

    Full Text Available Although human gamma activity (30-80 Hz associated with visual processing is often reported, it is not clear to what extend gamma activity can be reliably detected non-invasively from frontal areas during complex cognitive tasks such as long term memory (LTM formation. We conducted a memory experiment composed of 35 blocks each having three parts: LTM encoding, working memory (WM maintenance and LTM retrieval. In the LTM encoding and WM maintenance parts, participants had to respectively encode or maintain the order of three sequentially presented words. During LTM retrieval subjects had to reproduce these sequences. Using magnetoencephalography (MEG we identified significant differences in the gamma and beta activity. Robust gamma activity (55-65 Hz in left BA6 (supplementary motor area (SMA/pre-SMA was stronger during LTM rehearsal than during WM maintenance. The gamma activity was sustained throughout the 3.4 s rehearsal period during which a fixation cross was presented. Importantly, the difference in gamma band activity correlated with memory performance over subjects. Further we observed a weak gamma power difference in left BA6 during the first half of the LTM rehearsal interval larger for successfully than unsuccessfully reproduced word triplets. In the beta band, we found a power decrease in left anterior regions during LTM rehearsal compared to WM maintenance. Also this suppression of beta power correlated with memory performance over subjects. Our findings show that an extended network of brain areas, characterized by oscillatory activity in different frequency bands, supports the encoding of word sequences in LTM. Gamma band activity in BA6 possibly reflects memory processes associated with language and timing, and suppression of beta activity at left frontal sensors is likely to reflect the release of inhibition directly associated with the engagement of language functions.

  11. Retrieval per se is not sufficient to trigger reconsolidation of human fear memory.

    Science.gov (United States)

    Sevenster, Dieuwke; Beckers, Tom; Kindt, Merel

    2012-03-01

    Ample evidence suggests that consolidated memories, upon their retrieval, enter a labile state, in which they might be susceptible to change. It has been proposed that memory labilization allows for the integration of relevant information in the established memory trace (memory updating). Memory labilization and reconsolidation do not necessarily occur when a memory is being reactivated, but only when there is something to be learned during memory retrieval (prediction error). Thus, updating of a fear memory trace should not occur under retrieval conditions in which the outcome is fully predictable (no prediction error). Here, we addressed this issue, using a human differential fear conditioning procedure, by eliminating the very possibility of reinforcement of the reminder cue. A previously established fear memory (picture-shock pairings) was reactivated with shock-electrodes attached (Propranolol group, n=18) or unattached (Propranolol No-Shock Expectation group, n=19). We additionally tested a placebo-control group with the shock-electrodes attached (Placebo group, n=18). Reconsolidation was not triggered when nothing could be learned during the reminder trial, as noradrenergic blockade did not affect expression of the fear memory 24h later in the Propranolol No-Shock Expectation group. Only when the outcome of the retrieval cue was not fully predictable, propranolol, contrary to placebo, reduced the startle fear response and prevented the return of fear (reinstatement) the following day. In line with previous studies, skin conductance response and shock expectancies were not affected by propranolol. Remarkably, a double dissociation emerged between the emotional (startle response) and more cognitive expression (expectancies, SCR) of the fear memory. Our findings have important implications for reconsolidation blockade as treatment strategy for emotional disorders. First, fear reducing procedures that target the emotional component of fear memory do not

  12. Default, Cognitive, and Affective Brain Networks in Human Tinnitus

    Science.gov (United States)

    2015-10-01

    AWARD NUMBER: W81XWH-13-1-0491 TITLE: Default, Cognitive, and Affective Brain Networks in Human Tinnitus PRINCIPAL INVESTIGATOR: Jennifer R...SUBTITLE 5a. CONTRACT NUMBER Default, Cognitive and Affective Brain Networks in Human Tinnitus 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Tinnitus is a major health problem among those currently and formerly in military

  13. Robust stability of interval bidirectional associative memory neural network with time delays.

    Science.gov (United States)

    Liao, Xiaofeng; Wong, Kwok-wo

    2004-04-01

    In this paper, the conventional bidirectional associative memory (BAM) neural network with signal transmission delay is intervalized in order to study the bounded effect of deviations in network parameters and external perturbations. The resultant model is referred to as a novel interval dynamic BAM (IDBAM) model. By combining a number of different Lyapunov functionals with the Razumikhin technique, some sufficient conditions for the existence of unique equilibrium and robust stability are derived. These results are fairly general and can be verified easily. To go further, we extend our investigation to the time-varying delay case. Some robust stability criteria for BAM with perturbations of time-varying delays are derived. Besides, our approach for the analysis allows us to consider several different types of activation functions, including piecewise linear sigmoids with bounded activations as well as the usual C1-smooth sigmoids. We believe that the results obtained have leading significance in the design and application of BAM neural networks.

  14. Robust stability for stochastic bidirectional associative memory neural networks with time delays

    Science.gov (United States)

    Shu, H. S.; Lv, Z. W.; Wei, G. L.

    2008-02-01

    In this paper, the asymptotic stability is considered for a class of uncertain stochastic bidirectional associative memory neural networks with time delays and parameter uncertainties. The delays are time-invariant and the uncertainties are norm-bounded that enter into all network parameters. The aim of this paper is to establish easily verifiable conditions under which the delayed neural network is robustly asymptotically stable in the mean square for all admissible parameter uncertainties. By employing a Lyapunov-Krasovskii functional and conducting the stochastic analysis, a linear matrix inequality matrix inequality (LMI) approach is developed to derive the stability criteria. The proposed criteria can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed criteria.

  15. A psychopharmacological aspects of human emotional memory for emotional material.

    OpenAIRE

    Brignell, C. M.

    2004-01-01

    It is often assumed that emotional events are remembered in great clarity and detail. This thesis begins with a review of the literature on memory enhancement by emotional material. This enhancement may involve mechanisms that are psychologically and neurobiologically distinct from the mechanisms usually employed in memory for neutral material, such as modulation of consolidation by emotional arousal via noradrenaline action in the amygdala. Theoretically, pharmacological manipulation of nora...

  16. Short Sleep Makes Declarative Memories Vulnerable to Stress in Humans.

    Science.gov (United States)

    Cedernaes, Jonathan; Rångtell, Frida H; Axelsson, Emil K; Yeganeh, Adine; Vogel, Heike; Broman, Jan-Erik; Dickson, Suzanne L; Schiöth, Helgi B; Benedict, Christian

    2015-12-01

    This study sought to investigate the role of nocturnal sleep duration for the retrieval of oversleep consolidated memories, both prior to and after being cognitively stressed for ∼30 minutes the next morning. Participants learned object locations (declarative memory task comprising 15 card pairs) and a finger tapping sequence (procedural memory task comprising 5 digits) in the evening. After learning, participants either had a sleep opportunity of 8 hours (between ∼23:00 and ∼07:00, full sleep condition) or they could sleep between ∼03:00 and ∼07:00 (short sleep condition). Retrieval of both memory tasks was tested in the morning after each sleep condition, both before (∼08:30) and after being stressed (∼09:50). Sleep laboratory. 15 healthy young men. The analyses demonstrated that oversleep memory changes did not differ between sleep conditions. However, in their short sleep condition, following stress hallmarked by increased subjective stress feelings, the men were unable to maintain their pre-stress performance on the declarative memory task, whereas their performance on the procedural memory task remained unchanged. While men felt comparably subjectively stressed by the stress intervention, overall no differences between pre- and post-stress recalls were observed following a full night of sleep. The findings suggest that 8-h sleep duration, within the range recommended by the US National Sleep Foundation, may not only help consolidate newly learned procedural and declarative memories, but also ensure full access to both during periods of subjective stress. © 2015 Associated Professional Sleep Societies, LLC.

  17. Functional MR imaging of working memory in the human brain

    International Nuclear Information System (INIS)

    Na, Dong Gyu; Ryu, Jae Wook; Byun, Hong Sik; Lee, Eun Jeong; Chung, Woo In; Cho, Jae Min; Han, Boo Kyung; Choi, Dae Seob

    2000-01-01

    In order to investigate the functional brain anatomy associated with verbal and visual working memory, functional magnetic resonance imaging was performed. In ten normal right handed subjects, functional MR images were obtained using a 1.5-T MR scanner and the EPI BOLD technique. An item recognition task was used for stimulation, and during the activation period of the verbal working memory task, consonant letters were used. During the activation period of the visual working memory task, symbols or diagrams were employed instead of letters. For the post-processing of images, the SPM program was used, with the threshold of significance set at p < .001. We assessed activated brain areas during the two stimulation tasks and compared the activated regions between the two tasks. The prefrontal cortex and secondary visual cortex were activated bilaterally by both verbal and visual working memory tasks, and the patterns of activated signals were similar in both tasks. The superior parietal cortex was also activated by both tasks, with lateralization to the left in the verbal task, and bilaterally without lateralization in the visual task. The inferior frontal cortex, inferior parietal cortex and temporal gyrus were activated exclusively by the verbal working memory task, predominantly in the left hemisphere. The prefrontal cortex is activated by two stimulation tasks, and this is related to the function of the central executive. The language areas activated by the verbal working memory task may be a function of the phonological loop. Bilateral prefrontal and superior parietal cortices activated by the visual working memory task may be related to the visual maintenance of objects, representing visual working memory

  18. Functional MR imaging of working memory in the human brain

    Energy Technology Data Exchange (ETDEWEB)

    Na, Dong Gyu; Ryu, Jae Wook; Byun, Hong Sik; Lee, Eun Jeong; Chung, Woo In; Cho, Jae Min; Han, Boo Kyung [Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of); Choi, Dae Seob [Dongguk University College of Medicine, Seoul (Korea, Republic of)

    2000-03-01

    In order to investigate the functional brain anatomy associated with verbal and visual working memory, functional magnetic resonance imaging was performed. In ten normal right handed subjects, functional MR images were obtained using a 1.5-T MR scanner and the EPI BOLD technique. An item recognition task was used for stimulation, and during the activation period of the verbal working memory task, consonant letters were used. During the activation period of the visual working memory task, symbols or diagrams were employed instead of letters. For the post-processing of images, the SPM program was used, with the threshold of significance set at p < .001. We assessed activated brain areas during the two stimulation tasks and compared the activated regions between the two tasks. The prefrontal cortex and secondary visual cortex were activated bilaterally by both verbal and visual working memory tasks, and the patterns of activated signals were similar in both tasks. The superior parietal cortex was also activated by both tasks, with lateralization to the left in the verbal task, and bilaterally without lateralization in the visual task. The inferior frontal cortex, inferior parietal cortex and temporal gyrus were activated exclusively by the verbal working memory task, predominantly in the left hemisphere. The prefrontal cortex is activated by two stimulation tasks, and this is related to the function of the central executive. The language areas activated by the verbal working memory task may be a function of the phonological loop. Bilateral prefrontal and superior parietal cortices activated by the visual working memory task may be related to the visual maintenance of objects, representing visual working memory.

  19. Short-Term Memory for Space and Time Flexibly Recruit Complementary Sensory-Biased Frontal Lobe Attention Networks.

    Science.gov (United States)

    Michalka, Samantha W; Kong, Lingqiang; Rosen, Maya L; Shinn-Cunningham, Barbara G; Somers, David C

    2015-08-19

    The frontal lobes control wide-ranging cognitive functions; however, functional subdivisions of human frontal cortex are only coarsely mapped. Here, functional magnetic resonance imaging reveals two distinct visual-biased attention regions in lateral frontal cortex, superior precentral sulcus (sPCS) and inferior precentral sulcus (iPCS), anatomically interdigitated with two auditory-biased attention regions, transverse gyrus intersecting precentral sulcus (tgPCS) and caudal inferior frontal sulcus (cIFS). Intrinsic functional connectivity analysis demonstrates that sPCS and iPCS fall within a broad visual-attention network, while tgPCS and cIFS fall within a broad auditory-attention network. Interestingly, we observe that spatial and temporal short-term memory (STM), respectively, recruit visual and auditory attention networks in the frontal lobe, independent of sensory modality. These findings not only demonstrate that both sensory modality and information domain influence frontal lobe functional organization, they also demonstrate that spatial processing co-localizes with visual processing and that temporal processing co-localizes with auditory processing in lateral frontal cortex. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. Short-term memory for space and time flexibly recruit complementary sensory-biased frontal lobe attention networks

    Science.gov (United States)

    Michalka, Samantha W.; Kong, Lingqiang; Rosen, Maya L.; Shinn-Cunningham, Barbara G.; Somers, David C.

    2015-01-01

    Summary The frontal lobes control wide-ranging cognitive functions; however, functional subdivisions of human frontal cortex are only coarsely mapped. Here, functional magnetic resonance imaging reveals two distinct visual-biased attention regions in lateral frontal cortex, superior precentral sulcus (sPCS) and inferior precentral sulcus (iPCS), anatomically interdigitated with two auditory-biased attention regions, transverse gyrus intersecting precentral sulcus (tgPCS) and caudal inferior frontal sulcus (cIFS). Intrinsic functional connectivity analysis demonstrates that sPCS and iPCS fall within a broad visual-attention network, while tgPCS and cIFS fall within a broad auditory-attention network. Interestingly, we observe that spatial and temporal short-term memory (STM), respectively, recruit visual and auditory attention networks in the frontal lobe, independent of sensory modality. These findings not only demonstrate that both sensory modality and information domain influence frontal lobe functional organization, they also demonstrate that spatial processing co-localizes with visual processing and that temporal processing co-localizes with auditory processing in lateral frontal cortex. PMID:26291168

  1. 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.

  2. 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.

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

    Science.gov (United States)

    Sato, Naoyuki

    2013-01-01

    Theta band power (4-8 Hz) 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.

  4. Power shifts track serial position and modulate encoding in human episodic memory.

    Science.gov (United States)

    Serruya, Mijail D; Sederberg, Per B; Kahana, Michael J

    2014-02-01

    The first events in a series exert a powerful influence on cognition and behavior in both humans and animals. This is known as the law of primacy. Here, we analyze the neural correlates of primacy in humans by analyzing electrocorticographic recordings in 84 neurosurgical patients as they studied and subsequently recalled lists of common words. We found that spectral power in the gamma frequency band (28-100 Hz) was elevated at the start of the list and gradually subsided, whereas lower frequency (2-8 Hz) delta and theta band power exhibited the opposite trend. This gradual shift in the power spectrum was found across a widespread network of brain regions. The degree to which the subsequent memory effect was modulated by list (serial) position was most pronounced in medial temporal lobe structures. These results suggest that globally increased gamma and decreased delta-theta spectral powers reflect a brain state that predisposes medial temporal lobe structures to enhance the encoding and maintenance of early list items.

  5. Long-distance quantum communication over noisy networks without long-time quantum memory

    Science.gov (United States)

    Mazurek, Paweł; Grudka, Andrzej; Horodecki, Michał; Horodecki, Paweł; Łodyga, Justyna; Pankowski, Łukasz; PrzysieŻna, Anna

    2014-12-01

    The problem of sharing entanglement over large distances is crucial for implementations of quantum cryptography. A possible scheme for long-distance entanglement sharing and quantum communication exploits networks whose nodes share Einstein-Podolsky-Rosen (EPR) pairs. In Perseguers et al. [Phys. Rev. A 78, 062324 (2008), 10.1103/PhysRevA.78.062324] the authors put forward an important isomorphism between storing quantum information in a dimension D and transmission of quantum information in a D +1 -dimensional network. We show that it is possible to obtain long-distance entanglement in a noisy two-dimensional (2D) network, even when taking into account that encoding and decoding of a state is exposed to an error. For 3D networks we propose a simple encoding and decoding scheme based solely on syndrome measurements on 2D Kitaev topological quantum memory. Our procedure constitutes an alternative scheme of state injection that can be used for universal quantum computation on 2D Kitaev code. It is shown that the encoding scheme is equivalent to teleporting the state, from a specific node into a whole two-dimensional network, through some virtual EPR pair existing within the rest of network qubits. We present an analytic lower bound on fidelity of the encoding and decoding procedure, using as our main tool a modified metric on space-time lattice, deviating from a taxicab metric at the first and the last time slices.

  6. Memory effects induce structure in social networks with activity-driven agents

    International Nuclear Information System (INIS)

    Medus, A D; Dorso, C O

    2014-01-01

    Activity-driven modelling has recently been proposed as an alternative growth mechanism for time varying networks,displaying power-law degree distribution in time-aggregated representation. This approach assumes memoryless agents developing random connections with total disregard of their previous contacts. Thus, such an assumption leads to time-aggregated random networks that do not reproduce the positive degree-degree correlation and high clustering coefficient widely observed in real social networks. In this paper, we aim to study the incidence of the agents' long-term memory on the emergence of new social ties. To this end, we propose a dynamical network model assuming heterogeneous activity for agents, together with a triadic-closure step as main connectivity mechanism. We show that this simple mechanism provides some of the fundamental topological features expected for real social networks in their time-aggregated picture. We derive analytical results and perform extensive numerical simulations in regimes with and without population growth. Finally, we present an illustrative comparison with two case studies, one comprising face-to-face encounters in a closed gathering, while the other one corresponding to social friendship ties from an online social network. (paper)

  7. Novelty-Sensitive Dopaminergic Neurons in the Human Substantia Nigra Predict Success of Declarative Memory Formation.

    Science.gov (United States)

    Kamiński, Jan; Mamelak, Adam N; Birch, Kurtis; Mosher, Clayton P; Tagliati, Michele; Rutishauser, Ueli

    2018-04-12

    The encoding of information into long-term declarative memory is facilitated by dopamine. This process depends on hippocampal novelty signals, but it remains unknown how midbrain dopaminergic neurons are modulated by declarative-memory-based information. We recorded individual substantia nigra (SN) neurons and cortical field potentials in human patients performing a recognition memory task. We found that 25% of SN neurons were modulated by stimulus novelty. Extracellular waveform shape and anatomical location indicated that these memory-selective neurons were putatively dopaminergic. The responses of memory-selective neurons appeared 527 ms after stimulus onset, changed after a single trial, and were indicative of recognition accuracy. SN neurons phase locked to frontal cortical theta-frequency oscillations, and the extent of this coordination predicted successful memory formation. These data reveal that dopaminergic neurons in the human SN are modulated by memory signals and demonstrate a progression of information flow in the hippocampal-basal ganglia-frontal cortex loop for memory encoding. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  8. Peripheral inflammation acutely impairs human spatial memory via actions on medial temporal lobe glucose metabolism.

    Science.gov (United States)

    Harrison, Neil A; Doeller, Christian F; Voon, Valerie; Burgess, Neil; Critchley, Hugo D

    2014-10-01

    Inflammation impairs cognitive performance and is implicated in the progression of neurodegenerative disorders. Rodent studies demonstrated key roles for inflammatory mediators in many processes critical to memory, including long-term potentiation, synaptic plasticity, and neurogenesis. They also demonstrated functional impairment of medial temporal lobe (MTL) structures by systemic inflammation. However, human data to support this position are limited. Sequential fluorodeoxyglucose positron emission tomography together with experimentally induced inflammation was used to investigate effects of a systemic inflammatory challenge on human MTL function. Fluorodeoxyglucose positron emission tomography scanning was performed in 20 healthy participants before and after typhoid vaccination and saline control injection. After each scanning session, participants performed a virtual reality spatial memory task analogous to the Morris water maze and a mirror-tracing procedural memory control task. Fluorodeoxyglucose positron emission tomography data demonstrated an acute reduction in human MTL glucose metabolism after inflammation. The inflammatory challenge also selectively compromised human spatial, but not procedural, memory; this effect that was independent of actions on motivation or psychomotor response. Effects of inflammation on parahippocampal and rhinal glucose metabolism directly mediated actions of inflammation on spatial memory. These data demonstrate acute sensitivity of human MTL to mild peripheral inflammation, giving rise to associated functional impairment in the form of reduced spatial memory performance. Our findings suggest a mechanism for the observed epidemiologic link between inflammation and risk of age-related cognitive decline and progression of neurodegenerative disorders including Alzheimer's disease. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  9. Reflections of the social environment in chimpanzee memory: applying rational analysis beyond humans.

    Science.gov (United States)

    Stevens, Jeffrey R; Marewski, Julian N; Schooler, Lael J; Gilby, Ian C

    2016-08-01

    In cognitive science, the rational analysis framework allows modelling of how physical and social environments impose information-processing demands onto cognitive systems. In humans, for example, past social contact among individuals predicts their future contact with linear and power functions. These features of the human environment constrain the optimal way to remember information and probably shape how memory records are retained and retrieved. We offer a primer on how biologists can apply rational analysis to study animal behaviour. Using chimpanzees ( Pan troglodytes ) as a case study, we modelled 19 years of observational data on their social contact patterns. Much like humans, the frequency of past encounters in chimpanzees linearly predicted future encounters, and the recency of past encounters predicted future encounters with a power function. Consistent with the rational analyses carried out for human memory, these findings suggest that chimpanzee memory performance should reflect those environmental regularities. In re-analysing existing chimpanzee memory data, we found that chimpanzee memory patterns mirrored their social contact patterns. Our findings hint that human and chimpanzee memory systems may have evolved to solve similar information-processing problems. Overall, rational analysis offers novel theoretical and methodological avenues for the comparative study of cognition.

  10. Reflections of the social environment in chimpanzee memory: applying rational analysis beyond humans

    Science.gov (United States)

    Marewski, Julian N.; Schooler, Lael J.; Gilby, Ian C.

    2016-01-01

    In cognitive science, the rational analysis framework allows modelling of how physical and social environments impose information-processing demands onto cognitive systems. In humans, for example, past social contact among individuals predicts their future contact with linear and power functions. These features of the human environment constrain the optimal way to remember information and probably shape how memory records are retained and retrieved. We offer a primer on how biologists can apply rational analysis to study animal behaviour. Using chimpanzees (Pan troglodytes) as a case study, we modelled 19 years of observational data on their social contact patterns. Much like humans, the frequency of past encounters in chimpanzees linearly predicted future encounters, and the recency of past encounters predicted future encounters with a power function. Consistent with the rational analyses carried out for human memory, these findings suggest that chimpanzee memory performance should reflect those environmental regularities. In re-analysing existing chimpanzee memory data, we found that chimpanzee memory patterns mirrored their social contact patterns. Our findings hint that human and chimpanzee memory systems may have evolved to solve similar information-processing problems. Overall, rational analysis offers novel theoretical and methodological avenues for the comparative study of cognition. PMID:27853606

  11. 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.

  12. Dopamine in the medial amygdala network mediates human bonding.

    Science.gov (United States)

    Atzil, Shir; Touroutoglou, Alexandra; Rudy, Tali; Salcedo, Stephanie; Feldman, Ruth; Hooker, Jacob M; Dickerson, Bradford C; Catana, Ciprian; Barrett, Lisa Feldman

    2017-02-28

    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.

  13. 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.

  14. Novel transcriptional networks regulated by CLOCK in human neurons.

    Science.gov (United States)

    Fontenot, Miles R; Berto, Stefano; Liu, Yuxiang; Werthmann, Gordon; Douglas, Connor; Usui, Noriyoshi; Gleason, Kelly; Tamminga, Carol A; Takahashi, Joseph S; Konopka, Genevieve

    2017-11-01

    The molecular mechanisms underlying human brain evolution are not fully understood; however, previous work suggested that expression of the transcription factor CLOCK in the human cortex might be relevant to human cognition and disease. In this study, we investigated this novel transcriptional role for CLOCK in human neurons by performing chromatin immunoprecipitation sequencing for endogenous CLOCK in adult neocortices and RNA sequencing following CLOCK knockdown in differentiated human neurons in vitro. These data suggested that CLOCK regulates the expression of genes involved in neuronal migration, and a functional assay showed that CLOCK knockdown increased neuronal migratory distance. Furthermore, dysregulation of CLOCK disrupts coexpressed networks of genes implicated in neuropsychiatric disorders, and the expression of these networks is driven by hub genes with human-specific patterns of expression. These data support a role for CLOCK-regulated transcriptional cascades involved in human brain evolution and function. © 2017 Fontenot et al.; Published by Cold Spring Harbor Laboratory Press.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Human recognition in a video network

    Science.gov (United States)

    Bhanu, Bir

    2009-10-01

    Video networks is an emerging interdisciplinary field with significant and exciting scientific and technological challenges. It has great promise in solving many real-world problems and enabling a broad range of applications, including smart homes, video surveillance, environment and traffic monitoring, elderly care, intelligent environments, and entertainment in public and private spaces. This paper provides an overview of the design of a wireless video network as an experimental environment, camera selection, hand-off and control, anomaly detection. It addresses challenging questions for individual identification using gait and face at a distance and present new techniques and their comparison for robust identification.

  2. 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. Copyright © 2013 Elsevier Ltd. All rights reserved.

  3. 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

  4. Influence of reward motivation on human declarative memory.

    Science.gov (United States)

    Miendlarzewska, Ewa A; Bavelier, Daphne; Schwartz, Sophie

    2016-02-01

    Motivational relevance can prioritize information for memory encoding and consolidation based on reward value. In this review, we pinpoint the possible psychological and neural mechanisms by which reward promotes learning, from guiding attention to enhancing memory consolidation. We then discuss how reward value can spill-over from one conditioned stimulus to a non-conditioned stimulus. Such generalization can occur across perceptually similar items or through more complex relations, such as associative or logical inferences. Existing evidence suggests that the neurotransmitter dopamine boosts the formation of declarative memory for rewarded information and may also control the generalization of reward values. In particular, temporally-correlated activity in the hippocampus and in regions of the dopaminergic circuit may mediate value-based decisions and facilitate cross-item integration. Given the importance of generalization in learning, our review points to the need to study not only how reward affects later memory but how learned reward values may generalize to related representations and ultimately alter memory structure. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. What do you mean "drunk"? Convergent validation of multiple methods of mapping alcohol expectancy memory networks.

    Science.gov (United States)

    Reich, Richard R; Ariel, Idan; Darkes, Jack; Goldman, Mark S

    2012-09-01

    The configuration and activation of memory networks have been theorized as mechanisms that underlie the often observed link between alcohol expectancies and drinking. A key component of this network is the expectancy "drunk." The memory network configuration of "drunk" was mapped by using cluster analysis of data gathered from the paired-similarities task (PST) and the Alcohol Expectancy Multi-Axial Assessment (AEMAX). A third task, the free associates task (FA), assessed participants' strongest alcohol expectancy associates and was used as a validity check for the cluster analyses. Six hundred forty-seven 18-19-year-olds completed these measures and a measure of alcohol consumption at baseline assessment for a 5-year longitudinal study. For both the PST and AEMAX, "drunk" clustered with mainly negative and sedating effects (e.g., "sick," "dizzy," "sleepy") in lighter drinkers and with more positive and arousing effects (e.g., "happy," "horny," "outgoing") in heavier drinkers, showing that the cognitive organization of expectancies reflected drinker type (and might influence the choice to drink). Consistent with the cluster analyses, in participants who gave "drunk" as an FA response, heavier drinkers rated the word as more positive and arousing than lighter drinkers. Additionally, gender did not account for the observed drinker-type differences. These results support the notion that for some emerging adults, drinking may be linked to what they mean by the word "drunk." PsycINFO Database Record (c) 2012 APA, all rights reserved.

  6. 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.

  7. Working Memory Modulation of Frontoparietal Network Connectivity in First-Episode Schizophrenia

    DEFF Research Database (Denmark)

    Nielsen, Jesper Duemose; Madsen, Kristoffer Hougaard; Wang, Zheng

    2017-01-01

    Working memory (WM) impairment is regarded as a core aspect of schizophrenia. However, the neural mechanisms behind this cognitive deficit remain unclear. The connectivity of a frontoparietal network is known to be important for subserving WM. Using functional magnetic resonance imaging, the curr......Working memory (WM) impairment is regarded as a core aspect of schizophrenia. However, the neural mechanisms behind this cognitive deficit remain unclear. The connectivity of a frontoparietal network is known to be important for subserving WM. Using functional magnetic resonance imaging......, the current study investigated whether WM-dependent modulation of effective connectivity in this network is affected in a group of first-episode schizophrenia (FES) patients compared with similarly performing healthy participants during a verbal n-back task. Dynamic causal modeling (DCM) of the coupling...... between regions (left inferior frontal gyrus (IFG), left inferior parietal lobe (IPL), and primary visual area) identified in a psychophysiological interaction (PPI) analysis was performed to characterize effective connectivity during the n-back task. The PPI analysis revealed that the connectivity...

  8. Organizing smart networks and humans into augmented teams

    NARCIS (Netherlands)

    Neef, R.M.; Rijn, M. van; Keus, D.; Marck, J.W.

    2009-01-01

    This paper discusses the challenge of turning networks of sensors, computers, agents and humans into hybrid teams that are capable, effective and adaptive. We propose a functional model and illustrate how such a model can be put into practice, and augment the capabilities of the human organization.

  9. 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.......03, 0.49; p=0.03; N=22) whereas long-term had small (SMD=0.15; 95% CI=0.02, 0.27; p=0.02; N=37) effects on short-term memory. In contrast, acute exercise showed moderate to large (SMD=0.52; 95% CI=0.28, 0.75; p......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...

  10. Robust Stability Analysis of Neutral-Type Hybrid Bidirectional Associative Memory Neural Networks with Time-Varying Delays

    OpenAIRE

    Wei Feng; Simon X. Yang; Haixia Wu

    2014-01-01

    The global asymptotic robust stability of equilibrium is considered for neutral-type hybrid bidirectional associative memory neural networks with time-varying delays and parameters uncertainties. The results we obtained in this paper are delay-derivative-dependent and establish various relationships between the network parameters only. Therefore, the results of this paper are applicable to a larger class of neural networks and can be easily verified when compared with the previously reported ...

  11. A New Local Bipolar Autoassociative Memory Based on External Inputs of Discrete Recurrent Neural Networks With Time Delay.

    Science.gov (United States)

    Zhou, Caigen; Zeng, Xiaoqin; Luo, Chaomin; Zhang, Huaguang

    In this paper, local bipolar auto-associative memories are presented based on discrete recurrent neural networks with a class of gain type activation function. The weight parameters of neural networks are acquired by a set of inequalities without the learning procedure. The global exponential stability criteria are established to ensure the accuracy of the restored patterns by considering time delays and external inputs. The proposed methodology is capable of effectively overcoming spurious memory patterns and achieving memory capacity. The effectiveness, robustness, and fault-tolerant capability are validated by simulated experiments.In this paper, local bipolar auto-associative memories are presented based on discrete recurrent neural networks with a class of gain type activation function. The weight parameters of neural networks are acquired by a set of inequalities without the learning procedure. The global exponential stability criteria are established to ensure the accuracy of the restored patterns by considering time delays and external inputs. The proposed methodology is capable of effectively overcoming spurious memory patterns and achieving memory capacity. The effectiveness, robustness, and fault-tolerant capability are validated by simulated experiments.

  12. The 5-HT(4) receptor levels in hippocampus correlates inversely with memory test performance in humans

    DEFF Research Database (Denmark)

    Haahr, Mette Ewers; Fisher, Patrick; Holst, Klaus Kähler

    2013-01-01

    The cerebral serotonin (5-HT) system is involved in cognitive functions such as memory and learning and animal studies have repeatedly shown that stimulation of the 5-HT type 4 receptor (5-HT(4) R) facilitates memory and learning and further that the 5-HT(4) R modulates cellular memory processes...... in hippocampus. However, any associations between memory functions and the expression of the 5-HT(4) R in the human hippocampus have not been investigated. Using positron emission tomography with the tracer [(11) C]SB207145 and Reys Auditory Verbal Learning Test we aimed to examine the individual variation...... of the 5-HT4R binding in hippocampus in relation to memory acquisition and consolidation in healthy young volunteers. We found significant, negative associations between the immediate recall scores and left and right hippocampal BP(ND) , (p = 0.009 and p = 0.010 respectively) and between the right...

  13. 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.

  14. 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.

  15. Static human face recognition using artificial neural networks

    International Nuclear Information System (INIS)

    Qamar, R.; Shah, S.H.; Javed-ur-Rehman

    2003-01-01

    This paper presents a novel method of human face recognition using digital computers. A digital PC camera is used to take the BMP images of the human faces. An artificial neural network using Back Propagation Algorithm is developed as a recognition engine. The BMP images of the faces serve as the input patterns for this engine. A software 'Face Recognition' has been developed to recognize the human faces for which it is trained. Once the neural network is trained for patterns of the faces, the software is able to detect and recognize them with success rate of about 97%. (author)

  16. A regulatory network for human adenocarcinoma

    African Journals Online (AJOL)

    AJL

    2012-03-13

    Mar 13, 2012 ... Human adenocarcinoma (AC) is the most frequently diagnosed human lung cancer and its absolute incidence is increasing ... Lung carcinomas are usually classified as small-cell lung ..... such as embryonic development, reproduction, and. TYMS .... homeostatic processes including stem cell maintenance,.

  17. 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

  18. 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.

  19. Memory

    OpenAIRE

    Wager, Nadia

    2017-01-01

    This chapter will explore a response to traumatic victimisation which has divided the opinions of psychologists at an exponential rate. We will be examining amnesia for memories of childhood sexual abuse and the potential to recover these memories in adulthood. Whilst this phenomenon is generally accepted in clinical circles, it is seen as highly contentious amongst research psychologists, particularly experimental cognitive psychologists. The chapter will begin with a real case study of a wo...

  20. 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.

  1. Human Parahippocampal Cortex Supports Spatial Binding in Visual Working Memory.

    Science.gov (United States)

    Dundon, Neil Michael; Katshu, Mohammad Zia Ul Haq; Harry, Bronson; Roberts, Daniel; Leek, E Charles; Downing, Paul; Sapir, Ayelet; Roberts, Craig; d'Avossa, Giovanni

    2017-09-15

    Studies investigating the functional organization of the medial temporal lobe (MTL) suggest that parahippocampal cortex (PHC) generates representations of spatial and contextual information used by the hippocampus in the formation of episodic memories. However, evidence from animal studies also implicates PHC in spatial binding of visual information held in short term, working memory. Here we examined a 46-year-old man (P.J.), after he had recovered from bilateral medial occipitotemporal cortex strokes resulting in ischemic lesions of PHC and hippocampal atrophy, and a group of age-matched healthy controls. When recalling the color of 1 of 2 objects, P.J. misidentified the target when cued by its location, but not shape. When recalling the position of 1 of 3 objects, he frequently misidentified the target, which was cued by its color. Increasing the duration of the memory delay had no impact on the proportion of binding errors, but did significantly worsen recall precision in both P.J. and controls. We conclude that PHC may play a crucial role in spatial binding during encoding of visual information in working memory. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  2. Event-related brain potential correlates of human auditory sensory memory-trace formation.

    Science.gov (United States)

    Haenschel, Corinna; Vernon, David J; Dwivedi, Prabuddh; Gruzelier, John H; Baldeweg, Torsten

    2005-11-09

    The event-related potential (ERP) component mismatch negativity (MMN) is a neural marker of human echoic memory. MMN is elicited by deviant sounds embedded in a stream of frequent standards, reflecting the deviation from an inferred memory trace of the standard stimulus. The strength of this memory trace is thought to be proportional to the number of repetitions of the standard tone, visible as the progressive enhancement of MMN with number of repetitions (MMN memory-trace effect). However, no direct ERP correlates of the formation of echoic memory traces are currently known. This study set out to investigate changes in ERPs to different numbers of repetitions of standards, delivered in a roving-stimulus paradigm in which the frequency of the standard stimulus changed randomly between stimulus trains. Normal healthy volunteers (n = 40) were engaged in two experimental conditions: during passive listening and while actively discriminating changes in tone frequency. As predicted, MMN increased with increasing number of standards. However, this MMN memory-trace effect was caused mainly by enhancement with stimulus repetition of a slow positive wave from 50 to 250 ms poststimulus in the standard ERP, which is termed here "repetition positivity" (RP). This RP was recorded from frontocentral electrodes when participants were passively listening to or actively discriminating changes in tone frequency. RP may represent a human ERP correlate of rapid and stimulus-specific adaptation, a candidate neuronal mechanism underlying sensory memory formation in the auditory cortex.

  3. Epistasis between dopamine regulating genes identifies a nonlinear response of the human hippocampus during memory tasks.

    Science.gov (United States)

    Bertolino, Alessandro; Di Giorgio, Annabella; Blasi, Giuseppe; Sambataro, Fabio; Caforio, Grazia; Sinibaldi, Lorenzo; Latorre, Valeria; Rampino, Antonio; Taurisano, Paolo; Fazio, Leonardo; Romano, Raffaella; Douzgou, Sofia; Popolizio, Teresa; Kolachana, Bhaskar; Nardini, Marcello; Weinberger, Daniel R; Dallapiccola, Bruno

    2008-08-01

    Dopamine modulation of neuronal activity in prefrontal cortex maps to an inverted U-curve. Dopamine is also an important factor in regulation of hippocampal mediated memory processing. Here, we investigated the effect of genetic variation of dopamine inactivation via catechol-O-methyltransferase (COMT) and the dopamine transporter (DAT) on hippocampal activity in healthy humans during different memory conditions. Using blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) in 82 subjects matched for a series of demographic and genetic variables, we studied the effect of the COMT valine (Val)(158)methionine (Met) and the DAT 3' variable number tandem repeat (VNTR) polymorphisms on function of the hippocampus during encoding of recognition memory and during working memory. Our results consistently demonstrated a double dissociation so that DAT 9-repeat carrier alleles modulated activity in the hippocampus in the exact opposite direction of DAT 10/10-repeat alleles based on COMT Val(158)Met genotype during different memory conditions. Similar results were evident in ventrolateral and dorsolateral prefrontal cortex. These findings suggest that genetically determined dopamine signaling during memory processing maps to a nonlinear relationship also in the hippocampus. Our data also demonstrate in human brain epistasis of two genes implicated in dopamine signaling on brain activity during different memory conditions.

  4. Behavioral lifetime of human auditory sensory memory predicted by physiological measures.

    Science.gov (United States)

    Lu, Z L; Williamson, S J; Kaufman, L

    1992-12-04

    Noninvasive magnetoencephalography makes it possible to identify the cortical area in the human brain whose activity reflects the decay of passive sensory storage of information about auditory stimuli (echoic memory). The lifetime for decay of the neuronal activation trace in primary auditory cortex was found to predict the psychophysically determined duration of memory for the loudness of a tone. Although memory for the loudness of a specific tone is lost, the remembered loudness decays toward the global mean of all of the loudnesses to which a subject is exposed in a series of trials.

  5. Strong memory in time series of human magnetoencephalograms can identify photosensitive epilepsy

    International Nuclear Information System (INIS)

    Yulmetyev, R. M.; Yulmetyeva, D. G.; Haenggi, P.; Shimojo, S.; Bhattacharya, J.

    2007-01-01

    To discuss the salient role of statistical memory effects in human brain functioning, we have analyzed a set of stochastic memory quantifiers that reflects the dynamical characteristics of neuromagnetic responses of magnetoencephalographic signals to a flickering stimulus of different color combinations from a group of control subjects, and compared them with those for a patient with photosensitive epilepsy. We have discovered that the emergence of strong memory and the accompanying transition to a regular and robust regime of chaotic behavior of signals in separate areas for a patient most likely identifies the regions where the protective mechanism against the occurrence of photosensitive epilepsy is located

  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...... 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...

  7. 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.

  8. Comment on "Dynamic shifts of limited working memory resources in human vision".

    Science.gov (United States)

    Cowan, Nelson; Rouder, Jeffrey N

    2009-02-13

    Bays and Husain (Reports, 8 August 2008, p. 851) reported that human working memory, the limited information currently in mind, reflects resources distributed across all items in an array. In an alternative interpretation, memory is limited to several well-represented items. We argue that this item-limit model fits the extant data better than the distributed-resources model and is more interpretable theoretically.

  9. Comment on “Dynamic Shifts of Limited Working Memory Resources in Human Vision”

    Science.gov (United States)

    Cowan, Nelson; Rouder, Jeffrey N.

    2009-01-01

    Bays and Husain (Reports, 8 August 2008, p. 851) reported that human working memory, the limited information currently in mind, reflects resources distributed across all items in an array. In an alternative interpretation, memory is limited to several well-represented items. We argue that this item-limit model fits the extant data better than the distributed-resources model and is more interpretable theoretically. PMID:19213899

  10. Adaptive online inverse control of a shape memory alloy wire actuator using a dynamic neural network

    International Nuclear Information System (INIS)

    Mai, Huanhuan; Liao, Xiaofeng; Song, Gangbing

    2013-01-01

    Shape memory alloy (SMA) actuators exhibit severe hysteresis, a nonlinear behavior, which complicates control strategies and limits their applications. This paper presents a new approach to controlling an SMA actuator through an adaptive inverse model based controller that consists of a dynamic neural network (DNN) identifier, a copy dynamic neural network (CDNN) feedforward term and a proportional (P) feedback action. Unlike fixed hysteresis models used in most inverse controllers, the proposed one uses a DNN to identify online the relationship between the applied voltage to the actuator and the displacement (the inverse model). Even without a priori knowledge of the SMA hysteresis and without pre-training, the proposed controller can precisely control the SMA wire actuator in various tracking tasks by identifying online the inverse model of the SMA actuator. Experiments were conducted, and experimental results demonstrated real-time modeling capabilities of DNN and the performance of the adaptive inverse controller. (paper)

  11. Adaptive online inverse control of a shape memory alloy wire actuator using a dynamic neural network

    Science.gov (United States)

    Mai, Huanhuan; Song, Gangbing; Liao, Xiaofeng

    2013-01-01

    Shape memory alloy (SMA) actuators exhibit severe hysteresis, a nonlinear behavior, which complicates control strategies and limits their applications. This paper presents a new approach to controlling an SMA actuator through an adaptive inverse model based controller that consists of a dynamic neural network (DNN) identifier, a copy dynamic neural network (CDNN) feedforward term and a proportional (P) feedback action. Unlike fixed hysteresis models used in most inverse controllers, the proposed one uses a DNN to identify online the relationship between the applied voltage to the actuator and the displacement (the inverse model). Even without a priori knowledge of the SMA hysteresis and without pre-training, the proposed controller can precisely control the SMA wire actuator in various tracking tasks by identifying online the inverse model of the SMA actuator. Experiments were conducted, and experimental results demonstrated real-time modeling capabilities of DNN and the performance of the adaptive inverse controller.

  12. Robust state estimation for uncertain fuzzy bidirectional associative memory networks with time-varying delays

    Science.gov (United States)

    Vadivel, P.; Sakthivel, R.; Mathiyalagan, K.; Arunkumar, A.

    2013-09-01

    This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov-Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results.

  13. Robust state estimation for uncertain fuzzy bidirectional associative memory networks with time-varying delays

    International Nuclear Information System (INIS)

    Vadivel, P; Sakthivel, R; Mathiyalagan, K; Arunkumar, A

    2013-01-01

    This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov–Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results. (paper)

  14. 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.

  15. 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

  16. Achilles' ear? Inferior human short-term and recognition memory in the auditory modality.

    Science.gov (United States)

    Bigelow, James; Poremba, Amy

    2014-01-01

    Studies of the memory capabilities of nonhuman primates have consistently revealed a relative weakness for auditory compared to visual or tactile stimuli: extensive training is required to learn auditory memory tasks, and subjects are only capable of retaining acoustic information for a brief period of time. Whether a parallel deficit exists in human auditory memory remains an outstanding question. In the current study, a short-term memory paradigm was used to test human subjects' retention of simple auditory, visual, and tactile stimuli that were carefully equated in terms of discriminability, stimulus exposure time, and temporal dynamics. Mean accuracy did not differ significantly among sensory modalities at very short retention intervals (1-4 s). However, at longer retention intervals (8-32 s), accuracy for auditory stimuli fell substantially below that observed for visual and tactile stimuli. In the interest of extending the ecological validity of these findings, a second experiment tested recognition memory for complex, naturalistic stimuli that would likely be encountered in everyday life. Subjects were able to identify all stimuli when retention was not required, however, recognition accuracy following a delay period was again inferior for auditory compared to visual and tactile stimuli. Thus, the outcomes of both experiments provide a human parallel to the pattern of results observed in nonhuman primates. The results are interpreted in light of neuropsychological data from nonhuman primates, which suggest a difference in the degree to which auditory, visual, and tactile memory are mediated by the perirhinal and entorhinal cortices.

  17. Achilles' ear? Inferior human short-term and recognition memory in the auditory modality.

    Directory of Open Access Journals (Sweden)

    James Bigelow

    Full Text Available Studies of the memory capabilities of nonhuman primates have consistently revealed a relative weakness for auditory compared to visual or tactile stimuli: extensive training is required to learn auditory memory tasks, and subjects are only capable of retaining acoustic information for a brief period of time. Whether a parallel deficit exists in human auditory memory remains an outstanding question. In the current study, a short-term memory paradigm was used to test human subjects' retention of simple auditory, visual, and tactile stimuli that were carefully equated in terms of discriminability, stimulus exposure time, and temporal dynamics. Mean accuracy did not differ significantly among sensory modalities at very short retention intervals (1-4 s. However, at longer retention intervals (8-32 s, accuracy for auditory stimuli fell substantially below that observed for visual and tactile stimuli. In the interest of extending the ecological validity of these findings, a second experiment tested recognition memory for complex, naturalistic stimuli that would likely be encountered in everyday life. Subjects were able to identify all stimuli when retention was not required, however, recognition accuracy following a delay period was again inferior for auditory compared to visual and tactile stimuli. Thus, the outcomes of both experiments provide a human parallel to the pattern of results observed in nonhuman primates. The results are interpreted in light of neuropsychological data from nonhuman primates, which suggest a difference in the degree to which auditory, visual, and tactile memory are mediated by the perirhinal and entorhinal cortices.

  18. Theta Phase Synchronization Is the Glue that Binds Human Associative Memory.

    Science.gov (United States)

    Clouter, Andrew; Shapiro, Kimron L; Hanslmayr, Simon

    2017-10-23

    Episodic memories are information-rich, often multisensory events that rely on binding different elements [1]. The elements that will constitute a memory episode are processed in specialized but distinct brain modules. The binding of these elements is most likely mediated by fast-acting long-term potentiation (LTP), which relies on the precise timing of neural activity [2]. Theta oscillations in the hippocampus orchestrate such timing as demonstrated by animal studies in vitro [3, 4] and in vivo [5, 6], suggesting a causal role of theta activity for the formation of complex memory episodes, but direct evidence from humans is missing. Here, we show that human episodic memory formation depends on phase synchrony between different sensory cortices at the theta frequency. By modulating the luminance of visual stimuli and the amplitude of auditory stimuli, we directly manipulated the degree of phase synchrony between visual and auditory cortices. Memory for sound-movie associations was significantly better when the stimuli were presented in phase compared to out of phase. This effect was specific to theta (4 Hz) and did not occur in slower (1.7 Hz) or faster (10.5 Hz) frequencies. These findings provide the first direct evidence that episodic memory formation in humans relies on a theta-specific synchronization mechanism. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Achilles’ Ear? Inferior Human Short-Term and Recognition Memory in the Auditory Modality

    Science.gov (United States)

    Bigelow, James; Poremba, Amy

    2014-01-01

    Studies of the memory capabilities of nonhuman primates have consistently revealed a relative weakness for auditory compared to visual or tactile stimuli: extensive training is required to learn auditory memory tasks, and subjects are only capable of retaining acoustic information for a brief period of time. Whether a parallel deficit exists in human auditory memory remains an outstanding question. In the current study, a short-term memory paradigm was used to test human subjects’ retention of simple auditory, visual, and tactile stimuli that were carefully equated in terms of discriminability, stimulus exposure time, and temporal dynamics. Mean accuracy did not differ significantly among sensory modalities at very short retention intervals (1–4 s). However, at longer retention intervals (8–32 s), accuracy for auditory stimuli fell substantially below that observed for visual and tactile stimuli. In the interest of extending the ecological validity of these findings, a second experiment tested recognition memory for complex, naturalistic stimuli that would likely be encountered in everyday life. Subjects were able to identify all stimuli when retention was not required, however, recognition accuracy following a delay period was again inferior for auditory compared to visual and tactile stimuli. Thus, the outcomes of both experiments provide a human parallel to the pattern of results observed in nonhuman primates. The results are interpreted in light of neuropsychological data from nonhuman primates, which suggest a difference in the degree to which auditory, visual, and tactile memory are mediated by the perirhinal and entorhinal cortices. PMID:24587119

  20. Modulation of steady state functional connectivity in the default mode and working memory networks by cognitive load.

    Science.gov (United States)

    Newton, Allen T; Morgan, Victoria L; Rogers, Baxter P; Gore, John C

    2011-10-01

    Interregional correlations between blood oxygen level dependent (BOLD) magnetic resonance imaging (fMRI) signals in the resting state have been interpreted as measures of connectivity across the brain. Here we investigate whether such connectivity in the working memory and default mode networks is modulated by changes in cognitive load. Functional connectivity was measured in a steady-state verbal identity N-back task for three different conditions (N = 1, 2, and 3) as well as in the resting state. We found that as cognitive load increases, the functional connectivity within both the working memory the default mode network increases. To test whether functional connectivity between the working memory and the default mode networks changed, we constructed maps of functional connectivity to the working memory network as a whole and found that increasingly negative correlations emerged in a dorsal region of the posterior cingulate cortex. These results provide further evidence that low frequency fluctuations in BOLD signals reflect variations in neural activity and suggests interaction between the default mode network and other cognitive networks. Copyright © 2010 Wiley-Liss, Inc.

  1. Short-term memory of motor network performance via activity-dependent potentiation of Na+/K+ pump function.

    Science.gov (United States)

    Zhang, Hong-Yan; Sillar, Keith T

    2012-03-20

    Brain networks memorize previous performance to adjust their output in light of past experience. These activity-dependent modifications generally result from changes in synaptic strengths or ionic conductances, and ion pumps have only rarely been demonstrated to play a dynamic role. Locomotor behavior is produced by central pattern generator (CPG) networks and modified by sensory and descending signals to allow for changes in movement frequency, intensity, and duration, but whether or how the CPG networks recall recent activity is largely unknown. In Xenopus frog tadpoles, swim bout duration correlates linearly with interswim interval, suggesting that the locomotor network retains a short-term memory of previous output. We discovered an ultraslow, minute-long afterhyperpolarization (usAHP) in network neurons following locomotor episodes. The usAHP is mediated by an activity- and sodium spike-dependent enhancement of electrogenic Na(+)/K(+) pump function. By integrating spike frequency over time and linking the membrane potential of spinal neurons to network performance, the usAHP plays a dynamic role in short-term motor memory. Because Na(+)/K(+) pumps are ubiquitously expressed in neurons of all animals and because sodium spikes inevitably accompany network activity, the usAHP may represent a phylogenetically conserved but largely overlooked mechanism for short-term memory of neural network function. Copyright © 2012 Elsevier Ltd. All rights reserved.

  2. Amygdala Volume and Social Network Size in Humans

    OpenAIRE

    Bickart, Kevin C.; Wright, Christopher I.; Dautoff, Rebecca J.; Dickerson, Bradford C.; Barrett, Lisa Feldman

    2010-01-01

    We demonstrated that amygdala volume (corrected for total intracranial volume) positively correlated with the size and complexity of social networks in adult humans ranging in age from 19 to 83 years. This relationship was specific to the amygdala as compared to other subcortical structures. An exploratory analysis of the entire cortical mantle also revealed an association between social network variables and cortical thickness in three cortical areas, two of which share dense connectivity wi...

  3. Distinctiveness enhances long-term event memory in non-human primates, irrespective of reinforcement.

    Science.gov (United States)

    Lewis, Amy; Call, Josep; Berntsen, Dorthe

    2017-08-01

    Non-human primates are capable of recalling events that occurred as long as 3 years ago, and are able to distinguish between similar events; akin to human memory. In humans, distinctiveness enhances memory for events, however, it is unknown whether the same occurs in non-human primates. As such, we tested three great ape species on their ability to remember an event that varied in distinctiveness. Across three experiments, apes witnessed a baiting event in which one of three identical containers was baited with food. After a delay of 2 weeks, we tested their memory for the location of the baited container. Apes failed to recall the baited container when the event was undistinctive (Experiment 1), but were successful when it was distinctive (Experiment 2), although performance was equally good in a less-distinctive condition. A third experiment (Experiment 3) confirmed that distinctiveness, independent of reinforcement, was a consistent predictor of performance. These findings suggest that distinctiveness may enhance memory for events in non-human primates in the same way as in humans, and provides further evidence of basic similarities between the ways apes and humans remember past events. © 2017 Wiley Periodicals, Inc.

  4. Brain imaging and memory systems in humans: the contribution of PET methods

    International Nuclear Information System (INIS)

    Perani, D.

    1998-01-01

    The development of neuroimaging methods such as PET, has provided a new impulse to the study of the neural basis of cognitive functions, and has extended the field of inquiry from the analysis of the consequences of brain lesions to the functional investigations of brain activity, either in patients with selective neuropsychological deficits or in normal subjects engaged in cognitive tasks. Specific patterns of hypo-metabolism in neurological patients are associated with different profiles of memory deficits.[ 18 F]FDG PET studies have confirmed the association of episodic memory with the structures of Papez's circuit and have shown correlations between short-term and semantic memory and the language areas. The identification of anatomical-functional networks involved in specific components of memory function in normal subjects is the aim of several PET activation studies. The results are in agreement with 'neural network' models of the neural basis of memory, as complex functions subserved by multiple interconnected cortical and subcortical structures. (author)

  5. Social Rewards and Social Networks in the Human Brain.

    Science.gov (United States)

    Fareri, Dominic S; Delgado, Mauricio R

    2014-08-01

    The rapid development of social media and social networking sites in human society within the past decade has brought about an increased focus on the value of social relationships and being connected with others. Research suggests that we pursue socially valued or rewarding outcomes-approval, acceptance, reciprocity-as a means toward learning about others and fulfilling social needs of forming meaningful relationships. Focusing largely on recent advances in the human neuroimaging literature, we review findings highlighting the neural circuitry and processes that underlie pursuit of valued rewarding outcomes across non-social and social domains. We additionally discuss emerging human neuroimaging evidence supporting the idea that social rewards provide a gateway to establishing relationships and forming social networks. Characterizing the link between social network, brain, and behavior can potentially identify contributing factors to maladaptive influences on decision making within social situations. © The Author(s) 2014.

  6. Where vision meets memory: prefrontal-posterior networks for visual object constancy during categorization and recognition.

    Science.gov (United States)

    Schendan, Haline E; Stern, Chantal E

    2008-07-01

    Objects seen from unusual relative to more canonical views require more time to categorize and recognize, and, according to object model verification theories, additionally recruit prefrontal processes for cognitive control that interact with parietal processes for mental rotation. To test this using functional magnetic resonance imaging, people categorized and recognized known objects from unusual and canonical views. Canonical views activated some components of a default network more on categorization than recognition. Activation to unusual views showed that both ventral and dorsal visual pathways, and prefrontal cortex, have key roles in visual object constancy. Unusual views activated object-sensitive and mental rotation (and not saccade) regions in ventrocaudal intraparietal, transverse occipital, and inferotemporal sulci, and ventral premotor cortex for verification processes of model testing on any task. A collateral-lingual sulci "place" area activated for mental rotation, working memory, and unusual views on correct recognition and categorization trials to accomplish detailed spatial matching. Ventrolateral prefrontal cortex and object-sensitive lateral occipital sulcus activated for mental rotation and unusual views on categorization more than recognition, supporting verification processes of model prediction. This visual knowledge framework integrates vision and memory theories to explain how distinct prefrontal-posterior networks enable meaningful interactions with objects in diverse situations.

  7. Temporal span of human echoic memory and mismatch negativity: revisited.

    Science.gov (United States)

    Jääskeläinen, I P; Hautamäki, M; Näätänen, R; Ilmoniemi, R J

    1999-04-26

    The stimulus onset asynchrony (SOA)-related decrease in mismatch negativity (MMN) amplitude has been used to infer a putative auditory sensory memory duration of 4-10 s. However, both increased standard-to-standard (SSA) and standard-to-deviant (SDA) gaps could contribute to the effect. Fourteen subjects were presented with standard and deviant tones with short (0.35 s) and long (3.5 s) SOAs. In addition, the SSA and SDA were separately manipulated to test the relative contributions of slower rate of standard tone presentation and longer SDA gap to the SOA-related decrease in MMN amplitude. The MMN amplitude decreased with long SOA by 61%. Increases in SSA and SDA resulted in intermediate 47% and 31% decreases, these manipulations explaining 67% of the long SOA effect (pechoic memory length cannot be directly inferred from an MMN-SOA dependency function.

  8. Dynamic shifts of limited working memory resources in human vision.

    Science.gov (United States)

    Bays, Paul M; Husain, Masud

    2008-08-08

    Our ability to remember what we have seen is very limited. Most current views characterize this limit as a fixed number of items-only four objects-that can be held in visual working memory. We show that visual memory capacity is not fixed by the number of objects, but rather is a limited resource that is shared out dynamically between all items in the visual scene. This resource can be shifted flexibly between objects, with allocation biased by selective attention and toward targets of upcoming eye movements. The proportion of resources allocated to each item determines the precision with which it is remembered, a relation that we show is governed by a simple power law, allowing quantitative estimates of resource distribution in a scene.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Modeling human color categorization: Color discrimination and color memory

    OpenAIRE

    Heskes, T.; van den Broek, Egon; Lucas, P.; Hendriks, Maria A.; Vuurpijl, L.G.; Puts, M.J.H.; Wiegerinck, W.

    2003-01-01

    Color matching in Content-Based Image Retrieval is done using a color space and measuring distances between colors. Such an approach yields non-intuitive results for the user. We introduce color categories (or focal colors), determine that they are valid, and use them in two experiments. The experiments conducted prove the difference between color categorization by the cognitive processes color discrimination and color memory. In addition, they yield a Color Look-Up Table, which can improve c...

  15. Human Memory Limitations in Multi-Object Tracking.

    Science.gov (United States)

    1982-06-01

    processing concepts of Norman (1968) and Atkinson and Shiffrin (1968), and from the " levels of processing " formulation of Craik and Lockhart ...distinct memory representations that result from different levels of processing . Craik and Lockhart (1972) have argued convincingly for a process -oriented...learning and motivation (Vol. 2). New York: Academic Press, 1968, pp. 89-105. Craik , F. I. M., & Lockhart , R. S. Levels of processing

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

    Science.gov (United States)

    Cuppini, C; Magosso, E; Ursino, M

    2009-06-01

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

  17. 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. Copyright © 2014 Wiley Periodicals, Inc.

  18. 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.

  19. 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

    2015-01-01

    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. PMID:24335033

  20. 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

  1. Evidence for Functional Networks within the Human Brain's White Matter.

    Science.gov (United States)

    Peer, Michael; Nitzan, Mor; Bick, Atira S; Levin, Netta; Arzy, Shahar

    2017-07-05

    Investigation of the functional macro-scale organization of the human cortex is fundamental in modern neuroscience. Although numerous studies have identified networks of interacting functional modules in the gray-matter, limited research was directed to the functional organization of the white-matter. Recent studies have demonstrated that the white-matter exhibits blood oxygen level-dependent signal fluctuations similar to those of the gray-matter. Here we used these signal fluctuations to investigate whether the white-matter is organized as functional networks by applying a clustering analysis on resting-state functional MRI (RSfMRI) data from white-matter voxels, in 176 subjects (of both sexes). This analysis indicated the existence of 12 symmetrical white-matter functional networks, corresponding to combinations of white-matter tracts identified by diffusion tensor imaging. Six of the networks included interhemispheric commissural bridges traversing the corpus callosum. Signals in white-matter networks correlated with signals from functional gray-matter networks, providing missing knowledge on how these distributed networks communicate across large distances. These findings were replicated in an independent subject group and were corroborated by seed-based analysis in small groups and individual subjects. The identified white-matter functional atlases and analysis codes are available at http://mind.huji.ac.il/white-matter.aspx Our results demonstrate that the white-matter manifests an intrinsic functional organization as interacting networks of functional modules, similarly to the gray-matter, which can be investigated using RSfMRI. The discovery of functional networks within the white-matter may open new avenues of research in cognitive neuroscience and clinical neuropsychiatry. SIGNIFICANCE STATEMENT In recent years, functional MRI (fMRI) has revolutionized all fields of neuroscience, enabling identifications of functional modules and networks in the human

  2. 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.

  3. 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.

  4. Effects of network resolution on topological properties of human neocortex

    DEFF Research Database (Denmark)

    Romero-Garcia, Rafael; Atienza, Mercedes; Clemmensen, Line Katrine Harder

    2012-01-01

    Graph theoretical analyses applied to neuroimaging datasets have provided valuable insights into the large-scale anatomical organization of the human neocortex. Most of these studies were performed with different cortical scales leading to cortical networks with different levels of small-world or......Graph theoretical analyses applied to neuroimaging datasets have provided valuable insights into the large-scale anatomical organization of the human neocortex. Most of these studies were performed with different cortical scales leading to cortical networks with different levels of small...

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

    Science.gov (United States)

    Pedreira, María E.

    2013-01-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

  7. Small-world human brain networks: Perspectives and challenges.

    Science.gov (United States)

    Liao, Xuhong; Vasilakos, Athanasios V; He, Yong

    2017-06-01

    Modelling the human brain as a complex network has provided a powerful mathematical framework to characterize the structural and functional architectures of the brain. In the past decade, the combination of non-invasive neuroimaging techniques and graph theoretical approaches enable us to map human structural and functional connectivity patterns (i.e., connectome) at the macroscopic level. One of the most influential findings is that human brain networks exhibit prominent small-world organization. Such a network architecture in the human brain facilitates efficient information segregation and integration at low wiring and energy costs, which presumably results from natural selection under the pressure of a cost-efficiency balance. Moreover, the small-world organization undergoes continuous changes during normal development and ageing and exhibits dramatic alterations in neurological and psychiatric disorders. In this review, we survey recent advances regarding the small-world architecture in human brain networks and highlight the potential implications and applications in multidisciplinary fields, including cognitive neuroscience, medicine and engineering. Finally, we highlight several challenging issues and areas for future research in this rapidly growing field. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. 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.

  9. Sensitivity analysis of human brain structural network construction