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Sample records for modular neural oscillators

  1. Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations

    PubMed Central

    Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong

    2010-01-01

    Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information

  2. Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations.

    PubMed

    Wang, Sheng-Jun; Hilgetag, Claus C; Zhou, Changsong

    2011-01-01

    Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information

  3. Modular, Hierarchical Learning By Artificial Neural Networks

    NASA Technical Reports Server (NTRS)

    Baldi, Pierre F.; Toomarian, Nikzad

    1996-01-01

    Modular and hierarchical approach to supervised learning by artificial neural networks leads to neural networks more structured than neural networks in which all neurons fully interconnected. These networks utilize general feedforward flow of information and sparse recurrent connections to achieve dynamical effects. The modular organization, sparsity of modular units and connections, and fact that learning is much more circumscribed are all attractive features for designing neural-network hardware. Learning streamlined by imitating some aspects of biological neural networks.

  4. Modular, Hierarchical Learning By Artificial Neural Networks

    NASA Technical Reports Server (NTRS)

    Baldi, Pierre F.; Toomarian, Nikzad

    1996-01-01

    Modular and hierarchical approach to supervised learning by artificial neural networks leads to neural networks more structured than neural networks in which all neurons fully interconnected. These networks utilize general feedforward flow of information and sparse recurrent connections to achieve dynamical effects. The modular organization, sparsity of modular units and connections, and fact that learning is much more circumscribed are all attractive features for designing neural-network hardware. Learning streamlined by imitating some aspects of biological neural networks.

  5. A neural network with modular hierarchical learning

    NASA Technical Reports Server (NTRS)

    Baldi, Pierre F. (Inventor); Toomarian, Nikzad (Inventor)

    1994-01-01

    This invention provides a new hierarchical approach for supervised neural learning of time dependent trajectories. The modular hierarchical methodology leads to architectures which are more structured than fully interconnected networks. The networks utilize a general feedforward flow of information and sparse recurrent connections to achieve dynamic effects. The advantages include the sparsity of units and connections, the modular organization. A further advantage is that the learning is much more circumscribed learning than in fully interconnected systems. The present invention is embodied by a neural network including a plurality of neural modules each having a pre-established performance capability wherein each neural module has an output outputting present results of the performance capability and an input for changing the present results of the performance capabilitiy. For pattern recognition applications, the performance capability may be an oscillation capability producing a repeating wave pattern as the present results. In the preferred embodiment, each of the plurality of neural modules includes a pre-established capability portion and a performance adjustment portion connected to control the pre-established capability portion.

  6. Nonlinear Neural Network Oscillator.

    DTIC Science & Technology

    A nonlinear oscillator (10) includes a neural network (12) having at least one output (12a) for outputting a one dimensional vector. The neural ... neural network and the input of the input layer for modifying a magnitude and/or a polarity of the one dimensional output vector prior to the sample of...first or a second direction. Connection weights of the neural network are trained on a deterministic sequence of data from a chaotic source or may be a

  7. Adaptive Coupled Oscillators for Modular Robots

    NASA Astrophysics Data System (ADS)

    Hartono, Pitoyo; Nakane, Aito

    In this research we physically built several robotics modules that are able to self-discover a connection topology which allows them to generate a coordinated behavior as an integrated modular robot. We consider that this self-configurability of hardware module can potentially simplify the costly designing process of complicated robots and at the same time improve the resiliency of modular robots in the face of internal and external changes.

  8. Chimera States in Neural Oscillators

    NASA Astrophysics Data System (ADS)

    Bahar, Sonya; Glaze, Tera

    2014-03-01

    Chimera states have recently been explored both theoretically and experimentally, in various coupled nonlinear oscillators, ranging from phase-oscillator models to coupled chemical reactions. In a chimera state, both coherent and incoherent (or synchronized and desynchronized) states occur simultaneously in populations of identical oscillators. We investigate chimera behavior in a population of neural oscillators using the Huber-Braun model, a Hodgkin-Huxley-like model originally developed to characterize the temperature-dependent bursting behavior of mammalian cold receptors. One population of neurons is allowed to synchronize, with each neuron receiving input from all the others in its group (global within-group coupling). Subsequently, a second population of identical neurons is placed under an identical global within-group coupling, and the two populations are also coupled to each other (between-group coupling). For certain values of the coupling constants, the neurons in the two populations exhibit radically different synchronization behavior. We will discuss the range of chimera activity in the model, and discuss its implications for actual neural activity, such as unihemispheric sleep.

  9. Nonlinear system identification and control based on modular neural networks.

    PubMed

    Puscasu, Gheorghe; Codres, Bogdan

    2011-08-01

    A new approach for nonlinear system identification and control based on modular neural networks (MNN) is proposed in this paper. The computational complexity of neural identification can be greatly reduced if the whole system is decomposed into several subsystems. This is obtained using a partitioning algorithm. Each local nonlinear model is associated with a nonlinear controller. These are also implemented by neural networks. The switching between the neural controllers is done by a dynamical switcher, also implemented by neural networks, that tracks the different operating points. The proposed multiple modelling and control strategy has been successfully tested on simulated laboratory scale liquid-level system.

  10. Neural organization of the locomotive oscillator.

    PubMed

    Willner, B E; Miranker, W L; Lu, C P

    1993-01-01

    We study the relation of neural development, organization, and activity to behavior. We provide a model of the locomotive oscillator, a neural system supplying alternating stimulation to extensor and flexor muscles creating an oscillatory motion. We propose a protocol by which this neural system starting from unstructured, unconnected neural populations develops structure and function. The protocol is studied by both computer simulation and mathematical analysis. Our main results are 1. The locomotive oscillator self-organizes and maintains its organization, assuming certain properties of the neural populations. 2. Imperfections disturbing the functional adequacy of the neural populations may lead to the deterioration and disappearance of the oscillatory behavior. 3. The locomotive oscillator may fail to organize if the development is not staged in time.

  11. Hierarchical synchrony of phase oscillators in modular networks

    NASA Astrophysics Data System (ADS)

    Skardal, Per Sebastian; Restrepo, Juan G.

    2012-01-01

    We study synchronization of sinusoidally coupled phase oscillators on networks with modular structure and a large number of oscillators in each community. Of particular interest is the hierarchy of local and global synchrony, i.e., synchrony within and between communities, respectively. Using the recent ansatz of Ott and Antonsen [ChaosCHAOEH1054-150010.1063/1.2930766 18, 037113 (2008)], we find that the degree of local synchrony can be determined from a set of coupled low-dimensional equations. If the number of communities in the network is large, a low-dimensional description of global synchrony can be also found. Using these results, we study bifurcations between different types of synchrony. We find that, depending on the relative strength of local and global coupling, the transition to synchrony in the network can be mediated by local or global effects.

  12. Hierarchical synchrony of phase oscillators in modular networks.

    PubMed

    Skardal, Per Sebastian; Restrepo, Juan G

    2012-01-01

    We study synchronization of sinusoidally coupled phase oscillators on networks with modular structure and a large number of oscillators in each community. Of particular interest is the hierarchy of local and global synchrony, i.e., synchrony within and between communities, respectively. Using the recent ansatz of Ott and Antonsen [Chaos 18, 037113 (2008)], we find that the degree of local synchrony can be determined from a set of coupled low-dimensional equations. If the number of communities in the network is large, a low-dimensional description of global synchrony can be also found. Using these results, we study bifurcations between different types of synchrony. We find that, depending on the relative strength of local and global coupling, the transition to synchrony in the network can be mediated by local or global effects.

  13. Oscillation onset in neural delayed feedback

    SciTech Connect

    Longtin, A.

    1990-01-01

    This paper studies dynamical aspects of neural systems with delayed negative feedback modelled by nonlinear delay-differential equations. These systems undergo a Hopf bifurcation from a stable fixed point to a limit cycle oscillation as certain parameters are varied. We show that their frequency of oscillation is robust to parameter variations and noisy fluctuations, a property that makes these systems good candidates for pacemakers. The onset of oscillation is postponed by both additive and parametric noise in the sense that the state variable spends more time near the fixed point. Finally, we show that a distributed delay (rather than a fixed delay) also stabilizes the fixed point solution. 40 refs., 2 figs.

  14. A Modular Ring Architecture for Large Scale Neural Network Implementations

    NASA Astrophysics Data System (ADS)

    Jump, Lance B.; Ligomenides, Panos A.

    1989-11-01

    Constructing fully parallel, large scale, neural networks is complicated by the problems of providing for massive interconnectivity and of overcoming fan in/out limitations in area-efficient VLSI/WSI realizations. A modular, bus switched, neural ring architecture employing primitive ring (pRing) processors is proposed, which solves the fan in/out and connectivity problems by a dynamically reconfigurable communication ring that synchronously serves identical, radially connected, processing elements. It also allows cost versus performance trade-offs by the assignment of variable numbers of logical neurons to each physical processing element.

  15. A Flexible Behavioral Learning System with Modular Neural Networks

    NASA Astrophysics Data System (ADS)

    Takeuchi, Johane; Shouno, Osamu; Tsujino, Hiroshi

    Future robots/agents will perform situated behaviors for each user. Flexible behavioral learning is required for coping with diverse and unexpected users' situations. Unexpected situations are usually not tractable for machine learning systems that are designed for pre-defined problems. In order to realize such a flexible learning system, we were trying to create a learning model that can function in several different kinds of state transitions without specific adjustments for each transition as a first step. We constructed a modular neural network model based on reinforcement learning. We expected that combining a modular architecture with neural networks could accelerate the learning speed of neural networks. The inputs of our neural network model always include not only observed states but also memory information for any transition. In pure Markov decision processes, memory information is not necessary, rather it can lead to lower performance. On the other hand, partially observable conditions require memory information to select proper actions. We demonstrated that the new learning model could actually learn those multiple kinds of state transitions with the same architectures and parameters, and without pre-designed models of environments. This paper describes the performances of constructed models using probabilistically fluctuated Markov decision processes including partially observable conditions. In the test transitions, the observed state probabilistically fluctuated. The new learning model could function in those complex transitions. In addition, the learning speeds of our model are comparable to a reinforcement learning algorithm implemented with a pre-defined and optimized table-representation of states.

  16. Chimera-like States in Modular Neural Networks

    NASA Astrophysics Data System (ADS)

    Hizanidis, Johanne; Kouvaris, Nikos E.; Gorka, Zamora-López; Díaz-Guilera, Albert; Antonopoulos, Chris G.

    2016-01-01

    Chimera states, namely the coexistence of coherent and incoherent behavior, were previously analyzed in complex networks. However, they have not been extensively studied in modular networks. Here, we consider a neural network inspired by the connectome of the C. elegans soil worm, organized into six interconnected communities, where neurons obey chaotic bursting dynamics. Neurons are assumed to be connected with electrical synapses within their communities and with chemical synapses across them. As our numerical simulations reveal, the coaction of these two types of coupling can shape the dynamics in such a way that chimera-like states can happen. They consist of a fraction of synchronized neurons which belong to the larger communities, and a fraction of desynchronized neurons which are part of smaller communities. In addition to the Kuramoto order parameter ρ, we also employ other measures of coherence, such as the chimera-like χ and metastability λ indices, which quantify the degree of synchronization among communities and along time, respectively. We perform the same analysis for networks that share common features with the C. elegans neural network. Similar results suggest that under certain assumptions, chimera-like states are prominent phenomena in modular networks, and might provide insight for the behavior of more complex modular networks.

  17. Chimera-like States in Modular Neural Networks

    PubMed Central

    Hizanidis, Johanne; Kouvaris, Nikos E.; Gorka, Zamora-López; Díaz-Guilera, Albert; Antonopoulos, Chris G.

    2016-01-01

    Chimera states, namely the coexistence of coherent and incoherent behavior, were previously analyzed in complex networks. However, they have not been extensively studied in modular networks. Here, we consider a neural network inspired by the connectome of the C. elegans soil worm, organized into six interconnected communities, where neurons obey chaotic bursting dynamics. Neurons are assumed to be connected with electrical synapses within their communities and with chemical synapses across them. As our numerical simulations reveal, the coaction of these two types of coupling can shape the dynamics in such a way that chimera-like states can happen. They consist of a fraction of synchronized neurons which belong to the larger communities, and a fraction of desynchronized neurons which are part of smaller communities. In addition to the Kuramoto order parameter ρ, we also employ other measures of coherence, such as the chimera-like χ and metastability λ indices, which quantify the degree of synchronization among communities and along time, respectively. We perform the same analysis for networks that share common features with the C. elegans neural network. Similar results suggest that under certain assumptions, chimera-like states are prominent phenomena in modular networks, and might provide insight for the behavior of more complex modular networks. PMID:26796971

  18. A modular architecture for transparent computation in recurrent neural networks.

    PubMed

    Carmantini, Giovanni S; Beim Graben, Peter; Desroches, Mathieu; Rodrigues, Serafim

    2017-01-01

    Computation is classically studied in terms of automata, formal languages and algorithms; yet, the relation between neural dynamics and symbolic representations and operations is still unclear in traditional eliminative connectionism. Therefore, we suggest a unique perspective on this central issue, to which we would like to refer as transparent connectionism, by proposing accounts of how symbolic computation can be implemented in neural substrates. In this study we first introduce a new model of dynamics on a symbolic space, the versatile shift, showing that it supports the real-time simulation of a range of automata. We then show that the Gödelization of versatile shifts defines nonlinear dynamical automata, dynamical systems evolving on a vectorial space. Finally, we present a mapping between nonlinear dynamical automata and recurrent artificial neural networks. The mapping defines an architecture characterized by its granular modularity, where data, symbolic operations and their control are not only distinguishable in activation space, but also spatially localizable in the network itself, while maintaining a distributed encoding of symbolic representations. The resulting networks simulate automata in real-time and are programmed directly, in the absence of network training. To discuss the unique characteristics of the architecture and their consequences, we present two examples: (i) the design of a Central Pattern Generator from a finite-state locomotive controller, and (ii) the creation of a network simulating a system of interactive automata that supports the parsing of garden-path sentences as investigated in psycholinguistics experiments. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Dynamics of modularity of neural activity in the brain during development

    NASA Astrophysics Data System (ADS)

    Deem, Michael; Chen, Man

    2014-03-01

    Theory suggests that more modular systems can have better response functions at short times. This theory suggests that greater cognitive performance may be achieved for more modular neural activity, and that modularity of neural activity may, therefore, likely increase with development in children. We study the relationship between age and modularity of brain neural activity in developing children. The value of modularity calculated from fMRI data is observed to increase during childhood development and peak in young adulthood. We interpret these results as evidence of selection for plasticity in the cognitive function of the human brain. We present a model to illustrate how modularity can provide greater cognitive performance at short times and enhance fast, low-level, automatic cognitive processes. Conversely, high-level, effortful, conscious cognitive processes may not benefit from modularity. We use quasispecies theory to predict how the average modularity evolves with age, given a fitness function extracted from the model. We suggest further experiments exploring the effect of modularity on cognitive performance and suggest that modularity may be a potential biomarker for injury, rehabilitation, or disease.

  20. Development of modularity in the neural activity of childrenʼs brains

    NASA Astrophysics Data System (ADS)

    Chen, Man; Deem, Michael W.

    2015-02-01

    We study how modularity of the human brain changes as children develop into adults. Theory suggests that modularity can enhance the response function of a networked system subject to changing external stimuli. Thus, greater cognitive performance might be achieved for more modular neural activity, and modularity might likely increase as children develop. The value of modularity calculated from functional magnetic resonance imaging (fMRI) data is observed to increase during childhood development and peak in young adulthood. Head motion is deconvolved from the fMRI data, and it is shown that the dependence of modularity on age is independent of the magnitude of head motion. A model is presented to illustrate how modularity can provide greater cognitive performance at short times, i.e. task switching. A fitness function is extracted from the model. Quasispecies theory is used to predict how the average modularity evolves with age, illustrating the increase of modularity during development from children to adults that arises from selection for rapid cognitive function in young adults. Experiments exploring the effect of modularity on cognitive performance are suggested. Modularity may be a potential biomarker for injury, rehabilitation, or disease.

  1. Neural modularity helps organisms evolve to learn new skills without forgetting old skills.

    PubMed

    Ellefsen, Kai Olav; Mouret, Jean-Baptiste; Clune, Jeff

    2015-04-01

    A long-standing goal in artificial intelligence is creating agents that can learn a variety of different skills for different problems. In the artificial intelligence subfield of neural networks, a barrier to that goal is that when agents learn a new skill they typically do so by losing previously acquired skills, a problem called catastrophic forgetting. That occurs because, to learn the new task, neural learning algorithms change connections that encode previously acquired skills. How networks are organized critically affects their learning dynamics. In this paper, we test whether catastrophic forgetting can be reduced by evolving modular neural networks. Modularity intuitively should reduce learning interference between tasks by separating functionality into physically distinct modules in which learning can be selectively turned on or off. Modularity can further improve learning by having a reinforcement learning module separate from sensory processing modules, allowing learning to happen only in response to a positive or negative reward. In this paper, learning takes place via neuromodulation, which allows agents to selectively change the rate of learning for each neural connection based on environmental stimuli (e.g. to alter learning in specific locations based on the task at hand). To produce modularity, we evolve neural networks with a cost for neural connections. We show that this connection cost technique causes modularity, confirming a previous result, and that such sparsely connected, modular networks have higher overall performance because they learn new skills faster while retaining old skills more and because they have a separate reinforcement learning module. Our results suggest (1) that encouraging modularity in neural networks may help us overcome the long-standing barrier of networks that cannot learn new skills without forgetting old ones, and (2) that one benefit of the modularity ubiquitous in the brains of natural animals might be to

  2. Neural Modularity Helps Organisms Evolve to Learn New Skills without Forgetting Old Skills

    PubMed Central

    Ellefsen, Kai Olav; Mouret, Jean-Baptiste; Clune, Jeff

    2015-01-01

    A long-standing goal in artificial intelligence is creating agents that can learn a variety of different skills for different problems. In the artificial intelligence subfield of neural networks, a barrier to that goal is that when agents learn a new skill they typically do so by losing previously acquired skills, a problem called catastrophic forgetting. That occurs because, to learn the new task, neural learning algorithms change connections that encode previously acquired skills. How networks are organized critically affects their learning dynamics. In this paper, we test whether catastrophic forgetting can be reduced by evolving modular neural networks. Modularity intuitively should reduce learning interference between tasks by separating functionality into physically distinct modules in which learning can be selectively turned on or off. Modularity can further improve learning by having a reinforcement learning module separate from sensory processing modules, allowing learning to happen only in response to a positive or negative reward. In this paper, learning takes place via neuromodulation, which allows agents to selectively change the rate of learning for each neural connection based on environmental stimuli (e.g. to alter learning in specific locations based on the task at hand). To produce modularity, we evolve neural networks with a cost for neural connections. We show that this connection cost technique causes modularity, confirming a previous result, and that such sparsely connected, modular networks have higher overall performance because they learn new skills faster while retaining old skills more and because they have a separate reinforcement learning module. Our results suggest (1) that encouraging modularity in neural networks may help us overcome the long-standing barrier of networks that cannot learn new skills without forgetting old ones, and (2) that one benefit of the modularity ubiquitous in the brains of natural animals might be to

  3. Understanding the Emergence of Modularity in Neural Systems

    ERIC Educational Resources Information Center

    Bullinaria, John A.

    2007-01-01

    Modularity in the human brain remains a controversial issue, with disagreement over the nature of the modules that exist, and why, when, and how they emerge. It is a natural assumption that modularity offers some form of computational advantage, and hence evolution by natural selection has translated those advantages into the kind of modular…

  4. Metastability and chimera states in modular delay and pulse-coupled oscillator networks.

    PubMed

    Wildie, Mark; Shanahan, Murray

    2012-12-01

    Modular networks of delay-coupled and pulse-coupled oscillators are presented, which display both transient (metastable) synchronization dynamics and the formation of a large number of "chimera" states characterized by coexistent synchronized and desynchronized subsystems. We consider networks based on both community and small-world topologies. It is shown through simulation that the metastable behaviour of the system is dependent in all cases on connection delay, and a critical region is found that maximizes indices of both metastability and the prevalence of chimera states. We show dependence of phase coherence in synchronous oscillation on the level and strength of external connectivity between communities, and demonstrate that synchronization dynamics are dependent on the modular structure of the network. The long-term behaviour of the system is considered and the relevance of the model briefly discussed with emphasis on biological and neurobiological systems.

  5. Can computational efficiency alone drive the evolution of modularity in neural networks?

    PubMed Central

    Tosh, Colin R.

    2016-01-01

    Some biologists have abandoned the idea that computational efficiency in processing multipart tasks or input sets alone drives the evolution of modularity in biological networks. A recent study confirmed that small modular (neural) networks are relatively computationally-inefficient but large modular networks are slightly more efficient than non-modular ones. The present study determines whether these efficiency advantages with network size can drive the evolution of modularity in networks whose connective architecture can evolve. The answer is no, but the reason why is interesting. All simulations (run in a wide variety of parameter states) involving gradualistic connective evolution end in non-modular local attractors. Thus while a high performance modular attractor exists, such regions cannot be reached by gradualistic evolution. Non-gradualistic evolutionary simulations in which multi-modularity is obtained through duplication of existing architecture appear viable. Fundamentally, this study indicates that computational efficiency alone does not drive the evolution of modularity, even in large biological networks, but it may still be a viable mechanism when networks evolve by non-gradualistic means. PMID:27573614

  6. Can computational efficiency alone drive the evolution of modularity in neural networks?

    PubMed

    Tosh, Colin R

    2016-08-30

    Some biologists have abandoned the idea that computational efficiency in processing multipart tasks or input sets alone drives the evolution of modularity in biological networks. A recent study confirmed that small modular (neural) networks are relatively computationally-inefficient but large modular networks are slightly more efficient than non-modular ones. The present study determines whether these efficiency advantages with network size can drive the evolution of modularity in networks whose connective architecture can evolve. The answer is no, but the reason why is interesting. All simulations (run in a wide variety of parameter states) involving gradualistic connective evolution end in non-modular local attractors. Thus while a high performance modular attractor exists, such regions cannot be reached by gradualistic evolution. Non-gradualistic evolutionary simulations in which multi-modularity is obtained through duplication of existing architecture appear viable. Fundamentally, this study indicates that computational efficiency alone does not drive the evolution of modularity, even in large biological networks, but it may still be a viable mechanism when networks evolve by non-gradualistic means.

  7. Entrained neural oscillations in multiple frequency bands comodulate behavior

    PubMed Central

    Henry, Molly J.; Herrmann, Björn

    2014-01-01

    Our sensory environment is teeming with complex rhythmic structure, to which neural oscillations can become synchronized. Neural synchronization to environmental rhythms (entrainment) is hypothesized to shape human perception, as rhythmic structure acts to temporally organize cortical excitability. In the current human electroencephalography study, we investigated how behavior is influenced by neural oscillatory dynamics when the rhythmic fluctuations in the sensory environment take on a naturalistic degree of complexity. Listeners detected near-threshold gaps in auditory stimuli that were simultaneously modulated in frequency (frequency modulation, 3.1 Hz) and amplitude (amplitude modulation, 5.075 Hz); modulation rates and types were chosen to mimic the complex rhythmic structure of natural speech. Neural oscillations were entrained by both the frequency modulation and amplitude modulation in the stimulation. Critically, listeners’ target-detection accuracy depended on the specific phase–phase relationship between entrained neural oscillations in both the 3.1-Hz and 5.075-Hz frequency bands, with the best performance occurring when the respective troughs in both neural oscillations coincided. Neural-phase effects were specific to the frequency bands entrained by the rhythmic stimulation. Moreover, the degree of behavioral comodulation by neural phase in both frequency bands exceeded the degree of behavioral modulation by either frequency band alone. Our results elucidate how fluctuating excitability, within and across multiple entrained frequency bands, shapes the effective neural processing of environmental stimuli. More generally, the frequency-specific nature of behavioral comodulation effects suggests that environmental rhythms act to reduce the complexity of high-dimensional neural states. PMID:25267634

  8. Entrained neural oscillations in multiple frequency bands comodulate behavior.

    PubMed

    Henry, Molly J; Herrmann, Björn; Obleser, Jonas

    2014-10-14

    Our sensory environment is teeming with complex rhythmic structure, to which neural oscillations can become synchronized. Neural synchronization to environmental rhythms (entrainment) is hypothesized to shape human perception, as rhythmic structure acts to temporally organize cortical excitability. In the current human electroencephalography study, we investigated how behavior is influenced by neural oscillatory dynamics when the rhythmic fluctuations in the sensory environment take on a naturalistic degree of complexity. Listeners detected near-threshold gaps in auditory stimuli that were simultaneously modulated in frequency (frequency modulation, 3.1 Hz) and amplitude (amplitude modulation, 5.075 Hz); modulation rates and types were chosen to mimic the complex rhythmic structure of natural speech. Neural oscillations were entrained by both the frequency modulation and amplitude modulation in the stimulation. Critically, listeners' target-detection accuracy depended on the specific phase-phase relationship between entrained neural oscillations in both the 3.1-Hz and 5.075-Hz frequency bands, with the best performance occurring when the respective troughs in both neural oscillations coincided. Neural-phase effects were specific to the frequency bands entrained by the rhythmic stimulation. Moreover, the degree of behavioral comodulation by neural phase in both frequency bands exceeded the degree of behavioral modulation by either frequency band alone. Our results elucidate how fluctuating excitability, within and across multiple entrained frequency bands, shapes the effective neural processing of environmental stimuli. More generally, the frequency-specific nature of behavioral comodulation effects suggests that environmental rhythms act to reduce the complexity of high-dimensional neural states.

  9. Oscillation-Induced Signal Transmission and Gating in Neural Circuits

    PubMed Central

    Jahnke, Sven; Memmesheimer, Raoul-Martin; Timme, Marc

    2014-01-01

    Reliable signal transmission constitutes a key requirement for neural circuit function. The propagation of synchronous pulse packets through recurrent circuits is hypothesized to be one robust form of signal transmission and has been extensively studied in computational and theoretical works. Yet, although external or internally generated oscillations are ubiquitous across neural systems, their influence on such signal propagation is unclear. Here we systematically investigate the impact of oscillations on propagating synchrony. We find that for standard, additive couplings and a net excitatory effect of oscillations, robust propagation of synchrony is enabled in less prominent feed-forward structures than in systems without oscillations. In the presence of non-additive coupling (as mediated by fast dendritic spikes), even balanced oscillatory inputs may enable robust propagation. Here, emerging resonances create complex locking patterns between oscillations and spike synchrony. Interestingly, these resonances make the circuits capable of selecting specific pathways for signal transmission. Oscillations may thus promote reliable transmission and, in co-action with dendritic nonlinearities, provide a mechanism for information processing by selectively gating and routing of signals. Our results are of particular interest for the interpretation of sharp wave/ripple complexes in the hippocampus, where previously learned spike patterns are replayed in conjunction with global high-frequency oscillations. We suggest that the oscillations may serve to stabilize the replay. PMID:25503492

  10. Signal Processing, Pattern Formation and Adaptation in Neural Oscillators

    DTIC Science & Technology

    2016-11-29

    Hoppensteadt and Izhikevich (1996, 1997) showed that a weakly connected network of neural oscillators of identical natural frequencies can memorize...from the intrinsic dynamics of an emergent oscillation (Whittington et al., 2000), and the missing pulse rhythms used here enabled us to dissociate ...musical beat processing. The Neurosciences and Music III: Disorders and Plasticity. Annals of the New York Academy of Sciences, 1169, 89-92. Grahn

  11. Macroscopic Neural Oscillation during Skilled Reaching Movements in Humans

    PubMed Central

    Chung, Chun Kee

    2016-01-01

    The neural mechanism of skilled movements, such as reaching, has been considered to differ from that of rhythmic movement such as locomotion. It is generally thought that skilled movements are consciously controlled by the brain, while rhythmic movements are usually controlled autonomously by the spinal cord and brain stem. However, several studies in recent decades have suggested that neural networks in the spinal cord may also be involved in the generation of skilled movements. Moreover, a recent study revealed that neural activities in the motor cortex exhibit rhythmic oscillations corresponding to movement frequency during reaching movements as rhythmic movements. However, whether the oscillations are generated in the spinal cord or the cortical circuit in the motor cortex causes the oscillations is unclear. If the spinal cord is involved in the skilled movements, then similar rhythmic oscillations with time delays should be found in macroscopic neural activity. We measured whole-brain MEG signals during reaching. The MEG signals were analyzed using a dynamical analysis method. We found that rhythmic oscillations with time delays occur in all subjects during reaching movements. The results suggest that the corticospinal system is involved in the generation and control of the skilled movements as rhythmic movements. PMID:27524996

  12. High vs low frequency neural oscillations in schizophrenia.

    PubMed

    Moran, Lauren V; Hong, L Elliot

    2011-07-01

    There is growing recognition that neural oscillations are important in a wide range of perceptual and cognitive functions. One of the key issues in electrophysiological studies of schizophrenia is whether high or low frequency oscillations, or both, are related to schizophrenia because many brain functions are modulated with frequency specificities. Many recent electrophysiological studies of schizophrenia have focused on high frequency oscillations at gamma band and in general support gamma band dysfunction in schizophrenia. We discuss the concept that gamma oscillation abnormalities in schizophrenia often occur in the background of oscillation abnormalities of lower frequencies. The review discusses the basic neurobiology for the emergence of oscillations of all frequency bands in association with networks of inhibitory interneurons and the convergence and divergence of such mechanisms in generating high vs low frequency oscillations. We then review the literature of oscillatory frequency abnormalities identified in each frequency band in schizophrenia. By describing some of the key functional roles exerted by gamma, low frequencies, and their cross-frequency coupling, we conceptualize that even isolated alterations in gamma or low frequency oscillations may impact the interactions of high and low frequency bands that are involved in key cognitive functions. The review concludes that studying the full spectrum and the interaction of gamma and low frequency oscillations may be critical for deciphering the complex electrophysiological abnormalities observed in schizophrenia patients.

  13. What works in auditory working memory? A neural oscillations perspective.

    PubMed

    Wilsch, Anna; Obleser, Jonas

    2016-06-01

    Working memory is a limited resource: brains can only maintain small amounts of sensory input (memory load) over a brief period of time (memory decay). The dynamics of slow neural oscillations as recorded using magneto- and electroencephalography (M/EEG) provide a window into the neural mechanics of these limitations. Especially oscillations in the alpha range (8-13Hz) are a sensitive marker for memory load. Moreover, according to current models, the resultant working memory load is determined by the relative noise in the neural representation of maintained information. The auditory domain allows memory researchers to apply and test the concept of noise quite literally: Employing degraded stimulus acoustics increases memory load and, at the same time, allows assessing the cognitive resources required to process speech in noise in an ecologically valid and clinically relevant way. The present review first summarizes recent findings on neural oscillations, especially alpha power, and how they reflect memory load and memory decay in auditory working memory. The focus is specifically on memory load resulting from acoustic degradation. These findings are then contrasted with contextual factors that benefit neural as well as behavioral markers of memory performance, by reducing representational noise. We end on discussing the functional role of alpha power in auditory working memory and suggest extensions of the current methodological toolkit. This article is part of a Special Issue entitled SI: Auditory working memory.

  14. Entrainment of neural oscillations as a modifiable substrate of attention.

    PubMed

    Calderone, Daniel J; Lakatos, Peter; Butler, Pamela D; Castellanos, F Xavier

    2014-06-01

    Brain operation is profoundly rhythmic. Oscillations of neural excitability shape sensory, motor, and cognitive processes. Intrinsic oscillations also entrain to external rhythms, allowing the brain to optimize the processing of predictable events such as speech. Moreover, selective attention to a particular rhythm in a complex environment entails entrainment of neural oscillations to its temporal structure. Entrainment appears to form one of the core mechanisms of selective attention, which is likely to be relevant to certain psychiatric disorders. Deficient entrainment has been found in schizophrenia and dyslexia and mounting evidence also suggests that it may be abnormal in attention-deficit/hyperactivity disorder (ADHD). Accordingly, we suggest that studying entrainment in selective-attention paradigms is likely to reveal mechanisms underlying deficits across multiple disorders.

  15. Flow version of statistical neurodynamics for oscillator neural networks

    NASA Astrophysics Data System (ADS)

    Uchiyama, Satoki

    2012-04-01

    We consider a neural network of Stuart-Landau oscillators as an associative memory. This oscillator network with N elements is a system of an N-dimensional differential equation, works as an attractor neural network, and is expected to have no Lyapunov functions. Therefore, the technique of equilibrium statistical physics is not applicable to the study of this system in the thermodynamic limit. However, the simplicity of this system allows us to extend statistical neurodynamics [S. Amari, K. Maginu, Neural Netw. 1 (1988) 63-73], which was originally developed to analyse the discrete time evolution of the Hopfield model, into the version for continuous time evolution. We have developed and attempted to apply this method in the analysis of the phase transition of our model network.

  16. Collective oscillations in disordered neural networks.

    PubMed

    Olmi, Simona; Livi, Roberto; Politi, Antonio; Torcini, Alessandro

    2010-04-01

    We investigate the onset of collective oscillations in a excitatory pulse-coupled network of leaky integrate-and-fire neurons in the presence of quenched and annealed disorder. We find that the disorder induces a weak form of chaos that is analogous to that arising in the Kuramoto model for a finite number N of oscillators [O. V. Popovych, Phys. Rev. E 71 065201(R) (2005)]. In fact, the maximum Lyapunov exponent turns out to scale to zero for N-->infinity , with an exponent that is different for the two types of disorder. In the thermodynamic limit, the random-network dynamics reduces to that of a fully homogeneous system with a suitably scaled coupling strength. Moreover, we show that the Lyapunov spectrum of the periodically collective state scales to zero as 1/N{2}, analogously to the scaling found for the "splay state."

  17. Genesis and synchronization properties of fast neural oscillations

    NASA Astrophysics Data System (ADS)

    Bazhenov, Maxim; Rulkov, Nikolai

    2008-03-01

    Fast neural network oscillations in gamma (30-80 Hz) range are associated with attentiveness and sensory perception and have strong relation to both cognitive processing and temporal binding of sensory stimuli. These oscillations are found in different brain systems including cerebral cortex, hippocampus and olfactory bulb. Cortical gamma oscillations may become synchronized within 1-2 msec over distances up to a few millimeters. In this study we used computational network models to analyze basic synaptic mechanisms and synchronization properties of fast neural oscillations. Using the network models of synaptically coupled pyramidal neurons (up to 500,000 cells) and fast spiking interneurons (up to 125,000 cells) we found that the strength of feedback inhibition determined the network synchronization state: either global network oscillations with near zero phase lag between remote sites or waves of gamma activity propagating through the network. Long-range excitatory connections between pyramidal cells were not required for long-range synchronization. The model predicts that local inhibitory circuits can mediate global network synchronization with phase delays being much smaller than activity propagation time between remote network sites.

  18. Chaotic itinerancy in the oscillator neural network without Lyapunov functions

    NASA Astrophysics Data System (ADS)

    Uchiyama, Satoki; Fujisaka, Hirokazu

    2004-09-01

    Chaotic itinerancy (CI), which is defined as an incessant spontaneous switching phenomenon among attractor ruins in deterministic dynamical systems without Lyapunov functions, is numerically studied in the case of an oscillator neural network model. The model is the pseudoinverse-matrix version of the previous model [S. Uchiyama and H. Fujisaka, Phys. Rev. E 65, 061912 (2002)] that was studied theoretically with the aid of statistical neurodynamics. It is found that CI in neural nets can be understood as the intermittent dynamics of weakly destabilized chaotic retrieval solutions.

  19. Synchronization and cluster sequences in modular and evolving map-based neural networks

    NASA Astrophysics Data System (ADS)

    Maslennikov, Oleg V.; Nekorkin, Vladimir I.

    2016-06-01

    The impact of modularity and time delay for spiking neural networks is considered in the first part of this report. We show for different complex topologies that time delay controls regimes of inter-module synchronization as well as the oscillatory rate of modules. In the second part of the work we study a paradigmatic model of the evolving neural network whose topology is influenced by nodal dynamics which results in generating different cluster sequences. We show the conditions under which the sequences are robust to small perturbations of initial conditions, parameter detuning, and noise, while at the same are selective to information stimuli.

  20. Spontaneous Local Gamma Oscillation Selectively Enhances Neural Network Responsiveness

    PubMed Central

    Paik, Se-Bum; Kumar, Tribhawan; Glaser, Donald A.

    2009-01-01

    Synchronized oscillation is very commonly observed in many neuronal systems and might play an important role in the response properties of the system. We have studied how the spontaneous oscillatory activity affects the responsiveness of a neuronal network, using a neural network model of the visual cortex built from Hodgkin-Huxley type excitatory (E-) and inhibitory (I-) neurons. When the isotropic local E-I and I-E synaptic connections were sufficiently strong, the network commonly generated gamma frequency oscillatory firing patterns in response to random feed-forward (FF) input spikes. This spontaneous oscillatory network activity injects a periodic local current that could amplify a weak synaptic input and enhance the network's responsiveness. When E-E connections were added, we found that the strength of oscillation can be modulated by varying the FF input strength without any changes in single neuron properties or interneuron connectivity. The response modulation is proportional to the oscillation strength, which leads to self-regulation such that the cortical network selectively amplifies various FF inputs according to its strength, without requiring any adaptation mechanism. We show that this selective cortical amplification is controlled by E-E cell interactions. We also found that this response amplification is spatially localized, which suggests that the responsiveness modulation may also be spatially selective. This suggests a generalized mechanism by which neural oscillatory activity can enhance the selectivity of a neural network to FF inputs. PMID:19343222

  1. Spontaneous neural oscillations bias perception by modulating baseline excitability.

    PubMed

    Iemi, Luca; Chaumon, Maximilien; Crouzet, Sébastien M; Busch, Niko A

    2016-12-19

    The brain exhibits organised fluctuations of neural activity even in the absence of tasks or sensory input. A prominent type of such spontaneous activity is the alpha rhythm, which influences perception and interacts with other ongoing neural activity. It is currently hypothesised that states of decreased prestimulus alpha oscillations indicate enhanced neural excitability, resulting in improved perceptual acuity. Nevertheless, it remains debated how changes in excitability manifest at the behavioral level in perceptual tasks. We addressed this issue by comparing two alternative models describing the effect of spontaneous alpha power on signal detection. The first model assumes that decreased alpha power increases baseline excitability, amplifying the response to both signal and noise, predicting a liberal detection criterion with no effect on sensitivity. The second model predicts that decreased alpha power increases the trial-by-trial precision of the sensory response, resulting in improved sensitivity. We tested these models in two EEG experiments in humans where we analysed the effects of prestimulus alpha power on visual detection and discrimination using a signal detection framework. Both experiments provide strong evidence that decreased alpha power reflects a more liberal detection criterion, rather than improved sensitivity, consistent with the baseline model. In other words, when the task requires detecting stimulus presence vs. absence, reduced alpha oscillations make observers more likely to report the stimulus irrespective of actual stimulus presence. Contrary to previous interpretations, these results suggest that states of decreased alpha oscillations increase the global baseline excitability of sensory systems without affecting perceptual acuity. Spontaneous fluctuations of brain activity explain why a faint sensory stimulus is sometimes perceived and sometimes not. The prevailing view is that heightened neural excitability, indexed by decreased

  2. Spontaneous Neural Oscillations Bias Perception by Modulating Baseline Excitability.

    PubMed

    Iemi, Luca; Chaumon, Maximilien; Crouzet, Sébastien M; Busch, Niko A

    2017-01-25

    The brain exhibits organized fluctuations of neural activity, even in the absence of tasks or sensory input. A prominent type of such spontaneous activity is the alpha rhythm, which influences perception and interacts with other ongoing neural activity. It is currently hypothesized that states of decreased prestimulus α oscillations indicate enhanced neural excitability, resulting in improved perceptual acuity. Nevertheless, it remains debated how changes in excitability manifest at the behavioral level in perceptual tasks. We addressed this issue by comparing two alternative models describing the effect of spontaneous α power on signal detection. The first model assumes that decreased α power increases baseline excitability, amplifying the response to both signal and noise, predicting a liberal detection criterion with no effect on sensitivity. The second model predicts that decreased α power increases the trial-by-trial precision of the sensory response, resulting in improved sensitivity. We tested these models in two EEG experiments in humans where we analyzed the effects of prestimulus α power on visual detection and discrimination using a signal detection framework. Both experiments provide strong evidence that decreased α power reflects a more liberal detection criterion, rather than improved sensitivity, consistent with the baseline model. In other words, when the task requires detecting stimulus presence versus absence, reduced α oscillations make observers more likely to report the stimulus regardless of actual stimulus presence. Contrary to previous interpretations, these results suggest that states of decreased α oscillations increase the global baseline excitability of sensory systems without affecting perceptual acuity. Spontaneous fluctuations of brain activity explain why a faint sensory stimulus is sometimes perceived and sometimes not. The prevailing view is that heightened neural excitability, indexed by decreased α oscillations, promotes

  3. Patterns of interval correlations in neural oscillators with adaptation

    PubMed Central

    Schwalger, Tilo; Lindner, Benjamin

    2013-01-01

    Neural firing is often subject to negative feedback by adaptation currents. These currents can induce strong correlations among the time intervals between spikes. Here we study analytically the interval correlations of a broad class of noisy neural oscillators with spike-triggered adaptation of arbitrary strength and time scale. Our weak-noise theory provides a general relation between the correlations and the phase-response curve (PRC) of the oscillator, proves anti-correlations between neighboring intervals for adapting neurons with type I PRC and identifies a single order parameter that determines the qualitative pattern of correlations. Monotonically decaying or oscillating correlation structures can be related to qualitatively different voltage traces after spiking, which can be explained by the phase plane geometry. At high firing rates, the long-term variability of the spike train associated with the cumulative interval correlations becomes small, independent of model details. Our results are verified by comparison with stochastic simulations of the exponential, leaky, and generalized integrate-and-fire models with adaptation. PMID:24348372

  4. Oscillation propagation in neural networks with different topologies

    NASA Astrophysics Data System (ADS)

    Gao, Yang; Wang, Jianjun

    2011-03-01

    In light of the issue of oscillation propagation in neural networks, various topologies of FitzHugh-Nagumo neuron populations are investigated. External Gaussian white noise is injected into the first neuron only. Before the oscillation spreads to the other neurons in the network, some of the inherent stochasticity within the noise-induced oscillation of the first neuron is filtered out due to the neuron's nonlinear dynamics. Both the temporal and the spatial coherence of the evoked activity's propagation are analyzed in conjunction with the network topology randomness p, the coupling strength between neurons g, and the noise amplitude D. The temporal periodicity of the global neural network presents a typical coherence biresonance (CBR) characteristic with regard to the noise intensity. The network topology randomness exerts different influences on the resonance effects for different coupling strength regimes. At an intermediate coupling strength, the random shortcuts reinforce the interactions between the neurons, and then more stochasticity in the firings of the first neuron spreads within the network. Consequently, CBR is decreased with the increase of the network topology randomness. At a large coupling strength, the random shortcuts assist the nonlinearity in impairing the stochastic components, and consequently help to enhance the resonance effects, which differed significantly from previous related work. However, the degree of the spatial synchronization of the systems increases monotonically as the network topology randomness increases at any coupling strength.

  5. Patterns of interval correlations in neural oscillators with adaptation.

    PubMed

    Schwalger, Tilo; Lindner, Benjamin

    2013-01-01

    Neural firing is often subject to negative feedback by adaptation currents. These currents can induce strong correlations among the time intervals between spikes. Here we study analytically the interval correlations of a broad class of noisy neural oscillators with spike-triggered adaptation of arbitrary strength and time scale. Our weak-noise theory provides a general relation between the correlations and the phase-response curve (PRC) of the oscillator, proves anti-correlations between neighboring intervals for adapting neurons with type I PRC and identifies a single order parameter that determines the qualitative pattern of correlations. Monotonically decaying or oscillating correlation structures can be related to qualitatively different voltage traces after spiking, which can be explained by the phase plane geometry. At high firing rates, the long-term variability of the spike train associated with the cumulative interval correlations becomes small, independent of model details. Our results are verified by comparison with stochastic simulations of the exponential, leaky, and generalized integrate-and-fire models with adaptation.

  6. Gamma oscillations of spiking neural populations enhance signal discrimination.

    PubMed

    Masuda, Naoki; Doiron, Brent

    2007-11-01

    Selective attention is an important filter for complex environments where distractions compete with signals. Attention increases both the gamma-band power of cortical local field potentials and the spike-field coherence within the receptive field of an attended object. However, the mechanisms by which gamma-band activity enhances, if at all, the encoding of input signals are not well understood. We propose that gamma oscillations induce binomial-like spike-count statistics across noisy neural populations. Using simplified models of spiking neurons, we show how the discrimination of static signals based on the population spike-count response is improved with gamma induced binomial statistics. These results give an important mechanistic link between the neural correlates of attention and the discrimination tasks where attention is known to enhance performance. Further, they show how a rhythmicity of spike responses can enhance coding schemes that are not temporally sensitive.

  7. Sustained oscillations, irregular firing, and chaotic dynamics in hierarchical modular networks with mixtures of electrophysiological cell types

    PubMed Central

    Tomov, Petar; Pena, Rodrigo F. O.; Zaks, Michael A.; Roque, Antonio C.

    2014-01-01

    The cerebral cortex exhibits neural activity even in the absence of external stimuli. This self-sustained activity is characterized by irregular firing of individual neurons and population oscillations with a broad frequency range. Questions that arise in this context, are: What are the mechanisms responsible for the existence of neuronal spiking activity in the cortex without external input? Do these mechanisms depend on the structural organization of the cortical connections? Do they depend on intrinsic characteristics of the cortical neurons? To approach the answers to these questions, we have used computer simulations of cortical network models. Our networks have hierarchical modular architecture and are composed of combinations of neuron models that reproduce the firing behavior of the five main cortical electrophysiological cell classes: regular spiking (RS), chattering (CH), intrinsically bursting (IB), low threshold spiking (LTS), and fast spiking (FS). The population of excitatory neurons is built of RS cells (always present) and either CH or IB cells. Inhibitory neurons belong to the same class, either LTS or FS. Long-lived self-sustained activity states in our network simulations display irregular single neuron firing and oscillatory activity similar to experimentally measured ones. The duration of self-sustained activity strongly depends on the initial conditions, suggesting a transient chaotic regime. Extensive analysis of the self-sustained activity states showed that their lifetime expectancy increases with the number of network modules and is favored when the network is composed of excitatory neurons of the RS and CH classes combined with inhibitory neurons of the LTS class. These results indicate that the existence and properties of the self-sustained cortical activity states depend on both the topology of the network and the neuronal mixture that comprises the network. PMID:25228879

  8. Establishing a Statistical Link between Network Oscillations and Neural Synchrony

    PubMed Central

    Zhou, Pengcheng; Burton, Shawn D.; Snyder, Adam C.; Smith, Matthew A.; Urban, Nathaniel N.; Kass, Robert E.

    2015-01-01

    Pairs of active neurons frequently fire action potentials or “spikes” nearly synchronously (i.e., within 5 ms of each other). This spike synchrony may occur by chance, based solely on the neurons’ fluctuating firing patterns, or it may occur too frequently to be explicable by chance alone. When spike synchrony above chances levels is present, it may subserve computation for a specific cognitive process, or it could be an irrelevant byproduct of such computation. Either way, spike synchrony is a feature of neural data that should be explained. A point process regression framework has been developed previously for this purpose, using generalized linear models (GLMs). In this framework, the observed number of synchronous spikes is compared to the number predicted by chance under varying assumptions about the factors that affect each of the individual neuron’s firing-rate functions. An important possible source of spike synchrony is network-wide oscillations, which may provide an essential mechanism of network information flow. To establish the statistical link between spike synchrony and network-wide oscillations, we have integrated oscillatory field potentials into our point process regression framework. We first extended a previously-published model of spike-field association and showed that we could recover phase relationships between oscillatory field potentials and firing rates. We then used this new framework to demonstrate the statistical relationship between oscillatory field potentials and spike synchrony in: 1) simulated neurons, 2) in vitro recordings of hippocampal CA1 pyramidal cells, and 3) in vivo recordings of neocortical V4 neurons. Our results provide a rigorous method for establishing a statistical link between network oscillations and neural synchrony. PMID:26465621

  9. Analytical Insights on Theta-Gamma Coupled Neural Oscillators

    PubMed Central

    2013-01-01

    In this paper, we study the dynamics of a quadratic integrate-and-fire neuron, spiking in the gamma (30–100 Hz) range, coupled to a delta/theta frequency (1–8 Hz) neural oscillator. Using analytical and semianalytical methods, we were able to derive characteristic spiking times for the system in two distinct regimes (depending on parameter values): one regime where the gamma neuron is intrinsically oscillating in the absence of theta input, and a second one in which gamma spiking is directly gated by theta input, i.e., windows of gamma activity alternate with silence periods depending on the underlying theta phase. In the former case, we transform the equations such that the system becomes analogous to the Mathieu differential equation. By solving this equation, we can compute numerically the time to the first gamma spike, and then use singular perturbation theory to find successive spike times. On the other hand, in the excitable condition, we make direct use of singular perturbation theory to obtain an approximation of the time to first gamma spike, and then extend the result to calculate ensuing gamma spikes in a recursive fashion. We thereby give explicit formulas for the onset and offset of gamma spike burst during a theta cycle, and provide an estimation of the total number of spikes per theta cycle both for excitable and oscillator regimes. PMID:23945442

  10. BDNF Boosts Spike Fidelity in Chaotic Neural Oscillations

    PubMed Central

    Fujisawa, Shigeyoshi; Yamada, Maki K.; Nishiyama, Nobuyoshi; Matsuki, Norio; Ikegaya, Yuji

    2004-01-01

    Oscillatory activity and its nonlinear dynamics are of fundamental importance for information processing in the central nervous system. Here we show that in aperiodic oscillations, brain-derived neurotrophic factor (BDNF), a member of the neurotrophin family, enhances the accuracy of action potentials in terms of spike reliability and temporal precision. Cultured hippocampal neurons displayed irregular oscillations of membrane potential in response to sinusoidal 20-Hz somatic current injection, yielding wobbly orbits in the phase space, i.e., a strange attractor. Brief application of BDNF suppressed this unpredictable dynamics and stabilized membrane potential fluctuations, leading to rhythmical firing. Even in complex oscillations induced by external stimuli of 40 Hz (γ) on a 5-Hz (θ) carrier, BDNF-treated neurons generated more precisely timed spikes, i.e., phase-locked firing, coupled with θ-phase precession. These phenomena were sensitive to K252a, an inhibitor of tyrosine receptor kinases and appeared attributable to BDNF-evoked Na+ current. The data are the first indication of pharmacological control of endogenous chaos. BDNF diminishes the ambiguity of spike time jitter and thereby might assure neural encoding, such as spike timing-dependent synaptic plasticity. PMID:14990508

  11. Discovering Multimodal Behavior in Ms. Pac-Man through Evolution of Modular Neural Networks

    PubMed Central

    Schrum, Jacob; Miikkulainen, Risto

    2015-01-01

    Ms. Pac-Man is a challenging video game in which multiple modes of behavior are required: Ms. Pac-Man must escape ghosts when they are threats and catch them when they are edible, in addition to eating all pills in each level. Past approaches to learning behavior in Ms. Pac-Man have treated the game as a single task to be learned using monolithic policy representations. In contrast, this paper uses a framework called Modular Multi-objective NEAT (MM-NEAT) to evolve modular neural networks. Each module defines a separate behavior. The modules are used at different times according to a policy that can be human-designed (i.e. Multitask) or discovered automatically by evolution. The appropriate number of modules can be fixed or discovered using a genetic operator called Module Mutation. Several versions of Module Mutation are evaluated in this paper. Both fixed modular networks and Module Mutation networks outperform monolithic networks and Multitask networks. Interestingly, the best networks dedicate modules to critical behaviors (such as escaping when surrounded after luring ghosts near a power pill) that do not follow the customary division of the game into chasing edible and escaping threat ghosts. The results demonstrate that MM-NEAT can discover interesting and effective behavior for agents in challenging games. PMID:27030803

  12. Discovering Multimodal Behavior in Ms. Pac-Man through Evolution of Modular Neural Networks.

    PubMed

    Schrum, Jacob; Miikkulainen, Risto

    2016-03-12

    Ms. Pac-Man is a challenging video game in which multiple modes of behavior are required: Ms. Pac-Man must escape ghosts when they are threats and catch them when they are edible, in addition to eating all pills in each level. Past approaches to learning behavior in Ms. Pac-Man have treated the game as a single task to be learned using monolithic policy representations. In contrast, this paper uses a framework called Modular Multi-objective NEAT (MM-NEAT) to evolve modular neural networks. Each module defines a separate behavior. The modules are used at different times according to a policy that can be human-designed (i.e. Multitask) or discovered automatically by evolution. The appropriate number of modules can be fixed or discovered using a genetic operator called Module Mutation. Several versions of Module Mutation are evaluated in this paper. Both fixed modular networks and Module Mutation networks outperform monolithic networks and Multitask networks. Interestingly, the best networks dedicate modules to critical behaviors (such as escaping when surrounded after luring ghosts near a power pill) that do not follow the customary division of the game into chasing edible and escaping threat ghosts. The results demonstrate that MM-NEAT can discover interesting and effective behavior for agents in challenging games.

  13. Neural Oscillations Carry Speech Rhythm through to Comprehension.

    PubMed

    Peelle, Jonathan E; Davis, Matthew H

    2012-01-01

    A key feature of speech is the quasi-regular rhythmic information contained in its slow amplitude modulations. In this article we review the information conveyed by speech rhythm, and the role of ongoing brain oscillations in listeners' processing of this content. Our starting point is the fact that speech is inherently temporal, and that rhythmic information conveyed by the amplitude envelope contains important markers for place and manner of articulation, segmental information, and speech rate. Behavioral studies demonstrate that amplitude envelope information is relied upon by listeners and plays a key role in speech intelligibility. Extending behavioral findings, data from neuroimaging - particularly electroencephalography (EEG) and magnetoencephalography (MEG) - point to phase locking by ongoing cortical oscillations to low-frequency information (~4-8 Hz) in the speech envelope. This phase modulation effectively encodes a prediction of when important events (such as stressed syllables) are likely to occur, and acts to increase sensitivity to these relevant acoustic cues. We suggest a framework through which such neural entrainment to speech rhythm can explain effects of speech rate on word and segment perception (i.e., that the perception of phonemes and words in connected speech is influenced by preceding speech rate). Neuroanatomically, acoustic amplitude modulations are processed largely bilaterally in auditory cortex, with intelligible speech resulting in differential recruitment of left-hemisphere regions. Notable among these is lateral anterior temporal cortex, which we propose functions in a domain-general fashion to support ongoing memory and integration of meaningful input. Together, the reviewed evidence suggests that low-frequency oscillations in the acoustic speech signal form the foundation of a rhythmic hierarchy supporting spoken language, mirrored by phase-locked oscillations in the human brain.

  14. Neural Oscillations Carry Speech Rhythm through to Comprehension

    PubMed Central

    Peelle, Jonathan E.; Davis, Matthew H.

    2012-01-01

    A key feature of speech is the quasi-regular rhythmic information contained in its slow amplitude modulations. In this article we review the information conveyed by speech rhythm, and the role of ongoing brain oscillations in listeners’ processing of this content. Our starting point is the fact that speech is inherently temporal, and that rhythmic information conveyed by the amplitude envelope contains important markers for place and manner of articulation, segmental information, and speech rate. Behavioral studies demonstrate that amplitude envelope information is relied upon by listeners and plays a key role in speech intelligibility. Extending behavioral findings, data from neuroimaging – particularly electroencephalography (EEG) and magnetoencephalography (MEG) – point to phase locking by ongoing cortical oscillations to low-frequency information (~4–8 Hz) in the speech envelope. This phase modulation effectively encodes a prediction of when important events (such as stressed syllables) are likely to occur, and acts to increase sensitivity to these relevant acoustic cues. We suggest a framework through which such neural entrainment to speech rhythm can explain effects of speech rate on word and segment perception (i.e., that the perception of phonemes and words in connected speech is influenced by preceding speech rate). Neuroanatomically, acoustic amplitude modulations are processed largely bilaterally in auditory cortex, with intelligible speech resulting in differential recruitment of left-hemisphere regions. Notable among these is lateral anterior temporal cortex, which we propose functions in a domain-general fashion to support ongoing memory and integration of meaningful input. Together, the reviewed evidence suggests that low-frequency oscillations in the acoustic speech signal form the foundation of a rhythmic hierarchy supporting spoken language, mirrored by phase-locked oscillations in the human brain. PMID:22973251

  15. Oscillations and chaos in neural networks: an exactly solvable model.

    PubMed Central

    Wang, L P; Pichler, E E; Ross, J

    1990-01-01

    We consider a randomly diluted higher-order network with noise, consisting of McCulloch-Pitts neurons that interact by Hebbian-type connections. For this model, exact dynamical equations are derived and solved for both parallel and random sequential updating algorithms. For parallel dynamics, we find a rich spectrum of different behaviors including static retrieving and oscillatory and chaotic phenomena in different parts of the parameter space. The bifurcation parameters include first- and second-order neuronal interaction coefficients and a rescaled noise level, which represents the combined effects of the random synaptic dilution, interference between stored patterns, and additional background noise. We show that a marked difference in terms of the occurrence of oscillations or chaos exists between neural networks with parallel and random sequential dynamics. Images PMID:2251287

  16. Xenon-induced power oscillations in a generic small modular reactor

    NASA Astrophysics Data System (ADS)

    Kitcher, Evans Damenortey

    As world demand for energy continues to grow at unprecedented rates, the world energy portfolio of the future will inevitably include a nuclear energy contribution. It has been suggested that the Small Modular Reactor (SMR) could play a significant role in the spread of civilian nuclear technology to nations previously without nuclear energy. As part of the design process, the SMR design must be assessed for the threat to operations posed by xenon-induced power oscillations. In this research, a generic SMR design was analyzed with respect to just such a threat. In order to do so, a multi-physics coupling routine was developed with MCNP/MCNPX as the neutronics solver. Thermal hydraulic assessments were performed using a single channel analysis tool developed in Python. Fuel and coolant temperature profiles were implemented in the form of temperature dependent fuel cross sections generated using the SIGACE code and reactor core coolant densities. The Power Axial Offset (PAO) and Xenon Axial Offset (XAO) parameters were chosen to quantify any oscillatory behavior observed. The methodology was benchmarked against results from literature of startup tests performed at a four-loop PWR in Korea. The developed benchmark model replicated the pertinent features of the reactor within ten percent of the literature values. The results of the benchmark demonstrated that the developed methodology captured the desired phenomena accurately. Subsequently, a high fidelity SMR core model was developed and assessed. Results of the analysis revealed an inherently stable SMR design at beginning of core life and end of core life under full-power and half-power conditions. The effect of axial discretization, stochastic noise and convergence of the Monte Carlo tallies in the calculations of the PAO and XAO parameters was investigated. All were found to be quite small and the inherently stable nature of the core design with respect to xenon-induced power oscillations was confirmed. Finally, a

  17. The predictive roles of neural oscillations in speech motor adaptability.

    PubMed

    Sengupta, Ranit; Nasir, Sazzad M

    2016-06-01

    The human speech system exhibits a remarkable flexibility by adapting to alterations in speaking environments. While it is believed that speech motor adaptation under altered sensory feedback involves rapid reorganization of speech motor networks, the mechanisms by which different brain regions communicate and coordinate their activity to mediate adaptation remain unknown, and explanations of outcome differences in adaption remain largely elusive. In this study, under the paradigm of altered auditory feedback with continuous EEG recordings, the differential roles of oscillatory neural processes in motor speech adaptability were investigated. The predictive capacities of different EEG frequency bands were assessed, and it was found that theta-, beta-, and gamma-band activities during speech planning and production contained significant and reliable information about motor speech adaptability. It was further observed that these bands do not work independently but interact with each other suggesting an underlying brain network operating across hierarchically organized frequency bands to support motor speech adaptation. These results provide novel insights into both learning and disorders of speech using time frequency analysis of neural oscillations.

  18. Resonant hopping of a robot controlled by an artificial neural oscillator.

    PubMed

    Pelc, Evan H; Daley, Monica A; Ferris, Daniel P

    2008-06-01

    The bouncing gaits of terrestrial animals (hopping, running, trotting) can be modeled as a hybrid dynamic system, with spring-mass dynamics during stance and ballistic motion during the aerial phase. We used a simple hopping robot controlled by an artificial neural oscillator to test the ability of the neural oscillator to adaptively drive this hybrid dynamic system. The robot had a single joint, actuated by an artificial pneumatic muscle in series with a tendon spring. We examined how the oscillator-robot system responded to variation in two neural control parameters: descending neural drive and neuromuscular gain. We also tested the ability of the oscillator-robot system to adapt to variations in mechanical properties by changing the series and parallel spring stiffnesses. Across a 100-fold variation in both supraspinal gain and muscle gain, hopping frequency changed by less than 10%. The neural oscillator consistently drove the system at the resonant half-period for the stance phase, and adapted to a new resonant half-period when the muscle series and parallel stiffnesses were altered. Passive cycling of elastic energy in the tendon accounted for 70-79% of the mechanical work done during each hop cycle. Our results demonstrate that hopping dynamics were largely determined by the intrinsic properties of the mechanical system, not the specific choice of neural oscillator parameters. The findings provide the first evidence that an artificial neural oscillator will drive a hybrid dynamic system at partial resonance.

  19. KDI: a wireless power-efficient modular platform for pre-clinical evaluation of implantable neural recording designs.

    PubMed

    Foerster, M; Burdin, F; Seignon, F; Lambert, A; Vasquez, C; Charvet, G

    2014-01-01

    This paper presents a power-efficient modular wireless platform which has been designed for prototyping and pre-clinical evaluations of neural recording implants. This Kit for Designing Implants (KDI) is separated in function specific modules of 34×34mm which can be assembled as needed. Five modules have been designed and optimized for ultra-low power consumption and a protective casing has been designed for pre-clinical trials. Two different wireless modules have been compared and the KDI performances have been evaluated in terms of modularity, wireless throughput and power consumption.

  20. Analysis of oscillator neural networks for sparsely coded phase patterns

    NASA Astrophysics Data System (ADS)

    Nomura, Masaki; Aoyagi, Toshio

    2000-12-01

    We study a simple extended model of oscillator neural networks capable of storing sparsely coded phase patterns, in which information is encoded both in the mean activity level and in the timing of spikes. Applying the methods of statistical neurodynamics to our model, we investigate theoretically the model's associative memory capability by evaluating its maximum storage capacities and deriving its basins of attraction. It is shown that, as in the Hopfield model, the storage capacity diverges as the activity level decreases. We consider various practically and theoretically important cases. For example, it is revealed that a dynamically adjusted threshold mechanism enhances the retrieval ability of the associative memory. It is also found that, under suitable conditions, the network can recall patterns even in the case that patterns with different activity levels are stored at the same time. In addition, we examine the robustness with respect to damage of the synaptic connections. The validity of these theoretical results is confirmed by reasonable agreement with numerical simulations.

  1. Optimal Hierarchical Modular Topologies for Producing Limited Sustained Activation of Neural Networks

    PubMed Central

    Kaiser, Marcus; Hilgetag, Claus C.

    2009-01-01

    An essential requirement for the representation of functional patterns in complex neural networks, such as the mammalian cerebral cortex, is the existence of stable regimes of network activation, typically arising from a limited parameter range. In this range of limited sustained activity (LSA), the activity of neural populations in the network persists between the extremes of either quickly dying out or activating the whole network. Hierarchical modular networks were previously found to show a wider parameter range for LSA than random or small-world networks not possessing hierarchical organization or multiple modules. Here we explored how variation in the number of hierarchical levels and modules per level influenced network dynamics and occurrence of LSA. We tested hierarchical configurations of different network sizes, approximating the large-scale networks linking cortical columns in one hemisphere of the rat, cat, or macaque monkey brain. Scaling of the network size affected the number of hierarchical levels and modules in the optimal networks, also depending on whether global edge density or the numbers of connections per node were kept constant. For constant edge density, only few network configurations, possessing an intermediate number of levels and a large number of modules, led to a large range of LSA independent of brain size. For a constant number of node connections, there was a trend for optimal configurations in larger-size networks to possess a larger number of hierarchical levels or more modules. These results may help to explain the trend to greater network complexity apparent in larger brains and may indicate that this complexity is required for maintaining stable levels of neural activation. PMID:20514144

  2. Synchrony arising from a balanced synaptic plasticity in a network of heterogeneous neural oscillators

    NASA Astrophysics Data System (ADS)

    Karbowski, Jan; Ermentrout, G. Bard

    2002-03-01

    We investigate the dynamics of a recurrent network of coupled heterogeneous neural oscillators with experimentally observed spike-timing-dependent synaptic plasticity. We show both theoretically and by computer simulations that, in a regime of a balance between synaptic potentiation and depression, the network of such oscillators converges to a stable synchronous state. The stability of this state is fostered by flexible synaptic weights which adjust themselves based on the relative timing of firing of pre- and postsynaptic oscillators.

  3. Gamma and delta neural oscillations and association with clinical symptoms under subanesthetic ketamine.

    PubMed

    Hong, L Elliot; Summerfelt, Ann; Buchanan, Robert W; O'Donnell, Patricio; Thaker, Gunvant K; Weiler, Martin A; Lahti, Adrienne C

    2010-02-01

    Several electrical neural oscillatory abnormalities have been associated with schizophrenia, although the underlying mechanisms of these oscillatory problems are unclear. Animal studies suggest that one of the key mechanisms of neural oscillations is through glutamatergic regulation; therefore, neural oscillations may provide a valuable animal-clinical interface on studying glutamatergic dysfunction in schizophrenia. To identify glutamatergic control of neural oscillation relevant to human subjects, we studied the effects of ketamine, an N-methyl-D-aspartate antagonist that can mimic some clinical aspects of schizophrenia, on auditory-evoked neural oscillations using a paired-click paradigm. This was a double-blind, placebo-controlled, crossover study of ketamine vs saline infusion on 10 healthy subjects. Clinically, infusion of ketamine in subanesthetic dose significantly increased thought disorder, withdrawal-retardation, and dissociative symptoms. Ketamine significantly augmented high-frequency oscillations (gamma band at 40-85 Hz, p=0.006) and reduced low-frequency oscillations (delta band at 1-5 Hz, p<0.001) compared with placebo. Importantly, the combined effect of increased gamma and reduced delta frequency oscillations was significantly associated with more withdrawal-retardation symptoms experienced during ketamine administration (p=0.02). Ketamine also reduced gating of the theta-alpha (5-12 Hz) range oscillation, an effect that mimics previously described deficits in schizophrenia patients and their first-degree relatives. In conclusion, acute ketamine appeared to mimic some aspects of neural oscillatory deficits in schizophrenia, and showed an opposite effect on scalp-recorded gamma vs low-frequency oscillations. These electrical oscillatory indexes of subanesthetic ketamine can be potentially used to cross-examine glutamatergic pharmacological effects in translational animal and human studies.

  4. Identifying robust and sensitive frequency bands for interrogating neural oscillations.

    PubMed

    Shackman, Alexander J; McMenamin, Brenton W; Maxwell, Jeffrey S; Greischar, Lawrence L; Davidson, Richard J

    2010-07-15

    Recent years have seen an explosion of interest in using neural oscillations to characterize the mechanisms supporting cognition and emotion. Oftentimes, oscillatory activity is indexed by mean power density in predefined frequency bands. Some investigators use broad bands originally defined by prominent surface features of the spectrum. Others rely on narrower bands originally defined by spectral factor analysis (SFA). Presently, the robustness and sensitivity of these competing band definitions remains unclear. Here, a Monte Carlo-based SFA strategy was used to decompose the tonic ("resting" or "spontaneous") electroencephalogram (EEG) into five bands: delta (1-5Hz), alpha-low (6-9Hz), alpha-high (10-11Hz), beta (12-19Hz), and gamma (>21Hz). This pattern was consistent across SFA methods, artifact correction/rejection procedures, scalp regions, and samples. Subsequent analyses revealed that SFA failed to deliver enhanced sensitivity; narrow alpha sub-bands proved no more sensitive than the classical broadband to individual differences in temperament or mean differences in task-induced activation. Other analyses suggested that residual ocular and muscular artifact was the dominant source of activity during quiescence in the delta and gamma bands. This was observed following threshold-based artifact rejection or independent component analysis (ICA)-based artifact correction, indicating that such procedures do not necessarily confer adequate protection. Collectively, these findings highlight the limitations of several commonly used EEG procedures and underscore the necessity of routinely performing exploratory data analyses, particularly data visualization, prior to hypothesis testing. They also suggest the potential benefits of using techniques other than SFA for interrogating high-dimensional EEG datasets in the frequency or time-frequency (event-related spectral perturbation, event-related synchronization/desynchronization) domains.

  5. Identifying Robust and Sensitive Frequency Bands for Interrogating Neural Oscillations

    PubMed Central

    Shackman, Alexander J.; McMenamin, Brenton W.; Maxwell, Jeffrey S.; Greischar, Lawrence L.; Davidson, Richard J.

    2010-01-01

    Recent years have seen an explosion of interest in using neural oscillations to characterize the mechanisms supporting cognition and emotion. Oftentimes, oscillatory activity is indexed by mean power density in predefined frequency bands. Some investigators use broad bands originally defined by prominent surface features of the spectrum. Others rely on narrower bands originally defined by spectral factor analysis (SFA). Presently, the robustness and sensitivity of these competing band definitions remains unclear. Here, a Monte Carlo-based SFA strategy was used to decompose the tonic (“resting” or “spontaneous”) electroencephalogram (EEG) into five bands: delta (1–5Hz), alpha-low (6–9Hz), alpha-high (10–11Hz), beta (12–19Hz), and gamma (>21Hz). This pattern was consistent across SFA methods, artifact correction/rejection procedures, scalp regions, and samples. Subsequent analyses revealed that SFA failed to deliver enhanced sensitivity; narrow alpha sub-bands proved no more sensitive than the classical broadband to individual differences in temperament or mean differences in task-induced activation. Other analyses suggested that residual ocular and muscular artifact was the dominant source of activity during quiescence in the delta and gamma bands. This was observed following threshold-based artifact rejection or independent component analysis (ICA)-based artifact correction, indicating that such procedures do not necessarily confer adequate protection. Collectively, these findings highlight the limitations of several commonly used EEG procedures and underscore the necessity of routinely performing exploratory data analyses, particularly data visualization, prior to hypothesis testing. They also suggest the potential benefits of using techniques other than SFA for interrogating high-dimensional EEG datasets in the frequency or time-frequency (event-related spectral perturbation, event-related synchronization / desynchronization) domains. PMID

  6. Impulsivity and the Modular Organization of Resting-State Neural Networks

    PubMed Central

    Davis, F. Caroline; Knodt, Annchen R.; Sporns, Olaf; Lahey, Benjamin B.; Zald, David H.; Brigidi, Bart D.; Hariri, Ahmad R.

    2013-01-01

    Impulsivity is a complex trait associated with a range of maladaptive behaviors, including many forms of psychopathology. Previous research has implicated multiple neural circuits and neurotransmitter systems in impulsive behavior, but the relationship between impulsivity and organization of whole-brain networks has not yet been explored. Using graph theory analyses, we characterized the relationship between impulsivity and the functional segregation (“modularity”) of the whole-brain network architecture derived from resting-state functional magnetic resonance imaging (fMRI) data. These analyses revealed remarkable differences in network organization across the impulsivity spectrum. Specifically, in highly impulsive individuals, regulatory structures including medial and lateral regions of the prefrontal cortex were isolated from subcortical structures associated with appetitive drive, whereas these brain areas clustered together within the same module in less impulsive individuals. Further exploration of the modular organization of whole-brain networks revealed novel shifts in the functional connectivity between visual, sensorimotor, cortical, and subcortical structures across the impulsivity spectrum. The current findings highlight the utility of graph theory analyses of resting-state fMRI data in furthering our understanding of the neurobiological architecture of complex behaviors. PMID:22645253

  7. Simultaneous neural control of simple reaching and grasping with the modular prosthetic limb using intracranial EEG.

    PubMed

    Fifer, Matthew S; Hotson, Guy; Wester, Brock A; McMullen, David P; Wang, Yujing; Johannes, Matthew S; Katyal, Kapil D; Helder, John B; Para, Matthew P; Vogelstein, R Jacob; Anderson, William S; Thakor, Nitish V; Crone, Nathan E

    2014-05-01

    Intracranial electroencephalographic (iEEG) signals from two human subjects were used to achieve simultaneous neural control of reaching and grasping movements with the Johns Hopkins University Applied Physics Lab (JHU/APL) Modular Prosthetic Limb (MPL), a dexterous robotic prosthetic arm. We performed functional mapping of high gamma activity while the subject made reaching and grasping movements to identify task-selective electrodes. Independent, online control of reaching and grasping was then achieved using high gamma activity from a small subset of electrodes with a model trained on short blocks of reaching and grasping with no further adaptation. Classification accuracy did not decline (p < 0.05, one-way ANOVA) over three blocks of testing in either subject. Mean classification accuracy during independently executed overt reach and grasp movements for (Subject 1, Subject 2) were (0.85, 0.81) and (0.80, 0.96), respectively, and during simultaneous execution they were (0.83, 0.88) and (0.58, 0.88), respectively. Our models leveraged knowledge of the subject's individual functional neuroanatomy for reaching and grasping movements, allowing rapid acquisition of control in a time-sensitive clinical setting. We demonstrate the potential feasibility of verifying functionally meaningful iEEG-based control of the MPL prior to chronic implantation, during which additional capabilities of the MPL might be exploited with further training.

  8. Simultaneous Neural Control of Simple Reaching and Grasping with the Modular Prosthetic Limb using Intracranial EEG

    PubMed Central

    Fifer, Matthew S.; Hotson, Guy; Wester, Brock A.; McMullen, David; Wang, Yujing; Johannes, Matthew S.; Katyal, Kapil D.; Helder, John B.; Para, Matthew P.; Vogelstein, R. Jacob; Anderson, William S.; Thakor, Nitish V.; Crone, Nathan E.

    2014-01-01

    Intracranial electroencephalographic (iEEG) signals from two human subjects were used to achieve simultaneous neural control of reaching and grasping movements with the Johns Hopkins University Applied Physics Lab (JHU/APL) Modular Prosthetic Limb (MPL), a dexterous robotic prosthetic arm. We performed functional mapping of high gamma activity while the subject made reaching and grasping movements to identify task-selective electrodes. Independent, online control of reaching and grasping was then achieved using high gamma activity from a small subset of electrodes with a model trained on short blocks of reaching and grasping with no further adaptation. Classification accuracy did not decline (p<0.05, one-way ANOVA) over three blocks of testing in either subject. Mean classification accuracy during independently executed overt reach and grasp movements for (Subject 1, Subject 2) were (0.85, 0.81) and (0.80, 0.96) respectively, and during simultaneous execution they were (0.83, 0.88) and (0.58, 0.88) respectively. Our models leveraged knowledge of the subject's individual functional neuroanatomy for reaching and grasping movements, allowing rapid acquisition of control in a time-sensitive clinical setting. We demonstrate the potential feasibility of verifying functionally meaningful iEEG-based control of the MPL prior to chronic implantation, during which additional capabilities of the MPL might be exploited with further training. PMID:24235276

  9. Neural oscillations during non-rapid eye movement sleep as biomarkers of circuit dysfunction in schizophrenia.

    PubMed

    Gardner, Richard J; Kersanté, Flavie; Jones, Matthew W; Bartsch, Ullrich

    2014-04-01

    The neurophysiology of non-rapid eye movement sleep is characterized by the occurrence of neural network oscillations with distinct origins and frequencies, which act in concert to support sleep-dependent information processing. Thalamocortical circuits generate slow (0.25-4 Hz) oscillations reflecting synchronized temporal windows of cortical activity, whereas concurrent waxing and waning spindle oscillations (8-15 Hz) act to facilitate cortical plasticity. Meanwhile, fast (140-200 Hz) and brief (< 200 ms) hippocampal ripple oscillations are associated with the reactivation of neural assemblies recruited during prior wakefulness. The extent of the forebrain areas engaged by these oscillations, and the variety of cellular and synaptic mechanisms involved, make them sensitive assays of distributed network function. Each of these three oscillations makes crucial contributions to the offline memory consolidation processes supported by non-rapid eye movement sleep. Slow, spindle and ripple oscillations are therefore potential surrogates of cognitive function and may be used as diagnostic measures in a range of brain diseases. We review the evidence for disrupted slow, spindle and ripple oscillations in schizophrenia, linking pathophysiological mechanisms to the functional impact of these neurophysiological changes and drawing links with the cognitive symptoms that accompany this condition. Finally, we discuss potential therapies that may normalize the coordinated activity of these three oscillations in order to restore healthy cognitive function. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  10. Neural oscillations as a translational tool in schizophrenia research: rationale, paradigms and challenges.

    PubMed

    Phillips, Keith G; Uhlhaas, Peter J

    2015-02-01

    Neural oscillations have received recently a great deal of interest in schizophrenia research because of the possibility to integrate findings from non-invasive electro/magnetoencephalographical recordings with pre-clinical research, which could potentially lead to the identification of pathophysiological mechanisms and novel treatment targets. In the current paper, we review the potential as well as the challenges of this approach by summarizing findings on alterations in rhythmic activity from both animal models and human data which have implicated dysfunctional neural oscillations in the explanation of cognitive deficits and certain clinical symptoms of schizophrenia. Specifically, we will focus on findings that have examined neural oscillations during 1) perceptual processing, 2) working memory and executive processes and 3) spontaneous activity. The importance of the development of paradigms suitable for human and animal models is discussed as well as the search for mechanistic explanation for oscillatory dysfunctions. © The Author(s) 2015.

  11. Quantitative prediction of intermittent high-frequency oscillations in neural networks with supralinear dendritic interactions

    PubMed Central

    Memmesheimer, Raoul-Martin

    2010-01-01

    The explanation of higher neural processes requires an understanding of the dynamics of complex, spiking neural networks. So far, modeling studies have focused on networks with linear or sublinear dendritic input summation. However, recent single-neuron experiments have demonstrated strongly supralinear dendritic enhancement of synchronous inputs. What are the implications of this amplification for networks of neurons? Here, I show numerically and analytically that such networks can generate intermittent, strong increases of activity with high-frequency oscillations; the models developed predict the shape of these events and the oscillation frequency. As an example, for the hippocampal region CA1, events with 200-Hz oscillations are predicted. I argue that these dynamics provide a plausible explanation for experimentally observed sharp-wave/ripple events. High-frequency oscillations can involve the replay of spike patterns. The models suggest that these patterns may reflect underlying network structures. PMID:20511534

  12. Beta band oscillations in motor cortex reflect neural population signals that delay movement onset

    PubMed Central

    Khanna, Preeya; Carmena, Jose M

    2017-01-01

    Motor cortical beta oscillations have been reported for decades, yet their behavioral correlates remain unresolved. Some studies link beta oscillations to changes in underlying neural activity, but the specific behavioral manifestations of these reported changes remain elusive. To investigate how changes in population neural activity, beta oscillations, and behavior are linked, we recorded multi-scale neural activity from motor cortex while three macaques performed a novel neurofeedback task. Subjects volitionally brought their beta oscillatory power to an instructed state and subsequently executed an arm reach. Reaches preceded by a reduction in beta power exhibited significantly faster movement onset times than reaches preceded by an increase in beta power. Further, population neural activity was found to shift farther from a movement onset state during beta oscillations that were neurofeedback-induced or naturally occurring during reaching tasks. This finding establishes a population neural basis for slowed movement onset following periods of beta oscillatory activity. DOI: http://dx.doi.org/10.7554/eLife.24573.001 PMID:28467303

  13. Towards a proper estimation of phase-amplitude coupling in neural oscillations

    PubMed Central

    Dvorak, Dino; Fenton, André A.

    2014-01-01

    Background The phase-amplitude coupling (PAC) between distinct neural oscillations is critical to brain functions that include cross-scale organization, selection of attention, routing the flow of information through neural circuits, memory processing and information coding. Several methods for PAC estimation have been proposed but the limitations of PAC estimation as well as the assumptions about the data for accurate PAC estimation are unclear. New Method We define boundary conditions for standard PAC algorithms and propose “oscillation-triggered coupling” (OTC), a parameter-free, data-driven algorithm for unbiased estimation of PAC. OTC establishes a unified framework that treats individual oscillations as discrete events for estimating PAC from a set of oscillations and for characterizing events from time windows as short as a single modulating oscillation. Results For accurate PAC estimation, standard PAC algorithms require amplitude filters with a bandwidth at least twice the modulatory frequency. The phase filters must be moderately narrow-band, especially when the modulatory rhythm is non-sinusoidal. The minimally appropriate analysis window is ~10 seconds. We then demonstrate that OTC can characterize PAC by treating neural oscillations as discrete events rather than continuous phase and amplitude time series. Comparison with existing methods These findings show that in addition to providing the same information about PAC as the standard approach, OTC facilitates characterization of single oscillations and their sequences, in addition to explaining the role of individual oscillations in generating PAC patterns. Conclusions OTC allows PAC analysis at the level of individual oscillations and therefore enables investigation of PAC at the time scales of cognitive phenomena. PMID:24447842

  14. Emergence of Slow Collective Oscillations in Neural Networks with Spike-Timing Dependent Plasticity

    NASA Astrophysics Data System (ADS)

    Mikkelsen, Kaare; Imparato, Alberto; Torcini, Alessandro

    2013-05-01

    The collective dynamics of excitatory pulse coupled neurons with spike-timing dependent plasticity is studied. The introduction of spike-timing dependent plasticity induces persistent irregular oscillations between strongly and weakly synchronized states, reminiscent of brain activity during slow-wave sleep. We explain the oscillations by a mechanism, the Sisyphus Effect, caused by a continuous feedback between the synaptic adjustments and the coherence in the neural firing. Due to this effect, the synaptic weights have oscillating equilibrium values, and this prevents the system from relaxing into a stationary macroscopic state.

  15. A Modular Approach to Model Oscillating Control Surfaces Using Navier Stokes Equations

    NASA Technical Reports Server (NTRS)

    Guruswamy, Guru P.; Lee, Henry

    2014-01-01

    The use of active controls for rotorcraft is becoming more important for modern aerospace configurations. Efforts to reduce the vibrations of helicopter blades with use of active-controls are in progress. Modeling oscillating control surfaces using the linear aerodynamics theory is well established. However, higher-fidelity methods are needed to account for nonlinear effects, such as those that occur in transonic flow. The aeroelastic responses of a wing with an oscillating control surface, computed using the transonic small perturbation (TSP) theory, have been shown to cause important transonic flow effects such as a reversal of control surface effectiveness that occurs as the shock wave crosses the hinge line. In order to account for flow complexities such as blade-vortex interactions of rotor blades higher-fidelity methods based on the Navier-Stokes equations are used. Reference 6 presents a procedure that uses the Navier-Stokes equations with moving-sheared grids and demonstrates up to 8 degrees of control-surface amplitude, using a single grid. Later, this procedure was extended to accommodate larger amplitudes, based on sliding grid zones. The sheared grid method implemented in EulerlNavier-Stokes-based aeroelastic code ENS AERO was successfully applied to active control design by industry. Recently there are several papers that present results for oscillating control surface using Reynolds Averaged Navier-Stokes (RANS) equations. References 9 and 10 report 2-D cases by filling gaps with overset grids. Reference 9 compares integrated forces with the experiment at low oscillating frequencies whereas Ref. 10 reports parametric studies but with no validation. Reference II reports results for a 3D case by modeling the gap region with a deformed grid and compares force results with the experiment only at the mid-span of flap. In Ref. II grid is deformed to match the control surface deflections at the section where the measurements are made. However, there is no

  16. Distinction between Neural and Vascular BOLD Oscillations and Intertwined Heart Rate Oscillations at 0.1 Hz in the Resting State and during Movement

    PubMed Central

    Pfurtscheller, Gert; Schwerdtfeger, Andreas; Brunner, Clemens; Aigner, Christoph; Fink, David; Brito, Joana; Carmo, Marciano P.; Andrade, Alexandre

    2017-01-01

    In the resting state, blood oxygen level-dependent (BOLD) oscillations with a frequency of about 0.1 Hz are conspicuous. Whether their origin is neural or vascular is not yet fully understood. Furthermore, it is not clear whether these BOLD oscillations interact with slow oscillations in heart rate (HR). To address these two questions, we estimated phase-locking (PL) values between precentral gyrus (PCG) and insula in 25 scanner-naïve individuals during rest and stimulus-paced finger movements in both hemispheres. PL was quantified in terms of time delay and duration in the frequency band 0.07 to 0.13 Hz. Results revealed both positive and negative time delays. Positive time delays characterize neural BOLD oscillations leading in the PCG, whereas negative time delays represent vascular BOLD oscillations leading in the insula. About 50% of the participants revealed positive time delays distinctive for neural BOLD oscillations, either with short or long unilateral or bilateral phase-locking episodes. An expected preponderance of neural BOLD oscillations was found in the left hemisphere during right-handed movement and unexpectedly in the right hemisphere during rest. Only neural BOLD oscillations were significantly associated with heart rate variability (HRV) in the 0.1-Hz range in the first resting state. It is well known that participating in magnetic resonance imaging (MRI) studies may be frightening and cause anxiety. In this respect it is important to note that the most significant hemispheric asymmetry (p<0.002) with a right-sided dominance of neural BOLD and a left-sided dominance of vascular BOLD oscillations was found in the first resting session in the scanner-naïve individuals. Whether the enhanced left-sided perfusion (dominance of vascular BOLD) or the right-sided dominance of neural BOLD is related to the increased level of anxiety, attention or stress needs further research. PMID:28052074

  17. Distinction between Neural and Vascular BOLD Oscillations and Intertwined Heart Rate Oscillations at 0.1 Hz in the Resting State and during Movement.

    PubMed

    Pfurtscheller, Gert; Schwerdtfeger, Andreas; Brunner, Clemens; Aigner, Christoph; Fink, David; Brito, Joana; Carmo, Marciano P; Andrade, Alexandre

    2017-01-01

    In the resting state, blood oxygen level-dependent (BOLD) oscillations with a frequency of about 0.1 Hz are conspicuous. Whether their origin is neural or vascular is not yet fully understood. Furthermore, it is not clear whether these BOLD oscillations interact with slow oscillations in heart rate (HR). To address these two questions, we estimated phase-locking (PL) values between precentral gyrus (PCG) and insula in 25 scanner-naïve individuals during rest and stimulus-paced finger movements in both hemispheres. PL was quantified in terms of time delay and duration in the frequency band 0.07 to 0.13 Hz. Results revealed both positive and negative time delays. Positive time delays characterize neural BOLD oscillations leading in the PCG, whereas negative time delays represent vascular BOLD oscillations leading in the insula. About 50% of the participants revealed positive time delays distinctive for neural BOLD oscillations, either with short or long unilateral or bilateral phase-locking episodes. An expected preponderance of neural BOLD oscillations was found in the left hemisphere during right-handed movement and unexpectedly in the right hemisphere during rest. Only neural BOLD oscillations were significantly associated with heart rate variability (HRV) in the 0.1-Hz range in the first resting state. It is well known that participating in magnetic resonance imaging (MRI) studies may be frightening and cause anxiety. In this respect it is important to note that the most significant hemispheric asymmetry (p<0.002) with a right-sided dominance of neural BOLD and a left-sided dominance of vascular BOLD oscillations was found in the first resting session in the scanner-naïve individuals. Whether the enhanced left-sided perfusion (dominance of vascular BOLD) or the right-sided dominance of neural BOLD is related to the increased level of anxiety, attention or stress needs further research.

  18. Stimulus statistics shape oscillations in nonlinear recurrent neural networks.

    PubMed

    Lefebvre, Jérémie; Hutt, Axel; Knebel, Jean-François; Whittingstall, Kevin; Murray, Micah M

    2015-02-18

    Rhythmic activity plays a central role in neural computations and brain functions ranging from homeostasis to attention, as well as in neurological and neuropsychiatric disorders. Despite this pervasiveness, little is known about the mechanisms whereby the frequency and power of oscillatory activity are modulated, and how they reflect the inputs received by neurons. Numerous studies have reported input-dependent fluctuations in peak frequency and power (as well as couplings across these features). However, it remains unresolved what mediates these spectral shifts among neural populations. Extending previous findings regarding stochastic nonlinear systems and experimental observations, we provide analytical insights regarding oscillatory responses of neural populations to stimulation from either endogenous or exogenous origins. Using a deceptively simple yet sparse and randomly connected network of neurons, we show how spiking inputs can reliably modulate the peak frequency and power expressed by synchronous neural populations without any changes in circuitry. Our results reveal that a generic, non-nonlinear and input-induced mechanism can robustly mediate these spectral fluctuations, and thus provide a framework in which inputs to the neurons bidirectionally regulate both the frequency and power expressed by synchronous populations. Theoretical and computational analysis of the ensuing spectral fluctuations was found to reflect the underlying dynamics of the input stimuli driving the neurons. Our results provide insights regarding a generic mechanism supporting spectral transitions observed across cortical networks and spanning multiple frequency bands.

  19. Patterns of theta oscillation reflect the neural basis of individual differences in epistemic motivation

    PubMed Central

    Mussel, Patrick; Ulrich, Natalie; Allen, John J. B.; Osinsky, Roman; Hewig, Johannes

    2016-01-01

    Theta oscillations in the EEG have been shown to reflect ongoing cognitive processes related to mental effort. Here, we show that the pattern of theta oscillation in response to varying cognitive demands reflects stable individual differences in the personality trait epistemic motivation: Individuals with high levels of epistemic motivation recruit relatively more cognitive resources in response to situations possessing high, compared to low, cognitive demand; individuals with low levels do not show such a specific response. Our results provide direct evidence for the theory of the construct need for cognition and add to our understanding of the neural processes underlying theta oscillations. More generally, we provide an explanation how individual differences in personality traits might be represented on a neural level. PMID:27380648

  20. Information coding via spontaneous oscillations in neural ensembles

    NASA Astrophysics Data System (ADS)

    Wang, Yuqing; Wang, Z. D.

    2000-07-01

    How information is encoded and decoded via spontaneous oscillations is investigated by using an ensemble of Hodgkin-Huxley neurons. A signal can be encoded in spontaneous and highly irregular spike trains via high-order rate coding with the second-order statistics being relevant, in which the temporal structure and the correlation between the spikes are taken into account. Although the encoded information is implicitly contained in the spike train, it can be retrieved in the post-synaptic potential. The spontaneous oscillation is filtered and the irregularity of the spike train is suppressed. In particular, we show that an arbitrary signal can be transmitted reliably through spontaneous and highly irregular spike trains, and then be reconstructed downstream in the information transmission pathway.

  1. The Functional Role of Neural Oscillations in Non-Verbal Emotional Communication

    PubMed Central

    Symons, Ashley E.; El-Deredy, Wael; Schwartze, Michael; Kotz, Sonja A.

    2016-01-01

    Effective interpersonal communication depends on the ability to perceive and interpret nonverbal emotional expressions from multiple sensory modalities. Current theoretical models propose that visual and auditory emotion perception involves a network of brain regions including the primary sensory cortices, the superior temporal sulcus (STS), and orbitofrontal cortex (OFC). However, relatively little is known about how the dynamic interplay between these regions gives rise to the perception of emotions. In recent years, there has been increasing recognition of the importance of neural oscillations in mediating neural communication within and between functional neural networks. Here we review studies investigating changes in oscillatory activity during the perception of visual, auditory, and audiovisual emotional expressions, and aim to characterize the functional role of neural oscillations in nonverbal emotion perception. Findings from the reviewed literature suggest that theta band oscillations most consistently differentiate between emotional and neutral expressions. While early theta synchronization appears to reflect the initial encoding of emotionally salient sensory information, later fronto-central theta synchronization may reflect the further integration of sensory information with internal representations. Additionally, gamma synchronization reflects facilitated sensory binding of emotional expressions within regions such as the OFC, STS, and, potentially, the amygdala. However, the evidence is more ambiguous when it comes to the role of oscillations within the alpha and beta frequencies, which vary as a function of modality (or modalities), presence or absence of predictive information, and attentional or task demands. Thus, the synchronization of neural oscillations within specific frequency bands mediates the rapid detection, integration, and evaluation of emotional expressions. Moreover, the functional coupling of oscillatory activity across multiples

  2. The Functional Role of Neural Oscillations in Non-Verbal Emotional Communication.

    PubMed

    Symons, Ashley E; El-Deredy, Wael; Schwartze, Michael; Kotz, Sonja A

    2016-01-01

    Effective interpersonal communication depends on the ability to perceive and interpret nonverbal emotional expressions from multiple sensory modalities. Current theoretical models propose that visual and auditory emotion perception involves a network of brain regions including the primary sensory cortices, the superior temporal sulcus (STS), and orbitofrontal cortex (OFC). However, relatively little is known about how the dynamic interplay between these regions gives rise to the perception of emotions. In recent years, there has been increasing recognition of the importance of neural oscillations in mediating neural communication within and between functional neural networks. Here we review studies investigating changes in oscillatory activity during the perception of visual, auditory, and audiovisual emotional expressions, and aim to characterize the functional role of neural oscillations in nonverbal emotion perception. Findings from the reviewed literature suggest that theta band oscillations most consistently differentiate between emotional and neutral expressions. While early theta synchronization appears to reflect the initial encoding of emotionally salient sensory information, later fronto-central theta synchronization may reflect the further integration of sensory information with internal representations. Additionally, gamma synchronization reflects facilitated sensory binding of emotional expressions within regions such as the OFC, STS, and, potentially, the amygdala. However, the evidence is more ambiguous when it comes to the role of oscillations within the alpha and beta frequencies, which vary as a function of modality (or modalities), presence or absence of predictive information, and attentional or task demands. Thus, the synchronization of neural oscillations within specific frequency bands mediates the rapid detection, integration, and evaluation of emotional expressions. Moreover, the functional coupling of oscillatory activity across multiples

  3. Interacting oscillations in neural control of breathing: modeling and qualitative analysis

    PubMed Central

    Bacak, Bartholomew J.; Molkov, Yaroslav I.; Shevtsova, Natalia A.; Smith, Jeffrey C.; Rybak, Ilya A.

    2012-01-01

    In mammalian respiration, late-expiratory (late-E, or pre-inspiratory) oscillations emerge in abdominal motor output with increasing metabolic demands (e.g., during hypercapnia, hypoxia, etc.). These oscillations originate in the retrotrapezoid nucleus/parafacial respiratory group (RTN/pFRG) and couple with the respiratory oscillations generated by the interacting neural populations of the Bötzinger (BötC) and pre-Bötzinger (pre-BötC) complexes, representing the kernel of the respiratory central pattern generator. Recently, we analyzed experimental data on the generation of late-E oscillations and proposed a large-scale computational model that simulates the possible interactions between the BötC/pre-BötC and RTN/pFRG oscillations under different conditions. Here we describe a reduced model that maintains the essential features and architecture of the large-scale model, but relies on simplified activity-based descriptions of neural populations. This simplification allowed us to use methods of dynamical systems theory, such as fast-slow decomposition, bifurcation analysis, and phase plane analysis, to elucidate the mechanisms and dynamics of synchronization between the RTN/pFRG and BötC/pre-BötC oscillations. Three physiologically relevant behaviors have been analyzed: emergence and quantal acceleration of late-E oscillations during hypercapnia, transformation of the late-E activity into a biphasic-E activity during hypercapnic hypoxia, and quantal slowing of BötC/pre-BötC oscillations with the reduction of pre-BötC excitability. Each behavior is elicited by gradual changes in excitatory drives or other model parameters, reflecting specific changes in metabolic and/or physiological conditions. Our results provide important theoretical insights into interactions between RTN/pFRG and BötC/pre-BötC oscillations and the role of these interactions in the control of breathing under different metabolic conditions. PMID:20927576

  4. Cholinergic enhancement of visual attention and neural oscillations in the human brain.

    PubMed

    Bauer, Markus; Kluge, Christian; Bach, Dominik; Bradbury, David; Heinze, Hans Jochen; Dolan, Raymond J; Driver, Jon

    2012-03-06

    Cognitive processes such as visual perception and selective attention induce specific patterns of brain oscillations. The neurochemical bases of these spectral changes in neural activity are largely unknown, but neuromodulators are thought to regulate processing. The cholinergic system is linked to attentional function in vivo, whereas separate in vitro studies show that cholinergic agonists induce high-frequency oscillations in slice preparations. This has led to theoretical proposals that cholinergic enhancement of visual attention might operate via gamma oscillations in visual cortex, although low-frequency alpha/beta modulation may also play a key role. Here we used MEG to record cortical oscillations in the context of administration of a cholinergic agonist (physostigmine) during a spatial visual attention task in humans. This cholinergic agonist enhanced spatial attention effects on low-frequency alpha/beta oscillations in visual cortex, an effect correlating with a drug-induced speeding of performance. By contrast, the cholinergic agonist did not alter high-frequency gamma oscillations in visual cortex. Thus, our findings show that cholinergic neuromodulation enhances attentional selection via an impact on oscillatory synchrony in visual cortex, for low rather than high frequencies. We discuss this dissociation between high- and low-frequency oscillations in relation to proposals that lower-frequency oscillations are generated by feedback pathways within visual cortex.

  5. HIRREM™: a noninvasive, allostatic methodology for relaxation and auto-calibration of neural oscillations

    PubMed Central

    Gerdes, Lee; Gerdes, Peter; Lee, Sung W; H Tegeler, Charles

    2013-01-01

    Disturbances of neural oscillation patterns have been reported with many disease states. We introduce methodology for HIRREM™ (high-resolution, relational, resonance-based electroencephalic mirroring), also known as Brainwave Optimization™, a noninvasive technology to facilitate relaxation and auto-calibration of neural oscillations. HIRREM is a precision-guided technology for allostatic therapeutics, intended to help the brain calibrate its own functional set points to optimize fitness. HIRREM technology collects electroencephalic data through two-channel recordings and delivers a series of audible musical tones in near real time. Choices of tone pitch and timing are made by mathematical algorithms, principally informed by the dominant frequency in successive instants of time, to permit resonance between neural oscillatory frequencies and the musical tones. Relaxation of neural oscillations through HIRREM appears to permit auto-calibration toward greater hemispheric symmetry and more optimized proportionation of regional spectral power. To illustrate an application of HIRREM, we present data from a randomized clinical trial of HIRREM as an intervention for insomnia (n = 19). On average, there was reduction of right-dominant temporal lobe high-frequency (23–36 Hz) EEG asymmetry over the course of eight successive HIRREM sessions. There was a trend for correlation between reduction of right temporal lobe dominance and magnitude of insomnia symptom reduction. Disturbances of neural oscillation have implications for both neuropsychiatric health and downstream peripheral (somatic) physiology. The possibility of noninvasive optimization for neural oscillatory set points through HIRREM suggests potentially multitudinous roles for this technology. Research is currently ongoing to further explore its potential applications and mechanisms of action. PMID:23532171

  6. HIRREM™: a noninvasive, allostatic methodology for relaxation and auto-calibration of neural oscillations.

    PubMed

    Gerdes, Lee; Gerdes, Peter; Lee, Sung W; H Tegeler, Charles

    2013-03-01

    Disturbances of neural oscillation patterns have been reported with many disease states. We introduce methodology for HIRREM™ (high-resolution, relational, resonance-based electroencephalic mirroring), also known as Brainwave Optimization™, a noninvasive technology to facilitate relaxation and auto-calibration of neural oscillations. HIRREM is a precision-guided technology for allostatic therapeutics, intended to help the brain calibrate its own functional set points to optimize fitness. HIRREM technology collects electroencephalic data through two-channel recordings and delivers a series of audible musical tones in near real time. Choices of tone pitch and timing are made by mathematical algorithms, principally informed by the dominant frequency in successive instants of time, to permit resonance between neural oscillatory frequencies and the musical tones. Relaxation of neural oscillations through HIRREM appears to permit auto-calibration toward greater hemispheric symmetry and more optimized proportionation of regional spectral power. To illustrate an application of HIRREM, we present data from a randomized clinical trial of HIRREM as an intervention for insomnia (n = 19). On average, there was reduction of right-dominant temporal lobe high-frequency (23-36 Hz) EEG asymmetry over the course of eight successive HIRREM sessions. There was a trend for correlation between reduction of right temporal lobe dominance and magnitude of insomnia symptom reduction. Disturbances of neural oscillation have implications for both neuropsychiatric health and downstream peripheral (somatic) physiology. The possibility of noninvasive optimization for neural oscillatory set points through HIRREM suggests potentially multitudinous roles for this technology. Research is currently ongoing to further explore its potential applications and mechanisms of action.

  7. Synchrony and chaos in coupled oscillators and neural networks

    NASA Astrophysics Data System (ADS)

    Raghavachari, Sridhar

    1999-09-01

    This dissertation studies the dynamics of ensembles of coupled, dynamical elements with discrete and continuous time dynamics. Specific problems include the appearance of synchronous behavior in an ensemble of dynamical elements. We show that the dynamics of coupled map lattices with connectivity that scales with inter-site distance exhibit a transition from spatial disorder to spatially uniform temporal chaos as the scaling varies. We investigate the eigenvalue spectrum of the stochastic matrix characterizing fluctuations from the uniform state numerically and show that the spectrum is bounded, real and the largest eigenvalue (corresponding to the uniform solution) has a gap separating it from the remaining N-1 eigenvalues which correspond to non-uniform solutions. The width of this gap depends on the scaling exponent. We relate the stability of the uniform state to this gap and show that the state is globally stable even in a strongly chaotic region of the uncoupled map. Bursting is a prototypical pattern of voltage oscillations of membrane potentials of biological cells, where the membrane potential alternates between fast oscillations and a slow drift. These complex oscillations arise as a result of interactions between the kinetics of fast and slow ion channels. While bursting in isolated cells Is, well understood, the study of populations of interacting bursters is less developed. We study a one- dimensional continuum model of bursting and show that a spatial wave of bursting separating active and quiescent cells extinguishes synchronous bursting when the coupling is weak. This result places bounds on the measured values of coupling strength between secretory cells in the pancreas. The interactions of cellular and synaptic mechanisms acting on several timescales control rhythmic behavior in animals, such as locomotion, digestion and respiration. We explore a simple rhythmic circuit model with two cells reciprocally inhibiting each other with fast and slow

  8. Stationary oscillation of an impulsive delayed system and its application to chaotic neural networks.

    PubMed

    Sun, Jitao; Lin, Hai

    2008-09-01

    This paper investigates the stationary oscillation for an impulsive delayed system which represents a class of nonlinear hybrid systems. First, a new concept of S-stability is introduced for nonlinear impulsive delayed systems. Based on this new concept and fixed point theorem, the relationship between S-stability and stationary oscillation (i.e., existence, uniqueness and global stability of periodic solutions) for the nonlinear impulsive delayed system is explored. It is shown that the nonlinear impulsive delayed system has a stationary oscillation if the system is S-stable. Second, an easily verifiable sufficient condition is then obtained for stationary oscillations of nonautonomous neural networks with both time delays and impulses by using the new criterion. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed method.

  9. Fast and robust image segmentation by small-world neural oscillator networks.

    PubMed

    Li, Chunguang; Li, Yuke

    2011-06-01

    Inspired by the temporal correlation theory of brain functions, researchers have presented a number of neural oscillator networks to implement visual scene segmentation problems. Recently, it is shown that many biological neural networks are typical small-world networks. In this paper, we propose and investigate two small-world models derived from the well-known LEGION (locally excitatory and globally inhibitory oscillator network) model. To form a small-world network, we add a proper proportion of unidirectional shortcuts (random long-range connections) to the original LEGION model. With local connections and shortcuts, the neural oscillators can not only communicate with neighbors but also exchange phase information with remote partners. Model 1 introduces excitatory shortcuts to enhance the synchronization within an oscillator group representing the same object. Model 2 goes further to replace the global inhibitor with a sparse set of inhibitory shortcuts. Simulation results indicate that the proposed small-world models could achieve synchronization faster than the original LEGION model and are more likely to bind disconnected image regions belonging together. In addition, we argue that these two models are more biologically plausible.

  10. Coordinated infraslow neural and cardiac oscillations mark fragility and offline periods in mammalian sleep.

    PubMed

    Lecci, Sandro; Fernandez, Laura M J; Weber, Frederik D; Cardis, Romain; Chatton, Jean-Yves; Born, Jan; Lüthi, Anita

    2017-02-01

    Rodents sleep in bouts lasting minutes; humans sleep for hours. What are the universal needs served by sleep given such variability? In sleeping mice and humans, through monitoring neural and cardiac activity (combined with assessment of arousability and overnight memory consolidation, respectively), we find a previously unrecognized hallmark of sleep that balances two fundamental yet opposing needs: to maintain sensory reactivity to the environment while promoting recovery and memory consolidation. Coordinated 0.02-Hz oscillations of the sleep spindle band, hippocampal ripple activity, and heart rate sequentially divide non-rapid eye movement (non-REM) sleep into offline phases and phases of high susceptibility to external stimulation. A noise stimulus chosen such that sleeping mice woke up or slept through at comparable rates revealed that offline periods correspond to raising, whereas fragility periods correspond to declining portions of the 0.02-Hz oscillation in spindle activity. Oscillations were present throughout non-REM sleep in mice, yet confined to light non-REM sleep (stage 2) in humans. In both species, the 0.02-Hz oscillation predominated over posterior cortex. The strength of the 0.02-Hz oscillation predicted superior memory recall after sleep in a declarative memory task in humans. These oscillations point to a conserved function of mammalian non-REM sleep that cycles between environmental alertness and internal memory processing in 20- to 25-s intervals. Perturbed 0.02-Hz oscillations may cause memory impairment and ill-timed arousals in sleep disorders.

  11. Coordinated infraslow neural and cardiac oscillations mark fragility and offline periods in mammalian sleep

    PubMed Central

    Lecci, Sandro; Fernandez, Laura M. J.; Weber, Frederik D.; Cardis, Romain; Chatton, Jean-Yves; Born, Jan; Lüthi, Anita

    2017-01-01

    Rodents sleep in bouts lasting minutes; humans sleep for hours. What are the universal needs served by sleep given such variability? In sleeping mice and humans, through monitoring neural and cardiac activity (combined with assessment of arousability and overnight memory consolidation, respectively), we find a previously unrecognized hallmark of sleep that balances two fundamental yet opposing needs: to maintain sensory reactivity to the environment while promoting recovery and memory consolidation. Coordinated 0.02-Hz oscillations of the sleep spindle band, hippocampal ripple activity, and heart rate sequentially divide non–rapid eye movement (non-REM) sleep into offline phases and phases of high susceptibility to external stimulation. A noise stimulus chosen such that sleeping mice woke up or slept through at comparable rates revealed that offline periods correspond to raising, whereas fragility periods correspond to declining portions of the 0.02-Hz oscillation in spindle activity. Oscillations were present throughout non-REM sleep in mice, yet confined to light non-REM sleep (stage 2) in humans. In both species, the 0.02-Hz oscillation predominated over posterior cortex. The strength of the 0.02-Hz oscillation predicted superior memory recall after sleep in a declarative memory task in humans. These oscillations point to a conserved function of mammalian non-REM sleep that cycles between environmental alertness and internal memory processing in 20- to 25-s intervals. Perturbed 0.02-Hz oscillations may cause memory impairment and ill-timed arousals in sleep disorders. PMID:28246641

  12. Neural Oscillations and a Nascent Corticohippocampal Theory of Reference.

    PubMed

    Nieuwland, Mante S; Martin, Andrea E

    2017-01-27

    The ability to use words to refer to the world is vital to the communicative power of human language. In particular, the anaphoric use of words to refer to previously mentioned concepts (antecedents) allows dialogue to be coherent and meaningful. Psycholinguistic theory posits that anaphor comprehension involves reactivating a memory representation of the antecedent. Whereas this implies the involvement of recognition memory or the mnemonic subroutines by which people distinguish old from new, the neural processes for reference resolution are largely unknown. Here, we report time-frequency analysis of four EEG experiments to reveal the increased coupling of functional neural systems associated with referentially coherent expressions compared with referentially problematic expressions. Despite varying in modality, language, and type of referential expression, all experiments showed larger gamma-band power for referentially coherent expressions compared with referentially problematic expressions. Beamformer analysis in high-density Experiment 4 localized the gamma-band increase to posterior parietal cortex around 400-600 msec after anaphor onset and to frontal-temporal cortex around 500-1000 msec. We argue that the observed gamma-band power increases reflect successful referential binding and resolution, which links incoming information to antecedents through an interaction between the brain's recognition memory networks and frontal-temporal language network. We integrate these findings with previous results from patient and neuroimaging studies, and we outline a nascent corticohippocampal theory of reference.

  13. Cooperative recurrent modular neural networks for constrained optimization: a survey of models and applications

    PubMed Central

    2008-01-01

    Constrained optimization problems arise in a wide variety of scientific and engineering applications. Since several single recurrent neural networks when applied to solve constrained optimization problems for real-time engineering applications have shown some limitations, cooperative recurrent neural network approaches have been developed to overcome drawbacks of these single recurrent neural networks. This paper surveys in details work on cooperative recurrent neural networks for solving constrained optimization problems and their engineering applications, and points out their standing models from viewpoint of both convergence to the optimal solution and model complexity. We provide examples and comparisons to shown advantages of these models in the given applications. PMID:19003467

  14. Using Neural Pattern Classifiers to Quantify the Modularity of Conflict–Control Mechanisms in the Human Brain

    PubMed Central

    Jiang, Jiefeng; Egner, Tobias

    2014-01-01

    Resolving conflicting sensory and motor representations is a core function of cognitive control, but it remains uncertain to what degree control over different sources of conflict is implemented by shared (domain general) or distinct (domain specific) neural resources. Behavioral data suggest conflict–control to be domain specific, but results from neuroimaging studies have been ambivalent. Here, we employed multivoxel pattern analyses that can decode a brain region's informational content, allowing us to distinguish incidental activation overlap from actual shared information processing. We trained independent sets of “searchlight” classifiers on functional magnetic resonance imaging data to decode control processes associated with stimulus-conflict (Stroop task) and ideomotor-conflict (Simon task). Quantifying the proportion of domain-specific searchlights (capable of decoding only one type of conflict) and domain-general searchlights (capable of decoding both conflict types) in each subject, we found both domain-specific and domain-general searchlights, though the former were more common. When mapping anatomical loci of these searchlights across subjects, neural substrates of stimulus- and ideomotor-specific conflict–control were found to be anatomically consistent across subjects, whereas the substrates of domain-general conflict–control were not. Overall, these findings suggest a hybrid neural architecture of conflict–control that entails both modular (domain specific) and global (domain general) components. PMID:23402762

  15. Dynamic transitions among multiple oscillators of synchronized bursts in cultured neural networks

    NASA Astrophysics Data System (ADS)

    Hoan Kim, June; Heo, Ryoun; Choi, Joon Ho; Lee, Kyoung J.

    2014-04-01

    Synchronized neural bursts are a salient dynamic feature of biological neural networks, having important roles in brain functions. This report investigates the deterministic nature behind seemingly random temporal sequences of inter-burst intervals generated by cultured networks of cortical cells. We found that the complex sequences were an intricate patchwork of several noisy ‘burst oscillators’, whose periods covered a wide dynamic range, from a few tens of milliseconds to tens of seconds. The transition from one type of oscillator to another favored a particular passage, while the dwelling time between two neighboring transitions followed an exponential distribution showing no memory. With different amounts of bicuculline or picrotoxin application, we could also terminate the oscillators, generate new ones or tune their periods.

  16. Automated Grading of Gliomas using Deep Learning in Digital Pathology Images: A modular approach with ensemble of convolutional neural networks.

    PubMed

    Ertosun, Mehmet Günhan; Rubin, Daniel L

    2015-01-01

    Brain glioma is the most common primary malignant brain tumors in adults with different pathologic subtypes: Lower Grade Glioma (LGG) Grade II, Lower Grade Glioma (LGG) Grade III, and Glioblastoma Multiforme (GBM) Grade IV. The survival and treatment options are highly dependent of this glioma grade. We propose a deep learning-based, modular classification pipeline for automated grading of gliomas using digital pathology images. Whole tissue digitized images of pathology slides obtained from The Cancer Genome Atlas (TCGA) were used to train our deep learning modules. Our modular pipeline provides diagnostic quality statistics, such as precision, sensitivity and specificity, of the individual deep learning modules, and (1) facilitates training given the limited data in this domain, (2) enables exploration of different deep learning structures for each module, (3) leads to developing less complex modules that are simpler to analyze, and (4) provides flexibility, permitting use of single modules within the framework or use of other modeling or machine learning applications, such as probabilistic graphical models or support vector machines. Our modular approach helps us meet the requirements of minimum accuracy levels that are demanded by the context of different decision points within a multi-class classification scheme. Convolutional Neural Networks are trained for each module for each sub-task with more than 90% classification accuracies on validation data set, and achieved classification accuracy of 96% for the task of GBM vs LGG classification, 71% for further identifying the grade of LGG into Grade II or Grade III on independent data set coming from new patients from the multi-institutional repository.

  17. Automated Grading of Gliomas using Deep Learning in Digital Pathology Images: A modular approach with ensemble of convolutional neural networks

    PubMed Central

    Ertosun, Mehmet Günhan; Rubin, Daniel L.

    2015-01-01

    Brain glioma is the most common primary malignant brain tumors in adults with different pathologic subtypes: Lower Grade Glioma (LGG) Grade II, Lower Grade Glioma (LGG) Grade III, and Glioblastoma Multiforme (GBM) Grade IV. The survival and treatment options are highly dependent of this glioma grade. We propose a deep learning-based, modular classification pipeline for automated grading of gliomas using digital pathology images. Whole tissue digitized images of pathology slides obtained from The Cancer Genome Atlas (TCGA) were used to train our deep learning modules. Our modular pipeline provides diagnostic quality statistics, such as precision, sensitivity and specificity, of the individual deep learning modules, and (1) facilitates training given the limited data in this domain, (2) enables exploration of different deep learning structures for each module, (3) leads to developing less complex modules that are simpler to analyze, and (4) provides flexibility, permitting use of single modules within the framework or use of other modeling or machine learning applications, such as probabilistic graphical models or support vector machines. Our modular approach helps us meet the requirements of minimum accuracy levels that are demanded by the context of different decision points within a multi-class classification scheme. Convolutional Neural Networks are trained for each module for each sub-task with more than 90% classification accuracies on validation data set, and achieved classification accuracy of 96% for the task of GBM vs LGG classification, 71% for further identifying the grade of LGG into Grade II or Grade III on independent data set coming from new patients from the multi-institutional repository. PMID:26958289

  18. Massively parallel classification of single-trial EEG signals using a min-max modular neural network.

    PubMed

    Lu, Bao-Liang; Shin, Jonghan; Ichikawa, Michinori

    2004-03-01

    This paper presents a method for classifying single-trial electroencephalogram (EEG) signals using min-max modular neural networks implemented in a massively parallel way. The method has three main steps. First, a large-scale, complex EEG classification problem is simply divided into a reasonable number of two-class subproblems, as small as needed. Second, the two-class subproblems are simply learned by individual smaller network modules in parallel. Finally, all the individual trained network modules are integrated into a hierarchical, parallel, and modular classifier according to two module combination laws. To demonstrate the effectiveness of the method, we perform simulations on fifteen different four-class EEG classification tasks, each of which consists of 1491 training and 636 test data. These EEG classification tasks were created using a set of non-averaged, single-trial hippocampal EEG signals recorded from rats; the features of the EEG signals are extracted using wavelet transform techniques. The experimental results indicate that the proposed method has several attractive features. 1) The method is appreciably faster than the existing approach that is based on conventional multilayer perceptrons. 2) Complete learning of complex EEG classification problems can be easily realized, and better generalization performance can be achieved. 3) The method scales up to large-scale, complex EEG classification problems.

  19. Singular Hopf bifurcations and mixed-mode oscillations in a two-cell inhibitory neural network

    NASA Astrophysics Data System (ADS)

    Curtu, Rodica

    2010-05-01

    Recent studies of a firing rate model for neural competition as observed in binocular rivalry and central pattern generators [R. Curtu, A. Shpiro, N. Rubin, J. Rinzel, Mechanisms for frequency control in neuronal competition models, SIAM J. Appl. Dyn. Syst. 7 (2) (2008) 609-649] showed that the variation of the stimulus strength parameter can lead to rich and interesting dynamics. Several types of behavior were identified such as: fusion, equivalent to a steady state of identical activity levels for both neural units; oscillations due to either an escape or a release mechanism; and a winner-take-all state of bistability. The model consists of two neural populations interacting through reciprocal inhibition, each endowed with a slow negative-feedback process in the form of spike frequency adaptation. In this paper we report the occurrence of another complex oscillatory pattern, the mixed-mode oscillations (MMOs). They exist in the model at the transition between the relaxation oscillator dynamical regime and the winner-take-all regime. The system distinguishes itself from other neuronal models where MMOs were found by the following interesting feature: there is no autocatalysis involved (as in the examples of voltage-gated persistent inward currents and/or intrapopulation recurrent excitation) and therefore the two cells in the network are not intrinsic oscillators; the oscillations are instead a combined result of the mutual inhibition and the adaptation. We prove that the MMOs are due to a singular Hopf bifurcation point situated in close distance to the transition point to the winner-take-all case. We also show that in the vicinity of the singular Hopf other types of bifurcations exist and we construct numerically the corresponding diagrams.

  20. Midfrontal conflict-related theta-band power reflects neural oscillations that predict behavior.

    PubMed

    Cohen, Michael X; Donner, Tobias H

    2013-12-01

    Action monitoring and conflict resolution require the rapid and flexible coordination of activity in multiple brain regions. Oscillatory neural population activity may be a key physiological mechanism underlying such rapid and flexible network coordination. EEG power modulations of theta-band (4-8 Hz) activity over the human midfrontal cortex during response conflict have been proposed to reflect neural oscillations that support conflict detection and resolution processes. However, it has remained unclear whether this frequency-band-specific activity reflects neural oscillations or nonoscillatory responses (i.e., event-related potentials). Here, we show that removing the phase-locked component of the EEG did not reduce the strength of the conflict-related modulation of the residual (i.e., non-phase-locked) theta power over midfrontal cortex. Furthermore, within-subject regression analyses revealed that the non-phase-locked theta power was a significantly better predictor of the conflict condition than was the time-domain phase-locked EEG component. Finally, non-phase-locked theta power showed robust and condition-specific (high- vs. low-conflict) cross-trial correlations with reaction time, whereas the phase-locked component did not. Taken together, our results indicate that most of the conflict-related and behaviorally relevant midfrontal EEG signal reflects a modulation of ongoing theta-band oscillations that occurs during the decision process but is not phase-locked to the stimulus or to the response.

  1. Hermite Functional Link Neural Network for Solving the Van der Pol-Duffing Oscillator Equation.

    PubMed

    Mall, Susmita; Chakraverty, S

    2016-08-01

    Hermite polynomial-based functional link artificial neural network (FLANN) is proposed here to solve the Van der Pol-Duffing oscillator equation. A single-layer hermite neural network (HeNN) model is used, where a hidden layer is replaced by expansion block of input pattern using Hermite orthogonal polynomials. A feedforward neural network model with the unsupervised error backpropagation principle is used for modifying the network parameters and minimizing the computed error function. The Van der Pol-Duffing and Duffing oscillator equations may not be solved exactly. Here, approximate solutions of these types of equations have been obtained by applying the HeNN model for the first time. Three mathematical example problems and two real-life application problems of Van der Pol-Duffing oscillator equation, extracting the features of early mechanical failure signal and weak signal detection problems, are solved using the proposed HeNN method. HeNN approximate solutions have been compared with results obtained by the well known Runge-Kutta method. Computed results are depicted in term of graphs. After training the HeNN model, we may use it as a black box to get numerical results at any arbitrary point in the domain. Thus, the proposed HeNN method is efficient. The results reveal that this method is reliable and can be applied to other nonlinear problems too.

  2. Stochastic Oscillation in Self-Organized Critical States of Small Systems: Sensitive Resting State in Neural Systems

    NASA Astrophysics Data System (ADS)

    Wang, Sheng-Jun; Ouyang, Guang; Guang, Jing; Zhang, Mingsha; Wong, K. Y. Michael; Zhou, Changsong

    2016-01-01

    Self-organized critical states (SOCs) and stochastic oscillations (SOs) are simultaneously observed in neural systems, which appears to be theoretically contradictory since SOCs are characterized by scale-free avalanche sizes but oscillations indicate typical scales. Here, we show that SOs can emerge in SOCs of small size systems due to temporal correlation between large avalanches at the finite-size cutoff, resulting from the accumulation-release process in SOCs. In contrast, the critical branching process without accumulation-release dynamics cannot exhibit oscillations. The reconciliation of SOCs and SOs is demonstrated both in the sandpile model and robustly in biologically plausible neuronal networks. The oscillations can be suppressed if external inputs eliminate the prominent slow accumulation process, providing a potential explanation of the widely studied Berger effect or event-related desynchronization in neural response. The features of neural oscillations and suppression are confirmed during task processing in monkey eye-movement experiments. Our results suggest that finite-size, columnar neural circuits may play an important role in generating neural oscillations around the critical states, potentially enabling functional advantages of both SOCs and oscillations for sensitive response to transient stimuli.

  3. Attractors and Spectral Characteristics of Neural Structures Based on the Model of the Quantum Harmonic Oscillator

    SciTech Connect

    Rigatos, Gerasimos G.

    2007-09-06

    Neural computation based on principles of quantum mechanics can provide improved models of memory processes and brain functioning and is of importance for the realization of quantum computing machines. To this end, this paper studies neural structures with weights that follow the model of the quantum harmonic oscillator. These weights correspond to diffusing particles, which interact to each other as the theory of Brownian motion predicts. The learning of the stochastic weights (convergence of the diffusing particles to an equilibrium) is analyzed. In the case of associative memories the proposed neural model results in an exponential increase of the number of attractors. Spectral analysis shows that the stochastic weights satisfy an equation which is analogous to the principle of uncertainty.

  4. Experimental evaluation of a neural-oscillator-driven active mass damper system

    NASA Astrophysics Data System (ADS)

    Iba, Daisuke; Hongu, Junichi

    2014-03-01

    This paper proposes a new active dynamic absorber control system for high-rise buildings using a neural oscillator and a map, which estimates the amplitude level of the oscillator, and shows some experimental results by using an apparatus, which realizes the proposed control algorithm. The proposed system decides the travel distance and direction of the auxiliary mass of the dynamic absorber using the output of oscillator, which is the filtering result of structure acceleration responses by the property of the oscillator, and Amplitude-Phase map (AP-map) for estimation of the structural response in specific frequency between synchronization region, and then, transfer the auxiliary mass to the predetermined location by using a position controller. In addition, the developed active dynamic absorber system is mounted on the top of the experimental single degree of freedom structure, which represents high-rise buildings, and consists of the auxiliary mass, a DC motor, a ball screw, a microcomputer, a laser displacement sensor, and an acceleration sensor. The proposed AP-map and the algorithm to determine the travel direction of the mass using the oscillator output are embedded in the microcomputer. This paper starts by illuminating the relation among subsystems of the proposed system with reference to a block diagram, and then, shows experimental responses of the whole system excited by earthquakes to confirm the validity of the proposed system.

  5. Different patterns of puberty effect in neural oscillation to negative stimuli: sex differences.

    PubMed

    Yuan, Jiajin; Ju, Enxia; Yang, Jiemin; Chen, Xuhai; Li, Hong

    2014-12-01

    The present study investigated the impact of puberty on sex differences in neural sensitivity to negative stimuli. Event-related oscillation technique was used. Because girls are more vulnerable to affective disturbances than boys during adolescence, it was hypothesized that puberty exerts different influences on neural sensitivity to negative stimuli in boys and girls. EEGs were recorded for highly negative (HN), mildly negative (MN) and neutral pictures, when boys and girls distinct in pubertal status performed a non-emotional distracting task. No emotion effect and its interaction with sex and puberty were observed in response latencies. However, puberty influenced the gamma-band oscillation effect for negative stimuli differently for boys and girls: Pre-pubertal boys showed a significant emotion effect for HN stimuli, whose size was decreased in pubertal boys. By contrast, there was a significant emotion effect for HN stimuli in pubertal girls but not in pre-pubertal girls. On the other hand, the size of the emotion effect for HN stimuli was similar for pre-pubertal boys and girls; while this effect was significantly more pronounced in pubertal girls compared to pubertal boys. Additionally, the size of the emotion effect in gamma oscillations decreased as a function of pubertal development during both HN and MN stimulation in boys. For girls, the emotion effect in gamma oscillations increased with pubertal development during HN stimulation. Thus, puberty is associated with reduced neural sensitivity in boys but increased sensitivity in girls, in reaction to negative stimuli. The implications of these results for the psychopathology during adolescence were discussed.

  6. Neural oscillation, network, eloquent cortex and epileptogenic zone revealed by magnetoencephalography and awake craniotomy

    PubMed Central

    Idris, Zamzuri; Kandasamy, Regunath; Reza, Faruque; Abdullah, Jafri M.

    2014-01-01

    Background: Magnetoencephalography (MEG) is a method of functional neuroimaging. The concomitant use of MEG and electrocorticography has been found to be useful in elucidating neural oscillation and network, and to localize epileptogenic zone and functional cortex. We describe our early experience using MEG in neurosurgical patients, emphasizing on its impact on patient management as well as the enrichment of our knowledge in neurosciences. Materials and Methods: A total of 10 subjects were included; five patients had intraaxial tumors, one with an extraaxial tumor and brain compression, two with arteriovenous malformations, one with cerebral peduncle hemorrhage and one with sensorimotor cortical dysplasia. All patients underwent evoked and spontaneous MEG recordings. MEG data was processed at band-pass filtering frequency of between 0.1 and 300 Hz with a sampling rate of 1 kHz. MEG source localization was performed using either overdetermined equivalent current dipoles or underdetermined inversed solution. Neuromag collection of events software was used to study brain network and epileptogenic zone. The studied data were analyzed for neural oscillation in three patients; brain network and clinical manifestation in five patients; and for the location of epileptogenic zone and eloquent cortex in two patients. Results: We elucidated neural oscillation in three patients. One demonstrated oscillatory phenomenon on stimulation of the motor-cortex during awake surgery, and two had improvement in neural oscillatory parameters after surgery. Brain networks corresponding to clinico-anatomical relationships were depicted in five patients, and two networks were illustrated here. Finally, we demonstrated epilepsy cases in which MEG data was found to be useful in localizing the epileptogenic zones and functional cortices. Conclusion: The application of MEG while enhancing our knowledge in neurosciences also has a useful role in epilepsy and awake surgery. PMID:25685205

  7. A Modular Neural Network Scheme Applied to Fault Diagnosis in Electric Power Systems

    PubMed Central

    Flores, Agustín; Morant, Francisco

    2014-01-01

    This work proposes a new method for fault diagnosis in electric power systems based on neural modules. With this method the diagnosis is performed by assigning a neural module for each type of component comprising the electric power system, whether it is a transmission line, bus or transformer. The neural modules for buses and transformers comprise two diagnostic levels which take into consideration the logic states of switches and relays, both internal and back-up, with the exception of the neural module for transmission lines which also has a third diagnostic level which takes into account the oscillograms of fault voltages and currents as well as the frequency spectrums of these oscillograms, in order to verify if the transmission line had in fact been subjected to a fault. One important advantage of the diagnostic system proposed is that its implementation does not require the use of a network configurator for the system; it does not depend on the size of the power network nor does it require retraining of the neural modules if the power network increases in size, making its application possible to only one component, a specific area, or the whole context of the power system. PMID:25610897

  8. A modular neural network scheme applied to fault diagnosis in electric power systems.

    PubMed

    Flores, Agustín; Quiles, Eduardo; García, Emilio; Morant, Francisco; Correcher, Antonio

    2014-01-01

    This work proposes a new method for fault diagnosis in electric power systems based on neural modules. With this method the diagnosis is performed by assigning a neural module for each type of component comprising the electric power system, whether it is a transmission line, bus or transformer. The neural modules for buses and transformers comprise two diagnostic levels which take into consideration the logic states of switches and relays, both internal and back-up, with the exception of the neural module for transmission lines which also has a third diagnostic level which takes into account the oscillograms of fault voltages and currents as well as the frequency spectrums of these oscillograms, in order to verify if the transmission line had in fact been subjected to a fault. One important advantage of the diagnostic system proposed is that its implementation does not require the use of a network configurator for the system; it does not depend on the size of the power network nor does it require retraining of the neural modules if the power network increases in size, making its application possible to only one component, a specific area, or the whole context of the power system.

  9. Knowledge-based modularization and global optimization of artificial neural network models in hydrological forecasting.

    PubMed

    Corzo, Gerald; Solomatine, Dimitri

    2007-05-01

    Natural phenomena are multistationary and are composed of a number of interacting processes, so one single model handling all processes often suffers from inaccuracies. A solution is to partition data in relation to such processes using the available domain knowledge or expert judgment, to train separate models for each of the processes, and to merge them in a modular model (committee). In this paper a problem of water flow forecast in watershed hydrology is considered where the flow process can be presented as consisting of two subprocesses -- base flow and excess flow, so that these two processes can be separated. Several approaches to data separation techniques are studied. Two case studies with different forecast horizons are considered. Parameters of the algorithms responsible for data partitioning are optimized using genetic algorithms and global pattern search. It was found that modularization of ANN models using domain knowledge makes models more accurate, if compared with a global model trained on the whole data set, especially when forecast horizon (and hence the complexity of the modelled processes) is increased.

  10. Global exponential periodicity of a class of recurrent neural networks with oscillating parameters and time-varying delays.

    PubMed

    Chen, Boshan; Wang, Jun

    2005-11-01

    In this paper, we present the analytical results on the global exponential periodicity of a class of recurrent neural networks with oscillating parameters and time-varying delays. Sufficient conditions are derived for ascertaining the existence, uniqueness and global exponential periodicity of the oscillatory solution of such recurrent neural networks by using the comparison principle and mixed monotone operator method. The periodicity results extend or improve existing stability results for the class of recurrent neural networks with and without time delays.

  11. Spectral factorization-based current source density analysis of ongoing neural oscillations.

    PubMed

    Chand, Ganesh B; Dhamala, Mukesh

    2014-03-15

    Current source density (CSD) analysis is widely used in neurophysiological investigations intended to reveal the patterns of localized neuronal activity in terms of current sources and sinks. CSD is based on the second spatial derivatives of multi-electrode electrophysiological recordings, and can be applied to brain activity related to repeated external stimulations (evoked brain activity) or ongoing (spontaneous) brain activity. In evoked brain activity, event-related time-series averages of ensembles are used to compute CSD patterns. However, for ongoing neural activity, the lack of external events requires a different approach other than ensemble averaging. Here, we propose a new spectral factorization-based current source density (SF-CSD) analysis method for ongoing neural oscillations. We validated this new SF-CSD analysis method using simulated data and demonstrated its effectiveness by applying to experimental intra-cortical local field potentials recorded on multi-contact depth electrodes from monkeys performing selective visual attention tasks. The proposed method gives space-unbiased estimates since it does not rely on a reference for CSD calculation in the frequency-domain. The proposed SF-CSD method is expected to be a useful tool for systematic analysis of neural sources and oscillations from multi-site electrophysiological recordings. Copyright © 2013 Elsevier B.V. All rights reserved.

  12. Time scales of spike-train correlation for neural oscillators with common drive.

    PubMed

    Barreiro, Andrea K; Shea-Brown, Eric; Thilo, Evan L

    2010-01-01

    We examine the effect of the phase-resetting curve on the transfer of correlated input signals into correlated output spikes in a class of neural models receiving noisy superthreshold stimulation. We use linear-response theory to approximate the spike correlation coefficient in terms of moments of the associated exit time problem and contrast the results for type I vs type II models and across the different time scales over which spike correlations can be assessed. We find that, on long time scales, type I oscillators transfer correlations much more efficiently than type II oscillators. On short time scales this trend reverses, with the relative efficiency switching at a time scale that depends on the mean and standard deviation of input currents. This switch occurs over time scales that could be exploited by downstream circuits.

  13. Effect of random synaptic dilution on recalling dynamics in an oscillator neural network

    NASA Astrophysics Data System (ADS)

    Kitano, Katsunori; Aoyagi, Toshio

    1998-05-01

    In the present paper, we study the effect of random synaptic dilution in an oscillator neural network in which information is encoded by the relative timing of neuronal firing. In order to analyze the recalling process in this oscillator network, we apply the method of statistical neurodynamics. The results show that the dynamical equations are described by some macroscopic order parameters, such as that representing the overlap with the retrieved pattern. We also present the phase diagram showing both the basin of attraction and the equilibrium overlap in the retrieval state. Our results are supported by numerical simulation. Consequently, it is found that both the attractor and the basin are preserved even though dilution is promoted. Moreover, as compared with the basin of attraction in the traditional binary model, it is suggested that the oscillator model is more robust against the synaptic dilution. Taking into account the fact that oscillator networks contain more detailed information than binary networks, the obtained results constitute significant support for the plausibility of temporal coding.

  14. Switching dynamics of single and coupled VO2-based oscillators as elements of neural networks

    NASA Astrophysics Data System (ADS)

    Velichko, Andrey; Belyaev, Maksim; Putrolaynen, Vadim; Pergament, Alexander; Perminov, Valentin

    2017-01-01

    In the present paper, we report on the switching dynamics of both single and coupled VO2-based oscillators, with resistive and capacitive coupling, and explore the capability of their application in oscillatory neural networks. Based on these results, we further select an adequate SPICE model to describe the modes of operation of coupled oscillator circuits. Physical mechanisms influencing the time of forward and reverse electrical switching, that determine the applicability limits of the proposed model, are identified. For the resistive coupling, it is shown that synchronization takes place at a certain value of the coupling resistance, though it is unstable and a synchronization failure occurs periodically. For the capacitive coupling, two synchronization modes, with weak and strong coupling, are found. The transition between these modes is accompanied by chaotic oscillations. A decrease in the width of the spectrum harmonics in the weak-coupling mode, and its increase in the strong-coupling one, is detected. The dependences of frequencies and phase differences of the coupled oscillatory circuits on the coupling capacitance are found. Examples of operation of coupled VO2 oscillators as a central pattern generator are demonstrated.

  15. The Effect of Chronic Cannabinoids on Broadband EEG Neural Oscillations in Humans

    PubMed Central

    Skosnik, Patrick D; D'Souza, Deepak C; Steinmetz, Adam B; Edwards, Chad R; Vollmer, Jennifer M; Hetrick, William P; O'Donnell, Brian F

    2012-01-01

    Animal and cellular work has shown that central cannabinoid-1 receptors modulate neural oscillations in the gamma range (40 Hz), which may be important for normal perceptual and cognitive processes. In order to assess the effect of cannabinoids on broadband-frequency neural oscillations in humans, the current study examined the effect of chronic cannabis use on auditory steady-state responses (ASSRs) utilizing electroencephalography (EEG). Passive ASSRs were assessed using varying rates of binaural stimulation (auditory click-trains; 10–50 Hz in increments of 5 Hz; 80 dB SPL) in carefully screened cannabis users and controls. Chronic cannabis users (n=22; 12 h abstinence before study; positive 11-nor-9-carboxy-delta-9-tetrahydrocannabinol urine levels) and cannabis naïve controls (n=24) were evaluated. Time X frequency analyses on EEG data were performed using Fourier-based mean trial power (MTP) and phase-locking (inter-trial coherence; ITC). Transient ERPs to stimulus onset (auditory N100 components) were also evaluated. As predicted, a decrease in spectral power (MTP) at 40 Hz was observed in the cannabis group (p<0.018). No effects on phase-locking (ITC) or the N100 were observed. Further, within the cannabis group, lower 40 Hz power correlated with an earlier age of onset of cannabis use (p<0.04). These data suggest that chronic exposure to exogenous cannabinoids can alter the ability to generate neural oscillations, particularly in the gamma range. This is consistent with preclinical animal and cellular data, which may have implications for understanding the short- and long-term psychopharmacological effects of cannabis. PMID:22713908

  16. Δ9-THC Disrupts Gamma (γ)-Band Neural Oscillations in Humans.

    PubMed

    Cortes-Briones, Jose; Skosnik, Patrick D; Mathalon, Daniel; Cahill, John; Pittman, Brian; Williams, Ashley; Sewell, R Andrew; Ranganathan, Mohini; Roach, Brian; Ford, Judith; D'Souza, Deepak Cyril

    2015-08-01

    Gamma (γ)-band oscillations play a key role in perception, associative learning, and conscious awareness and have been shown to be disrupted by cannabinoids in animal studies. The goal of this study was to determine whether cannabinoids disrupt γ-oscillations in humans and whether these effects relate to their psychosis-relevant behavioral effects. The acute, dose-related effects of Δ-9-tetrahydrocannabinol (Δ(9)-THC) on the auditory steady-state response (ASSR) were studied in humans (n=20) who completed 3 test days during which they received intravenous Δ(9)-THC (placebo, 0.015, and 0.03 mg/kg) in a double-blind, randomized, crossover, and counterbalanced design. Electroencephalography (EEG) was recorded while subjects listened to auditory click trains presented at 20, 30, and 40 Hz. Psychosis-relevant effects were measured with the Positive and Negative Syndrome scale (PANSS). Δ(9)-THC (0.03 mg/kg) reduced intertrial coherence (ITC) in the 40 Hz condition compared with 0.015 mg/kg and placebo. No significant effects were detected for 30 and 20 Hz stimulation. Furthermore, there was a negative correlation between 40 Hz ITC and PANSS subscales and total scores under the influence of Δ(9)-THC. Δ(9)-THC (0.03 mg/kg) reduced evoked power during 40 Hz stimulation at a trend level. Recent users of cannabis showed blunted Δ(9)-THC effects on ITC and evoked power. We show for the first time in humans that cannabinoids disrupt γ-band neural oscillations. Furthermore, there is a relationship between disruption of γ-band neural oscillations and psychosis-relevant phenomena induced by cannabinoids. These findings add to a growing literature suggesting some overlap between the acute effects of cannabinoids and the behavioral and psychophysiological alterations observed in psychotic disorders.

  17. Altered neural oscillations during multisensory integration in adolescents with fetal alcohol spectrum disorder.

    PubMed

    Bolaños, Alfredo D; Coffman, Brian A; Candelaria-Cook, Felicha T; Kodituwakku, Piyadasa; Stephen, Julia M

    2017-09-25

    Children with fetal alcohol spectrum disorder (FASD), who were exposed to alcohol in utero, display a broad range of sensory, cognitive, and behavioral deficits, which are broadly theorized to be rooted in altered brain function and structure. Based on the role of neural oscillations in multisensory integration from past studies, we hypothesized that adolescents with FASD would show a decrease in oscillatory power during event-related gamma oscillatory activity (30-100Hz), when compared to typically-developing healthy controls (HC), and that such decrease in oscillatory power would predict behavioral performance. We measured sensory neurophysiology using magnetoencephalography (MEG) during passive auditory (A), somatosensory (S), and multisensory (synchronous A/S) stimulation in 19 adolescents (12-21yrs) with FASD and 23 age- and gender-matched HC. We employed a cross-hemisphere multisensory paradigm to assess interhemispheric connectivity deficits in children with FASD. Time-frequency analysis of MEG data revealed a significant decrease in gamma oscillatory power for both unisensory and multisensory conditions in the FASD group relative to HC, based on permutation testing of significant group differences. Greater beta oscillatory power (15-30 Hz) was also noted in the FASD group compared to HC in both unisensory and multisensory conditions. Regression analysis revealed greater predictive power of multisensory oscillations from unisensory oscillations in the FASD group compared to the HC group. Furthermore, multisensory oscillatory power, for both groups, predicted performance on the Intra-Extradimensional Set Shift Task and the Cambridge Gambling Task. Altered oscillatory power in the FASD group may reflect a restricted ability to process somatosensory and multisensory stimuli during day-to-day interactions. These alterations in neural oscillations may be associated with the neurobehavioral deficits experienced by adolescents with FASD, and may carry over to

  18. Disrupted Gamma-Band Neural Oscillations During Coherent Motion Perception in Heavy Cannabis Users

    PubMed Central

    Skosnik, Patrick D; Krishnan, Giri P; D'Souza, Deepak C; Hetrick, William P; O'Donnell, Brian F

    2014-01-01

    Previous work in animals and humans has shown that exogenous cannabinoids disrupt time-locked, evoked gamma oscillations (30–80 Hz). However, no studies to date have examined the effect of cannabis on non-time-locked, induced gamma oscillations during more complex Gestalt perception. The current study therefore utilized electroencephalography (EEG) to examine gamma oscillations during coherent motion perception in heavy cannabis users and controls. Chronic cannabis users (n=24; 12 h abstinence before study; positive 11-nor-9-carboxy-delta-9-tetrahydrocannabinol urine levels) and cannabis-naive controls (n=23) were evaluated. Stimuli consisted of random dot kinetograms (RDKs) that subjects passively viewed during three different conditions: coherent motion, incoherent motion, and static. Time × frequency analysis on EEG data was performed using Fourier-based mean trial power (MTP). Transient event-related potentials (ERPs) to stimulus onset (visual N100 and P200 components) were also evaluated. The results showed that the coherent motion condition produced a robust increase in neural activity in the gamma range (induced power from 40 to 59 Hz) as compared with the incoherent motion and static conditions. As predicted, the cannabis group showed significant reductions in induced gamma power in the coherent condition relative to healthy controls. No differences were observed between the groups in the N100 or P200 components, indicating intact primary sensory processing. Finally, cannabis users showed a trend toward increased scores on the Chapman Perceptual Aberration Scale (PAS) that was positively correlated with total years of active cannabis use. These data suggest that cannabis use may interfere with the generation of induced gamma-band neural oscillations that could in part mediate the perceptual-altering effects of exogenous cannabinoids. PMID:24990428

  19. Δ9-THC Disrupts Gamma (γ)-Band Neural Oscillations in Humans

    PubMed Central

    Cortes-Briones, Jose; Skosnik, Patrick D; Mathalon, Daniel; Cahill, John; Pittman, Brian; Williams, Ashley; Sewell, R Andrew; Ranganathan, Mohini; Roach, Brian; Ford, Judith; D'Souza, Deepak Cyril

    2015-01-01

    Gamma (γ)-band oscillations play a key role in perception, associative learning, and conscious awareness and have been shown to be disrupted by cannabinoids in animal studies. The goal of this study was to determine whether cannabinoids disrupt γ-oscillations in humans and whether these effects relate to their psychosis-relevant behavioral effects. The acute, dose-related effects of Δ-9-tetrahydrocannabinol (Δ9-THC) on the auditory steady-state response (ASSR) were studied in humans (n=20) who completed 3 test days during which they received intravenous Δ9-THC (placebo, 0.015, and 0.03 mg/kg) in a double-blind, randomized, crossover, and counterbalanced design. Electroencephalography (EEG) was recorded while subjects listened to auditory click trains presented at 20, 30, and 40 Hz. Psychosis-relevant effects were measured with the Positive and Negative Syndrome scale (PANSS). Δ9-THC (0.03 mg/kg) reduced intertrial coherence (ITC) in the 40 Hz condition compared with 0.015 mg/kg and placebo. No significant effects were detected for 30 and 20 Hz stimulation. Furthermore, there was a negative correlation between 40 Hz ITC and PANSS subscales and total scores under the influence of Δ9-THC. Δ9-THC (0.03 mg/kg) reduced evoked power during 40 Hz stimulation at a trend level. Recent users of cannabis showed blunted Δ9-THC effects on ITC and evoked power. We show for the first time in humans that cannabinoids disrupt γ-band neural oscillations. Furthermore, there is a relationship between disruption of γ-band neural oscillations and psychosis-relevant phenomena induced by cannabinoids. These findings add to a growing literature suggesting some overlap between the acute effects of cannabinoids and the behavioral and psychophysiological alterations observed in psychotic disorders. PMID:25709097

  20. Mean-field theory of globally coupled integrate-and-fire neural oscillators with dynamic synapses

    NASA Astrophysics Data System (ADS)

    Bressloff, P. C.

    1999-08-01

    We analyze the effects of synaptic depression or facilitation on the existence and stability of the splay or asynchronous state in a population of all-to-all, pulse-coupled neural oscillators. We use mean-field techniques to derive conditions for the local stability of the splay state and determine how stability depends on the degree of synaptic depression or facilitation. We also consider the effects of noise. Extensions of the mean-field results to finite networks are developed in terms of the nonlinear firing time map.

  1. Neural oscillations associated with the primacy and recency effects of verbal working memory.

    PubMed

    Stephane, Massoud; Ince, Nuri F; Kuskowski, Michael; Leuthold, Arthur; Tewfik, Ahmed H; Nelson, Katie; McClannahan, Kate; Fletcher, Charles R; Tadipatri, Vijay Aditya

    2010-04-12

    For sequential information, the first (primacy) and last (recency) items are better remembered than items in the middle of the sequence. The cognitive operations and neural correlates for the primacy and recency effects are unclear. In this paper, we investigate brain oscillations associated with these effects. MEG recordings were obtained on 19 subjects performing a modified Sternberg paradigm. Correlation analyses were performed between brain oscillatory activity and primacy and recency indices. Oscillatory activity during information maintenance, not encoding, was correlated with the primacy and recency effects. The primacy effect was associated with occipital post-desynchrony, and temporal post-synchrony. The recency effect was associated with parietal and temporal desynchrony. Differences were also observed according to the maintenance strategy. These data indicate that the primacy and recency effects are related to different neural, and likely cognitive, operations that are dependant on the strategy for information maintenance. Published by Elsevier Ireland Ltd.

  2. Stability switches and multistability coexistence in a delay-coupled neural oscillators system.

    PubMed

    Song, Zigen; Xu, Jian

    2012-11-21

    In this paper, we present a neural network system composed of two delay-coupled neural oscillators, where each of these can be regarded as the dynamical system describing the average activity of neural population. Analyzing the corresponding characteristic equation, the local stability of rest state is studied. The system exhibits the switch phenomenon between the rest state and periodic activity. Furthermore, the Hopf bifurcation is analyzed and the bifurcation curve is given in the parameters plane. The stability of the bifurcating periodic solutions and direction of the Hopf bifurcation are exhibited. Regarding time delay and coupled weight as the bifurcation parameters, the Fold-Hopf bifurcation is investigated in detail in terms of the central manifold reduction and normal form method. The neural system demonstrates the coexistence of the rest states and periodic activities in the different parameter regions. Employing the normal form of the original system, the coexistence regions are illustrated approximately near the Fold-Hopf singularity point. Finally, numerical simulations are performed to display more complex dynamics. The results illustrate that system may exhibit the rich coexistence of the different neuro-computational properties, such as the rest states, periodic activities, and quasi-periodic behavior. In particular, some periodic activities can evolve into the bursting-type behaviors with the varying time delay. It implies that the coexistence of the quasi-periodic activity and bursting-type behavior can be obtained if the suitable value of system parameter is chosen.

  3. The formation of synchronization cliques during the development of modular neural networks.

    PubMed

    Fuchs, Einat; Ayali, Amir; Ben-Jacob, Eshel; Boccaletti, Stefano

    2009-07-31

    Modular organization is a special feature shared by many biological and social networks alike. It is a hallmark for systems exhibiting multitasking, in which individual tasks are performed by separated and yet coordinated functional groups. Understanding how networks of segregated modules develop to support coordinated multitasking functionalities is the main topic of the current study. Using simulations of biologically inspired neuronal networks during development, we study the formation of functional groups (cliques) and inter-neuronal synchronization. The results indicate that synchronization cliques first develop locally according to the explicit network topological organization. Later on, at intermediate connectivity levels, when networks have both local segregation and long-range integration, new synchronization cliques with distinctive properties are formed. In particular, by defining a new measure of synchronization centrality, we identify at these developmental stages dominant neurons whose functional centrality largely exceeds the topological one. These are generated mainly in a few dominant clusters that become the centers of the newly formed synchronization cliques. We show that by the local synchronization properties at the very early developmental stages, it is possible to predict with high accuracy which clusters will become dominant in later stages of network development.

  4. Robust synchronization of coupled neural oscillators using the derivative-free nonlinear Kalman Filter.

    PubMed

    Rigatos, Gerasimos

    2014-12-01

    A synchronizing control scheme for coupled neural oscillators of the FitzHugh-Nagumo type is proposed. Using differential flatness theory the dynamical model of two coupled neural oscillators is transformed into an equivalent model in the linear canonical (Brunovsky) form. A similar linearized description is succeeded using differential geometry methods and the computation of Lie derivatives. For such a model it becomes possible to design a state feedback controller that assures the synchronization of the membrane's voltage variations for the two neurons. To compensate for disturbances that affect the neurons' model as well as for parametric uncertainties and variations a disturbance observer is designed based on Kalman Filtering. This consists of implementation of the standard Kalman Filter recursion on the linearized equivalent model of the coupled neurons and computation of state and disturbance estimates using the diffeomorphism (relations about state variables transformation) provided by differential flatness theory. After estimating the disturbance terms in the neurons' model their compensation becomes possible. The performance of the synchronization control loop is tested through simulation experiments.

  5. A Kalman filtering approach to robust synchronization of coupled neural oscillators

    NASA Astrophysics Data System (ADS)

    Rigatos, Gerasimos G.; Rigatou, Efthymia G.

    2013-10-01

    A synchronizing control scheme for coupled neural oscillators of the FitzHugh-Nagumo type is proposed. Using differential flatness theory the dynamical model of the coupled neural oscillators is transformed into an equivalent model in the linear canonical (Brunovsky) form. A similar linearized description is succeeded using differential geometry methods and the computation of Lie Derivatives. For such a model it becomes possible to design a state feedback controller that assures synchronization for the state variables of the two neurons. To compensate for disturbances that affect the neurons' model as well as for parametric uncertainties and variations a disturbance observer is designed based on Kalman Filtering. This consists of implementation of the standard Kalman Filter recursion on the linearized equivalent model of the coupled neurons and on computation of state and disturbance estimates using the diffeomorphism (relations about state variables transformation) provided by differential flatness theory. After estimating the disturbance terms in the neurons' model their compensation becomes possible. The performance of the synchronization control loop is tested through simulation experiments.

  6. Speaker's hand gestures modulate speech perception through phase resetting of ongoing neural oscillations.

    PubMed

    Biau, Emmanuel; Torralba, Mireia; Fuentemilla, Lluis; de Diego Balaguer, Ruth; Soto-Faraco, Salvador

    2015-07-01

    Speakers often accompany speech with spontaneous beat gestures in natural spoken communication. These gestures are usually aligned with lexical stress and can modulate the saliency of their affiliate words. Here we addressed the consequences of beat gestures on the neural correlates of speech perception. Previous studies have highlighted the role played by theta oscillations in temporal prediction of speech. We hypothesized that the sight of beat gestures may influence ongoing low-frequency neural oscillations around the onset of the corresponding words. Electroencephalographic (EEG) recordings were acquired while participants watched a continuous, naturally recorded discourse. The phase-locking value (PLV) at word onset was calculated from the EEG from pairs of identical words that had been pronounced with and without a concurrent beat gesture in the discourse. We observed an increase in PLV in the 5-6 Hz theta range as well as a desynchronization in the 8-10 Hz alpha band around the onset of words preceded by a beat gesture. These findings suggest that beats help tune low-frequency oscillatory activity at relevant moments during natural speech perception, providing a new insight of how speech and paralinguistic information are integrated.

  7. Neural oscillations as a signature of efficient coding in the presence of synaptic delays

    PubMed Central

    Chalk, Matthew; Gutkin, Boris; Denève, Sophie

    2016-01-01

    Cortical networks exhibit 'global oscillations', in which neural spike times are entrained to an underlying oscillatory rhythm, but where individual neurons fire irregularly, on only a fraction of cycles. While the network dynamics underlying global oscillations have been well characterised, their function is debated. Here, we show that such global oscillations are a direct consequence of optimal efficient coding in spiking networks with synaptic delays and noise. To avoid firing unnecessary spikes, neurons need to share information about the network state. Ideally, membrane potentials should be strongly correlated and reflect a 'prediction error' while the spikes themselves are uncorrelated and occur rarely. We show that the most efficient representation is when: (i) spike times are entrained to a global Gamma rhythm (implying a consistent representation of the error); but (ii) few neurons fire on each cycle (implying high efficiency), while (iii) excitation and inhibition are tightly balanced. This suggests that cortical networks exhibiting such dynamics are tuned to achieve a maximally efficient population code. DOI: http://dx.doi.org/10.7554/eLife.13824.001 PMID:27383272

  8. Event-related potentials and neural oscillations dissociate levels of cognitive control.

    PubMed

    Lu, Mingou; Doñamayor, Nuria; Münte, Thomas F; Bahlmann, Jörg

    2017-03-01

    Recent models of human behavior suggest a hierarchical organization of cognitive control processes. These models assume that different sub-goals of cognitive control processes are nested in each other, such that higher-level sub-goals can only be accomplished when lower-level sub-goals have been realized. While the neuroanatomical localization of this organizational principle has already been successfully tested, the exact temporal nature remains to be explored. The present study applied event-related potentials (ERPs) and investigated neural oscillations during performance of three different nested cognitive control tasks. Results demonstrated a parametric modulation of the P300 component as well as beta-band (13-25Hz) oscillations as a function of different levels of cognitive control. Moreover, conditions requiring flexible updating of information exhibited similar alpha-band (8-13Hz) oscillations, which differed from the condition without flexible updating (low-level). These results suggest dissociable mechanisms of flexible information updating and complexity of cognitive control processes indexed by different oscillatory effects.

  9. Coherent neural oscillations predict future motor and language improvement after stroke.

    PubMed

    Nicolo, Pierre; Rizk, Sviatlana; Magnin, Cécile; Pietro, Marie Di; Schnider, Armin; Guggisberg, Adrian G

    2015-10-01

    Recent findings have demonstrated that stroke lesions affect neural communication in the entire brain. However, it is less clear whether network interactions are also relevant for plasticity and repair. This study investigated whether the coherence of neural oscillations at language or motor nodes is associated with future clinical improvement. Twenty-four stroke patients underwent high-density EEG recordings and standardized motor and language tests at 2-3 weeks (T0) and 3 months (T1) after stroke onset. In addition, EEG and motor assessments were obtained from a second population of 18 stroke patients. The graph theoretical measure of weighted node degree at language and motor areas was computed as the sum of absolute imaginary coherence with all other brain regions and compared to the amount of clinical improvement from T0 to T1. At T0, beta-band weighted node degree at the ipsilesional motor cortex was linearly correlated with better subsequent motor improvement, while beta-band weighted node degree at Broca's area was correlated with better language improvement. Clinical recovery was further associated with contralesional theta-band weighted node degree. These correlations were each specific to the corresponding brain area and independent of initial clinical severity, age, and lesion size. Findings were reproduced in the second stroke group. Conversely, later coherence increases occurring between T0 and T1 were associated with less clinical improvement. Improvement of language and motor functions after stroke is therefore associated with inter-regional synchronization of neural oscillations in the first weeks after stroke. A better understanding of network mechanisms of plasticity may lead to new prognostic biomarkers and therapeutic targets.See Ward (doi:10.1093/brain/awv265) for a scientific commentary on this article. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please

  10. Neuronal current magnetic resonance imaging of evoked potentials and neural oscillations

    NASA Astrophysics Data System (ADS)

    Jiang, Xia

    Despite its great success, the current functional magnetic resonance imaging (MRI) technique relies on changes in cerebral hemodynamic parameters to infer the underlying neural activities, and as a result is limited in its spatial and temporal resolutions. In this dissertation, we discuss the feasibility of neuronal current MRI (nc-MRI), a novel technique in which the small magnetic field changes caused by neuronal electrical activities are directly measured by MRI. Two studies are described. In the first study, we investigated the feasibility of detecting the magnetic field produced by sensory evoked potentials. To eliminate the blood-oxygen-level-dependent (BOLD) effect on the MRI signal, which confounded most previous studies, an octopus visual system model was developed, which, for the first time, allowed for an in vivo investigation of nc-MRI in a BOLD-free environment. Electrophysiological responses were measured in the octopus retina and optical lobe to guide the nc-MRI acquisition. Our results indicated that no nc-MRI signal change related to neuronal activation could be detected at 0.2°/0.2% threshold for signal phase/magnitude respectively, while robust electrophysiological responses were recorded. In the second study, we discuss the feasibility of detecting neural oscillations with MRI, Based on previous studies, a novel approach was proposed in which an external oscillatory field was exploited as the excitation pulse under a spin-locked condition. This approach has the advantages of increased sensitivity and lowered physiological noise. Successful detection of sub-nanotesla field was demonstrated in phantom. Our results suggest that evoked potentials are too weak for nc-MRI detection with the current hardware, and that previous positive findings were likely due to hemodynamic confounders. On the other hand, oscillatory magnetic field can be efficiently detected in phantom. Given the stronger equivalent current dipoles produced by neural oscillations

  11. Modeling the influences of nanoparticles on neural field oscillations in thalamocortical networks.

    PubMed

    Busse, Michael; Kraegeloh, Annette; Arzt, Eduard; Strauss, Daniel J

    2012-01-01

    The purpose of this study is twofold. First, we present a simplified multiscale modeling approach integrating activity on the scale of ionic channels into the spatiotemporal scale of neural field potentials: Resting upon a Hodgkin-Huxley based single cell model we introduced a neuronal feedback circuit based on the Llinás-model of thalamocortical activity and binding, where all cell specific intrinsic properties were adopted from patch-clamp measurements. In this paper, we expand this existing model by integrating the output to the spatiotemporal scale of field potentials. Those are supposed to originate from the parallel activity of a variety of synchronized thalamocortical columns at the quasi-microscopic level, where the involved neurons are gathered together in units. Second and more important, we study the possible effects of nanoparticles (NPs) that are supposed to interact with thalamic cells of our network model. In two preliminary studies we demonstrated in vitro and in vivo effects of NPs on the ionic channels of single neurons and thereafter on neuronal feedback circuits. By means of our new model we assumed now NPs induced changes on the ionic currents of the involved thalamic neurons. Here we found extensive diversified pattern formations of neural field potentials when comparing to the modeled activity without neuromodulating NPs addition. This model provides predictions about the influences of NPs on spatiotemporal neural field oscillations in thalamocortical networks. These predictions can be validated by high spatiotemporal resolution electrophysiological measurements like voltage sensitive dyes and multiarray recordings.

  12. Organization of face and object recognition in modular neural network models.

    PubMed

    Dailey, M N.; Cottrell, G W.

    1999-10-01

    There is strong evidence that face processing in the brain is localized. The double dissociation between prosopagnosia, a face recognition deficit occurring after brain damage, and visual object agnosia, difficulty recognizing other kinds of complex objects, indicates that face and non-face object recognition may be served by partially independent neural mechanisms. In this paper, we use computational models to show how the face processing specialization apparently underlying prosopagnosia and visual object agnosia could be attributed to (1) a relatively simple competitive selection mechanism that, during development, devotes neural resources to the tasks they are best at performing, (2) the developing infant's need to perform subordinate classification (identification) of faces early on, and (3) the infant's low visual acuity at birth. Inspired by de Schonen, Mancini and Liegeois' arguments (1998) [de Schonen, S., Mancini, J., Liegeois, F. (1998). About functional cortical specialization: the development of face recognition. In: F. Simon & G. Butterworth, The development of sensory, motor, and cognitive capacities in early infancy (pp. 103-116). Hove, UK: Psychology Press] that factors like these could bias the visual system to develop a processing subsystem particularly useful for face recognition, and Jacobs and Kosslyn's experiments (1994) [Jacobs, R. A., & Kosslyn, S. M. (1994). Encoding shape and spatial relations-the role of receptive field size in coordination complementary representations. Cognitive Science, 18(3), 361-368] in the mixtures of experts (ME) modeling paradigm, we provide a preliminary computational demonstration of how this theory accounts for the double dissociation between face and object processing. We present two feed-forward computational models of visual processing. In both models, the selection mechanism is a gating network that mediates a competition between modules attempting to classify input stimuli. In Model I, when the modules

  13. Genetic and neural modularity underlie the evolution of schooling behavior in threespine sticklebacks.

    PubMed

    Greenwood, Anna K; Wark, Abigail R; Yoshida, Kohta; Peichel, Catherine L

    2013-10-07

    Although descriptions of striking diversity in animal behavior are plentiful, little is known about the mechanisms by which behaviors change and evolve between groups. To fully understand behavioral evolution, it will be necessary to identify the genetic mechanisms that mediate behavioral change in a natural context. Genetic analysis of behavior can also reveal associations between behavior and morphological or neural phenotypes, providing insight into the proximate mechanisms that control behavior. Relatively few studies to date have successfully identified genes or genomic regions that contribute to behavioral variation among natural populations or species, particularly in vertebrates. Here, we apply genetic approaches to dissect a complex social behavior that has long fascinated biologists, schooling behavior. We performed quantitative trait locus (QTL) analysis of schooling in an F2 intercross between strongly schooling marine and weakly schooling benthic sticklebacks (Gasterosteus aculeatus) and found that distinct genetic modules control different aspects of schooling behavior. Two key components of the behavior, tendency to school and body position when schooling, are uncorrelated in hybrids and map to different genomic regions. Our results further point to a genetic link between one behavioral component, schooling position, and variation in the neurosensory lateral line. Copyright © 2013 Elsevier Ltd. All rights reserved.

  14. Regulation of modular Cyclin and CDK feedback loops by an E2F transcription oscillator in the mammalian cell cycle.

    PubMed

    Lavi, Orit; Ginsberg, Doron; Louzoun, Yoram

    2011-04-01

    The cell cycle is regulated by a large number of enzymes and transcription factors. We have developed a modular description of the cell cycle, based on a set of interleaved modular feedback loops, each leading to a cyclic behavior. The slowest loop is the E2F transcription and ubiquitination, which determines the cycling frequency of the entire cell cycle. Faster feedback loops describe the dynamics of each Cyclin by itself. Our model shows that the cell cycle progression as well as the checkpoints of the cell cycle can be understood through the interactions between the main E2F feedback loop and the driven Cyclin feedback loops. Multiple models were proposed for the cell cycle dynamics; each with differing basic mechanisms. We here propose a new generic formalism. In contrast with existing models, the proposed formalism allows a straightforward analysis and understanding of the dynamics, neglecting the details of each interaction. This model is not sensitive to small changes in the parameters used and it reproduces the observed behavior of the transcription factor E2F and different Cyclins in continuous or regulated cycling conditions. The modular description of the cell cycle resolves the gap between cyclic models, solely based on protein-protein reactions and transcription reactions based models. Beyond the explanation of existing observations, this model suggests the existence of unknown interactions, such as the need for a functional interaction between Cyclin B and retinoblastoma protein (Rb) de-phosphorylation.

  15. Multiple-scale dynamics in neural systems: learning, synchronization and network oscillations

    NASA Astrophysics Data System (ADS)

    Zhigulin, Valentin P.

    Many dynamical processes that take place in neural systems involve interactions between multiple temporal and/or spatial scales which lead to the emergence of new dynamical phenomena. Two of them are studied in this thesis: learning-induced robustness and enhancement of synchronization in small neural circuits; and emergence of global spatio-temporal dynamics from local interactions in neural networks.Chapter 2 presents the study of synchronization of two model neurons coupled through a synapse with spike-timing dependent plasticity (STDP). It shows that this form of learning leads to the enlargement of frequency locking zones and makes synchronization much more robust to noise than classical synchronization mediated by non-plastic synapses. A simple discrete-time map model is presented that enables deep understanding of this phenomenon and demonstrates its generality. Chapter 3 extends these results by demonstrating enhancement of synchronization in a hybrid circuit with living postsynaptic neuron. The robustness of STDP-mediated synchronization is further confirmed with simulations of stochastic plasticity.Chapter 4 studies the entrainment of a heterogeneous network of electrically coupled neurons by periodic stimulation. It demonstrates that, when compared to the case of non-plastic input synapses, inputs with STDP enhance coherence of network oscillations and improve robustness of synchronization to the variability of network properties. The observed mechanism may play a role in synchronization of hippocampal neural ensembles.Chapter 5 proposes a new type of artificial synaptic connection that combines fast reaction of an electrical synapse with plasticity of a chemical synapse. It shows that such synapse mediates regularization of chaos in a circuit of two chaotic bursting neurons and leads to structural stability of the regularized state. Such plastic electrical synapse may be used in the development of robust neural prosthetics.Chapter 6 suggests a new

  16. Human intracranial high-frequency activity during memory processing: neural oscillations or stochastic volatility?

    PubMed

    Burke, John F; Ramayya, Ashwin G; Kahana, Michael J

    2015-04-01

    Intracranial high-frequency activity (HFA), which refers to fast fluctuations in electrophysiological recordings, increases during memory processing. Two views have emerged to explain this effect: (1) HFA reflects a synchronous signal, related to underlying gamma oscillations, that plays a mechanistic role in human memory and (2) HFA reflects an asynchronous signal that is a non-specific marker of brain activation. We review recent data supporting each of these views and conclude that HFA during memory processing is more consistent with an asynchronous signal. Memory-related HFA is therefore best conceptualized as a biomarker of neural activation that can functionally map memory with high spatial and temporal precision. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Phase synchrony facilitates binding and segmentation of natural images in a coupled neural oscillator network.

    PubMed

    Finger, Holger; König, Peter

    2013-01-01

    Synchronization has been suggested as a mechanism of binding distributed feature representations facilitating segmentation of visual stimuli. Here we investigate this concept based on unsupervised learning using natural visual stimuli. We simulate dual-variable neural oscillators with separate activation and phase variables. The binding of a set of neurons is coded by synchronized phase variables. The network of tangential synchronizing connections learned from the induced activations exhibits small-world properties and allows binding even over larger distances. We evaluate the resulting dynamic phase maps using segmentation masks labeled by human experts. Our simulation results show a continuously increasing phase synchrony between neurons within the labeled segmentation masks. The evaluation of the network dynamics shows that the synchrony between network nodes establishes a relational coding of the natural image inputs. This demonstrates that the concept of binding by synchrony is applicable in the context of unsupervised learning using natural visual stimuli.

  18. Model of rhythmic ball bouncing using a visually controlled neural oscillator.

    PubMed

    Avrin, Guillaume; Siegler, Isabelle Anne; Makarov, Maria; Rodriguez-Ayerbe, Pedro

    2017-08-09

    The present paper investigates the sensory-driven modulations of Central Pattern Generators dynamics that can be expected to reproduce human behavior during rhythmic hybrid tasks. We propose a theoretical model of human sensorimotor behavior able to account for the observed data from the ball-bouncing task. The novel control architecture is composed of a Matsuoka neural oscillator parametrically controlled by a sensorimotor controller and coupled with the environment through visual sensory feedback. The architecture's ability to reproduce human-like performance during the ball-bouncing task in the presence of perturbations is quantified by comparison of simulated and recorded trials. The results suggest that human visual control of the task is achieved on-line. The adaptive behavior is made possible by a parametric and state control of the limit cycle emerging from the interaction of the rhythmic pattern generator, the musculoskeletal system and the environment. Copyright © 2017, Journal of Neurophysiology.

  19. Phase synchrony facilitates binding and segmentation of natural images in a coupled neural oscillator network

    PubMed Central

    Finger, Holger; König, Peter

    2014-01-01

    Synchronization has been suggested as a mechanism of binding distributed feature representations facilitating segmentation of visual stimuli. Here we investigate this concept based on unsupervised learning using natural visual stimuli. We simulate dual-variable neural oscillators with separate activation and phase variables. The binding of a set of neurons is coded by synchronized phase variables. The network of tangential synchronizing connections learned from the induced activations exhibits small-world properties and allows binding even over larger distances. We evaluate the resulting dynamic phase maps using segmentation masks labeled by human experts. Our simulation results show a continuously increasing phase synchrony between neurons within the labeled segmentation masks. The evaluation of the network dynamics shows that the synchrony between network nodes establishes a relational coding of the natural image inputs. This demonstrates that the concept of binding by synchrony is applicable in the context of unsupervised learning using natural visual stimuli. PMID:24478685

  20. Mixed Mode Oscillations and Synchronous Activity in Noise Induced Modified Morris-Lecar Neural System

    NASA Astrophysics Data System (ADS)

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

    The modified three-dimensional (3D) Morris-Lecar (M-L) model is very useful to understand the spiking activities of neurons. The present article addresses the random dynamical behavior of a modified M-L model driven by a white Gaussian noise with mean zero and unit spectral density. The applied stimulus can be expressed as a random term. Such random perturbations are represented by a white Gaussian noise current added through the electrical potential of membrane of the excitatory principal cells. The properties of the stochastic system (perturbed one) and noise induced mixed mode oscillation are analyzed. The Lyapunov spectrum is computed to present the nature of the system dynamics. The noise intensity is varied while keeping fixed the predominant parameters of the model in their ranges and also observed the changes in the dynamical behavior of the system. The dynamical synchronization is studied in the coupled M-L systems interconnected by excitatory and inhibitory neurons with noisy electrical coupling and verified with similarity functions. This result suggests the potential benefits of noise and noise induced oscillations which have been observed in real neurons and how that affects the dynamics of the neural model as well as the coupled systems. The analysis reports that the modified M-L system which has the limit cycle behavior can show a type of phase locking behavior which follows either period adding (i.e. 1:1, 2:1, 3:1, 4:1) sequences or Farey sequences. For the coupled neural systems, complete synchronization is shown for sufficient noisy coupling strength.

  1. Abnormal Neural Oscillations in Schizophrenia Assessed by Spectral Power Ratio of MEG During Word Processing.

    PubMed

    Xu, Tingting; Stephane, Massoud; Parhi, Keshab K

    2016-11-01

    This study investigated spectral power of neural oscillations associated with word processing in schizophrenia. Magnetoencephalography (MEG) data were acquired from 12 schizophrenia patients and 10 healthy controls during a visual word processing task. Two spectral power ratio (SPR) feature sets: the band power ratio (BPR) and the window power ratio (WPR) were extracted from MEG data in five frequency bands, four time windows of word processing, and at locations covering whole head. Cluster-based nonparametric permutation tests were employed to identify SPRs that show significant between-group difference. Machine learning based feature selection and classification techniques were then employed to select optimal combinations of the significant SPR features, and distinguish schizophrenia patients from healthy controls. We identified three BPR clusters and three WPR clusters that show significant oscillation power difference between groups. These include the theta/delta, alpha/delta and beta/delta BPRs during base-to-encode and encode time windows, and the beta band WPR from base to encode and from encode to post-encode windows. Based on two WPR and one BPR features combined, over 95% cross-validation classification accuracy was achieved using three different linear classifiers separately. These features may have potential as quantitative markers that discriminate schizophrenia patients and healthy controls; however, this needs further validation on larger samples.

  2. Neural oscillations and synchronization differentially support evidence accumulation in perceptual and value-based decision making.

    PubMed

    Polanía, Rafael; Krajbich, Ian; Grueschow, Marcus; Ruff, Christian C

    2014-05-07

    Organisms make two types of decisions on a regular basis. Perceptual decisions are determined by objective states of the world (e.g., melons are bigger than apples), whereas value-based decisions are determined by subjective preferences (e.g., I prefer apples to melons). Theoretical accounts suggest that both types of choice involve neural computations accumulating evidence for the choice alternatives; however, little is known about the overlap or differences in the processes underlying perceptual versus value-based decisions. We analyzed EEG recordings during a paradigm where perceptual- and value-based choices were based on identical stimuli. For both types of choice, evidence accumulation was evident in parietal gamma-frequency oscillations, whereas a similar frontal signal was unique for value-based decisions. Fronto-parietal synchronization of these signals predicted value-based choice accuracy. These findings uncover how decisions emerge from topographic- and frequency-specific oscillations that accumulate distinct aspects of evidence, with large-scale synchronization as a mechanism integrating these spatially distributed signals.

  3. The Effect of Inhibitory Neuron on the Evolution Model of Higher-Order Coupling Neural Oscillator Population

    PubMed Central

    Qi, Yi; Wang, Rubin; Jiao, Xianfa; Du, Ying

    2014-01-01

    We proposed a higher-order coupling neural network model including the inhibitory neurons and examined the dynamical evolution of average number density and phase-neural coding under the spontaneous activity and external stimulating condition. The results indicated that increase of inhibitory coupling strength will cause decrease of average number density, whereas increase of excitatory coupling strength will cause increase of stable amplitude of average number density. Whether the neural oscillator population is able to enter the new synchronous oscillation or not is determined by excitatory and inhibitory coupling strength. In the presence of external stimulation, the evolution of the average number density is dependent upon the external stimulation and the coupling term in which the dominator will determine the final evolution. PMID:24516505

  4. Neural oscillations in the temporal pole for a temporally congruent audio-visual speech detection task

    PubMed Central

    Ohki, Takefumi; Gunji, Atsuko; Takei, Yuichi; Takahashi, Hidetoshi; Kaneko, Yuu; Kita, Yosuke; Hironaga, Naruhito; Tobimatsu, Shozo; Kamio, Yoko; Hanakawa, Takashi; Inagaki, Masumi; Hiraki, Kazuo

    2016-01-01

    Though recent studies have elucidated the earliest mechanisms of processing in multisensory integration, our understanding of how multisensory integration of more sustained and complicated stimuli is implemented in higher-level association cortices is lacking. In this study, we used magnetoencephalography (MEG) to determine how neural oscillations alter local and global connectivity during multisensory integration processing. We acquired MEG data from 15 healthy volunteers performing an audio-visual speech matching task. We selected regions of interest (ROIs) using whole brain time-frequency analyses (power spectrum density and wavelet transform), then applied phase amplitude coupling (PAC) and imaginary coherence measurements to them. We identified prominent delta band power in the temporal pole (TP), and a remarkable PAC between delta band phase and beta band amplitude. Furthermore, imaginary coherence analysis demonstrated that the temporal pole and well-known multisensory areas (e.g., posterior parietal cortex and post-central areas) are coordinated through delta-phase coherence. Thus, our results suggest that modulation of connectivity within the local network, and of that between the local and global network, is important for audio-visual speech integration. In short, these neural oscillatory mechanisms within and between higher-level association cortices provide new insights into the brain mechanism underlying audio-visual integration. PMID:27897244

  5. Prediction of the Wrist Joint Position During a Postural Tremor Using Neural Oscillators and an Adaptive Controller

    PubMed Central

    Kobravi, Hamid Reza; Ali, Sara Hemmati; Vatandoust, Masood; Marvi, Rasoul

    2016-01-01

    The prediction of the joint angle position, especially during tremor bursts, can be useful for detecting, tracking, and forecasting tremors. Thus, this research proposes a new model for predicting the wrist joint position during rhythmic bursts and inter-burst intervals. Since a tremor is an approximately rhythmic and roughly sinusoidal movement, neural oscillators have been selected to underlie the proposed model. Two neural oscillators were adopted. Electromyogram (EMG) signals were recorded from the extensor carpi radialis and flexor carpi radialis muscles concurrent with the joint angle signals of a stroke subject in an arm constant-posture. The output frequency of each oscillator was equal to the frequency corresponding to the maximum value of power spectrum related to the rhythmic wrist joint angle signals which had been recorded during a postural tremor. The phase shift between the outputs of the two oscillators was equal to the phase shift between the muscle activation of the wrist flexor and extensor muscles. The difference between the two oscillators’ output signals was considered the main pattern. Along with a proportional compensator, an adaptive neural controller has adjusted the amplitude of the main pattern in such a way so as to minimize the wrist joint prediction error during a stroke patient's tremor burst and a healthy subject's generated artificial tremor. In regard to the range of wrist joint movement during the observed rhythmic motions, a calculated prediction error is deemed acceptable. PMID:27186540

  6. The relationship between aerobic fitness and neural oscillations during visuo-spatial attention in young adults.

    PubMed

    Wang, Chun-Hao; Liang, Wei-Kuang; Tseng, Philip; Muggleton, Neil G; Juan, Chi-Hung; Tsai, Chia-Liang

    2015-04-01

    While the cognitive benefits of aerobic fitness have been widely investigated, current findings in young adults remain unclear. Specifically, little is known about how these effects are reflected in the time-frequency domain. This study thus assessed the relationship between aerobic fitness and neural oscillations during visuo-spatial attention. A between-subjects design that included 20 participants with higher aerobic fitness (age = 21.95 ± 2.24 years; VO2max = 58.98 ± 6.94 ml/kg/min) and 20 age- and gender-matched lower aerobic fitness participants (age = 23.25 ± 2.07 years; VO2max = 35.87 ± 3.41 ml/kg/min) was used to examine the fitness-related differences in performance and neuroelectric indexes during a Posner visuo-spatial attention paradigm. The results demonstrated that high-fitness participants, in comparison with their low-fitness counterparts, showed faster reaction times as well as greater modulation of oscillatory theta and beta power during target processing, regardless of cue types. Moreover, the neurocognitive correlation showed that higher theta power was related to better task performance. Collectively, these findings suggest that aerobic fitness is associated with general enhanced attentional control in relation to visuo-spatial processing, as evidenced through greater motor preparation and in particular the up-regulation of attentional processing in healthy young adults. The present study may contribute to current knowledge by revealing the relationship between aerobic fitness and modulation of brain oscillations.

  7. Gamma oscillations as a neural signature of shifting times in narrative language.

    PubMed

    Brederoo, Sanne Gøren; Bos, Laura Simone; Dragoy, Olga; Bastiaanse, Roelien; Baggio, Giosuè

    2015-01-01

    Verbs and other temporal expressions allow speakers to specify the location of events in time, as well as to move back and forth in time, shifting in a narrative between past, present and future. The referential flexibility of temporal expressions is well understood in linguistics but its neurocognitive bases remain unknown. We aimed at obtaining a neural signature of shifting times in narrative language. We recorded and analyzed event-related brain potentials (ERPs) and oscillatory responses to the adverb 'now' and to the second main verb in Punctual ('An hour ago the boy stole a candy and now he peeled the fruit') and Iterative ('The entire afternoon the boy stole candy and now he peeled the fruit') contexts. 'An hour ago' introduces a time frame that lies entirely in the past, 'now' shifts the narrative to the present, and 'peeled' shifts it back to the past. These two referential shifts in Punctual contexts are expected to leave very similar traces on neural responses. In contrast, 'The entire afternoon' specifies a time frame that may encompass past, present and future, such that both 'now' and 'peeled' are consistent with it. Here, no time shift is required. We found no difference in ERPs between Punctual and Iterative contexts either at 'now' or at the second verb. However, reference shifts modulated oscillatory signals. 'Now' and the second verb in Punctual contexts resulted in similar responses: an increase in gamma power with a left-anterior distribution. Gamma bursts were absent in Iterative contexts. We propose that gamma oscillations here reflect the binding of temporal variables to the values allowed by constraints introduced by temporal expressions in discourse.

  8. Gamma Oscillations as a Neural Signature of Shifting Times in Narrative Language

    PubMed Central

    Brederoo, Sanne Gøren; Bos, Laura Simone; Dragoy, Olga; Bastiaanse, Roelien; Baggio, Giosuè

    2015-01-01

    Verbs and other temporal expressions allow speakers to specify the location of events in time, as well as to move back and forth in time, shifting in a narrative between past, present and future. The referential flexibility of temporal expressions is well understood in linguistics but its neurocognitive bases remain unknown. We aimed at obtaining a neural signature of shifting times in narrative language. We recorded and analyzed event-related brain potentials (ERPs) and oscillatory responses to the adverb ‘now’ and to the second main verb in Punctual (‘An hour ago the boy stole a candy and now he peeled the fruit’) and Iterative (‘The entire afternoon the boy stole candy and now he peeled the fruit’) contexts. ‘An hour ago’ introduces a time frame that lies entirely in the past, ‘now’ shifts the narrative to the present, and ‘peeled’ shifts it back to the past. These two referential shifts in Punctual contexts are expected to leave very similar traces on neural responses. In contrast, ‘The entire afternoon’ specifies a time frame that may encompass past, present and future, such that both ‘now’ and ‘peeled’ are consistent with it. Here, no time shift is required. We found no difference in ERPs between Punctual and Iterative contexts either at ‘now’ or at the second verb. However, reference shifts modulated oscillatory signals. ‘Now’ and the second verb in Punctual contexts resulted in similar responses: an increase in gamma power with a left-anterior distribution. Gamma bursts were absent in Iterative contexts. We propose that gamma oscillations here reflect the binding of temporal variables to the values allowed by constraints introduced by temporal expressions in discourse. PMID:25874576

  9. Speed of synchronization in complex networks of neural oscillators: analytic results based on Random Matrix Theory.

    PubMed

    Timme, Marc; Geisel, Theo; Wolf, Fred

    2006-03-01

    We analyze the dynamics of networks of spiking neural oscillators. First, we present an exact linear stability theory of the synchronous state for networks of arbitrary connectivity. For general neuron rise functions, stability is determined by multiple operators, for which standard analysis is not suitable. We describe a general nonstandard solution to the multioperator problem. Subsequently, we derive a class of neuronal rise functions for which all stability operators become degenerate and standard eigenvalue analysis becomes a suitable tool. Interestingly, this class is found to consist of networks of leaky integrate-and-fire neurons. For random networks of inhibitory integrate-and-fire neurons, we then develop an analytical approach, based on the theory of random matrices, to precisely determine the eigenvalue distributions of the stability operators. This yields the asymptotic relaxation time for perturbations to the synchronous state which provides the characteristic time scale on which neurons can coordinate their activity in such networks. For networks with finite in-degree, i.e., finite number of presynaptic inputs per neuron, we find a speed limit to coordinating spiking activity. Even with arbitrarily strong interaction strengths neurons cannot synchronize faster than at a certain maximal speed determined by the typical in-degree.

  10. Stability of two cluster solutions in pulse coupled networks of neural oscillators.

    PubMed

    Chandrasekaran, Lakshmi; Achuthan, Srisairam; Canavier, Carmen C

    2011-04-01

    Phase response curves (PRCs) have been widely used to study synchronization in neural circuits comprised of pacemaking neurons. They describe how the timing of the next spike in a given spontaneously firing neuron is affected by the phase at which an input from another neuron is received. Here we study two reciprocally coupled clusters of pulse coupled oscillatory neurons. The neurons within each cluster are presumed to be identical and identically pulse coupled, but not necessarily identical to those in the other cluster. We investigate a two cluster solution in which all oscillators are synchronized within each cluster, but in which the two clusters are phase locked at nonzero phase with each other. Intuitively, one might expect this solution to be stable only when synchrony within each isolated cluster is stable, but this is not the case. We prove rigorously the stability of the two cluster solution and show how reciprocal coupling can stabilize synchrony within clusters that cannot synchronize in isolation. These stability results for the two cluster solution suggest a mechanism by which reciprocal coupling between brain regions can induce local synchronization via the network feedback loop.

  11. When problem size matters: differential effects of brain stimulation on arithmetic problem solving and neural oscillations.

    PubMed

    Rütsche, Bruno; Hauser, Tobias U; Jäncke, Lutz; Grabner, Roland H

    2015-01-01

    The problem size effect is a well-established finding in arithmetic problem solving and is characterized by worse performance in problems with larger compared to smaller operand size. Solving small and large arithmetic problems has also been shown to involve different cognitive processes and distinct electroencephalography (EEG) oscillations over the left posterior parietal cortex (LPPC). In this study, we aimed to provide further evidence for these dissociations by using transcranial direct current stimulation (tDCS). Participants underwent anodal (30min, 1.5 mA, LPPC) and sham tDCS. After the stimulation, we recorded their neural activity using EEG while the participants solved small and large arithmetic problems. We found that the tDCS effects on performance and oscillatory activity critically depended on the problem size. While anodal tDCS improved response latencies in large arithmetic problems, it decreased solution rates in small arithmetic problems. Likewise, the lower-alpha desynchronization in large problems increased, whereas the theta synchronization in small problems decreased. These findings reveal that the LPPC is differentially involved in solving small and large arithmetic problems and demonstrate that the effects of brain stimulation strikingly differ depending on the involved neuro-cognitive processes.

  12. Phasic bursting pattern of postural responses may reflect internal dynamics: simulation of trunk reflexes with a neural oscillator model.

    PubMed

    Wulf, Arne; Wagner, Heiko; Wulf, Thomas; Schinowski, David; Puta, Christian; Anders, Christoph; Chong, Sook Yee

    2012-10-11

    Postural responses are usually investigated as reflexes. Several trials are averaged, and trial-to-trial variations are interpreted as noise. Several studies providing single-trial data plots revealed oscillations that may be cancelled out in averaged time series. Variations between single trials may also be interpreted as a consequence of changed dynamic properties of the neural circuitries. Therefore, we propose a Matsuoka oscillator model to describe single-trial postural responses to external perturbations. The applicability of the model was demonstrated by a comparison between simulations and experimental electromyographic (EMG) data. Vertical force perturbations of durations 0.4 s and 0.2 s were applied via a handle to 10 subjects. Handle force was used as model input, and EMG data from the external oblique muscles was compared with simulation output. Model coefficients were optimized by a least-squares algorithm. The optimization produced a good similarity between simulation and experimental data with determination coefficients of r(2)=0.7 and greater. Furthermore, as a model validation, the model coefficients were used to predict other perturbation trials with similarities between predictions and respective EMG data of about r(2)=0.45, which was in the range of trial-to-trial EMG variability. The observed oscillations are assumed to originate from the central nervous system with changes in the neural circuitries between trials. Hence, the oscillations in single trial responses which are usually regarded as noise might be generated by the dynamics of a neural oscillator. Copyright © 2012 Elsevier Ltd. All rights reserved.

  13. Recognition of abstract objects via neural oscillators: interaction among topological organization, associative memory and gamma band synchronization.

    PubMed

    Ursino, Mauro; Magosso, Elisa; Cuppini, Cristiano

    2009-02-01

    Synchronization of neural activity in the gamma band is assumed to play a significant role not only in perceptual processing, but also in higher cognitive functions. Here, we propose a neural network of Wilson-Cowan oscillators to simulate recognition of abstract objects, each represented as a collection of four features. Features are ordered in topological maps of oscillators connected via excitatory lateral synapses, to implement a similarity principle. Experience on previous objects is stored in long-range synapses connecting the different topological maps, and trained via timing dependent Hebbian learning (previous knowledge principle). Finally, a downstream decision network detects the presence of a reliable object representation, when all features are oscillating in synchrony. Simulations performed giving various simultaneous objects to the network (from 1 to 4), with some missing and/or modified properties suggest that the network can reconstruct objects, and segment them from the other simultaneously present objects, even in case of deteriorated information, noise, and moderate correlation among the inputs (one common feature). The balance between sensitivity and specificity depends on the strength of the Hebbian learning. Achieving a correct reconstruction in all cases, however, requires ad hoc selection of the oscillation frequency. The model represents an attempt to investigate the interactions among topological maps, autoassociative memory, and gamma-band synchronization, for recognition of abstract objects.

  14. Interactive effect of light colours and temporal synergism of circadian neural oscillations in reproductive regulation of Japanese quail.

    PubMed

    Yadav, Suneeta; Chaturvedi, Chandra Mohini

    2016-09-01

    Avian literature reports the modulation of 'photoperiodic gonadal responses' by the temporal phase relation of serotonergic and dopaminergic oscillations in Japanese quail. But, the modulation of 'light colour responses' by the temporal synergism of neural oscillations is not yet known. Hence the present study was designed to investigate the interaction of the light colour (blue, red) and the phase relation of neural oscillations in the reproductive regulation of Japanese quail. Three week old male Japanese quail were divided into two groups and maintained under a long day length condition (16L:8D) and were exposed to a 30 lux intensity of blue LED (light emitting diode) (B LED) and a red LED light (R LED). At the age of 15.5weeks, quail of one subgroup of B LED were injected with serotonin precursor (5-HTP) and dopamine precursor (l-DOPA) 12hrs apart (B LED+12-hr) and those of the R LED group were injected with the same drugs (5mg/100g body weight over a period of thirteen days) but 8hrs apart (R LED+8-hr). The remaining subgroups of both the light colour groups (B LED & R LED) received normal saline twice daily and served as controls. Cloacal gland volume was recorded weekly until 35.5weeks of age when the study was terminated and reproductive parameters (testicular volume, GSI, seminiferous tubule diameter and plasma testosterone) were assessed. Results indicate that the 8-hr temporal phase relation of neural oscillations suppresses reproductive activity even during the photosensitive phase of the red light exposed quail (R LED+8-hr) compare to the R LED controls. On the other hand, the 12-hr temporal phase relation stimulates the gonadal development of the B LED+12-hr quail compared to the B LED controls which after completing one cycle entered into a regressive phase and remained sexually quiescent. These experiments suggest that the temporal phase relations of circadian neural oscillations, in addition to modulating the classical photoperiodic responses, may

  15. Object segmentation and recovery via neural oscillators implementing the similarity and prior knowledge gestalt rules.

    PubMed

    Ursino, Mauro; Magosso, Elisa; La Cara, Giuseppe-Emiliano; Cuppini, Cristiano

    2006-09-01

    Object recognition requires the solution of the binding and segmentation problems, i.e., grouping different features to achieve a coherent representation. Synchronization of neural activity in the gamma-band, associated with gestalt perception, has often been proposed as a putative mechanism to solve these problems, not only as to low-level processing, but also in higher cortical functions. In the present work, a network of Wilson-Cowan oscillators is used to segment simultaneous objects, and recover an object from partial or corrupted information, by implementing two gestalt rules: similarity and prior knowledge. The network consists of H different areas, each devoted to representation of a particular feature of the object, according to a topological organization. The similarity law is realized via lateral intra-area connections, arranged as a "Mexican-hat". Prior knowledge is realized via inter-area connections, which link properties belonging to a previously memorized object. A global inhibitor allows segmentation of several objects avoiding interference. Simulation results, performed using three simultaneous input objects, show that the network is able to detect an object even in difficult conditions (i.e., when some features are absent or shifted with respect to the original one). Moreover, the trade-off between sensitivity (capacity to detect true positives) and specificity (capacity to reject false positives) can be controlled acting on the extension of lateral synapses (i.e., on the level of accepted similarity). Finally, the network can also deal with correlated objects, i.e., objects which have some common features. Simulations performed using a different number of objects (2, 3, 4 or 5) suggest that the network is able to segment and recall up to four objects, but the oscillation frequency must increase, the lower the number of objects simultaneously present. The model, although quite simpler compared with neurophysiology, may represent a theoretical

  16. Oscillation and coding in a formal neural network considered as a guide for plausible simulations of the insect olfactory system.

    PubMed

    Horcholle-Bossavit, Ginette; Quenet, Brigitte; Foucart, Olivier

    2007-01-01

    For the analysis of coding mechanisms in the insect olfactory system, a fully connected network of synchronously updated McCulloch and Pitts neurons (MC-P type) was developed [Quenet, B., Horn, D., 2003. The dynamic neural filter: a binary model of spatio-temporal coding. Neural Comput. 15 (2), 309-329]. Considering the update time as an intrinsic clock, this "Dynamic Neural Filter" (DNF), which maps regions of input space into spatio-temporal sequences of neuronal activity, is able to produce exact binary codes extracted from the synchronized activities recorded at the level of projection neurons (PN) in the locust antennal lobe (AL) in response to different odors [Wehr, M., Laurent, G., 1996. Odor encoding by temporal sequences of firing in oscillating neural assemblies. Nature 384, 162-166]. Here, in a first step, we separate the populations of PN and local inhibitory neurons (LN) and use the DNF as a guide for simulations based on biological plausible neurons (Hodgkin-Huxley: H-H type). We show that a parsimonious network of 10 H-H neurons generates action potentials whose timing represents the required codes. In a second step, we construct a new type of DNF in order to study the population dynamics when different delays are taken into account. We find synaptic matrices which lead to both the emergence of robust oscillations and spatio-temporal patterns, using a formal criterion, based on a Normalized Euclidian Distance (NED), in order to measure the use of the temporal dimension as a coding dimension by the DNF. Similarly to biological PN, the activity of excitatory neurons in the model can be both phase-locked to different cycles of oscillations which remind local field potential (LFP), and nevertheless exhibit dynamic behavior complex enough to be the basis of spatio-temporal codes.

  17. On the neural implausibility of the modular mind: Evidence for distributed construction dissolves boundaries between perception, cognition, and emotion.

    PubMed

    Hackel, Leor M; Larson, Grace M; Bowen, Jeffrey D; Ehrlich, Gaven A; Mann, Thomas C; Middlewood, Brianna; Roberts, Ian D; Eyink, Julie; Fetterolf, Janell C; Gonzalez, Fausto; Garrido, Carlos O; Kim, Jinhyung; O'Brien, Thomas C; O'Malley, Ellen E; Mesquita, Batja; Barrett, Lisa Feldman

    2016-01-01

    Firestone & Scholl (F&S) rely on three problematic assumptions about the mind (modularity, reflexiveness, and context-insensitivity) to argue cognition does not fundamentally influence perception. We highlight evidence indicating that perception, cognition, and emotion are constructed through overlapping, distributed brain networks characterized by top-down activity and context-sensitivity. This evidence undermines F&S's ability to generalize from case studies to the nature of perception.

  18. Modular, Multilayer Perceptron

    NASA Technical Reports Server (NTRS)

    Cheng, Li-Jen; Liu, Tsuen-Hsi

    1991-01-01

    Combination of proposed modular, multilayer perceptron and algorithm for its operation recognizes new objects after relatively brief retraining sessions. (Perceptron is multilayer, feedforward artificial neural network fully connected and trained via back-propagation learning algorithm.) Knowledge pertaining to each object to be recognized resides in subnetwork of full network, therefore not necessary to retrain full network to recognize each new object.

  19. Mouse neuroblastoma cell-based model and the effect of epileptic events on calcium oscillations and neural spikes

    NASA Astrophysics Data System (ADS)

    Kim, Suhwan; Jung, Unsang; Baek, Juyoung; Lee, Sangwon; Jung, Woonggyu; Kim, Jeehyun; Kang, Shinwon

    2013-01-01

    Recently, mouse neuroblastoma cells have been considered as an attractive model for the study of human neurological and prion diseases, and they have been intensively used as a model system in different areas. For example, the differentiation of neuro2a (N2A) cells, receptor-mediated ion current, and glutamate-induced physiological responses have been actively investigated with these cells. These mouse neuroblastoma N2A cells are of interest because they grow faster than other cells of neural origin and have a number of other advantages. The calcium oscillations and neural spikes of mouse neuroblastoma N2A cells in epileptic conditions are evaluated. Based on our observations of neural spikes in these cells with our proposed imaging modality, we reported that they can be an important model in epileptic activity studies. We concluded that mouse neuroblastoma N2A cells produce epileptic spikes in vitro in the same way as those produced by neurons or astrocytes. This evidence suggests that increased levels of neurotransmitter release due to the enhancement of free calcium from 4-aminopyridine causes the mouse neuroblastoma N2A cells to produce epileptic spikes and calcium oscillations.

  20. Mouse neuroblastoma cell based model and the effect of epileptic events on calcium oscillations and neural spikes

    NASA Astrophysics Data System (ADS)

    Kim, Suhwan; Baek, Juyeong; Jung, Unsang; Lee, Sangwon; Jung, Woonggyu; Kim, Jeehyun; Kang, Shinwon

    2013-05-01

    Recently, Mouse neuroblastoma cells are considered as an attractive model for the study of human neurological and prion diseases, and intensively used as a model system in different areas. Among those areas, differentiation of neuro2a (N2A) cells, receptor mediated ion current, and glutamate induced physiological response are actively investigated. The reason for the interest to mouse neuroblastoma N2A cells is that they have a fast growing rate than other cells in neural origin with a few another advantages. This study evaluated the calcium oscillations and neural spikes recording of mouse neuroblastoma N2A cells in an epileptic condition. Based on our observation of neural spikes in mouse N2A cell with our proposed imaging modality, we report that mouse neuroblastoma N2A cells can be an important model related to epileptic activity studies. It is concluded that the mouse neuroblastoma N2A cells produce the epileptic spikes in vitro in the same way as produced by the neurons or the astrocytes. This evidence advocates the increased and strong level of neurotransmitters release by enhancement in free calcium using the 4-aminopyridine which causes the mouse neuroblastoma N2A cells to produce the epileptic spikes and calcium oscillation.

  1. Neurodynamic oscillators

    NASA Technical Reports Server (NTRS)

    Espinosa, Ismael; Gonzalez, Hortensia; Quiza, Jorge; Gonazalez, J. Jesus; Arroyo, Ruben; Lara, Ritaluz

    1995-01-01

    Oscillation of electrical activity has been found in many nervous systems, from invertebrates to vertebrates including man. There exists experimental evidence of very simple circuits with the capability of oscillation. Neurons with intrinsic oscillation have been found and also neural circuits where oscillation is a property of the network. These two types of oscillations coexist in many instances. It is nowadays hypothesized that behind synchronization and oscillation there is a system of coupled oscillators responsible for activities that range from locomotion and feature binding in vision to control of sleep and circadian rhythms. The huge knowledge that has been acquired on oscillators from the times of Lord Rayleigh has made the simulation of neural oscillators a very active endeavor. This has been enhanced with more recent physiological findings about small neural circuits by means of intracellular and extracellular recordings as well as imaging methods. The future of this interdisciplinary field looks very promising; some researchers are going into quantum mechanics with the idea of trying to provide a quantum description of the brain. In this work we describe some simulations using neuron models by means of which we form simple neural networks that have the capability of oscillation. We analyze the oscillatory activity with root locus method, cross-correlation histograms, and phase planes. In the more complicated neural network models there is the possibility of chaotic oscillatory activity and we study that by means of Lyapunov exponents. The companion paper shows an example of that kind.

  2. Stochastic dynamics of uncoupled neural oscillators: Fokker-Planck studies with the finite element method

    SciTech Connect

    Galan, Roberto F.; Urban, Nathaniel N.; Ermentrout, G. Bard

    2007-11-15

    We have investigated the effect of the phase response curve on the dynamics of oscillators driven by noise in two limit cases that are especially relevant for neuroscience. Using the finite element method to solve the Fokker-Planck equation we have studied (i) the impact of noise on the regularity of the oscillations quantified as the coefficient of variation, (ii) stochastic synchronization of two uncoupled phase oscillators driven by correlated noise, and (iii) their cross-correlation function. We show that, in general, the limit of type II oscillators is more robust to noise and more efficient at synchronizing by correlated noise than type I.

  3. Stochastic dynamics of uncoupled neural oscillators: Fokker-Planck studies with the finite element method

    NASA Astrophysics Data System (ADS)

    Galán, Roberto F.; Ermentrout, G. Bard; Urban, Nathaniel N.

    2007-11-01

    We have investigated the effect of the phase response curve on the dynamics of oscillators driven by noise in two limit cases that are especially relevant for neuroscience. Using the finite element method to solve the Fokker-Planck equation we have studied (i) the impact of noise on the regularity of the oscillations quantified as the coefficient of variation, (ii) stochastic synchronization of two uncoupled phase oscillators driven by correlated noise, and (iii) their cross-correlation function. We show that, in general, the limit of type II oscillators is more robust to noise and more efficient at synchronizing by correlated noise than type I.

  4. Differential modulation of global and local neural oscillations in REM sleep by homeostatic sleep regulation

    PubMed Central

    Kim, Bowon; Kocsis, Bernat; Hwang, Eunjin; Kim, Youngsoo; Strecker, Robert E.; McCarley, Robert W.; Choi, Jee Hyun

    2017-01-01

    Homeostatic rebound in rapid eye movement (REM) sleep normally occurs after acute sleep deprivation, but REM sleep rebound settles on a persistently elevated level despite continued accumulation of REM sleep debt during chronic sleep restriction (CSR). Using high-density EEG in mice, we studied how this pattern of global regulation is implemented in cortical regions with different functions and network architectures. We found that across all areas, slow oscillations repeated the behavioral pattern of persistent enhancement during CSR, whereas high-frequency oscillations showed progressive increases. This pattern followed a common rule despite marked topographic differences. The findings suggest that REM sleep slow oscillations may translate top-down homeostatic control to widely separated brain regions whereas fast oscillations synchronizing local neuronal ensembles escape this global command. These patterns of EEG oscillation changes are interpreted to reconcile two prevailing theories of the function of sleep, synaptic homeostasis and sleep dependent memory consolidation. PMID:28193862

  5. Differential modulation of global and local neural oscillations in REM sleep by homeostatic sleep regulation.

    PubMed

    Kim, Bowon; Kocsis, Bernat; Hwang, Eunjin; Kim, Youngsoo; Strecker, Robert E; McCarley, Robert W; Choi, Jee Hyun

    2017-02-28

    Homeostatic rebound in rapid eye movement (REM) sleep normally occurs after acute sleep deprivation, but REM sleep rebound settles on a persistently elevated level despite continued accumulation of REM sleep debt during chronic sleep restriction (CSR). Using high-density EEG in mice, we studied how this pattern of global regulation is implemented in cortical regions with different functions and network architectures. We found that across all areas, slow oscillations repeated the behavioral pattern of persistent enhancement during CSR, whereas high-frequency oscillations showed progressive increases. This pattern followed a common rule despite marked topographic differences. The findings suggest that REM sleep slow oscillations may translate top-down homeostatic control to widely separated brain regions whereas fast oscillations synchronizing local neuronal ensembles escape this global command. These patterns of EEG oscillation changes are interpreted to reconcile two prevailing theories of the function of sleep, synaptic homeostasis and sleep dependent memory consolidation.

  6. Olfactory system gamma oscillations: the physiological dissection of a cognitive neural system

    PubMed Central

    Rojas-Líbano, Daniel

    2008-01-01

    Oscillatory phenomena have been a focus of dynamical systems research since the time of the classical studies on the pendulum by Galileo. Fast cortical oscillations also have a long and storied history in neurophysiology, and olfactory oscillations have led the way with a depth of explanation not present in the literature of most other cortical systems. From the earliest studies of odor-evoked oscillations by Adrian, many reports have focused on mechanisms and functional associations of these oscillations, in particular for the so-called gamma oscillations. As a result, much information is now available regarding the biophysical mechanisms that underlie the oscillations in the mammalian olfactory system. Recent studies have expanded on these and addressed functionality directly in mammals and in the analogous insect system. Sub-bands within the rodent gamma oscillatory band associated with specific behavioral and cognitive states have also been identified. All this makes oscillatory neuronal networks a unique interdisciplinary platform from which to study neurocognitive and dynamical phenomena in intact, freely behaving animals. We present here a summary of what has been learned about the functional role and mechanisms of gamma oscillations in the olfactory system as a guide for similar studies in other cortical systems. PMID:19003484

  7. Prediction of arm trajectory from the neural activities of the primary motor cortex with modular connectionist architecture.

    PubMed

    Choi, Kyuwan; Hirose, Hideaki; Sakurai, Yoshio; Iijima, Toshio; Koike, Yasuharu

    2009-11-01

    In our previous study [Koike, Y., Hirose, H., Sakurai, Y., Iijima T., (2006). Prediction of arm trajectory from a small number of neuron activities in the primary motor cortex. Neuroscience Research, 55, 146-153], we succeeded in reconstructing muscle activities from the offline combination of single neuron activities recorded in a serial manner in the primary motor cortex of a monkey and in reconstructing the joint angles from the reconstructed muscle activities during a movement condition using an artificial neural network. However, the joint angles during a static condition were not reconstructed. The difficulties of reconstruction under both static and movement conditions mainly arise due to muscle properties such as the velocity-tension relationship and the length-tension relationship. In this study, in order to overcome the limitations due to these muscle properties, we divided an artificial neural network into two networks: one for movement control and the other for posture control. We also trained the gating network to switch between the two neural networks. As a result, the gating network switched the modules properly, and the accuracy of the estimated angles improved compared to the case of using only one artificial neural network.

  8. Experimental evaluation of a control system for active mass dampers consisting of a position controller and neural oscillator

    NASA Astrophysics Data System (ADS)

    Sasaki, T.; Iba, D.; Hongu, J.; Nakamura, M.; Moriwaki, I.

    2016-09-01

    This paper shows experimental performance evaluation of a new control system for active mass dampers (AMDs). The proposed control system consists of a position controller and neural oscillator, and is designed for the solution of a stroke limitation problem of an auxiliary mass of the AMDs. The neural oscillator synchronizing with the response of a structure generates a signal, which is utilized for switching of motion direction of the auxiliary mass and for travel distances of the auxiliary mass. According to the generated signal, the position controller drives the auxiliary mass to the target values, and the reaction force resulting from the movement of the auxiliary mass is transmitted to the structure, and reduces the vibration amplitude of the structure. Our previous research results showed that the proposed system could reduce the vibration of the structure while the motion of auxiliary mass was suppressed within the restriction; however the control performance was evaluated numerically. In order to put the proposed system to practical use, the system should be evaluated experimentally. This paper starts by illustrating the relation among subsystems of the proposed system, and then, shows experimental responses of a structure model with the AMD excited by earthquakes on a shaker to confirm the validity of the system.

  9. Estimation of inter-modular connectivity from the local field potentials in a hierarchical modular network

    NASA Astrophysics Data System (ADS)

    Cui, Xue-Mei; Kim, Won Sup; Hwang, Dong-Uk; Han, Seung Kee

    2015-05-01

    We propose a method of estimating inter-modular connectivity in a hierarchical modular network. The method is based on an analysis of inverse phase synchronization applied to the local field potentials on a hierarchical modular network of phase oscillators. For a strong-coupling strength, the inverse phase synchronization index of the local field potentials for two modules depends linearly on the corresponding inter-modular connectivity defined as the number of links connecting the modules. The method might enable us to estimate the inter-modular connectivity in various complex systems from the inverse phase synchronization index of the mesoscopic modular activities.

  10. Patterned porous silicon photonic crystals with modular surface chemistry for spatial control of neural stem cell differentiation

    NASA Astrophysics Data System (ADS)

    Huang, Tiffany H.; Pei, Yi; Zhang, Douglas; Li, Yanfen; Kilian, Kristopher A.

    2016-05-01

    We present a strategy to spatially define regions of gold and nanostructured silicon photonics, each with materials-specific surface chemistry, for azide-alkyne cycloaddition of different bioactive peptides. Neural stem cells are spatially directed to undergo neurogenesis and astrogenesis as a function of both surface properties and peptide identity.We present a strategy to spatially define regions of gold and nanostructured silicon photonics, each with materials-specific surface chemistry, for azide-alkyne cycloaddition of different bioactive peptides. Neural stem cells are spatially directed to undergo neurogenesis and astrogenesis as a function of both surface properties and peptide identity. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr08327c

  11. Open Ephys electroencephalography (Open Ephys +EEG): a modular, low-cost, open-source solution to human neural recording.

    PubMed

    Black, Christopher; Voigts, Jakob; Agrawal, Uday; Ladow, Max; Santoyo, Juan; Moore, Christopher; Jones, Stephanie

    2017-03-07

    Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. For example, EEG signals have been used to regulate anesthetic delivery, to control brain-computer interfaces, and to drive transcranial alternating current stimulation for the treatment of psychiatric illness. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. This rigidity makes it extremely difficult or infeasible to adapt EEG to novel closed-loop experiments. For instance, many current systems are not able to communicate with software and hardware from other vendors, nor are they able to achieve low-latency timescales (100 ms) necessary to operate on the fast patterns of neural activities. Recently, open-source alternatives to commercial systems have been developed that can eliminate these problems, driving down research costs and promoting collaborations and innovations. Here, we present methods to expand the use of a commercially available, open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings providing a novel technique for low-cost, easily-adaptable EEG recording. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys + EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments.

  12. High-frequency neural oscillations and visual processing deficits in schizophrenia

    PubMed Central

    Tan, Heng-Ru May; Lana, Luiz; Uhlhaas, Peter J.

    2013-01-01

    Visual information is fundamental to how we understand our environment, make predictions, and interact with others. Recent research has underscored the importance of visuo-perceptual dysfunctions for cognitive deficits and pathophysiological processes in schizophrenia. In the current paper, we review evidence for the relevance of high frequency (beta/gamma) oscillations towards visuo-perceptual dysfunctions in schizophrenia. In the first part of the paper, we examine the relationship between beta/gamma band oscillations and visual processing during normal brain functioning. We then summarize EEG/MEG-studies which demonstrate reduced amplitude and synchrony of high-frequency activity during visual stimulation in schizophrenia. In the final part of the paper, we identify neurobiological correlates as well as offer perspectives for future research to stimulate further inquiry into the role of high-frequency oscillations in visual processing impairments in the disorder. PMID:24130535

  13. The corollary discharge in humans is related to synchronous neural oscillations

    PubMed Central

    Chen, Chi-Ming A.; Mathalon, Daniel H.; Roach, Brian J.; Cavus, Idil; Spencer, Dennis D.; Ford, Judith M.

    2014-01-01

    How do animals distinguish between sensations coming from external sources and those resulting from their own actions? A corollary discharge system has evolved that involves the transmission of a copy of motor commands to sensory cortex, where the expected sensation is generated. Through this mechanism, sensations are tagged as coming from self, and responsiveness to them is minimized. The present study investigated whether neural phase synchrony between motor command and auditory cortical areas is related to the suppression of the auditory cortical response. We recorded electrocorticograms from the human brain during a vocalizing/listening task. Neural phase synchrony between Broca’s area and auditory cortex in the gamma band (35 Hz to ~50 Hz) in the 50 ms time window preceding speech onset was greater during vocalizing than listening to a playback of the same spoken sounds. Because pre-speech neural synchrony was correlated (r = −0.83, p = 0.006) with the subsequent suppression of the auditory cortical response to the spoken sound, we hypothesize that phase synchrony in the gamma band between Broca’s area and auditory cortex is the neural instantiation of the transmission of a copy of motor commands. We suggest that neural phase synchrony of gamma frequencies may contribute to transmission of corollary discharges in humans. PMID:20946054

  14. Hemispheric Asymmetry of Endogenous Neural Oscillations in Young Children: Implications for Hearing Speech In Noise

    PubMed Central

    Thompson, Elaine C.; Woodruff Carr, Kali; White-Schwoch, Travis; Tierney, Adam; Nicol, Trent; Kraus, Nina

    2016-01-01

    Speech signals contain information in hierarchical time scales, ranging from short-duration (e.g., phonemes) to long-duration cues (e.g., syllables, prosody). A theoretical framework to understand how the brain processes this hierarchy suggests that hemispheric lateralization enables specialized tracking of acoustic cues at different time scales, with the left and right hemispheres sampling at short (25 ms; 40 Hz) and long (200 ms; 5 Hz) periods, respectively. In adults, both speech-evoked and endogenous cortical rhythms are asymmetrical: low-frequency rhythms predominate in right auditory cortex, and high-frequency rhythms in left auditory cortex. It is unknown, however, whether endogenous resting state oscillations are similarly lateralized in children. We investigated cortical oscillations in children (3–5 years; N = 65) at rest and tested our hypotheses that this temporal asymmetry is evident early in life and facilitates recognition of speech in noise. We found a systematic pattern of increasing leftward asymmetry for higher frequency oscillations; this pattern was more pronounced in children who better perceived words in noise. The observed connection between left-biased cortical oscillations in phoneme-relevant frequencies and speech-in-noise perception suggests hemispheric specialization of endogenous oscillatory activity may support speech processing in challenging listening environments, and that this infrastructure is present during early childhood. PMID:26804355

  15. Category-Specific Neural Oscillations Predict Recall Organization During Memory Search

    PubMed Central

    Morton, Neal W.; Kahana, Michael J.; Rosenberg, Emily A.; Baltuch, Gordon H.; Litt, Brian; Sharan, Ashwini D.; Sperling, Michael R.; Polyn, Sean M.

    2013-01-01

    Retrieved-context models of human memory propose that as material is studied, retrieval cues are constructed that allow one to target particular aspects of past experience. We examined the neural predictions of these models by using electrocorticographic/depth recordings and scalp electroencephalography (EEG) to characterize category-specific oscillatory activity, while participants studied and recalled items from distinct, neurally discriminable categories. During study, these category-specific patterns predict whether a studied item will be recalled. In the scalp EEG experiment, category-specific activity during study also predicts whether a given item will be recalled adjacent to other same-category items, consistent with the proposal that a category-specific retrieval cue is used to guide memory search. Retrieved-context models suggest that integrative neural circuitry is involved in the construction and maintenance of the retrieval cue. Consistent with this hypothesis, we observe category-specific patterns that rise in strength as multiple same-category items are studied sequentially, and find that individual differences in this category-specific neural integration during study predict the degree to which a participant will use category information to organize memory search. Finally, we track the deployment of this retrieval cue during memory search: Category-specific patterns are stronger when participants organize their responses according to the category of the studied material. PMID:22875859

  16. Prediction of psychosis using neural oscillations and machine learning in neuroleptic-naïve at-risk patients.

    PubMed

    Ramyead, Avinash; Studerus, Erich; Kometer, Michael; Uttinger, Martina; Gschwandtner, Ute; Fuhr, Peter; Riecher-Rössler, Anita

    2016-06-01

    This study investigates whether abnormal neural oscillations, which have been shown to precede the onset of frank psychosis, could be used towards the individualised prediction of psychosis in clinical high-risk patients. We assessed the individualised prediction of psychosis by detecting specific patterns of beta and gamma oscillations using machine-learning algorithms. Prediction models were trained and tested on 53 neuroleptic-naïve patients with a clinical high-risk for psychosis. Of these, 18 later transitioned to psychosis. All patients were followed up for at least 3 years. For an honest estimation of the generalisation capacity, the predictive performance of the models was assessed in unseen test cases using repeated nested cross-validation. Transition to psychosis could be predicted from current-source density (CSD; area under the curve [AUC] = 0.77), but not from lagged phase synchronicity data (LPS; AUC = 0.56). Combining both modalities did not improve the predictive accuracy (AUC = 0.78). The left superior temporal gyrus, the left inferior parietal lobule and the precuneus most strongly contributed to the prediction of psychosis. Our results suggest that CSD measurements extracted from clinical resting state EEG can help to improve the prediction of psychosis on a single-subject level.

  17. What changes in neural oscillations can reveal about developmental cognitive neuroscience: language development as a case in point.

    PubMed

    Maguire, Mandy J; Abel, Alyson D

    2013-10-01

    EEG is a primary method for studying temporally precise neuronal processes across the lifespan. Most of this work focuses on event related potentials (ERPs); however, using time-locked time frequency analysis to decompose the EEG signal can identify and distinguish multiple changes in brain oscillations underlying cognition (Bastiaansen et al., 2010). Further this measure is thought to reflect changes in inter-neuronal communication more directly than ERPs (Nunez and Srinivasan, 2006). Although time frequency has elucidated cognitive processes in adults, applying it to cognitive development is still rare. Here, we review the basics of neuronal oscillations, some of what they reveal about adult cognitive function, and what little is known relating to children. We focus on language because it develops early and engages complex cortical networks. Additionally, because time frequency analysis of the EEG related to adult language comprehension has been incredibly informative, using similar methods with children will shed new light on current theories of language development and increase our understanding of how neural processes change over the lifespan. Our goal is to emphasize the power of this methodology and encourage its use throughout developmental cognitive neuroscience. Copyright © 2013 Elsevier Ltd. All rights reserved.

  18. Widespread neural oscillations in the delta band dissociate rule convergence from rule divergence during creative idea generation.

    PubMed

    Boot, Nathalie; Baas, Matthijs; Mühlfeld, Elisabeth; de Dreu, Carsten K W; van Gaal, Simon

    2017-09-01

    Critical to creative cognition and performance is both the generation of multiple alternative solutions in response to open-ended problems (divergent thinking) and a series of cognitive operations that converges on the correct or best possible answer (convergent thinking). Although the neural underpinnings of divergent and convergent thinking are still poorly understood, several electroencephalography (EEG) studies point to differences in alpha-band oscillations between these thinking modes. We reason that, because most previous studies employed typical block designs, these pioneering findings may mainly reflect the more sustained aspects of creative processes that extend over longer time periods, and that still much is unknown about the faster-acting neural mechanisms that dissociate divergent from convergent thinking during idea generation. To this end, we developed a new event-related paradigm, in which we measured participants' tendency to implicitly follow a rule set by examples, versus breaking that rule, during the generation of novel names for specific categories (e.g., pasta, planets). This approach allowed us to compare the oscillatory dynamics of rule convergent and rule divergent idea generation and at the same time enabled us to measure spontaneous switching between these thinking modes on a trial-to-trial basis. We found that, relative to more systematic, rule convergent thinking, rule divergent thinking was associated with widespread decreases in delta band activity. Therefore, this study contributes to advancing our understanding of the neural underpinnings of creativity by addressing some methodological challenges that neuroscientific creativity research faces. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Modular entanglement.

    PubMed

    Gualdi, Giulia; Giampaolo, Salvatore M; Illuminati, Fabrizio

    2011-02-04

    We introduce and discuss the concept of modular entanglement. This is the entanglement that is established between the end points of modular systems composed by sets of interacting moduli of arbitrarily fixed size. We show that end-to-end modular entanglement scales in the thermodynamic limit and rapidly saturates with the number of constituent moduli. We clarify the mechanisms underlying the onset of entanglement between distant and noninteracting quantum systems and its optimization for applications to quantum repeaters and entanglement distribution and sharing.

  20. Chaotic itinerancy within the coupled dynamics between a physical body and neural oscillator networks.

    PubMed

    Park, Jihoon; Mori, Hiroki; Okuyama, Yuji; Asada, Minoru

    2017-01-01

    Chaotic itinerancy is a phenomenon in which the state of a nonlinear dynamical system spontaneously explores and attracts certain states in a state space. From this perspective, the diverse behavior of animals and its spontaneous transitions lead to a complex coupled dynamical system, including a physical body and a brain. Herein, a series of simulations using different types of non-linear oscillator networks (i.e., regular, small-world, scale-free, random) with a musculoskeletal model (i.e., a snake-like robot) as a physical body are conducted to understand how the chaotic itinerancy of bodily behavior emerges from the coupled dynamics between the body and the brain. A behavior analysis (behavior clustering) and network analysis for the classified behavior are then applied. The former consists of feature vector extraction from the motions and classification of the movement patterns that emerged from the coupled dynamics. The network structures behind the classified movement patterns are revealed by estimating the "information networks" different from the given non-linear oscillator networks based on the transfer entropy which finds the information flow among neurons. The experimental results show that: (1) the number of movement patterns and their duration depend on the sensor ratio to control the balance of strength between the body and the brain dynamics and on the type of the given non-linear oscillator networks; and (2) two kinds of information networks are found behind two kinds movement patterns with different durations by utilizing the complex network measures, clustering coefficient and the shortest path length with a negative and a positive relationship with the duration periods of movement patterns. The current results seem promising for a future extension of the method to a more complicated body and environment. Several requirements are also discussed.

  1. Abnormal task driven neural oscillations in multiple sclerosis: A visuomotor MEG study.

    PubMed

    Barratt, Eleanor L; Tewarie, Prejaas K; Clarke, Margareta A; Hall, Emma L; Gowland, Penny A; Morris, Peter G; Francis, Susan T; Evangelou, Nikos; Brookes, Matthew J

    2017-02-27

    Multiple sclerosis (MS) is a debilitating disease commonly attributed to degradation of white matter myelin. Symptoms include fatigue, as well as problems associated with vision and movement. Although areas of demyelination in white matter are observed routinely in patients undergoing MRI scans, such measures are often a poor predictor of disease severity. For this reason, it is instructive to measure associated changes in brain function. Widespread white-matter demyelination may lead to delays of propagation of neuronal activity, and with its excellent temporal resolution, magnetoencephalography can be used to probe such delays in controlled conditions (e.g., during a task). In healthy subjects, responses to visuomotor tasks are well documented: in motor cortex, movement elicits a localised decrease in the power of beta band oscillations (event-related beta desynchronisation) followed by an increase above baseline on movement cessation (post-movement beta rebound (PMBR)). In visual cortex, visual stimulation generates increased gamma oscillations. In this study, we use a visuomotor paradigm to measure these responses in MS patients and compare them to age- and gender-matched healthy controls. We show a significant increase in the time-to-peak of the PMBR in patients which correlates significantly with the symbol digit modalities test: a measure of information processing speed. A significant decrease in the amplitude of visual gamma oscillations in patients is also seen. These findings highlight the potential value of electrophysiological imaging in generating a new understanding of visual disturbances and abnormal motor control in MS patients. Hum Brain Mapp, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

  2. Chaotic itinerancy within the coupled dynamics between a physical body and neural oscillator networks

    PubMed Central

    Mori, Hiroki; Okuyama, Yuji; Asada, Minoru

    2017-01-01

    Chaotic itinerancy is a phenomenon in which the state of a nonlinear dynamical system spontaneously explores and attracts certain states in a state space. From this perspective, the diverse behavior of animals and its spontaneous transitions lead to a complex coupled dynamical system, including a physical body and a brain. Herein, a series of simulations using different types of non-linear oscillator networks (i.e., regular, small-world, scale-free, random) with a musculoskeletal model (i.e., a snake-like robot) as a physical body are conducted to understand how the chaotic itinerancy of bodily behavior emerges from the coupled dynamics between the body and the brain. A behavior analysis (behavior clustering) and network analysis for the classified behavior are then applied. The former consists of feature vector extraction from the motions and classification of the movement patterns that emerged from the coupled dynamics. The network structures behind the classified movement patterns are revealed by estimating the “information networks” different from the given non-linear oscillator networks based on the transfer entropy which finds the information flow among neurons. The experimental results show that: (1) the number of movement patterns and their duration depend on the sensor ratio to control the balance of strength between the body and the brain dynamics and on the type of the given non-linear oscillator networks; and (2) two kinds of information networks are found behind two kinds movement patterns with different durations by utilizing the complex network measures, clustering coefficient and the shortest path length with a negative and a positive relationship with the duration periods of movement patterns. The current results seem promising for a future extension of the method to a more complicated body and environment. Several requirements are also discussed. PMID:28796797

  3. Phase reduction analysis of coupled neural oscillators: application to epileptic seizure dynamics

    NASA Astrophysics Data System (ADS)

    Takeshita, Daisuke; Sato, Yasuomi; Bahar, Sonya

    2006-03-01

    Epileptic seizures are generally held to be result from excess and synchronized neural activity. To investigate how seizures initiate, we develop a model of a neocortical network based on a model suggested by Wilson [1]. We simulate the effect of the potassium channel blocker 4-aminopyridine, which is often used in experiments to induce epileptic seizures, by decreasing the conductance of the potassium channels (gK) in neurons in our model. We applied phase reduction to the Wilson model to study how gK in the model affects the stability of the phase difference. At a normal value of gK, the stable phase difference is small, but the neurons are not exactly in phase. At low gK, in-phase and out-of-phase firing patterns become simultaneously stable. We constructed a network of 20 by 20 neurons. By decreasing gK to zero, a dramatic increase in the amplitude of mean field was observed. This is due to the fact that in-phase firing becomes stable at low gK. The pattern was similar to local field potential in 4-aminopyridine induced seizures. Therefore, it was concluded that the neural activity in drug-induced seizure may be caused by a bifurcation in stable phase differences between neurons. [1] Wilson H.R., J. Theor. Biol. (1999) 200, 375-388 [2] Ermentrout, G.B. and Kopell, N., SIAM J. Math. Anal. (1984), 215-237

  4. Neural compensation for mechanical loading of the hand during coupled oscillations of the hand and foot.

    PubMed

    Baldissera, F; Cavallari, P

    2001-07-01

    The role of kinaesthetic afferences in controlling coupling of voluntary oscillation of the hand and foot, both in-phase and anti-phase, was investigated by modifying the mechanical properties of one of the two segments (the hand) with applied inertial or elastic loads. Loads consisted of a lead disk, rotating coaxially with the wrist (total inertial momentum 15 g m2), or in two symmetrical rubber bands (elasticity, 4 g deg(-1)) connected 5 cm away from the wrist pivot. Experiments were performed on five male and five female subjects. Both the frequency responses of the hand and foot (i.e. the phase relations between the onset of muscular activation in limb extensors and the onset of the related movement) and the inter-limb phase relations (the phase differences between the hand and foot movement cycles and between the onsets of the electromyographic (EMG) activity in hand and foot extensors) were analysed. The hand frequency-response was fitted with a 2nd-order model, allowing us to describe the loaded and unloaded conditions through the changes in the model response. Inertial loading induced an immediate and steep decay in the frequency response, with a clear-cut reduction of the model resonance frequency, while elastic loading shifted the response to the right and upwards. Inter-limb phase relations were only partially affected by inertial loading of the hand. Despite the fact that the load strongly increased the difference between the frequency-responses of the hand and foot, when hand and foot were oscillated in-phase only about half of this difference remained as an increased phase-lag between hand and foot oscillations. The other half was offset by an advance of the contraction of the hand movers with respect to the foot movers. This compensation mechanism was more effective during anti-phase than during in-phase movements. Elastic loading improved inter-limb synchronisation, since it superimposed the hand frequency-response on that of the foot. In this

  5. Slow State Transitions of Sustained Neural Oscillations by Activity-Dependent Modulation of Intrinsic Excitability

    PubMed Central

    Fröhlich, Flavio; Bazhenov, Maxim; Timofeev, Igor; Steriade, Mircea; Sejnowski, Terrence J.

    2010-01-01

    Little is known about the dynamics and mechanisms of transitions between tonic firing and bursting in cortical networks. Here, we use a computational model of a neocortical circuit with extracellular potassium dynamics to show that activity-dependent modulation of intrinsic excitability can lead to sustained oscillations with slow transitions between two distinct firing modes: fast run (tonic spiking or fast bursts with few spikes) and slow bursting. These transitions are caused by a bistability with hysteresis in a pyramidal cell model. Balanced excitation and inhibition stabilizes a network of pyramidal cells and inhibitory interneurons in the bistable region and causes sustained periodic alternations between distinct oscillatory states. During spike-wave seizures, neocortical paroxysmal activity exhibits qualitatively similar slow transitions between fast run and bursting. We therefore predict that extracellular potassium dynamics can cause alternating episodes of fast and slow oscillatory states in both normal and epileptic neocortical networks. PMID:16763023

  6. Complex patterns arise through spontaneous symmetry breaking in dense homogeneous networks of neural oscillators

    NASA Astrophysics Data System (ADS)

    Singh, Rajeev; Menon, Shakti N.; Sinha, Sitabhra

    2016-02-01

    There has been much interest in understanding collective dynamics in networks of brain regions due to their role in behavior and cognitive function. Here we show that a simple, homogeneous system of densely connected oscillators, representing the aggregate activity of local brain regions, can exhibit a rich variety of dynamical patterns emerging via spontaneous breaking of permutation or translational symmetries. Upon removing just a few connections, we observe a striking departure from the mean-field limit in terms of the collective dynamics, which implies that the sparsity of these networks may have very important consequences. Our results suggest that the origins of some of the complicated activity patterns seen in the brain may be understood even with simple connection topologies.

  7. Neural alpha oscillations index the balance between self-other integration and segregation in real-time joint action.

    PubMed

    Novembre, Giacomo; Sammler, Daniela; Keller, Peter E

    2016-08-01

    Shared knowledge and interpersonal coordination are prerequisites for most forms of social behavior. Influential approaches to joint action have conceptualized these capacities in relation to the separate constructs of co-representation (knowledge) and self-other entrainment (coordination). Here we investigated how brain mechanisms involved in co-representation and entrainment interact to support joint action. To do so, we used a musical joint action paradigm to show that the neural mechanisms underlying co-representation and self-other entrainment are linked via a process - indexed by EEG alpha oscillations - regulating the balance between self-other integration and segregation in real time. Pairs of pianists performed short musical items while action familiarity and interpersonal (behavioral) synchronization accuracy were manipulated in a factorial design. Action familiarity referred to whether or not pianists had rehearsed the musical material performed by the other beforehand. Interpersonal synchronization was manipulated via congruent or incongruent tempo change instructions that biased performance timing towards the impending, new tempo. It was observed that, when pianists were familiar with each other's parts, millisecond variations in interpersonal synchronized behavior were associated with a modulation of alpha power over right centro-parietal scalp regions. Specifically, high behavioral entrainment was associated with self-other integration, as indexed by alpha suppression. Conversely, low behavioral entrainment encouraged reliance on internal knowledge and thus led to self-other segregation, indexed by alpha enhancement. These findings suggest that alpha oscillations index the processing of information about self and other depending on the compatibility of internal knowledge and external (environmental) events at finely resolved timescales.

  8. Self-Sustained Relaxation Oscillations in Time-Delay Neural Systems

    NASA Astrophysics Data System (ADS)

    Glyzin, S. D.; Kolesov, A. Yu; Rozov, N. Kh

    2016-06-01

    A new method to model the phenomena ’bursting’ and ’buffering’ in neural systems is represented. Namely, a singularly perturbed nonlinear scalar differential difference equation with two delays is introduced, which is a mathematical model of a single neuron. It is shown that for suitably chosen parameters this equation has a stable periodic solution with an arbitrary prescribed number of asymptotically high impulses (spikes) on a period interval. It is also shown that the buffering phenomenon occurs in a one-dimensional chain of diffusively coupled neurons of this type: as the number of components in the chain grows in a way compatible with a decrease of the diffusion coefficient, the number of co-existing stable periodic motions increases indefinitely.

  9. Motor expertise modulates neural oscillations and temporal dynamics of cognitive control.

    PubMed

    Wang, Chun-Hao; Yang, Cheng-Ta; Moreau, David; Muggleton, Neil G

    2017-09-01

    The field of motor expertise in athletes has recently been receiving increasing levels of investigation. However, there has been less investigation of how dynamic changes in behavior and in neural activity as a result of sporting participation might result in superiority for athletes in domain-general cognition. We used a flanker task to investigate conflict-related behavioral measures, such as mean reaction time (RT) and RT variability, in conjunction with electroencephalographic (EEG) measures, including N2d, theta activity power, and inter-trial phase coherence (ITPC). These measures were compared for 18 badminton players, an interceptive sport requiring the performance of skills in a fast-changing and unpredictable environment, and 18 athletic controls (14 track-and-field athletes and 4 dragon boat athletes), with high fitness levels but no requirement for skills such as responses to their opponents. Results showed that badminton players made faster and less variable responses on the flanker task than athletic controls, regardless of stimulus congruency levels. For EEG measures, both badminton players and athletic controls showed comparable modulations of conflicting on midfrontal N2 and theta power. However, such an effect on ITPC values was found only for the badminton players. The behavior-EEG correlation seen suggests that smaller changes in RT variability induced by conflicting process in badminton players may be attributable to greater stability in the neural processes in these individuals. Because these findings were independent from aerobic fitness levels, it seems such differences are likely due to training-induced adaptations, consistent with the idea of specific transfer from cognitive components involved in sport training to domain-general cognition. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Ingroup/outgroup membership modulates fairness consideration: neural signatures from ERPs and EEG oscillations

    PubMed Central

    Wang, Yiwen; Zhang, Zhen; Bai, Liying; Lin, Chongde; Osinsky, Roman; Hewig, Johannes

    2017-01-01

    Previous studies have shown that ingroup/outgroup membership influences individual’s fairness considerations. However, it is not clear yet how group membership influences brain activity when a recipient evaluates the fairness of asset distribution. In this study, subjects participated as recipients in an Ultimatum Game with alleged members of both an experimentally induced ingroup and outgroup. They either received extremely unequal, moderately unequal, or equal offers from proposers while electroencephalogram was recorded. Behavioral results showed that the acceptance rates for unequal offers were higher when interacting with ingroup partners than with outgroup partners. Analyses of event related potentials revealed that proposers’ group membership modulated offer evaluation at earlier processing stages. Feedback-related negativity was more negative for extremely and moderately unequal offers compared to equal offers in the ingroup interaction whereas it did not show differential responses to different offers in the outgroup interaction. Analyses of event related oscillations revealed that the theta power (4–6 Hz) was larger for moderately unequal offers than equal offers in the ingroup interaction whereas it did not show differential responses to different offers in the outgroup interaction. Thus, early mechanisms of fairness evaluation are strongly modulated by the ingroup/outgroup membership of the interaction partner. PMID:28051156

  11. Vulnerability to paroxysmal oscillations in delayed neural networks: A basis for nocturnal frontal lobe epilepsy?

    NASA Astrophysics Data System (ADS)

    Quan, Austin; Osorio, Ivan; Ohira, Toru; Milton, John

    2011-12-01

    Resonance can occur in bistable dynamical systems due to the interplay between noise and delay (τ) in the absence of a periodic input. We investigate resonance in a two-neuron model with mutual time-delayed inhibitory feedback. For appropriate choices of the parameters and inputs three fixed-point attractors co-exist: two are stable and one is unstable. In the absence of noise, delay-induced transient oscillations (referred to herein as DITOs) arise whenever the initial function is tuned sufficiently close to the unstable fixed-point. In the presence of noisy perturbations, DITOs arise spontaneously. Since the correlation time for the stationary dynamics is ˜τ, we approximated a higher order Markov process by a three-state Markov chain model by rescaling time as t → 2sτ, identifying the states based on whether the sub-intervals were completely confined to one basin of attraction (the two stable attractors) or straddled the separatrix, and then determining the transition probability matrix empirically. The resultant Markov chain model captured the switching behaviors including the statistical properties of the DITOs. Our observations indicate that time-delayed and noisy bistable dynamical systems are prone to generate DITOs as switches between the two attractors occur. Bistable systems arise transiently in situations when one attractor is gradually replaced by another. This may explain, for example, why seizures in certain epileptic syndromes tend to occur as sleep stages change.

  12. Ingroup/outgroup membership modulates fairness consideration: neural signatures from ERPs and EEG oscillations.

    PubMed

    Wang, Yiwen; Zhang, Zhen; Bai, Liying; Lin, Chongde; Osinsky, Roman; Hewig, Johannes

    2017-01-04

    Previous studies have shown that ingroup/outgroup membership influences individual's fairness considerations. However, it is not clear yet how group membership influences brain activity when a recipient evaluates the fairness of asset distribution. In this study, subjects participated as recipients in an Ultimatum Game with alleged members of both an experimentally induced ingroup and outgroup. They either received extremely unequal, moderately unequal, or equal offers from proposers while electroencephalogram was recorded. Behavioral results showed that the acceptance rates for unequal offers were higher when interacting with ingroup partners than with outgroup partners. Analyses of event related potentials revealed that proposers' group membership modulated offer evaluation at earlier processing stages. Feedback-related negativity was more negative for extremely and moderately unequal offers compared to equal offers in the ingroup interaction whereas it did not show differential responses to different offers in the outgroup interaction. Analyses of event related oscillations revealed that the theta power (4-6 Hz) was larger for moderately unequal offers than equal offers in the ingroup interaction whereas it did not show differential responses to different offers in the outgroup interaction. Thus, early mechanisms of fairness evaluation are strongly modulated by the ingroup/outgroup membership of the interaction partner.

  13. Network of phase-locking oscillators and a possible model for neural synchronization

    NASA Astrophysics Data System (ADS)

    Piqueira, José Roberto C.

    2011-09-01

    In order to model the synchronization of brain signals, a three-node fully-connected network is presented. The nodes are considered to be voltage control oscillator neurons (VCON) allowing to conjecture about how the whole process depends on synaptic gains, free-running frequencies and delays. The VCON, represented by phase-locked loops (PLL), are fully-connected and, as a consequence, an asymptotically stable synchronous state appears. Here, an expression for the synchronous state frequency is derived and the parameter dependence of its stability is discussed. Numerical simulations are performed providing conditions for the use of the derived formulae. Model differential equations are hard to be analytically treated, but some simplifying assumptions combined with simulations provide an alternative formulation for the long-term behavior of the fully-connected VCON network. Regarding this kind of network as models for brain frequency signal processing, with each PLL representing a neuron (VCON), conditions for their synchronization are proposed, considering the different bands of brain activity signals and relating them to synaptic gains, delays and free-running frequencies. For the delta waves, the synchronous state depends strongly on the delays. However, for alpha, beta and theta waves, the free-running individual frequencies determine the synchronous state.

  14. Stochastic slowly adapting ionic currents may provide a decorrelation mechanism for neural oscillators by causing wander in the intrinsic period.

    PubMed

    Norman, Sharon E; Butera, Robert J; Canavier, Carmen C

    2016-09-01

    Oscillatory neurons integrate their synaptic inputs in fundamentally different ways than normally quiescent neurons. We show that the oscillation period of invertebrate endogenous pacemaker neurons wanders, producing random fluctuations in the interspike intervals (ISI) on a time scale of seconds to minutes, which decorrelates pairs of neurons in hybrid circuits constructed using the dynamic clamp. The autocorrelation of the ISI sequence remained high for many ISIs, but the autocorrelation of the ΔISI series had on average a single nonzero value, which was negative at a lag of one interval. We reproduced these results using a simple integrate and fire (IF) model with a stochastic population of channels carrying an adaptation current with a stochastic component that was integrated with a slow time scale, suggesting that a similar population of channels underlies the observed wander in the period. Using autoregressive integrated moving average (ARIMA) models, we found that a single integrator and a single moving average with a negative coefficient could simulate both the experimental data and the IF model. Feeding white noise into an integrator with a slow time constant is sufficient to produce the autocorrelation structure of the ISI series. Moreover, the moving average clearly accounted for the autocorrelation structure of the ΔISI series and is biophysically implemented in the IF model using slow stochastic adaptation. The observed autocorrelation structure may be a neural signature of slow stochastic adaptation, and wander generated in this manner may be a general mechanism for limiting episodes of synchronized activity in the nervous system.

  15. Pre-target neural oscillations predict variability in the detection of small pitch changes.

    PubMed

    Florin, Esther; Vuvan, Dominique; Peretz, Isabelle; Baillet, Sylvain

    2017-01-01

    Pitch discrimination is important for language or music processing. Previous studies indicate that auditory perception depends on pre-target neural activity. However, so far the pre-target electrophysiological conditions which enable the detection of small pitch changes are not well studied, but might yield important insights into pitch-processing. We used magnetoencephalography (MEG) source imaging to reveal the pre-target effects of successful auditory detection of small pitch deviations from a sequence of standard tones. Participants heard a sequence of four pure tones and had to determine whether the last target tone was different or identical to the first three standard sounds. We found that successful pitch change detection could be predicted from the amplitude of theta (4-8 Hz) oscillatory activity in the right inferior frontal gyrus (IFG) as well as beta (12-30 Hz) oscillatory activity in the right auditory cortex. These findings confirm and extend evidence for the involvement of theta as well as beta-band activity in auditory perception.

  16. Effects of Exercise in Immersive Virtual Environments on Cortical Neural Oscillations and Mental State.

    PubMed

    Vogt, Tobias; Herpers, Rainer; Askew, Christopher D; Scherfgen, David; Strüder, Heiko K; Schneider, Stefan

    2015-01-01

    Virtual reality environments are increasingly being used to encourage individuals to exercise more regularly, including as part of treatment those with mental health or neurological disorders. The success of virtual environments likely depends on whether a sense of presence can be established, where participants become fully immersed in the virtual environment. Exposure to virtual environments is associated with physiological responses, including cortical activation changes. Whether the addition of a real exercise within a virtual environment alters sense of presence perception, or the accompanying physiological changes, is not known. In a randomized and controlled study design, moderate-intensity Exercise (i.e., self-paced cycling) and No-Exercise (i.e., automatic propulsion) trials were performed within three levels of virtual environment exposure. Each trial was 5 minutes in duration and was followed by posttrial assessments of heart rate, perceived sense of presence, EEG, and mental state. Changes in psychological strain and physical state were generally mirrored by neural activation patterns. Furthermore, these changes indicated that exercise augments the demands of virtual environment exposures and this likely contributed to an enhanced sense of presence.

  17. Effects of Exercise in Immersive Virtual Environments on Cortical Neural Oscillations and Mental State

    PubMed Central

    Vogt, Tobias; Herpers, Rainer; Askew, Christopher D.; Scherfgen, David; Strüder, Heiko K.; Schneider, Stefan

    2015-01-01

    Virtual reality environments are increasingly being used to encourage individuals to exercise more regularly, including as part of treatment those with mental health or neurological disorders. The success of virtual environments likely depends on whether a sense of presence can be established, where participants become fully immersed in the virtual environment. Exposure to virtual environments is associated with physiological responses, including cortical activation changes. Whether the addition of a real exercise within a virtual environment alters sense of presence perception, or the accompanying physiological changes, is not known. In a randomized and controlled study design, moderate-intensity Exercise (i.e., self-paced cycling) and No-Exercise (i.e., automatic propulsion) trials were performed within three levels of virtual environment exposure. Each trial was 5 minutes in duration and was followed by posttrial assessments of heart rate, perceived sense of presence, EEG, and mental state. Changes in psychological strain and physical state were generally mirrored by neural activation patterns. Furthermore, these changes indicated that exercise augments the demands of virtual environment exposures and this likely contributed to an enhanced sense of presence. PMID:26366305

  18. Pre-target neural oscillations predict variability in the detection of small pitch changes

    PubMed Central

    Vuvan, Dominique; Peretz, Isabelle; Baillet, Sylvain

    2017-01-01

    Pitch discrimination is important for language or music processing. Previous studies indicate that auditory perception depends on pre-target neural activity. However, so far the pre-target electrophysiological conditions which enable the detection of small pitch changes are not well studied, but might yield important insights into pitch-processing. We used magnetoencephalography (MEG) source imaging to reveal the pre-target effects of successful auditory detection of small pitch deviations from a sequence of standard tones. Participants heard a sequence of four pure tones and had to determine whether the last target tone was different or identical to the first three standard sounds. We found that successful pitch change detection could be predicted from the amplitude of theta (4–8 Hz) oscillatory activity in the right inferior frontal gyrus (IFG) as well as beta (12–30 Hz) oscillatory activity in the right auditory cortex. These findings confirm and extend evidence for the involvement of theta as well as beta-band activity in auditory perception. PMID:28542644

  19. Increases in inspiratory neural drive in response to rapid oscillating airflow braking forces (vibration).

    PubMed

    Sumners, David Paul; Green, David A; Mileva, Katya N; Bowtell, Joanna L

    2008-02-29

    To investigate whether 10 breaths against a vibration stimulus elicits increments of spontaneous and maximal inspiratory mouth pressure (maxMP) and tidal mean inspiratory flow (iV(T)/T(I)) upon stimulus removal. Twelve healthy subjects (8 female, 4 male; 22-50 years old), recruited from the University student body, completed 3 maximal inspirations before (pre) and after (post) 10 inspirations against resistive loading with a vibration-type stimulus (VIB; youbreathe, Exoscience Ltd., London, UK), pressure-matched resistive loading (RES) or resting breathing (CON; no load). The trials were presented in a random order. maxMP and involuntary tidal breathing were compared pre and post conditioning. Inspiratory neural drive increased only after VIB as evidenced by increased tidal and maxMP and mean inspiratory flow (iV(T)/T(I); p < 0.05). There was no effect of either resistance or control breathing on maximal maxMP or tidal responses. Ten conditioning breaths of VIB lead to increased maximal inspiratory mouth pressure and spontaneous mouth pressure and mean inspiratory flow possibly through a common mechanism of increased descending respiratory drive.

  20. Distinguishing neurocognitive processes reflected by P600 effects: evidence from ERPs and neural oscillations.

    PubMed

    Regel, Stefanie; Meyer, Lars; Gunter, Thomas C

    2014-01-01

    Research on language comprehension using event-related potentials (ERPs) reported distinct ERP components reliably related to the processing of semantic (N400) and syntactic information (P600). Recent ERP studies have challenged this well-defined distinction by showing P600 effects for semantic and pragmatic anomalies. So far, it is still unresolved whether the P600 reflects specific or rather common processes. The present study addresses this question by investigating ERPs in response to a syntactic and pragmatic (irony) manipulation, as well as a combined syntactic and pragmatic manipulation. For the syntactic condition, a morphosyntactic violation was applied, whereas for the pragmatic condition, such as "That is rich", either an ironic or literal interpretation was achieved, depending on the prior context. The ERPs at the critical word showed a LAN-P600 pattern for syntactically incorrect sentences relative to correct ones. For ironic compared to literal sentences, ERPs showed a P200 effect followed by a P600 component. In comparison of the syntax-related P600 to the irony-related P600, distributional differences were found. Moreover, for the P600 time window (i.e., 500-900 ms), different changes in theta power between the syntax and pragmatics effects were found, suggesting that different patterns of neural activity contributed to each respective effect. Thus, both late positivities seem to be differently sensitive to these two types of linguistic information, and might reflect distinct neurocognitive processes, such as reanalysis of the sentence structure versus pragmatic reanalysis.

  1. A driven active mass damper by using output of a neural oscillator (effects of position control system changes on vibration mitigation performance)

    NASA Astrophysics Data System (ADS)

    Hongu, J.; Iba, D.; Sasaki, T.; Nakamura, M.; Moriwaki, I.

    2015-03-01

    In this paper, a design method for a PD controller, which is a part of a new active mass damper system using a neural oscillator for high-rise buildings, is proposed. The new system mimicking the motion of bipedal mammals is a quite simple system, which has the neural oscillator synchronizing with the acceleration response of the structure. The travel distance and direction of the auxiliary mass of the active mass damper is decided by the output of the neural oscillator, and then, the auxiliary mass is transferred to the decided location by using the PD controller. Therefore, the performance of the PD controller must be evaluated by the vibration energy absorbing efficiency by the system. In order to bring the actual path driven by the PD controller in closer alignment with the ideal path, which is assumed to be a sinusoidal wave under resonance, firstly, the path of the auxiliary mass driven by the PD controller is analytically derived, and the inner product between the vector of ideal and analytical path is evaluated. And then, the PD gain is decided by the maximum value of the inner product. Finally, numerical simulations confirm the validity of the proposed design method of the PD controller.

  2. Oxytocin affects spontaneous neural oscillations in trauma-exposed war veterans

    PubMed Central

    Eidelman-Rothman, Moranne; Goldstein, Abraham; Levy, Jonathan; Weisman, Omri; Schneiderman, Inna; Mankuta, David; Zagoory-Sharon, Orna; Feldman, Ruth

    2015-01-01

    Exposure to combat-related trauma often leads to lifetime functional impairments. Previous research demonstrated the effects of oxytocin (OT) administration on brain regions implicated in post-traumatic stress disorder (PTSD); yet OT’s effects on brain patterns in trauma-exposed veterans have not been studied. In the current study the effects of OT on spontaneous brain oscillatory activity were measured in 43 veterans using magnetoencephalography (MEG): 28 veterans who were exposed to a combat-related trauma and 15 trauma-unexposed controls. Participants participated in two experimental sessions and were administered OT or placebo (PBO) in a double-blind, placebo-control, within-subject design. Following OT/PBO administration, participants underwent a whole-head MEG scan. Plasma and salivary OT levels were assessed each session. Spontaneous brain activity measured during a 2-min resting period was subjected to source-localization analysis. Trauma-exposed veterans showed higher resting-state alpha (8–13 Hz) activity compared to controls in the left dorsolateral prefrontal cortex (dlPFC), specifically in the superior frontal gyrus (SFG) and the middle frontal gyrus (MFG), indicating decreased neural activity in these regions. The higher alpha activity was “normalized” following OT administration and under OT, group differences were no longer found. Increased resting-state alpha was associated with lower baseline plasma OT, reduced salivary OT reactivity, and more re-experiencing symptoms. These findings demonstrate effects of OT on resting-state brain functioning in prefrontal regions subserving working memory and cognitive control, which are disrupted in PTSD. Results raise the possibility that OT, traditionally studied in social contexts, may also enhance performance in cognitive tasks associated with working memory and cognitive control following trauma exposure. PMID:26175673

  3. Oxytocin affects spontaneous neural oscillations in trauma-exposed war veterans.

    PubMed

    Eidelman-Rothman, Moranne; Goldstein, Abraham; Levy, Jonathan; Weisman, Omri; Schneiderman, Inna; Mankuta, David; Zagoory-Sharon, Orna; Feldman, Ruth

    2015-01-01

    Exposure to combat-related trauma often leads to lifetime functional impairments. Previous research demonstrated the effects of oxytocin (OT) administration on brain regions implicated in post-traumatic stress disorder (PTSD); yet OT's effects on brain patterns in trauma-exposed veterans have not been studied. In the current study the effects of OT on spontaneous brain oscillatory activity were measured in 43 veterans using magnetoencephalography (MEG): 28 veterans who were exposed to a combat-related trauma and 15 trauma-unexposed controls. Participants participated in two experimental sessions and were administered OT or placebo (PBO) in a double-blind, placebo-control, within-subject design. Following OT/PBO administration, participants underwent a whole-head MEG scan. Plasma and salivary OT levels were assessed each session. Spontaneous brain activity measured during a 2-min resting period was subjected to source-localization analysis. Trauma-exposed veterans showed higher resting-state alpha (8-13 Hz) activity compared to controls in the left dorsolateral prefrontal cortex (dlPFC), specifically in the superior frontal gyrus (SFG) and the middle frontal gyrus (MFG), indicating decreased neural activity in these regions. The higher alpha activity was "normalized" following OT administration and under OT, group differences were no longer found. Increased resting-state alpha was associated with lower baseline plasma OT, reduced salivary OT reactivity, and more re-experiencing symptoms. These findings demonstrate effects of OT on resting-state brain functioning in prefrontal regions subserving working memory and cognitive control, which are disrupted in PTSD. Results raise the possibility that OT, traditionally studied in social contexts, may also enhance performance in cognitive tasks associated with working memory and cognitive control following trauma exposure.

  4. Distinguishing Neurocognitive Processes Reflected by P600 Effects: Evidence from ERPs and Neural Oscillations

    PubMed Central

    Regel, Stefanie; Meyer, Lars; Gunter, Thomas C.

    2014-01-01

    Research on language comprehension using event-related potentials (ERPs) reported distinct ERP components reliably related to the processing of semantic (N400) and syntactic information (P600). Recent ERP studies have challenged this well-defined distinction by showing P600 effects for semantic and pragmatic anomalies. So far, it is still unresolved whether the P600 reflects specific or rather common processes. The present study addresses this question by investigating ERPs in response to a syntactic and pragmatic (irony) manipulation, as well as a combined syntactic and pragmatic manipulation. For the syntactic condition, a morphosyntactic violation was applied, whereas for the pragmatic condition, such as “That is rich”, either an ironic or literal interpretation was achieved, depending on the prior context. The ERPs at the critical word showed a LAN-P600 pattern for syntactically incorrect sentences relative to correct ones. For ironic compared to literal sentences, ERPs showed a P200 effect followed by a P600 component. In comparison of the syntax-related P600 to the irony-related P600, distributional differences were found. Moreover, for the P600 time window (i.e., 500–900 ms), different changes in theta power between the syntax and pragmatics effects were found, suggesting that different patterns of neural activity contributed to each respective effect. Thus, both late positivities seem to be differently sensitive to these two types of linguistic information, and might reflect distinct neurocognitive processes, such as reanalysis of the sentence structure versus pragmatic reanalysis. PMID:24844290

  5. Can modular psychological concepts like affect and emotion be assigned to a distinct subset of regional neural circuits?. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

    NASA Astrophysics Data System (ADS)

    Fehr, Thorsten; Herrmann, Manfred

    2015-06-01

    regional brain systems or neural modules, but rather suggest highly complex and cross-linked neural networks individually shaped by livelong learning and experience [e.g., 6,7,10,13]. This holds in particular true for complex emotional phenomena such as aggression or empathy in social interaction [8,13]. It thus remains questionable, whether - beyond primary sensory and motor-processing - a small number of modular sub-systems sufficiently cover the organisation of specific phenomenological and social features of perception and behaviour [7,10].

  6. Modularity of music processing.

    PubMed

    Peretz, Isabelle; Coltheart, Max

    2003-07-01

    The music faculty is not a monolithic entity that a person either has or does not. Rather, it comprises a set of neurally isolable processing components, each having the potential to be specialized for music. Here we propose a functional architecture for music processing that captures the typical properties of modular organization. The model rests essentially on the analysis of music-related deficits in neurologically impaired individuals, but provides useful guidelines for exploring the music faculty in normal people, using methods such as neuroimaging.

  7. Stochastic slowly adapting ionic currents may provide a decorrelation mechanism for neural oscillators by causing wander in the intrinsic period

    PubMed Central

    Norman, Sharon E.; Butera, Robert J.

    2016-01-01

    Oscillatory neurons integrate their synaptic inputs in fundamentally different ways than normally quiescent neurons. We show that the oscillation period of invertebrate endogenous pacemaker neurons wanders, producing random fluctuations in the interspike intervals (ISI) on a time scale of seconds to minutes, which decorrelates pairs of neurons in hybrid circuits constructed using the dynamic clamp. The autocorrelation of the ISI sequence remained high for many ISIs, but the autocorrelation of the ΔISI series had on average a single nonzero value, which was negative at a lag of one interval. We reproduced these results using a simple integrate and fire (IF) model with a stochastic population of channels carrying an adaptation current with a stochastic component that was integrated with a slow time scale, suggesting that a similar population of channels underlies the observed wander in the period. Using autoregressive integrated moving average (ARIMA) models, we found that a single integrator and a single moving average with a negative coefficient could simulate both the experimental data and the IF model. Feeding white noise into an integrator with a slow time constant is sufficient to produce the autocorrelation structure of the ISI series. Moreover, the moving average clearly accounted for the autocorrelation structure of the ΔISI series and is biophysically implemented in the IF model using slow stochastic adaptation. The observed autocorrelation structure may be a neural signature of slow stochastic adaptation, and wander generated in this manner may be a general mechanism for limiting episodes of synchronized activity in the nervous system. PMID:27281746

  8. The relative efficiency of modular and non-modular networks of different size

    PubMed Central

    Tosh, Colin R.; McNally, Luke

    2015-01-01

    Most biological networks are modular but previous work with small model networks has indicated that modularity does not necessarily lead to increased functional efficiency. Most biological networks are large, however, and here we examine the relative functional efficiency of modular and non-modular neural networks at a range of sizes. We conduct a detailed analysis of efficiency in networks of two size classes: ‘small’ and ‘large’, and a less detailed analysis across a range of network sizes. The former analysis reveals that while the modular network is less efficient than one of the two non-modular networks considered when networks are small, it is usually equally or more efficient than both non-modular networks when networks are large. The latter analysis shows that in networks of small to intermediate size, modular networks are much more efficient that non-modular networks of the same (low) connective density. If connective density must be kept low to reduce energy needs for example, this could promote modularity. We have shown how relative functionality/performance scales with network size, but the precise nature of evolutionary relationship between network size and prevalence of modularity will depend on the costs of connectivity. PMID:25631996

  9. Modular shield

    DOEpatents

    Snyder, Keith W.

    2002-01-01

    A modular system for containing projectiles has a sheet of material including at least a polycarbonate layer held by a metal frame having a straight frame member corresponding to each straight edge of the sheet. Each frame member has a U-shaped shield channel covering and holding a straight edge of the sheet and an adjacent U-shaped clamp channel rigidly held against the shield channel. A flexible gasket separates each sheet edge from its respective shield channel; and each frame member is fastened to each adjacent frame member only by clamps extending between adjacent clamp channels.

  10. Modular Certification

    NASA Technical Reports Server (NTRS)

    Rushby, John; Miner, Paul S. (Technical Monitor)

    2002-01-01

    Airplanes are certified as a whole: there is no established basis for separately certifying some components, particularly software-intensive ones, independently of their specific application in a given airplane. The absence of separate certification inhibits the development of modular components that could be largely "precertified" and used in several different contexts within a single airplane, or across many different airplanes. In this report, we examine the issues in modular certification of software components and propose an approach based on assume-guarantee reasoning. We extend the method from verification to certification by considering behavior in the presence of failures. This exposes the need for partitioning, and separation of assumptions and guarantees into normal and abnormal cases. We then identify three classes of property that must be verified within this framework: safe function, true guarantees, and controlled failure. We identify a particular assume-guarantee proof rule (due to McMillan) that is appropriate to the applications considered, and formally verify its soundness in PVS.

  11. From modular to centralized organization of synchronization in functional areas of the cat cerebral cortex.

    PubMed

    Gómez-Gardeñes, Jesús; Zamora-López, Gorka; Moreno, Yamir; Arenas, Alex

    2010-08-26

    Recent studies have pointed out the importance of transient synchronization between widely distributed neural assemblies to understand conscious perception. These neural assemblies form intricate networks of neurons and synapses whose detailed map for mammals is still unknown and far from our experimental capabilities. Only in a few cases, for example the C. elegans, we know the complete mapping of the neuronal tissue or its mesoscopic level of description provided by cortical areas. Here we study the process of transient and global synchronization using a simple model of phase-coupled oscillators assigned to cortical areas in the cerebral cat cortex. Our results highlight the impact of the topological connectivity in the developing of synchronization, revealing a transition in the synchronization organization that goes from a modular decentralized coherence to a centralized synchronized regime controlled by a few cortical areas forming a Rich-Club connectivity pattern.

  12. Modular robot

    DOEpatents

    Ferrante, Todd A.

    1997-01-01

    A modular robot may comprise a main body having a structure defined by a plurality of stackable modules. The stackable modules may comprise a manifold, a valve module, and a control module. The manifold may comprise a top surface and a bottom surface having a plurality of fluid passages contained therein, at least one of the plurality of fluid passages terminating in a valve port located on the bottom surface of the manifold. The valve module is removably connected to the manifold and selectively fluidically connects the plurality of fluid passages contained in the manifold to a supply of pressurized fluid and to a vent. The control module is removably connected to the valve module and actuates the valve module to selectively control a flow of pressurized fluid through different ones of the plurality of fluid passages in the manifold. The manifold, valve module, and control module are mounted together in a sandwich-like manner and comprise a main body. A plurality of leg assemblies are removably connected to the main body and are removably fluidically connected to the fluid passages in the manifold so that each of the leg assemblies can be selectively actuated by the flow of pressurized fluid in different ones of the plurality of fluid passages in the manifold.

  13. Modular robot

    DOEpatents

    Ferrante, T.A.

    1997-11-11

    A modular robot may comprise a main body having a structure defined by a plurality of stackable modules. The stackable modules may comprise a manifold, a valve module, and a control module. The manifold may comprise a top surface and a bottom surface having a plurality of fluid passages contained therein, at least one of the plurality of fluid passages terminating in a valve port located on the bottom surface of the manifold. The valve module is removably connected to the manifold and selectively fluidically connects the plurality of fluid passages contained in the manifold to a supply of pressurized fluid and to a vent. The control module is removably connected to the valve module and actuates the valve module to selectively control a flow of pressurized fluid through different ones of the plurality of fluid passages in the manifold. The manifold, valve module, and control module are mounted together in a sandwich-like manner and comprise a main body. A plurality of leg assemblies are removably connected to the main body and are removably fluidically connected to the fluid passages in the manifold so that each of the leg assemblies can be selectively actuated by the flow of pressurized fluid in different ones of the plurality of fluid passages in the manifold. 12 figs.

  14. Experience Drives Synchronization: The phase and Amplitude Dynamics of Neural Oscillations to Musical Chords Are Differentially Modulated by Musical Expertise.

    PubMed

    Pallesen, Karen Johanne; Bailey, Christopher J; Brattico, Elvira; Gjedde, Albert; Palva, J Matias; Palva, Satu

    2015-01-01

    Musical expertise is associated with structural and functional changes in the brain that underlie facilitated auditory perception. We investigated whether the phase locking (PL) and amplitude modulations (AM) of neuronal oscillations in response to musical chords are correlated with musical expertise and whether they reflect the prototypicality of chords in Western tonal music. To this aim, we recorded magnetoencephalography (MEG) while musicians and non-musicians were presented with common prototypical major and minor chords, and with uncommon, non-prototypical dissonant and mistuned chords, while watching a silenced movie. We then analyzed the PL and AM of ongoing oscillations in the theta (4-8 Hz) alpha (8-14 Hz), beta- (14-30 Hz) and gamma- (30-80 Hz) bands to these chords. We found that musical expertise was associated with strengthened PL of ongoing oscillations to chords over a wide frequency range during the first 300 ms from stimulus onset, as opposed to increased alpha-band AM to chords over temporal MEG channels. In musicians, the gamma-band PL was strongest to non-prototypical compared to other chords, while in non-musicians PL was strongest to minor chords. In both musicians and non-musicians the long-latency (> 200 ms) gamma-band PL was also sensitive to chord identity, and particularly to the amplitude modulations (beats) of the dissonant chord. These findings suggest that musical expertise modulates oscillation PL to musical chords and that the strength of these modulations is dependent on chord prototypicality.

  15. Active mass damper system for high-rise buildings using neural oscillator and position controller considering stroke limitation of the auxiliary mass

    NASA Astrophysics Data System (ADS)

    Hongu, J.; Iba, D.; Nakamura, M.; Moriwaki, I.

    2016-04-01

    This paper proposes a problem-solving method for the stroke limitation problem, which is related to auxiliary masses of active mass damper systems for high-rise buildings. The proposed method is used in a new simple control system for the active mass dampers mimicking the motion of bipedal mammals, which has a neural oscillator synchronizing with the acceleration response of structures and a position controller. In the system, the travel distance and direction of the auxiliary mass of the active mass damper is determined by reference to the output of the neural oscillator, and then, the auxiliary mass is transferred to the decided location by using a PID controller. The one of the purpose of the previouslyproposed system is stroke restriction problem avoidance of the auxiliary mass during large earthquakes by the determination of the desired value within the stroke limitation of the auxiliary mass. However, only applying the limited desired value could not rigorously restrict the auxiliary mass within the limitation, because the excessive inertia force except for the control force produced by the position controller affected on the motion of the auxiliary mass. In order to eliminate the effect on the auxiliary mass by the structural absolute acceleration, a cancellation method is introduced by adding a term to the control force of the position controller. We first develop the previously-proposed system for the active mass damper and the additional term for cancellation, and verity through numerical experiments that the new system is able to operate the auxiliary mass within the restriction during large earthquakes. Based on the comparison of the proposed system with the LQ system, a conclusion was drawn regarding which the proposed neuronal system with the additional term appears to be able to limit the stroke of the auxiliary mass of the AMD.

  16. "Can waiting awaken the resting brain?" A comparison of waiting- and cognitive task-induced attenuation of very low frequency neural oscillations.

    PubMed

    Hsu, Chia-Fen; Broyd, Samantha J; Helps, Suzannah K; Benikos, Nicholas; Sonuga-Barke, Edmund J S

    2013-08-02

    The default mode network (DMN) is characterised by coherent very low frequency (VLF) neural oscillations in the resting brain. The attenuation of this activity has been demonstrated following the transition from rest to performance of a broad range of cognitive goal-directed tasks. Whether the activity of resting state VLF oscillations is attenuated during non-cognitive goal-directed tasks such as waiting for rewarding outcomes is not known. This study examined the VLF EEG power from resting to performance of attention demanding task and two types of goal-directed waiting tasks. The association between the attenuation of VLF EEG power and Attention-Deficit/Hyperactivity Disorder (ADHD) symptoms was examined. Direct current EEG (DC-EEG) data were collected from 32 healthy young adults (half high and half low ADHD symptom scorers) during (i) a rest state, (ii) while performing a cognitive demanding reaction time task (2CRT), and (iii) while undertaking each of two different goal-directed waiting conditions: "forced-to-wait (FW)" and "choose-to-wait (CW)" tasks. The spatial distribution of VLF EEG power across scalp was similar to that seen in previous resting VLF EEG studies. Significant rest-to-task attenuation of VLF EEG power occurred during the 2CRT and the CW task, but not during the FW task. The association between self-ratings of ADHD symptoms and waiting-induced attenuation was not significant. This study suggests VLF EEG power attenuation that occurs following rest-to-task transition is not simply determined by changes in cognitive load. The goal-directed nature of a task, its motivated nature and/or the involvement of effortful attention may also contribute. Future studies should explore the attenuation of resting state VLF oscillations during waiting and impulsive choice.

  17. Experience Drives Synchronization: The phase and Amplitude Dynamics of Neural Oscillations to Musical Chords Are Differentially Modulated by Musical Expertise

    PubMed Central

    Pallesen, Karen Johanne; Bailey, Christopher J.; Brattico, Elvira; Gjedde, Albert; Palva, J. Matias; Palva, Satu

    2015-01-01

    Musical expertise is associated with structural and functional changes in the brain that underlie facilitated auditory perception. We investigated whether the phase locking (PL) and amplitude modulations (AM) of neuronal oscillations in response to musical chords are correlated with musical expertise and whether they reflect the prototypicality of chords in Western tonal music. To this aim, we recorded magnetoencephalography (MEG) while musicians and non-musicians were presented with common prototypical major and minor chords, and with uncommon, non-prototypical dissonant and mistuned chords, while watching a silenced movie. We then analyzed the PL and AM of ongoing oscillations in the theta (4–8 Hz) alpha (8–14 Hz), beta- (14–30 Hz) and gamma- (30–80 Hz) bands to these chords. We found that musical expertise was associated with strengthened PL of ongoing oscillations to chords over a wide frequency range during the first 300 ms from stimulus onset, as opposed to increased alpha-band AM to chords over temporal MEG channels. In musicians, the gamma-band PL was strongest to non-prototypical compared to other chords, while in non-musicians PL was strongest to minor chords. In both musicians and non-musicians the long-latency (> 200 ms) gamma-band PL was also sensitive to chord identity, and particularly to the amplitude modulations (beats) of the dissonant chord. These findings suggest that musical expertise modulates oscillation PL to musical chords and that the strength of these modulations is dependent on chord prototypicality. PMID:26291324

  18. Early gamma oscillations during rapid auditory processing in children with a language-learning impairment: Changes in neural mass activity after training

    PubMed Central

    Heim, Sabine; Keil, Andreas; Choudhury, Naseem; Friedman, Jennifer Thomas; Benasich, April A.

    2013-01-01

    Children with language-learning impairment (LLI) have consistently shown difficulty with tasks requiring precise, rapid auditory processing. Remediation based on neural plasticity assumes that the temporal precision of neural coding can be improved by intensive training protocols. Here, we examined the extent to which early oscillatory responses in auditory cortex change after audio-visual training, using combined source modeling and time-frequency analysis of the human electroencephalogram (EEG). Twenty-one elementary school students diagnosed with LLI underwent the intervention for an average of 32 days. Pre- and post-training assessments included standardized language/literacy tests and EEG recordings in response to fast-rate tone doublets. Twelve children with typical language development were also tested twice, with no intervention given. Behaviorally, improvements on measures of language were observed in the LLI group following completion of training. During the first EEG assessment, we found reduced amplitude and phase-locking of early (45–75 ms) oscillations in the gamma-band range (29–52 Hz), specifically in the LLI group, for the second stimulus of the tone doublet. Amplitude reduction for the second tone was no longer evident for the LLI children post-intervention, although these children still exhibited attenuated phase-locking. Our findings suggest that specific aspects of inefficient sensory cortical processing in LLI are ameliorated after training. PMID:23352997

  19. Early gamma oscillations during rapid auditory processing in children with a language-learning impairment: changes in neural mass activity after training.

    PubMed

    Heim, Sabine; Keil, Andreas; Choudhury, Naseem; Thomas Friedman, Jennifer; Benasich, April A

    2013-04-01

    Children with language-learning impairment (LLI) have consistently shown difficulty with tasks requiring precise, rapid auditory processing. Remediation based on neural plasticity assumes that the temporal precision of neural coding can be improved by intensive training protocols. Here, we examined the extent to which early oscillatory responses in auditory cortex change after audio-visual training, using combined source modeling and time-frequency analysis of the human electroencephalogram (EEG). Twenty-one elementary school students diagnosed with LLI underwent the intervention for an average of 32 days. Pre- and post-training assessments included standardized language/literacy tests and EEG recordings in response to fast-rate tone doublets. Twelve children with typical language development were also tested twice, with no intervention given. Behaviorally, improvements on measures of language were observed in the LLI group following completion of training. During the first EEG assessment, we found reduced amplitude and phase-locking of early (45-75 ms) oscillations in the gamma-band range (29-52 Hz), specifically in the LLI group, for the second stimulus of the tone doublet. Amplitude reduction for the second tone was no longer evident for the LLI children post-intervention, although these children still exhibited attenuated phase-locking. Our findings suggest that specific aspects of inefficient sensory cortical processing in LLI are ameliorated after training. Copyright © 2013 Elsevier Ltd. All rights reserved.

  20. Modularity Induced Gating and Delays in Neuronal Networks

    PubMed Central

    Shein-Idelson, Mark; Cohen, Gilad; Hanein, Yael

    2016-01-01

    Neural networks, despite their highly interconnected nature, exhibit distinctly localized and gated activation. Modularity, a distinctive feature of neural networks, has been recently proposed as an important parameter determining the manner by which networks support activity propagation. Here we use an engineered biological model, consisting of engineered rat cortical neurons, to study the role of modular topology in gating the activity between cell populations. We show that pairs of connected modules support conditional propagation (transmitting stronger bursts with higher probability), long delays and propagation asymmetry. Moreover, large modular networks manifest diverse patterns of both local and global activation. Blocking inhibition decreased activity diversity and replaced it with highly consistent transmission patterns. By independently controlling modularity and disinhibition, experimentally and in a model, we pose that modular topology is an important parameter affecting activation localization and is instrumental for population-level gating by disinhibition. PMID:27104350

  1. The brain's resting-state activity is shaped by synchronized cross-frequency coupling of neural oscillations

    PubMed Central

    Florin, Esther; Baillet, Sylvain

    2015-01-01

    Functional imaging of the resting brain consistently reveals broad motifs of correlated blood oxygen level dependent (BOLD) activity that engage cerebral regions from distinct functional systems. Yet, the neurophysiological processes underlying these organized, large-scale fluctuations remain to be uncovered. Using magnetoencephalography (MEG) imaging during rest in 12 healthy subjects we analyse the resting state networks and their underlying neurophysiology. We first demonstrate non-invasively that cortical occurrences of high-frequency oscillatory activity are conditioned to the phase of slower spontaneous fluctuations in neural ensembles. We further show that resting-state networks emerge from synchronized phase-amplitude coupling across the brain. Overall, these findings suggest a unified principle of local-to-global neural signaling for long-range brain communication. PMID:25680519

  2. Modular Fixturing System

    NASA Technical Reports Server (NTRS)

    Littell, Justin Anderson (Inventor); Street, Jon P. (Inventor)

    2017-01-01

    The modular fixturing system of the present invention is modular, reusable and capable of significant customization, both in terms of system radius and system height, allowing it to be arranged and rearranged in numerous unique configurations. The system includes multiple modular stanchions having stanchion shafts and stanchion feet that removably attach to apertures in a table. Angle brackets attached to the modular stanchions support shelves. These shelves in turn provide support to work pieces during fabrication processes such as welding.

  3. Portable modular detection system

    DOEpatents

    Brennan, James S.; Singh, Anup; Throckmorton, Daniel J.; Stamps, James F.

    2009-10-13

    Disclosed herein are portable and modular detection devices and systems for detecting electromagnetic radiation, such as fluorescence, from an analyte which comprises at least one optical element removably attached to at least one alignment rail. Also disclosed are modular detection devices and systems having an integrated lock-in amplifier and spatial filter and assay methods using the portable and modular detection devices.

  4. Dynamics of overlapping structures in modular networks.

    PubMed

    Almendral, J A; Leyva, I; Li, D; Sendiña-Nadal, I; Havlin, S; Boccaletti, S

    2010-07-01

    Modularity is a fundamental feature of real networks, being intimately bounded to their functionality, i.e., to their capability of performing parallel tasks in a coordinated way. Although the modular structure of real graphs has been intensively studied, very little is known on the interactions between functional modules of a graph. Here, we present a general method based on synchronization of networking oscillators, that is able to detect overlapping structures in multimodular environments. We furthermore report the full analytical and theoretical description on the relationship between the overlapping dynamics and the underlying network topology. The method is illustrated by means of a series of applications.

  5. Dynamics of everyday life: rigorous modular modeling in neurobiology based on Bloch's dynamical theorem.

    PubMed

    McCollum, Gin; Roberts, Patrick D

    2004-12-01

    Natural, everyday sensorimotor behaviors, such as rising from sitting, typically have an intrinsic organization of several levels of analysis. Taking this intrinsic organization as key to understanding neural dynamics is neither a top-down nor a bottom-up approach, but rather a meshing of multiple centers and levels of analysis. Motor control requires body dynamics that are consistent with physical dynamics, besides the more microscopic levels of neural dynamics. The dynamics of separate movements have been investigated as if the ends can be capped off, separated from the rest of the individual's life. Is this dynamically correct? Even chaotic behavior is deterministic. However, the mathematics of nonlinear oscillations is not all of dynamics. This paper relates Bloch's dynamical theorem to the modular, conditional approach to sensorimotor and other neural functioning. Bloch's dynamical theorem lays a foundation for the piecewise study of structurally accurate dynamics in theoretical neurobiology. Piecewise studies can be used as a modeling option complementary to the methods of nonlinear oscillator dynamics. By applying Bloch's theorem, dynamics of movements analyzed piecewise can be extended into a smooth flow on any manifold, either as a whole or conditionally. Conditional dynamics makes dynamical modeling options explicit, often depending on what variables the organism can control, and allows one to take different modeling options at different junctures in analyzing the same phenomenon. For example, this approach allows the study of complex motor control problems to be reduced to modular constructions using singularities and flow lines. Dynamical contingencies are expressed using the mathematics of ordered structures. This paper presents Bloch's dynamical theorem and its relevance to model construction in theoretical neurobiology. Specific examples, integrated into physiological and behavioral context, are cited from the literature.

  6. microRNA input into a neural ultradian oscillator controls emergence and timing of alternative cell states.

    PubMed

    Goodfellow, Marc; Phillips, Nicholas E; Manning, Cerys; Galla, Tobias; Papalopulu, Nancy

    2014-03-04

    Progenitor maintenance, timed differentiation and the potential to enter quiescence are three fundamental processes that underlie the development of any organ system. In the nervous system, progenitor cells show short-period oscillations in the expression of the transcriptional repressor Hes1, while neurons and quiescent progenitors show stable low and high levels of Hes1, respectively. Here we use experimental data to develop a mathematical model of the double-negative interaction between Hes1 and a microRNA, miR-9, with the aim of understanding how cells transition from one state to another. We show that the input of miR-9 into the Hes1 oscillator tunes its oscillatory dynamics, and endows the system with bistability and the ability to measure time to differentiation. Our results suggest that a relatively simple and widespread network of cross-repressive interactions provides a unifying framework for progenitor maintenance, the timing of differentiation and the emergence of alternative cell states.

  7. Open Ephys electroencephalography (Open Ephys  +  EEG): a modular, low-cost, open-source solution to human neural recording

    NASA Astrophysics Data System (ADS)

    Black, Christopher; Voigts, Jakob; Agrawal, Uday; Ladow, Max; Santoyo, Juan; Moore, Christopher; Jones, Stephanie

    2017-06-01

    Objective. Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. We focused on mitigating these issues by implementing open-source tools to develop a new EEG platform to drive down research costs and promote collaboration and innovation. Approach. Here, we present methods to expand the open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys  +  EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments. Main results. The Open Ephys  +  EEG system can record reliable human EEG data, as well as human EMG data. A side-by-side comparison of eyes closed 8-14 Hz activity between the Open Ephys  +  EEG system and the Brainvision ActiCHamp EEG system showed similar average power and signal to noise. Significance. Open Ephys  +  EEG enables users to acquire high-quality human EEG data comparable to that of commercially available systems, while maintaining the price point and extensibility inherent to open-source systems.

  8. Modular processes in mind and brain.

    PubMed

    Sternberg, Saul

    2011-05-01

    One approach to understanding a complex process starts with an attempt to divide it into modules·, sub-processes that are independent in some sense, and have distinct functions. In this paper, I discuss an approach to the modular decomposition of neural and mental processes. Several examples of process decomposition are presented, together with discussion of inferential requirements. Two examples are of well-established and purely behavioural realizations of the approach (signal detection theory applied to discrimination data; the method of additive factors applied to reaction-time data), and lead to the identification of mental modules. Other examples, leading to the identification of modular neural processes, use brain measures, including the fMRI signal, the latencies of electrophysiological events, and their amplitudes. Some measures are pure (reflecting just one process), while others are composite. Two of the examples reveal mental and neural modules that correspond. Attempts to associate brain regions with behaviourally defined processing modules that use a brain manipulation (transcranial magnetic stimulation, TMS) are promising but incomplete. I show why the process-decomposition approach discussed here, in which the criterion for modularity is separate modifiability, is superior for modular decomposition to the more frequently used task comparison procedure (often used in cognitive neuropsychology) and to its associated subtraction method. To demonstrate the limitations of task comparison, I describe the erroneous conclusion to which it has led about sleep deprivation, and the interpretive difficulties in a TMS study.

  9. Modular control system for optogenetic experiments

    NASA Astrophysics Data System (ADS)

    Sowiński, Mikołaj; Kulik, Paweł; Kasprowicz, Grzegorz; Mankiewicz, Lech; Krawczyk, Rafał D.; Jarosiński, Jakub; Czajkowski, Rafał; Knapska, Ewelina; Puścian, Alicja; Kowalski, Jakub; Rusakov, Konstantin; Przywózki, Tomasz; Rasiński, Paweł; Juszczyk, Bartłomiej

    2016-09-01

    This article presents a modular control system used in Eco-HAB experimentation system. Features specific to the solution are covered. Control system is described in details. The architecture is outlined in the context of requirements to be met. Modes of utilization of implantable device, time synchronization, localization service and antenna driving oscillation fine-tuning as well as preliminary experiments in preparation are described.

  10. Nature's Autonomous Oscillators

    NASA Technical Reports Server (NTRS)

    Mayr, H. G.; Yee, J.-H.; Mayr, M.; Schnetzler, R.

    2012-01-01

    Nonlinearity is required to produce autonomous oscillations without external time dependent source, and an example is the pendulum clock. The escapement mechanism of the clock imparts an impulse for each swing direction, which keeps the pendulum oscillating at the resonance frequency. Among nature's observed autonomous oscillators, examples are the quasi-biennial oscillation and bimonthly oscillation of the Earth atmosphere, and the 22-year solar oscillation. The oscillations have been simulated in numerical models without external time dependent source, and in Section 2 we summarize the results. Specifically, we shall discuss the nonlinearities that are involved in generating the oscillations, and the processes that produce the periodicities. In biology, insects have flight muscles, which function autonomously with wing frequencies that far exceed the animals' neural capacity; Stretch-activation of muscle contraction is the mechanism that produces the high frequency oscillation of insect flight, discussed in Section 3. The same mechanism is also invoked to explain the functioning of the cardiac muscle. In Section 4, we present a tutorial review of the cardio-vascular system, heart anatomy, and muscle cell physiology, leading up to Starling's Law of the Heart, which supports our notion that the human heart is also a nonlinear oscillator. In Section 5, we offer a broad perspective of the tenuous links between the fluid dynamical oscillators and the human heart physiology.

  11. Implementing Modular A Levels.

    ERIC Educational Resources Information Center

    Holding, Gordon

    This document, which is designed for curriculum managers at British further education (FE) colleges, presents basic information on the implementation and perceived benefits of the General Certificate of Education (GCE) modular A (Advanced) levels. The information was synthesized from a survey of 12 FE colleges that introduced the modular A levels…

  12. Modular tokamak configuration

    SciTech Connect

    Thomson, S.L.

    1985-01-01

    This report is concerned with the modular tokamak configuration, and presents information on the following topics: modularity; external vacuum boundary; vertical maintenance; combined reactor building/biological shield with totally remote maintenance; independent TF coils; minimum TF coil bore; saddle PF coils; and heat transport system in bore.

  13. Modular Buildings Buying Guide.

    ERIC Educational Resources Information Center

    Morris, Susan

    1991-01-01

    Suggests that child care program directors who are expanding their programs or opening new child care centers investigate the possibility of renting, leasing, or purchasing a modular building. Discusses the advantages of modular buildings over conventional building construction or rented space in an occupied building. Provides information about…

  14. COMT and DRD2/ANKK-1 gene-gene interaction account for resetting of gamma neural oscillations to auditory stimulus-driven attention

    PubMed Central

    Garcia-Garcia, Manuel; Zarnowiec, Katarzyna; SanMiguel, Iria; Escera, Carles; Clemente, Immaculada C.

    2017-01-01

    Attention capture by potentially relevant environmental stimuli is critical for human survival, yet it varies considerably among individuals. A large series of studies has suggested that attention capture may depend on the cognitive balance between maintenance and manipulation of mental representations and the flexible switch between goal-directed representations and potentially relevant stimuli outside the focus of attention; a balance that seems modulated by a prefrontostriatal dopamine pathway. Here, we examined inter-individual differences in the cognitive control of attention through studying the effects of two single nucleotide polymorphisms regulating dopamine at the prefrontal cortex and the striatum (i.e., COMTMet108/158Val and ANKK1/DRD2TaqIA) on stimulus-driven attention capture. Healthy adult participants (N = 40) were assigned to different groups according to the combination of the polymorphisms COMTMet108/158Val and ANKK1/DRD2TaqIA, and were instructed to perform on a well-established distraction protocol. Performance in individuals with a balance between prefrontal dopamine display and striatal receptor density was slowed down by the occurrence of unexpected distracting events, while those with a rather unbalanced dopamine activity were able maintain task performance with no time delay, yet at the expense of a slightly lower accuracy. This advantage, associated to their distinct genetic profiles, was paralleled by an electrophysiological mechanism of phase-resetting of gamma neural oscillation to the novel, distracting events. Taken together, the current results suggest that the epistatic interaction between COMTVal108/158Met and ANKK1/DRD2 TaqIa genetic polymorphisms lies at the basis of stimulus-driven attention capture. PMID:28222164

  15. COMT and DRD2/ANKK-1 gene-gene interaction account for resetting of gamma neural oscillations to auditory stimulus-driven attention.

    PubMed

    Garcia-Garcia, Manuel; Via, Marc; Zarnowiec, Katarzyna; SanMiguel, Iria; Escera, Carles; Clemente, Immaculada C

    2017-01-01

    Attention capture by potentially relevant environmental stimuli is critical for human survival, yet it varies considerably among individuals. A large series of studies has suggested that attention capture may depend on the cognitive balance between maintenance and manipulation of mental representations and the flexible switch between goal-directed representations and potentially relevant stimuli outside the focus of attention; a balance that seems modulated by a prefrontostriatal dopamine pathway. Here, we examined inter-individual differences in the cognitive control of attention through studying the effects of two single nucleotide polymorphisms regulating dopamine at the prefrontal cortex and the striatum (i.e., COMTMet108/158Val and ANKK1/DRD2TaqIA) on stimulus-driven attention capture. Healthy adult participants (N = 40) were assigned to different groups according to the combination of the polymorphisms COMTMet108/158Val and ANKK1/DRD2TaqIA, and were instructed to perform on a well-established distraction protocol. Performance in individuals with a balance between prefrontal dopamine display and striatal receptor density was slowed down by the occurrence of unexpected distracting events, while those with a rather unbalanced dopamine activity were able maintain task performance with no time delay, yet at the expense of a slightly lower accuracy. This advantage, associated to their distinct genetic profiles, was paralleled by an electrophysiological mechanism of phase-resetting of gamma neural oscillation to the novel, distracting events. Taken together, the current results suggest that the epistatic interaction between COMTVal108/158Met and ANKK1/DRD2 TaqIa genetic polymorphisms lies at the basis of stimulus-driven attention capture.

  16. The effects of high-frequency oscillations in hippocampal electrical activities on the classification of epileptiform events using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Chiu, Alan W. L.; Jahromi, Shokrollah S.; Khosravani, Houman; Carlen, Peter L.; Bardakjian, Berj L.

    2006-03-01

    The existence of hippocampal high-frequency electrical activities (greater than 100 Hz) during the progression of seizure episodes in both human and animal experimental models of epilepsy has been well documented (Bragin A, Engel J, Wilson C L, Fried I and Buzsáki G 1999 Hippocampus 9 137-42 Khosravani H, Pinnegar C R, Mitchell J R, Bardakjian B L, Federico P and Carlen P L 2005 Epilepsia 46 1-10). However, this information has not been studied between successive seizure episodes or utilized in the application of seizure classification. In this study, we examine the dynamical changes of an in vitro low Mg2+ rat hippocampal slice model of epilepsy at different frequency bands using wavelet transforms and artificial neural networks. By dividing the time-frequency spectrum of each seizure-like event (SLE) into frequency bins, we can analyze their burst-to-burst variations within individual SLEs as well as between successive SLE episodes. Wavelet energy and wavelet entropy are estimated for intracellular and extracellular electrical recordings using sufficiently high sampling rates (10 kHz). We demonstrate that the activities of high-frequency oscillations in the 100-400 Hz range increase as the slice approaches SLE onsets and in later episodes of SLEs. Utilizing the time-dependent relationship between different frequency bands, we can achieve frequency-dependent state classification. We demonstrate that activities in the frequency range 100-400 Hz are critical for the accurate classification of the different states of electrographic seizure-like episodes (containing interictal, preictal and ictal states) in brain slices undergoing recurrent spontaneous SLEs. While preictal activities can be classified with an average accuracy of 77.4 ± 6.7% utilizing the frequency spectrum in the range 0-400 Hz, we can also achieve a similar level of accuracy by using a nonlinear relationship between 100-400 Hz and <4 Hz frequency bands only.

  17. Modular kinetic analysis.

    PubMed

    Krab, Klaas

    2011-01-01

    Modularization is an important strategy to tackle the study of complex biological systems. Modular kinetic analysis (MKA) is a quantitative method to extract kinetic information from such a modularized system that can be used to determine the control and regulatory structure of the system, and to pinpoint and quantify the interaction of effectors with the system. The principles of the method are described, and the relation with metabolic control analysis is discussed. Examples of application of MKA are given. Copyright © 2011 Elsevier Inc. All rights reserved.

  18. Modular tokamak magnetic system

    DOEpatents

    Yang, Tien-Fang

    1988-01-01

    A modular tokamak system comprised of a plurality of interlocking moldules. Each module is comprised of a vacuum vessel section, a toroidal field coil, moldular saddle coils which generate a poloidal magnetic field and ohmic heating coils.

  19. Successful modular cosmology

    NASA Astrophysics Data System (ADS)

    Kadota, Kenji; Stewart, Ewan D.

    2003-07-01

    We present a modular cosmology scenario where the difficulties encountered in conventional modular cosmology are solved in a self-consistent manner, with definite predictions to be tested by observation. Notably, the difficulty of the dilaton finding its way to a precarious weak coupling minimum is made irrelevant by having eternal modular inflation at the vacuum supersymmetry breaking scale after the dilaton is stabilised. Neither this eternal inflation nor the subsequent non-slow-roll modular inflation destabilise the dilaton from its precarious minimum due to the low energy scale of the inflation and consequent small back reaction on the dilaton potential. The observed flat CMB spectrum is obtained from fluctuations in the angular component of a modulus near a symmetric point, which are hugely magnified by the roll down of the modulus to Planckian values, allowing them to dominate the final curvature perturbation. We also give precise calculations of the spectral index and its running.

  20. A Modular Robotic Architecture

    DTIC Science & Technology

    1990-11-01

    DATES COVERED AD-A232 007 Januar 1991 professional paper5 FUNOING NUMBERS A MODULAR ROBOTIC ARCHITECTURE PR: ZE92 WU: DN300029 PE: 0602936N - S. AUTHOR...mobile robots will help alleviate these problems, and, if made widely available, will promote standardization and compatibility among systems throughout...the industry. The Modular Robotic Architecture (MRA) is a generic control system that meets the above needs by providing developers with a standard set

  1. Modularity and mental architecture.

    PubMed

    Robbins, Philip

    2013-11-01

    Debates about the modularity of cognitive architecture have been ongoing for at least the past three decades, since the publication of Fodor's landmark book The Modularity of Mind. According to Fodor, modularity is essentially tied to informational encapsulation, and as such is only found in the relatively low-level cognitive systems responsible for perception and language. According to Fodor's critics in the evolutionary psychology camp, modularity simply reflects the fine-grained functional specialization dictated by natural selection, and it characterizes virtually all aspects of cognitive architecture, including high-level systems for judgment, decision making, and reasoning. Though both of these perspectives on modularity have garnered support, the current state of evidence and argument suggests that a broader skepticism about modularity may be warranted. WIREs Cogn Sci 2013, 4:641-649. doi: 10.1002/wcs.1255 CONFLICT OF INTEREST: The author has declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website.

  2. Symmetric modular torsatron

    DOEpatents

    Rome, J.A.; Harris, J.H.

    1984-01-01

    A fusion reactor device is provided in which the magnetic fields for plasma confinement in a toroidal configuration is produced by a plurality of symmetrical modular coils arranged to form a symmetric modular torsatron referred to as a symmotron. Each of the identical modular coils is helically deformed and comprise one field period of the torsatron. Helical segments of each coil are connected by means of toroidally directed windbacks which may also provide part of the vertical field required for positioning the plasma. The stray fields of the windback segments may be compensated by toroidal coils. A variety of magnetic confinement flux surface configurations may be produced by proper modulation of the winding pitch of the helical segments of the coils, as in a conventional torsatron, winding the helix on a noncircular cross section and varying the poloidal and radial location of the windbacks and the compensating toroidal ring coils.

  3. Self Evolving Modular Network

    NASA Astrophysics Data System (ADS)

    Tokunaga, Kazuhiro; Kawabata, Nobuyuki; Furukawa, Tetsuo

    We propose a novel modular network called the Self-Evolving Modular Network (SEEM). The SEEM has a modular network architecture with a graph structure and these following advantages: (1) new modules are added incrementally to allow the network to adapt in a self-organizing manner, and (2) graph's paths are formed based on the relationships between the models represented by modules. The SEEM is expected to be applicable to evolving functions of an autonomous robot in a self-organizing manner through interaction with the robot's environment and categorizing large-scale information. This paper presents the architecture and an algorithm for the SEEM. Moreover, performance characteristic and effectiveness of the network are shown by simulations using cubic functions and a set of 3D-objects.

  4. Modular optical detector system

    DOEpatents

    Horn, Brent A.; Renzi, Ronald F.

    2006-02-14

    A modular optical detector system. The detector system is designed to detect the presence of molecules or molecular species by inducing fluorescence with exciting radiation and detecting the emitted fluorescence. Because the system is capable of accurately detecting and measuring picomolar concentrations it is ideally suited for use with microchemical analysis systems generally and capillary chromatographic systems in particular. By employing a modular design, the detector system provides both the ability to replace various elements of the detector system without requiring extensive realignment or recalibration of the components as well as minimal user interaction with the system. In addition, the modular concept provides for the use and addition of a wide variety of components, including optical elements (lenses and filters), light sources, and detection means, to fit particular needs.

  5. Modular biowaste monitoring system

    NASA Technical Reports Server (NTRS)

    Fogal, G. L.

    1975-01-01

    The objective of the Modular Biowaste Monitoring System Program was to generate and evaluate hardware for supporting shuttle life science experimental and diagnostic programs. An initial conceptual design effort established requirements and defined an overall modular system for the collection, measurement, sampling and storage of urine and feces biowastes. This conceptual design effort was followed by the design, fabrication and performance evaluation of a flight prototype model urine collection, volume measurement and sampling capability. No operational or performance deficiencies were uncovered as a result of the performance evaluation tests.

  6. Modular Optofluidic Systems (MOPS)

    NASA Astrophysics Data System (ADS)

    Ackermann, Tobias N.; Dietvorst, Jiri; Sanchis, Ana; Salvador, Juan P.; Munoz-Berbel, Xavier; Alvarez-Conde, Erica; Kopp, Daniel; Zappe, Hans; Marco, M.-Pilar; Llobera, Andreu

    2016-12-01

    Elementary PDMS-based building blocks of fluidic, optical and optofluidic components for Lab on a chip (LOC) platforms has here been developed. All individual modules are compatible and can be anchored and released with the help of puzzle-type connectors This approach is a powerful toolbox to create modular optofluidic systems (MOPS), which can be modified/upgraded to user needs and in-situ reconfigurable. In addition, the PDMS can locally be functionalized, defining a modular biosensor. Measurements in absorbance and fluorescence have been pursued as demonstrator.

  7. Modular total absorption spectrometer

    NASA Astrophysics Data System (ADS)

    Karny, M.; Rykaczewski, K. P.; Fijałkowska, A.; Rasco, B. C.; Wolińska-Cichocka, M.; Grzywacz, R. K.; Goetz, K. C.; Miller, D.; Zganjar, E. F.

    2016-11-01

    The design and performance of the Modular Total Absorption Spectrometer built and commissioned at the Oak Ridge National Laboratory is presented. The active volume of the detector is approximately one ton of NaI(Tl), which results in very high full γ energy peak efficiency of 71% at 6 MeV and nearly flat efficiency of around 81.5% for low energy γ-rays between 300 keV and 1 MeV. In addition to the high peak efficiency, the modular construction of the detector permits the use of a γ-coincidence technique in data analysis as well as β-delayed neutron observation.

  8. Modular invariant inflation

    SciTech Connect

    Kobayashi, Tatsuo; Nitta, Daisuke; Urakawa, Yuko

    2016-08-08

    Modular invariance is a striking symmetry in string theory, which may keep stringy corrections under control. In this paper, we investigate a phenomenological consequence of the modular invariance, assuming that this symmetry is preserved as well as in a four dimensional (4D) low energy effective field theory. As a concrete setup, we consider a modulus field T whose contribution in the 4D effective field theory remains invariant under the modular transformation and study inflation drived by T. The modular invariance restricts a possible form of the scalar potenntial. As a result, large field models of inflation are hardly realized. Meanwhile, a small field model of inflation can be still accomodated in this restricted setup. The scalar potential traced during the slow-roll inflation mimics the hilltop potential V{sub ht}, but it also has a non-negligible deviation from V{sub ht}. Detecting the primordial gravitational waves predicted in this model is rather challenging. Yet, we argue that it may be still possible to falsify this model by combining the information in the reheating process which can be determined self-completely in this setup.

  9. Modular invariant gaugino condensation

    SciTech Connect

    Gaillard, M.K.

    1991-05-09

    The construction of effective supergravity lagrangians for gaugino condensation is reviewed and recent results are presented that are consistent with modular invariance and yield a positive definite potential of the noscale type. Possible implications for phenomenology are briefly discussed. 29 refs.

  10. Modular invariant inflation

    NASA Astrophysics Data System (ADS)

    Kobayashi, Tatsuo; Nitta, Daisuke; Urakawa, Yuko

    2016-08-01

    Modular invariance is a striking symmetry in string theory, which may keep stringy corrections under control. In this paper, we investigate a phenomenological consequence of the modular invariance, assuming that this symmetry is preserved as well as in a four dimensional (4D) low energy effective field theory. As a concrete setup, we consider a modulus field T whose contribution in the 4D effective field theory remains invariant under the modular transformation and study inflation drived by T. The modular invariance restricts a possible form of the scalar potenntial. As a result, large field models of inflation are hardly realized. Meanwhile, a small field model of inflation can be still accomodated in this restricted setup. The scalar potential traced during the slow-roll inflation mimics the hilltop potential Vht, but it also has a non-negligible deviation from Vht. Detecting the primordial gravitational waves predicted in this model is rather challenging. Yet, we argue that it may be still possible to falsify this model by combining the information in the reheating process which can be determined self-completely in this setup.

  11. A Modular CAI System.

    ERIC Educational Resources Information Center

    Van Der Mast, Charles

    The experimental CAI system which is being tested at Delft University of Technology is structured in a modular manner to account for high changeability. The concept formulated for this project was the outcome of research into technological, organizational, and educational developments in CAI, and the enumeration of the common aspects of the…

  12. Modular core holder

    SciTech Connect

    Mueller, J.; Cole, C.W.; Hamid, S.; Lucas, J.K.

    1991-03-05

    This patent describes a modular core holder. It comprises: a sleeve, forming an internal cavity for receiving a core. The sleeve including segments; support means, overlying the sleeve, for supporting the sleeve; and access means, positioned between at least two of the segments of the sleeve, for allowing measurement of conditions within the internal cavity.

  13. MRV - Modular Robotic Vehicle

    NASA Technical Reports Server (NTRS)

    Ridley, Justin; Bluethmann, Bill

    2015-01-01

    The Modular Robotic Vehicle, or MRV, completed in 2013, was developed at the Johnson Space Center in order to advance technologies which have applications for future vehicles both in space and on Earth. With seating for two people, MRV is a fully electric vehicle modeled as a "city car", suited for busy urban environments.

  14. Modular Perspectives on Bilingualism.

    ERIC Educational Resources Information Center

    Francis, Norbert

    2002-01-01

    This research review traces the current discussion on models of bilingualism to the contributions of Vygotsky and Luria. Proposes that a modular approach to studying the different aspects of bilingual development promises to chart a course toward finding a broader common ground around research findings and interpretations that appear to be…

  15. Modularity in robotic systems

    NASA Technical Reports Server (NTRS)

    Tesar, Delbert; Butler, Michael S.

    1989-01-01

    Most robotic systems today are designed one at a time, at a high cost of time and money. This wasteful approach has been necessary because the industry has not established a foundation for the continued evolution of intelligent machines. The next generation of robots will have to be generic, versatile machines capable of absorbing new technology rapidly and economically. This approach is demonstrated in the success of the personal computer, which can be upgraded or expanded with new software and hardware at virtually every level. Modularity is perceived as a major opportunity to reduce the 6 to 7 year design cycle time now required for new robotic manipulators, greatly increasing the breadth and speed of diffusion of robotic systems in manufacturing. Modularity and its crucial role in the next generation of intelligent machines are the focus of interest. The main advantages that modularity provides are examined; types of modules needed to create a generic robot are discussed. Structural modules designed by the robotics group at the University of Texas at Austin are examined to demonstrate the advantages of modular design.

  16. Modular functional organisation of the axial locomotor system in salamanders.

    PubMed

    Cabelguen, Jean-Marie; Charrier, Vanessa; Mathou, Alexia

    2014-02-01

    Most investigations on tetrapod locomotion have been concerned with limb movements. However, there is compelling evidence that the axial musculoskeletal system contributes to important functions during locomotion. Adult salamanders offer a remarkable opportunity to examine these functions because these amphibians use axial undulations to propel themselves in both aquatic and terrestrial environments. In this article, we review the currently available biological data on axial functions during various locomotor modes in salamanders. We also present data showing the modular organisation of the neural networks that generate axial synergies during locomotion. The functional implication of this modular organisation is discussed.

  17. Modular reflector concept study

    NASA Astrophysics Data System (ADS)

    Vaughan, D. H.

    1981-02-01

    The feasibility was studied of constructing large space structures, specifically a 100 meter paraboloidal R.F. reflector, by individually deploying a number of relatively small structural modules, and then joining them to form a single large structure in orbit. The advantage of this approach is that feasibility of a large antenna may be demonstrated by ground and flight tests of several smaller and less costly subelements. Thus, initial development costs are substantially reduced and a high degree of reliability can be obtained without commitment to construction of a very large system. The three candidate structural concepts investigated are: (1) the deployable cell module; (2) the paraboloidal extendable truss antenna adapted to modular assembly; and (3) the modular extendable truss antenna (META).

  18. Modular space station

    NASA Technical Reports Server (NTRS)

    1972-01-01

    The modular space station comprising small, shuttle-launched modules, and characterized by low initial cost and incremental manning, is described. The initial space station is designed to be delivered into orbit by three space shuttles and assembled in space. The three sections are the power/subsystems module, the crew/operations module, and the general purpose laboratory module. It provides for a crew of six. Subsequently duplicate/crew/operations and power/subsystems modules will be mated to the original modules, and provide for an additional six crewmen. A total of 17 research and applications modules is planned, three of which will be free-flying modules. Details are given on the program plan, modular characteristics, logistics, experiment support capability and requirements, operations analysis, design support analyses, and shuttle interfaces.

  19. ATIS - A modular approach

    NASA Astrophysics Data System (ADS)

    Kirson, Allan

    The author describes a modular approach to the design of an in-vehicle navigation and route guidance system that supports a phased implementation of the technology, and anticipates expected differences in implementation in different parts of the world and for different makes and models of vehicle. A series of sensors in the vehicle are used to determine the vehicle's position by dead reckoning and map-matching. The system then calculates the best route to the selected destination, taking into account the real-time traffic information received from a traffic management center, and presents route guidance instructions to the user as the route is traversed. Attention is given to modularity considerations, vehicle positioning, driver support, vehicle-to-infrastructure communications, and the role of standards.

  20. Modular reflector concept study

    NASA Technical Reports Server (NTRS)

    Vaughan, D. H.

    1981-01-01

    The feasibility was studied of constructing large space structures, specifically a 100 meter paraboloidal R.F. reflector, by individually deploying a number of relatively small structural modules, and then joining them to form a single large structure in orbit. The advantage of this approach is that feasibility of a large antenna may be demonstrated by ground and flight tests of several smaller and less costly subelements. Thus, initial development costs are substantially reduced and a high degree of reliability can be obtained without commitment to construction of a very large system. The three candidate structural concepts investigated are: (1) the deployable cell module; (2) the paraboloidal extendable truss antenna adapted to modular assembly; and (3) the modular extendable truss antenna (META).

  1. Quantum spaces are modular

    NASA Astrophysics Data System (ADS)

    Freidel, Laurent; Leigh, Robert G.; Minic, Djordje

    2016-11-01

    At present, our notion of space is a classical concept. Taking the point of view that quantum theory is more fundamental than classical physics, and that space should be given a purely quantum definition, we revisit the notion of Euclidean space from the point of view of quantum mechanics. Since space appears in physics in the form of labels on relativistic fields or Schrödinger wave functionals, we propose to define Euclidean quantum space as a choice of polarization for the Heisenberg algebra of quantum theory. We show, following Mackey, that generically, such polarizations contain a fundamental length scale and that contrary to what is implied by the Schrödinger polarization, they possess topologically distinct spectra. These are the modular spaces. We show that they naturally come equipped with additional geometrical structures usually encountered in the context of string theory or generalized geometry. Moreover, we show how modular space reconciles the presence of a fundamental scale with translation and rotation invariance. We also discuss how the usual classical notion of space comes out as a form of thermodynamical limit of modular space while the Schrödinger space is a singular limit.

  2. Brain oscillations in neuropsychiatric disease.

    PubMed

    Başar, Erol

    2013-09-01

    The term "brain (or neural) oscillations" refers to the rhythmic and/or repetitive electrical activity generated spontaneously and in response to stimuli by neural tissue in the central nervous system. The importance of brain oscillations in sensory-cognitive processes has become increasingly evident. It has also become clear that event-related oscillations are modified in many types of neuropathology, in particular in cognitive impairment. This review discusses methods such as evoked/event-related oscillations and spectra, coherence analysis, and phase locking. It gives examples of applications of essential methods and concepts in bipolar disorder that provide a basis for fundamental notions regarding neurophysiologic biomarkers in cognitive impairment. The take-home message is that in the development of diagnostic and pharmacotherapeutic strategies, neurophysiologic data should be analyzed in a framework that uses a multiplicity of methods and frequency bands.

  3. [Modular enteral nutrition in pediatrics].

    PubMed

    Murillo Sanchís, S; Prenafeta Ferré, M T; Sempere Luque, M D

    1991-01-01

    Modular Enteral Nutrition may be a substitute for Parenteral Nutrition in children with different pathologies. Study of 4 children with different pathologies selected from a group of 40 admitted to the Maternal-Childrens Hospital "Valle de Hebrón" in Barcelona, who received modular enteral nutrition. They were monitored on a daily basis by the Dietician Service. Modular enteral nutrition consists of modules of proteins, peptides, lipids, glucids and mineral salts-vitamins. 1.--Craneo-encephalic traumatisms with loss of consciousness, Feeding with a combination of parenteral nutrition and modular enteral nutrition for 7 days. In view of the tolerance and good results of the modular enteral nutrition, the parenteral nutrition was suspended and modular enteral nutrition alone used up to a total of 43 days. 2.--55% burns with 36 days of hyperproteic modular enteral nutrition together with normal feeding. A more rapid recovery was achieved with an increase in total proteins and albumin. 3.--Persistent diarrhoea with 31 days of modular enteral nutrition, 5 days on parenteral nutrition alone and 8 days on combined parenteral nutrition and modular enteral nutrition. In view of the tolerance and good results of the modular enteral nutrition, the parenteral nutrition was suspended. 4.--Mucoviscidosis with a total of 19 days on modular enteral nutrition, 12 of which were exclusively on modular enteral nutrition and 7 as a night supplement to normal feeding. We administered proteic intakes of up to 20% of the total calorific intake and in concentrations of up to 1.2 calories/ml of the final preparation, always with a good tolerance. Modular enteral nutrition can and should be used as a substitute for parenteral nutrition in children with different pathologies, thus preventing the complications inherent in parenteral nutrition.

  4. Neural Cross-Frequency Coupling: Connecting Architectures, Mechanisms, and Functions.

    PubMed

    Hyafil, Alexandre; Giraud, Anne-Lise; Fontolan, Lorenzo; Gutkin, Boris

    2015-11-01

    Neural oscillations are ubiquitously observed in the mammalian brain, but it has proven difficult to tie oscillatory patterns to specific cognitive operations. Notably, the coupling between neural oscillations at different timescales has recently received much attention, both from experimentalists and theoreticians. We review the mechanisms underlying various forms of this cross-frequency coupling. We show that different types of neural oscillators and cross-frequency interactions yield distinct signatures in neural dynamics. Finally, we associate these mechanisms with several putative functions of cross-frequency coupling, including neural representations of multiple environmental items, communication over distant areas, internal clocking of neural processes, and modulation of neural processing based on temporal predictions.

  5. LMDS Lightweight Modular Display System.

    DTIC Science & Technology

    1982-02-16

    LIGHTWEIGHT MODULAR DISPLAY SYSTEM %C AD Gomez SW Wolfe EW Davenport BD Calder 16 February 1982 * / DTrSJUL 22 3829 Approved for public release...375 4. TITLE (and Subtitle) S. TYPE OF REPORT & PERIOD COVERED Oct 77 to Jan 82 LMDS LIGHTWEIGHT MODULAR DISPLAY SYSTEM S. PERFORMING ORG. REPORT...Processing Power Distribution Modular Display Low Cost Tactical Display Tactical Tablet Lightweight Display General Purpose Dispiay Functional Modules Touch

  6. Robotic hand with modular extensions

    DOEpatents

    Salisbury, Curt Michael; Quigley, Morgan

    2015-01-20

    A robotic device is described herein. The robotic device includes a frame that comprises a plurality of receiving regions that are configured to receive a respective plurality of modular robotic extensions. The modular robotic extensions are removably attachable to the frame at the respective receiving regions by way of respective mechanical fuses. Each mechanical fuse is configured to trip when a respective modular robotic extension experiences a predefined load condition, such that the respective modular robotic extension detaches from the frame when the load condition is met.

  7. Modular analysis of biological networks.

    PubMed

    Kaltenbach, Hans-Michael; Stelling, Jörg

    2012-01-01

    The analysis of complex biological networks has traditionally relied on decomposition into smaller, semi-autonomous units such as individual signaling pathways. With the increased scope of systems biology (models), rational approaches to modularization have become an important topic. With increasing acceptance of de facto modularity in biology, widely different definitions of what constitutes a module have sparked controversies. Here, we therefore review prominent classes of modular approaches based on formal network representations. Despite some promising research directions, several important theoretical challenges remain open on the way to formal, function-centered modular decompositions for dynamic biological networks.

  8. Latching chains in K-nearest-neighbor and modular small-world networks.

    PubMed

    Song, Sanming; Yao, Hongxun; Simonov, Alexander Yurievich

    2015-01-01

    Latching dynamics retrieve pattern sequences successively by neural adaption and pattern correlation. We have previously proposed a modular latching chain model in Song et al. (2014) to better accommodate the structured transitions in the brain. Different cortical areas have different network structures. To explore how structural parameters like rewiring probability, threshold, noise and feedback connections affect the latching dynamics, two different connection schemes, K-nearest-neighbor network and modular network both having modular structure are considered. Latching chains are measured using two proposed measures characterizing length of intra-modular latching chains and sequential inter-modular association transitions. Our main findings include: (1) With decreasing threshold coefficient and rewiring probability, both the K-nearest-neighbor network and the modular network experience quantitatively similar phase change processes. (2) The modular network exhibits selectively enhanced latching in the small-world range of connectivity. (3) The K-nearest-neighbor network is more robust to changes in rewiring probability, while the modular network is more robust to the presence of noise pattern pairs and to changes in the strength of feedback connections. According to our findings, the relationships between latching chains in K-nearest-neighbor and modular networks and different forms of cognition and information processing emerging in the brain are discussed.

  9. Modular biometric system

    NASA Astrophysics Data System (ADS)

    Hsu, Charles; Viazanko, Michael; O'Looney, Jimmy; Szu, Harold

    2009-04-01

    Modularity Biometric System (MBS) is an approach to support AiTR of the cooperated and/or non-cooperated standoff biometric in an area persistent surveillance. Advanced active and passive EOIR and RF sensor suite is not considered here. Neither will we consider the ROC, PD vs. FAR, versus the standoff POT in this paper. Our goal is to catch the "most wanted (MW)" two dozens, separately furthermore ad hoc woman MW class from man MW class, given their archrivals sparse front face data basis, by means of various new instantaneous input called probing faces. We present an advanced algorithm: mini-Max classifier, a sparse sample realization of Cramer-Rao Fisher bound of the Maximum Likelihood classifier that minimize the dispersions among the same woman classes and maximize the separation among different man-woman classes, based on the simple feature space of MIT Petland eigen-faces. The original aspect consists of a modular structured design approach at the system-level with multi-level architectures, multiple computing paradigms, and adaptable/evolvable techniques to allow for achieving a scalable structure in terms of biometric algorithms, identification quality, sensors, database complexity, database integration, and component heterogenity. MBS consist of a number of biometric technologies including fingerprints, vein maps, voice and face recognitions with innovative DSP algorithm, and their hardware implementations such as using Field Programmable Gate arrays (FPGAs). Biometric technologies and the composed modularity biometric system are significant for governmental agencies, enterprises, banks and all other organizations to protect people or control access to critical resources.

  10. Modular Biometric Monitoring System

    NASA Technical Reports Server (NTRS)

    Chmiel, Alan J. (Inventor); Humphreys, Bradley T. (Inventor)

    2017-01-01

    A modular system for acquiring biometric data includes a plurality of data acquisition modules configured to sample biometric data from at least one respective input channel at a data acquisition rate. A representation of the sampled biometric data is stored in memory of each of the plurality of data acquisition modules. A central control system is in communication with each of the plurality of data acquisition modules through a bus. The central control system is configured to control communication of data, via the bus, with each of the plurality of data acquisition modules.

  11. Geometric Kac Moody modularity

    NASA Astrophysics Data System (ADS)

    Lynker, Monika; Schimmrigk, Rolf

    2006-05-01

    It is shown how the arithmetic structure of algebraic curves encoded in the Hasse-Weil L-function can be related to affine Kac-Moody algebras. This result is useful in relating the arithmetic geometry of Calabi-Yau varieties to the underlying exactly solvable theory. In the case of the genus three Fermat curve we identify the Hasse-Weil L-function with the Mellin transform of the twist of a number theoretic modular form derived from the string function of a non-twisted affine Lie algebra. The twist character is associated to the number field of quantum dimensions of the conformal field theory.

  12. Modular space station facilities.

    NASA Technical Reports Server (NTRS)

    Parker, P. J.

    1973-01-01

    The modular space station will operate as a general purpose laboratory (GPL). In addition, the space station will be able to support many attached or free-flying research and application modules that would be dedicated to specific projects like astronomy or earth observations. The GPL primary functions have been organized into functional laboratories including an electrical/electronics laboratory, a mechanical sciences laboratory, an experiment and test isolation laboratory, a hard data process facility, a data evaluation facility, an optical sciences laboratory, a biomedical and biosciences laboratory, and an experiment/secondary command and control center.

  13. Modular gear bearings

    NASA Technical Reports Server (NTRS)

    Vranish, John M. (Inventor)

    2009-01-01

    A gearing system using modular gear bearing components. Each component is composed of a core, one or more modules attached to the core and two or more fastening modules rigidly attaching the modules to the core. The modules, which are attached to the core, may consist of gears, rollers or gear bearing components. The core orientation affects the orientation of the modules attached to the core. This is achieved via the keying arrangement of the core and the component modules that attach to the core. Such an arrangement will also facilitate the phase tuning of gear modules with respect to the core and other gear modules attached to the core.

  14. Modular and Hierarchically Modular Organization of Brain Networks

    PubMed Central

    Meunier, David; Lambiotte, Renaud; Bullmore, Edward T.

    2010-01-01

    Brain networks are increasingly understood as one of a large class of information processing systems that share important organizational principles in common, including the property of a modular community structure. A module is topologically defined as a subset of highly inter-connected nodes which are relatively sparsely connected to nodes in other modules. In brain networks, topological modules are often made up of anatomically neighboring and/or functionally related cortical regions, and inter-modular connections tend to be relatively long distance. Moreover, brain networks and many other complex systems demonstrate the property of hierarchical modularity, or modularity on several topological scales: within each module there will be a set of sub-modules, and within each sub-module a set of sub-sub-modules, etc. There are several general advantages to modular and hierarchically modular network organization, including greater robustness, adaptivity, and evolvability of network function. In this context, we review some of the mathematical concepts available for quantitative analysis of (hierarchical) modularity in brain networks and we summarize some of the recent work investigating modularity of structural and functional brain networks derived from analysis of human neuroimaging data. PMID:21151783

  15. Neural rhythmic symphony of human walking observation: Upside-down and Uncoordinated condition on cortical theta, alpha, beta and gamma oscillations

    PubMed Central

    Zarka, David; Cevallos, Carlos; Petieau, Mathieu; Hoellinger, Thomas; Dan, Bernard; Cheron, Guy

    2014-01-01

    Biological motion observation has been recognized to produce dynamic change in sensorimotor activation according to the observed kinematics. Physical plausibility of the spatial-kinematic relationship of human movement may play a major role in the top-down processing of human motion recognition. Here, we investigated the time course of scalp activation during observation of human gait in order to extract and use it on future integrated brain-computer interface using virtual reality (VR). We analyzed event related potentials (ERP), the event related spectral perturbation (ERSP) and the inter-trial coherence (ITC) from high-density EEG recording during video display onset (−200–600 ms) and the steady state visual evoked potentials (SSVEP) inside the video of human walking 3D-animation in three conditions: Normal; Upside-down (inverted images); and Uncoordinated (pseudo-randomly mixed images). We found that early visual evoked response P120 was decreased in Upside-down condition. The N170 and P300b amplitudes were decreased in Uncoordinated condition. In Upside-down and Uncoordinated conditions, we found decreased alpha power and theta phase-locking. As regards gamma oscillation, power was increased during the Upside-down animation and decreased during the Uncoordinated animation. An SSVEP-like response oscillating at about 10 Hz was also described showing that the oscillating pattern is enhanced 300 ms after the heel strike event only in the Normal but not in the Upside-down condition. Our results are consistent with most of previous point-light display studies, further supporting possible use of virtual reality for neurofeedback applications. PMID:25278847

  16. Modular antenna design study

    NASA Technical Reports Server (NTRS)

    Ribble, J. W.

    1981-01-01

    The mechanical design of a modular antenna concept was developed sufficiently to allow manufacture of a working demonstration model of a module, to predict mass properties, and to make performance estimates for antenna reflectors composed of these modules. The primary features of this concept are: (1) each module is an autonomous structural element which can be attached to adjacent modules through a three point connection; (2) the upper surface is a folding hexagonal truss plate mechanism which serves as the supporting structure for a reflective surface; and (3) the entire truss and surface can be folded into a cylindrical envelope in which all truss elements are essentially parallel. The kinematic studies and engineering demonstration model fully verified the deployment kinematics, stowing philosophy, and deployment sequencing for large antenna modules. It was established that such modules can be stowed in packages as small as 25 cm in diameter, using 1.27 cm diameter structural tubes. The development activity indicates that this deployable modular approach towards building large structures in space will support erection of 450 m apertures for operation up to 3 GHz with a single space shuttle flight.

  17. Modular reflector concept study

    NASA Technical Reports Server (NTRS)

    Vaughan, D. H.

    1981-01-01

    A study was conducted to evaluate the feasibility of space erecting a 100 meter paraboloidal radio frequency reflector by joining a number of individually deployed structural modules. Three module design concepts were considered: (1) the deployable cell module (DCM); (2) the modular paraboloidal erectable truss antenna (Mod-PETA); and (3) the modular erectable truss antenna (META). With the space shuttle (STS) as the launch system, the methodology of packaging and stowing in the orbiter, and of dispensing, deploying and joining, in orbit, were studied and the necessary support equipment identified. The structural performance of the completed reflectors was evaluated and their overall operational capability and feasibility were evaluated and compared. The potential of the three concepts to maintain stable shape in the space environment was determined. Their ability to operate at radio frequencies of 1 GHz and higher was assessed assuming the reflector surface to consist of a number of flat, hexagonal facets. A parametric study was performed to determine figure degradation as a function of reflector size, flat facet size, and f/D ratio.

  18. Modular radiochemistry synthesis system

    SciTech Connect

    Satyamurthy, Nagichettiar; Barrio, Jorge R.; Amarasekera, Bernard; Van Dam, R. Michael; Olma, Sebastian; Williams, Dirk; Eddings, Mark; Shen, Clifton Kwang-Fu

    2015-12-15

    A modular chemical production system includes multiple modules for performing a chemical reaction, particularly of radiochemical compounds, from a remote location. One embodiment comprises a reaction vessel including a moveable heat source with the position thereof relative to the reaction vessel being controllable from a remote position. Alternatively the heat source may be fixed in location and the reaction vial is moveable into and out of the heat source. The reaction vessel has one or more sealing plugs, the positioning of which in relationship to the reaction vessel is controllable from a remote position. Also the one or more reaction vessel sealing plugs can include one or more conduits there through for delivery of reactants, gases at atmospheric or an elevated pressure, inert gases, drawing a vacuum and removal of reaction end products to and from the reaction vial, the reaction vial with sealing plug in position being operable at elevated pressures. The modular chemical production system is assembled from modules which can each include operating condition sensors and controllers configured for monitoring and controlling the individual modules and the assembled system from a remote position. Other modules include, but are not limited to a Reagent Storage and Delivery Module, a Cartridge Purification Module, a Microwave Reaction Module, an External QC/Analysis/Purification Interface Module, an Aliquotting Module, an F-18 Drying Module, a Concentration Module, a Radiation Counting Module, and a Capillary Reactor Module.

  19. Modular radiochemistry synthesis system

    DOEpatents

    Satyamurthy, Nagichettiar; Barrio, Jorge R; Amarasekera, Bernard; Van Dam, R. Michael; Olma, Sebastian; Williams, Dirk; Eddings, Mark A; Shen, Clifton Kwang-Fu

    2015-02-10

    A modular chemical production system includes multiple modules for performing a chemical reaction, particularly of radiochemical compounds, from a remote location. One embodiment comprises a reaction vessel including a moveable heat source with the position thereof relative to the reaction vessel being controllable from a remote position. Alternatively the heat source may be fixed in location and the reaction vial is moveable into and out of the heat source. The reaction vessel has one or more sealing plugs, the positioning of which in relationship to the reaction vessel is controllable from a remote position. Also the one or more reaction vessel sealing plugs can include one or more conduits there through for delivery of reactants, gases at atmospheric or an elevated pressure, inert gases, drawing a vacuum and removal of reaction end products to and from the reaction vial, the reaction vial with sealing plug in position being operable at elevated pressures. The modular chemical production system is assembled from modules which can each include operating condition sensors and controllers configured for monitoring and controlling the individual modules and the assembled system from a remote position. Other modules include, but are not limited to a Reagent Storage and Delivery Module, a Cartridge Purification Module, a Microwave Reaction Module, an External QC/Analysis/Purification Interface Module, an Aliquotting Module, an F-18 Drying Module, a Concentration Module, a Radiation Counting Module, and a Capillary Reactor Module.

  20. Preheating after modular inflation

    NASA Astrophysics Data System (ADS)

    Barnaby, Neil; Bond, J. Richard; Huang, Zhiqi; Kofman, Lev

    2009-12-01

    We study (p)reheating in modular (closed string) inflationary scenarios, with a special emphasis on Kähler moduli/Roulette models. It is usually assumed that reheating in such models occurs through perturbative decays. However, we find that there are very strong non-perturbative preheating decay channels related to the particular shape of the inflaton potential (which is highly nonlinear and has a very steep minimum). Preheating after modular inflation, proceeding through a combination of tachyonic instability and broad-band parametric resonance, is perhaps the most violent example of preheating after inflation known in the literature. Further, we consider the subsequent transfer of energy to the standard model sector in scenarios where the standard model particles are confined to a D7-brane wrapping the inflationary blow-up cycle of the compactification manifold or, more interestingly, a non-inflationary blow-up cycle. We explicitly identify the decay channels of the inflaton in these two scenarios. We also consider the case where the inflationary cycle shrinks to the string scale at the end of inflation; here a field theoretical treatment of reheating is insufficient and one must turn instead to a stringy description. We estimate the decay rate of the inflaton and the reheat temperature for various scenarios.

  1. Modular Robotic Vehicle

    NASA Technical Reports Server (NTRS)

    Borroni-Bird, Christopher E. (Inventor); Vitale, Robert L. (Inventor); Lee, Chunhao J. (Inventor); Ambrose, Robert O. (Inventor); Bluethmann, William J. (Inventor); Junkin, Lucien Q. (Inventor); Lutz, Jonathan J. (Inventor); Guo, Raymond (Inventor); Lapp, Anthony Joseph (Inventor); Ridley, Justin S. (Inventor)

    2015-01-01

    A modular robotic vehicle includes a chassis, driver input devices, an energy storage system (ESS), a power electronics module (PEM), modular electronic assemblies (eModules) connected to the ESS via the PEM, one or more master controllers, and various embedded controllers. Each eModule includes a drive wheel containing a propulsion-braking module, and a housing containing propulsion and braking control assemblies with respective embedded propulsion and brake controllers, and a mounting bracket covering a steering control assembly with embedded steering controllers. The master controller, which is in communication with each eModule and with the driver input devices, communicates with and independently controls each eModule, by-wire, via the embedded controllers to establish a desired operating mode. Modes may include a two-wheel, four-wheel, diamond, and omni-directional steering modes as well as a park mode. A bumper may enable docking with another vehicle, with shared control over the eModules of the vehicles.

  2. Modular radiochemistry synthesis system

    SciTech Connect

    Satyamurthy, Nagichettiar; Barrio, Jorge R.; Amarasekera, Bernard; Van Dam, Michael R.; Olma, Sebastian; Williams, Dirk; Eddings, Mark; Shen, Clifton Kwang-Fu

    2016-11-01

    A modular chemical production system includes multiple modules for performing a chemical reaction, particularly of radiochemical compounds, from a remote location. One embodiment comprises a reaction vessel including a moveable heat source with the position thereof relative to the reaction vessel being controllable from a remote position. Alternatively the heat source may be fixed in location and the reaction vial is moveable into and out of the heat source. The reaction vessel has one or more sealing plugs, the positioning of which in relationship to the reaction vessel is controllable from a remote position. Also the one or more reaction vessel sealing plugs can include one or more conduits there through for delivery of reactants, gases at atmospheric or an elevated pressure, inert gases, drawing a vacuum and removal of reaction end products to and from the reaction vial, the reaction vial with sealing plug in position being operable at elevated pressures. The modular chemical production system is assembled from modules which can each include operating condition sensors and controllers configured for monitoring and controlling the individual modules and the assembled system from a remote position. Other modules include, but are not limited to a Reagent Storage and Delivery Module, a Cartridge Purification Module, a Microwave Reaction Module, an External QC/Analysis/Purification Interface Module, an Aliquotting Module, an F-18 Drying Module, a Concentration Module, a Radiation Counting Module, and a Capillary Reactor Module.

  3. Dynamics of a neural system with a multiscale architecture

    PubMed Central

    Breakspear, Michael; Stam, Cornelis J

    2005-01-01

    The architecture of the brain is characterized by a modular organization repeated across a hierarchy of spatial scales—neurons, minicolumns, cortical columns, functional brain regions, and so on. It is important to consider that the processes governing neural dynamics at any given scale are not only determined by the behaviour of other neural structures at that scale, but also by the emergent behaviour of smaller scales, and the constraining influence of activity at larger scales. In this paper, we introduce a theoretical framework for neural systems in which the dynamics are nested within a multiscale architecture. In essence, the dynamics at each scale are determined by a coupled ensemble of nonlinear oscillators, which embody the principle scale-specific neurobiological processes. The dynamics at larger scales are ‘slaved’ to the emergent behaviour of smaller scales through a coupling function that depends on a multiscale wavelet decomposition. The approach is first explicated mathematically. Numerical examples are then given to illustrate phenomena such as between-scale bifurcations, and how synchronization in small-scale structures influences the dynamics in larger structures in an intuitive manner that cannot be captured by existing modelling approaches. A framework for relating the dynamical behaviour of the system to measured observables is presented and further extensions to capture wave phenomena and mode coupling are suggested. PMID:16087448

  4. Neuromechanical principles underlying movement modularity and their implications for rehabilitation

    PubMed Central

    Ting, Lena H.; Chiel, Hillel J.; Trumbower, Randy D.; Allen, Jessica L.; McKay, J. Lucas; Hackney, Madeleine E.; Kesar, Trisha M.

    2015-01-01

    Summary Neuromechanical principles define the properties and problems that shape neural solutions for movement. Although the theoretical and experimental evidence is debated, we present arguments for consistent structures in motor patterns, i.e. motor modules, that are neuromechanical solutions for movement particular to an individual and shaped by evolutionary, developmental, and learning processes. As a consequence, motor modules may be useful in assessing sensorimotor deficits specific to an individual, and define targets for the rational development of novel rehabilitation therapies that enhance neural plasticity and sculpt motor recovery. We propose that motor module organization is disrupted and may be improved by therapy in spinal cord injury, stroke, and Parkinson’s disease. Recent studies provide insights into the yet unknown underlying neural mechanisms of motor modules, motor impairment and motor learning, and may lead to better understanding of the causal nature of modularity and its underlying neural substrates. PMID:25856485

  5. Quantum modular forms, mock modular forms, and partial theta functions

    NASA Astrophysics Data System (ADS)

    Kimport, Susanna

    Defined by Zagier in 2010, quantum modular forms have been the subject of an explosion of recent research. Many of these results are aimed at discovering examples of these functions, which are defined on the rational numbers and have "nice" modularity properties. Though the subject is in its early stages, numerous results (including Zagier's original examples) show these objects naturally arising from many areas of mathematics as limits of other modular-like functions. One such family of examples is due to Folsom, Ono, and Rhoades, who connected these new objects to partial theta functions (introduced by Rogers in 1917) and mock modular forms (about which there is a rich theory, whose origins date back to Ramanujan in 1920). In this thesis, we build off of the work of Folsom, Ono, and Rhoades by providing an infinite family of quantum modular forms of arbitrary positive half-integral weight. Further, this family of quantum modular forms "glues" mock modular forms to partial theta functions and is constructed from a so-called "universal" mock theta function by extending a method of Eichler and Zagier (originally defined for holomorphic Jacobi forms) into a non-holomorphic setting. In addition to the infinite family, we explore the weight 1/2 and 3/2 functions in more depth. For both of these weights, we are able to explicitly write down the quantum modular form, as well as the corresponding "errors to modularity," which can be shown to be Mordell integrals of specific theta functions and, as a consequence, are real-analytic functions. Finally, we turn our attention to the partial theta functions associated with these low weight examples. Berndt and Kim provide asymptotic expansions for a certain class of partial theta functions as q approaches 1 radially within the unit disk. Here, we extend this work to not only obtain asymptotic expansions for this class of functions as q approaches any root of unity, but also for a certain class of derivatives of these functions

  6. Spacecraft Modularity for Serviceable Satellites

    NASA Technical Reports Server (NTRS)

    Rossetti, Dino; Keer, Beth; Panek, John; Ritter, Bob; Reed, Benjamin; Cepollina, Frank

    2015-01-01

    Spacecraft modularity has been a topic of interest at NASA since the 1970s, when the Multi-­-Mission Modular Spacecraft (MMS) was developed at the Goddard Space Flight Center. Since then, modular concepts have been employed for a variety of spacecraft and, as in the case of the Hubble Space Telescope (HST) and the International Space Station (ISS), have been critical to the success of on-­- orbit servicing. Modularity is even more important for future robotic servicing. Robotic satellite servicing technologies under development by NASA can extend mission life and reduce lifecycle cost and risk. These are optimized when the target spacecraft is designed for servicing, including advanced modularity. This paper will explore how spacecraft design, as demonstrated by the Reconfigurable Operational spacecraft for Science and Exploration (ROSE) spacecraft architecture, and servicing technologies can be developed in parallel to fully take advantage of the promise of both.

  7. Spacecraft Modularity for Serviceable Satellites

    NASA Technical Reports Server (NTRS)

    Reed, Benjamin B.; Rossetti, Dino; Keer, Beth; Panek, John; Cepollina, Frank; Ritter, Robert

    2015-01-01

    Spacecraft modularity has been a topic of interest at NASA since the 1970s, when the Multi-Mission Modular Spacecraft (MMS) was developed at the Goddard Space Flight Center. Since then, modular concepts have been employed for a variety of spacecraft and, as in the case of the Hubble Space Telescope (HST) and the International Space Station (ISS), have been critical to the success of on-orbit servicing. Modularity is even more important for future robotic servicing. Robotic satellite servicing technologies under development by NASA can extend mission life and reduce life-cycle cost and risk. These are optimized when the target spacecraft is designed for servicing, including advanced modularity. This paper will explore how spacecraft design, as demonstrated by the Reconfigurable Operational spacecraft for Science and Exploration (ROSE) spacecraft architecture, and servicing technologies can be developed in parallel to fully take advantage of the promise of both.

  8. Mathematical Analysis and Simulations of the Neural Circuit for Locomotion in Lampreys

    NASA Astrophysics Data System (ADS)

    Zhaoping, Li; Lewis, Alex; Scarpetta, Silvia

    2004-05-01

    We analyze the dynamics of the neural circuit of the lamprey central pattern generator. This analysis provides insight into how neural interactions form oscillators and enable spontaneous oscillations in a network of damped oscillators, which were not apparent in previous simulations or abstract phase oscillator models. We also show how the different behavior regimes (characterized by phase and amplitude relationships between oscillators) of forward or backward swimming, and turning, can be controlled using the neural connection strengths and external inputs.

  9. Modular Flooring System

    NASA Technical Reports Server (NTRS)

    Thate, Robert

    2012-01-01

    The modular flooring system (MFS) was developed to provide a portable, modular, durable carpeting solution for NASA fs Robotics Alliance Project fs (RAP) outreach efforts. It was also designed to improve and replace a modular flooring system that was too heavy for safe use and transportation. The MFS was developed for use as the flooring for various robotics competitions that RAP utilizes to meet its mission goals. One of these competitions, the FIRST Robotics Competition (FRC), currently uses two massive rolls of broadloom carpet for the foundation of the arena in which the robots are contained during the competition. The area of the arena is approximately 30 by 72 ft (approximately 9 by 22 m). This carpet is very cumbersome and requires large-capacity vehicles, and handling equipment and personnel to transport and deploy. The broadloom carpet sustains severe abuse from the robots during a regular three-day competition, and as a result, the carpet is not used again for competition. Similarly, broadloom carpets used for trade shows at convention centers around the world are typically discarded after only one use. This innovation provides a green solution to this wasteful practice. Each of the flooring modules in the previous system weighed 44 lb (.20 kg). The improvements in the overall design of the system reduce the weight of each module by approximately 22 lb (.10 kg) (50 %), and utilize an improved "module-to-module" connection method that is superior to the previous system. The MFS comprises 4-by-4-ft (.1.2-by- 1.2-m) carpet module assemblies that utilize commercially available carpet tiles that are bonded to a lightweight substrate. The substrate surface opposite from the carpeted surface has a module-to-module connecting interface that allows for the modules to be connected, one to the other, as the modules are constructed. This connection is hidden underneath the modules, creating a smooth, co-planar flooring surface. The modules are stacked and strapped

  10. A neural jet charge tagger for the measurement of the B$0\\atop{s}$-$\\bar{B}$$0\\atop{s}$ oscillation frequency at CDF

    SciTech Connect

    Lecci, Claudia

    2005-07-01

    A Jet Charge Tagger algorithm for b-flavour tagging for the measurement of Δms at CDF has been presented. The tagger is based on a b-track probability variable and a b-jet probability variable, both obtained by combining the information available in b$\\bar{b}$ events with a Neural Network. The tagging power measured on data is 0.917 ± 0.031% e+SVT sample; 0.938 ± 0.029% μ+SVT sample which is ~30% larger than the cut based Jet Charge Tagger employed for the B$0\\atop{s}$ mixing analysis presented by CDF at the Winter Conferences 2005. The improved power of the tagger is due to the selection of the b-jet with a Neural Network variable, which uses correlated jet variables in an optimal way. The development of the track and jet probability has profited from studies performed on simulated events, which allowed to understand better the features of b$\\bar{b}$ events. For the first time in the CDF B group a Monte Carlo sample comprising flavour creation and additional b$\\bar{b}$ production processes has been examined and compared to Run II data. It has been demonstrated that a Monte Carlo sample with only flavour creation b$\\bar{b}$ production processes is not sufficient to describe b$\\bar{b}$ data collected at CDF. The sample with additional processes introduced in this thesis is thus essential for tagging studies. Although the event description is satisfactory, the flavour information in the Monte Carlo sample differs with respect to data. This difference needs to be clarified by further studies. In addition, the track and the jet probabilities are the first official tools based on Neural Networks for B-Physics at CDF. They have proven that the simulation is understood to such an advanced level that Neural Networks can be employed. Further work is going on in this direction: a Soft Electron and a Soft Muon Tagger based on Neural Networks are under development as of now. Several possible tagger setups have been studied and the Jet Charge Tagger reached

  11. From neural oscillations to reasoning ability: Simulating the effect of the theta-to-gamma cycle length ratio on individual scores in a figural analogy test.

    PubMed

    Chuderski, Adam; Andrelczyk, Krzysztof

    2015-02-01

    Several existing computational models of working memory (WM) have predicted a positive relationship (later confirmed empirically) between WM capacity and the individual ratio of theta to gamma oscillatory band lengths. These models assume that each gamma cycle represents one WM object (e.g., a binding of its features), whereas the theta cycle integrates such objects into the maintained list. As WM capacity strongly predicts reasoning, it might be expected that this ratio also predicts performance in reasoning tasks. However, no computational model has yet explained how the differences in the theta-to-gamma ratio found among adult individuals might contribute to their scores on a reasoning test. Here, we propose a novel model of how WM capacity constraints figural analogical reasoning, aimed at explaining inter-individual differences in reasoning scores in terms of the characteristics of oscillatory patterns in the brain. In the model, the gamma cycle encodes the bindings between objects/features and the roles they play in the relations processed. Asynchrony between consecutive gamma cycles results from lateral inhibition between oscillating bindings. Computer simulations showed that achieving the highest WM capacity required reaching the optimal level of inhibition. When too strong, this inhibition eliminated some bindings from WM, whereas, when inhibition was too weak, the bindings became unstable and fell apart or became improperly grouped. The model aptly replicated several empirical effects and the distribution of individual scores, as well as the patterns of correlations found in the 100-people sample attempting the same reasoning task. Most importantly, the model's reasoning performance strongly depended on its theta-to-gamma ratio in same way as the performance of human participants depended on their WM capacity. The data suggest that proper regulation of oscillations in the theta and gamma bands may be crucial for both high WM capacity and effective complex

  12. Modular arctic structures system

    SciTech Connect

    Reusswig, G. H.

    1984-12-04

    A modular and floatable offshore exploration and production platform system for use in shallow arctic waters is disclosed. A concrete base member is floated to the exploration or production site, and ballated into a predredged cavity. The cavity and base are sized to provide a stable horizontal base 30 feet below the mean water/ice plane. An exploration or production platform having a massive steel base is floated to the site and ballasted into position on the base. Together, the platform, base and ballast provide a massive gravity structure that is capable of resisting large ice and wave forces that impinge on the structure. The steel platform has a sloping hourglass profile to deflect horizontal ice loads vertically, and convert the horizontal load to a vertical tensile stress, which assists in breaking the ice as it advances toward the structure.

  13. Modular small hydro configuration

    NASA Astrophysics Data System (ADS)

    1981-09-01

    Smaller sites (those under 750 kilowatts) which previously were not attractive to develop using equipment intended for application at larger scale sites, were the focal point in the conception of a system which utilizes standard industrial components which are generally available within short procurement times. Such components were integrated into a development scheme for sites having 20 feet to 150 feet of head. The modular small hydro configuration maximizes the use of available components and minimizes modification of existing civil works. A key aspect of the development concept is the use of a vertical turbine multistage pump, used in the reverse mode as a hydraulic turbine. The configuration allows for automated operation and control of the hydroelectric facilities with sufficient flexibility for inclusion of potential hydroelectric sites into dispersed storage and generation (DSG) utility grid systems.

  14. Modular error embedding

    DOEpatents

    Sandford, II, Maxwell T.; Handel, Theodore G.; Ettinger, J. Mark

    1999-01-01

    A method of embedding auxiliary information into the digital representation of host data containing noise in the low-order bits. The method applies to digital data representing analog signals, for example digital images. The method reduces the error introduced by other methods that replace the low-order bits with auxiliary information. By a substantially reverse process, the embedded auxiliary data can be retrieved easily by an authorized user through use of a digital key. The modular error embedding method includes a process to permute the order in which the host data values are processed. The method doubles the amount of auxiliary information that can be added to host data values, in comparison with bit-replacement methods for high bit-rate coding. The invention preserves human perception of the meaning and content of the host data, permitting the addition of auxiliary data in the amount of 50% or greater of the original host data.

  15. Modular Optical PDV System

    SciTech Connect

    Araceli Rutkowski, David Esquibel

    2008-12-11

    A modular optical photon Doppler velocimetry (PDV) detector system has been developed by using readily available optical components with a 20-GHz Miteq optical detector into eight channels of single-wide modules integrated into a 3U rack unit (1U = 1.75 inches) with a common power supply. Optical fibers were precisely trimmed, welded, and timed within each unit. This system has been used to collect dynamic velocity data on various physics experiments. An optical power meter displays the laser input power to the module and optical power at the detector. An adjustable micro-electromechanical system (MEMS) optical attenuator is used to adjust the amount of unshifted light entering the detector. Front panel LEDs show the presence of power to the module. A fully loaded chassis with eight channels consumes 45 watts of power. Each chassis requires 1U spacing above and below for heat management. Modules can be easily replaced.

  16. Modular weapon control unit

    SciTech Connect

    Boccabella, M.F.; McGovney, G.N.

    1997-01-01

    The goal of the Modular Weapon Control Unit (MWCU) program was to design and develop a reconfigurable weapon controller (programmer/sequencer) that can be adapted to different weapon systems based on the particular requirements for that system. Programmers from previous systems are conceptually the same and perform similar tasks. Because of this commonality and the amount of re-engineering necessary with the advent of every new design, the idea of a modular, adaptable system has emerged. Also, the controller can be used in more than one application for a specific weapon system. Functionality has been divided into a Processor Module (PM) and an Input/Output Module (IOM). The PM will handle all operations that require calculations, memory, and timing. The IOM will handle interfaces to the rest of the system, input level shifting, output drive capability, and detection of interrupt conditions. Configuration flexibility is achieved in two ways. First, the operation of the PM is determined by a surface mount Read-Only Memory (ROM). Other surface-mount components can be added or neglected as necessary for functionality. Second, IOMs consist of configurable input buffers, configurable output drivers, and configurable interrupt generation. Further, these modules can be added singly or in groups to a Processor Module to achieve the required I/O configuration. The culmination of this LDRD was the building of both Processor Module and Input/Output Module. The MWCU was chosen as a test system to evaluate Low-Temperature Co-fired Ceramic (LTCC) technology, desirable for high component density and good thermal characteristics.

  17. Spacecraft Modularity for Serviceable Satellites

    NASA Technical Reports Server (NTRS)

    Rossetti, Dino; Keer, Beth; Panek, John; Reed, Benjamin; Cepollina, Frank; Ritter, Robert

    2015-01-01

    Satellite servicing has been a proven capability of NASA since the first servicing missions in the 1980s with astronauts on the space shuttle. This capability enabled the on-orbit assembly of the International Space Station (ISS) and saved the Hubble Space Telescope (HST) mission following the discovery of the flawed primary mirror. The effectiveness and scope of servicing opportunities, especially using robotic servicers, is a function of how cooperative a spacecraft is. In this paper, modularity will be presented as a critical design aspect for a spacecraft that is cooperative from a servicing perspective. Different features of modularity are discussed using examples from HST and the Multimission Modular Spacecraft (MMS) program from the 1980s and 1990s. The benefits of modularity will be presented including those directly related to servicing and those outside of servicing including reduced costs and increased flexibility. The new Reconfigurable Operational spacecraft for Science and Exploration (ROSE) concept is introduced as an affordable implementation of modularity that provides cost savings and flexibility. Key aspects of the ROSE architecture are discussed such as the module design and the distributed avionics architecture. The ROSE concept builds on the experience from MMS and due to its modularity, would be highly suitable as a future client for on-orbit servicing.

  18. Power oscillator

    DOEpatents

    Gitsevich, Aleksandr

    2001-01-01

    An oscillator includes an amplifier having an input and an output, and an impedance transformation network connected between the input of the amplifier and the output of the amplifier, wherein the impedance transformation network is configured to provide suitable positive feedback from the output of the amplifier to the input of the amplifier to initiate and sustain an oscillating condition, and wherein the impedance transformation network is configured to protect the input of the amplifier from a destructive feedback signal. One example of the oscillator is a single active element device capable of providing over 70 watts of power at over 70% efficiency. Various control circuits may be employed to match the driving frequency of the oscillator to a plurality of tuning states of the lamp.

  19. Raindrop oscillations

    NASA Technical Reports Server (NTRS)

    Beard, K. V.

    1982-01-01

    A model of the change in shape of a raindrop is presented. Raindrops measured by two orthogonal cameras were classified by shape and orientation to determine the nature of the oscillation. A physical model based on potential energy was then developed to study the amplitude variation of oscillating drops. The model results show that oscillations occur about the equilibrium axis ratio, but the time average axis ratio if significantly more spherical for large amplitudes because of asymmetry in the surface potential energy. A generalization of the model to oscillations produced by turbulence yields average axis ratios that are consistent with the camera measurements. The model results for average axis ratios were applied to rainfall studies with a dual polarized radar.

  20. The Modular Adaptive Ribosome.

    PubMed

    Yadav, Anupama; Radhakrishnan, Aparna; Panda, Anshuman; Singh, Amartya; Sinha, Himanshu; Bhanot, Gyan

    2016-01-01

    The ribosome is an ancient machine, performing the same function across organisms. Although functionally unitary, recent experiments suggest specialized roles for some ribosomal proteins. Our central thesis is that ribosomal proteins function in a modular fashion to decode genetic information in a context dependent manner. We show through large data analyses that although many ribosomal proteins are essential with consistent effect on growth in different conditions in yeast and similar expression across cell and tissue types in mice and humans, some ribosomal proteins are used in an environment specific manner. The latter set of variable ribosomal proteins further function in a coordinated manner forming modules, which are adapted to different environmental cues in different organisms. We show that these environment specific modules of ribosomal proteins in yeast have differential genetic interactions with other pathways and their 5'UTRs show differential signatures of selection in yeast strains, presumably to facilitate adaptation. Similarly, we show that in higher metazoans such as mice and humans, different modules of ribosomal proteins are expressed in different cell types and tissues. A clear example is nervous tissue that uses a ribosomal protein module distinct from the rest of the tissues in both mice and humans. Our results suggest a novel stratification of ribosomal proteins that could have played a role in adaptation, presumably to optimize translation for adaptation to diverse ecological niches and tissue microenvironments.

  1. The Modular Adaptive Ribosome

    PubMed Central

    Yadav, Anupama; Radhakrishnan, Aparna; Panda, Anshuman; Singh, Amartya; Sinha, Himanshu; Bhanot, Gyan

    2016-01-01

    The ribosome is an ancient machine, performing the same function across organisms. Although functionally unitary, recent experiments suggest specialized roles for some ribosomal proteins. Our central thesis is that ribosomal proteins function in a modular fashion to decode genetic information in a context dependent manner. We show through large data analyses that although many ribosomal proteins are essential with consistent effect on growth in different conditions in yeast and similar expression across cell and tissue types in mice and humans, some ribosomal proteins are used in an environment specific manner. The latter set of variable ribosomal proteins further function in a coordinated manner forming modules, which are adapted to different environmental cues in different organisms. We show that these environment specific modules of ribosomal proteins in yeast have differential genetic interactions with other pathways and their 5’UTRs show differential signatures of selection in yeast strains, presumably to facilitate adaptation. Similarly, we show that in higher metazoans such as mice and humans, different modules of ribosomal proteins are expressed in different cell types and tissues. A clear example is nervous tissue that uses a ribosomal protein module distinct from the rest of the tissues in both mice and humans. Our results suggest a novel stratification of ribosomal proteins that could have played a role in adaptation, presumably to optimize translation for adaptation to diverse ecological niches and tissue microenvironments. PMID:27812193

  2. Modular Approach to Spintronics.

    PubMed

    Camsari, Kerem Yunus; Ganguly, Samiran; Datta, Supriyo

    2015-06-11

    There has been enormous progress in the last two decades, effectively combining spintronics and magnetics into a powerful force that is shaping the field of memory devices. New materials and phenomena continue to be discovered at an impressive rate, providing an ever-increasing set of building blocks that could be exploited in designing transistor-like functional devices of the future. The objective of this paper is to provide a quantitative foundation for this building block approach, so that new discoveries can be integrated into functional device concepts, quickly analyzed and critically evaluated. Through careful benchmarking against available theory and experiment we establish a set of elemental modules representing diverse materials and phenomena. These elemental modules can be integrated seamlessly to model composite devices involving both spintronic and nanomagnetic phenomena. We envision the library of modules to evolve both by incorporating new modules and by improving existing modules as the field progresses. The primary contribution of this paper is to establish the ground rules or protocols for a modular approach that can build a lasting bridge between materials scientists and circuit designers in the field of spintronics and nanomagnetics.

  3. Modular Isotopic Thermoelectric Generator

    SciTech Connect

    Schock, Alfred

    1981-04-03

    Advanced RTG concepts utilizing improved thermoelectric materials and converter concepts are under study at Fairchild for DOE. The design described here is based on DOE's newly developed radioisotope heat source, and on an improved silicon-germanium material and a multicouple converter module under development at Syncal. Fairchild's assignment was to combine the above into an attractive power system for use in space, and to assess the specific power and other attributes of that design. The resultant design is highly modular, consisting of standard RTG slices, each producing ~24 watts at the desired output voltage of 28 volt. Thus, the design could be adapted to various space missions over a wide range of power levels, with little or no redesign. Each RTG slice consists of a 250-watt heat source module, eight multicouple thermoelectric modules, and standard sections of insulator, housing, radiator fins, and electrical circuit. The design makes it possible to check each thermoelectric module for electrical performance, thermal contact, leaktightness, and performance stability, after the generator is fully assembled; and to replace any deficient modules without disassembling the generator or perturbing the others. The RTG end sections provide the spring-loaded supports required to hold the free-standing heat source stack together during launch vibration. Details analysis indicates that the design offers a substantial improvement in specific power over the present generator of RTGs, using the same heat source modules. There are three copies in the file.

  4. Modular Approach to Spintronics

    PubMed Central

    Camsari, Kerem Yunus; Ganguly, Samiran; Datta, Supriyo

    2015-01-01

    There has been enormous progress in the last two decades, effectively combining spintronics and magnetics into a powerful force that is shaping the field of memory devices. New materials and phenomena continue to be discovered at an impressive rate, providing an ever-increasing set of building blocks that could be exploited in designing transistor-like functional devices of the future. The objective of this paper is to provide a quantitative foundation for this building block approach, so that new discoveries can be integrated into functional device concepts, quickly analyzed and critically evaluated. Through careful benchmarking against available theory and experiment we establish a set of elemental modules representing diverse materials and phenomena. These elemental modules can be integrated seamlessly to model composite devices involving both spintronic and nanomagnetic phenomena. We envision the library of modules to evolve both by incorporating new modules and by improving existing modules as the field progresses. The primary contribution of this paper is to establish the ground rules or protocols for a modular approach that can build a lasting bridge between materials scientists and circuit designers in the field of spintronics and nanomagnetics. PMID:26066079

  5. Assembly of a Neural Analog Computer. Phase 2

    DTIC Science & Technology

    1994-02-15

    Neural Computer . Analog VLSI Implementation of Neural Systems, IEEE Carver Mead, Mohammed Ismail, Eds., Kiluwer Academic Publishers, Boston, MA. 1989... Analog Neural Compuer With Modular Architecture for Real-Time Dynamic Computations . IEEE Transactions On Solid State Circuits V 27 82.-92 1992. 9...D FINAL REPORT PHASE II ONR CONTRACT # N00014-91-c-0204 ASSEMBLY OF A NEURAL ANALOG COMPUTER This documen: he- tbeen approved fox public reiease and

  6. Galactic oscillations

    NASA Technical Reports Server (NTRS)

    Miller, R. H.; Smith, B. F.

    1994-01-01

    A stable galaxy, if excited above its ground state, oscillates about that ground state. If it is resonably robust, it can support oscillations of large amplitude. Normal mode oscillations, with surprisingly large amplitudes, have been seen in numerical experiments. Observational evidence shows that real galaxies also oscillate. Galaxies ring like a bell in the experiments, and ringing continues undamped long after initial transients have died out. Their total kinetic energy oscillates with an amplitude as large as 10% of the mean. A fundamental mode dominates. It is homologous expansion/contraction of the entire galaxy (no nodes). Inward or outward velocities due to this mode are sufficiently large in the outer reaches of a galaxy to account for kinematic warps in observed velocity fields. A second spherically symmetrical mode has one node and is important near the center of the galaxy. It may be the driving force behind bulges in spiral galaxies. Two other normal modes have been identified as well. This appears to be the first experimental demonstration of normal mode oscillations within stable galaxy models.

  7. Modular Stirling Radioisotope Generator

    NASA Technical Reports Server (NTRS)

    Schmitz, Paul C.; Mason, Lee S.; Schifer, Nicholas A.

    2015-01-01

    High efficiency radioisotope power generators will play an important role in future NASA space exploration missions. Stirling Radioisotope Generators (SRG) have been identified as a candidate generator technology capable of providing mission designers with an efficient, high specific power electrical generator. SRGs high conversion efficiency has the potential to extend the limited Pu-238 supply when compared with current Radioisotope Thermoelectric Generators (RTG). Due to budgetary constraints, the Advanced Stirling Radioisotope Generator (ASRG) was canceled in the fall of 2013. Over the past year a joint study by NASA and DOE called the Nuclear Power Assessment Study (NPAS) recommended that Stirling technologies continue to be explored. During the mission studies of the NPAS, spare SRGs were sometimes required to meet mission power system reliability requirements. This led to an additional mass penalty and increased isotope consumption levied on certain SRG-based missions. In an attempt to remove the spare power system, a new generator architecture is considered which could increase the reliability of a Stirling generator and provide a more fault-tolerant power system. This new generator called the Modular Stirling Radioisotope Generator (MSRG) employs multiple parallel Stirling convertor/controller strings, all of which share the heat from the General Purpose Heat Source (GPHS) modules. For this design, generators utilizing one to eight GPHS modules were analyzed, which provide about 50 to 450 watts DC to the spacecraft, respectively. Four Stirling convertors are arranged around each GPHS module resulting in from 4 to 32 Stirling/controller strings. The convertors are balanced either individually or in pairs, and are radiatively coupled to the GPHS modules. Heat is rejected through the housing/radiator which is similar in construction to the ASRG. Mass and power analysis for these systems indicate that specific power may be slightly lower than the ASRG and

  8. Modular Stirling Radioisotope Generator

    NASA Technical Reports Server (NTRS)

    Schmitz, Paul C.; Mason, Lee S.; Schifer, Nicholas A.

    2016-01-01

    High-efficiency radioisotope power generators will play an important role in future NASA space exploration missions. Stirling Radioisotope Generators (SRGs) have been identified as a candidate generator technology capable of providing mission designers with an efficient, high-specific-power electrical generator. SRGs high conversion efficiency has the potential to extend the limited Pu-238 supply when compared with current Radioisotope Thermoelectric Generators (RTGs). Due to budgetary constraints, the Advanced Stirling Radioisotope Generator (ASRG) was canceled in the fall of 2013. Over the past year a joint study by NASA and the Department of Energy (DOE) called the Nuclear Power Assessment Study (NPAS) recommended that Stirling technologies continue to be explored. During the mission studies of the NPAS, spare SRGs were sometimes required to meet mission power system reliability requirements. This led to an additional mass penalty and increased isotope consumption levied on certain SRG-based missions. In an attempt to remove the spare power system, a new generator architecture is considered, which could increase the reliability of a Stirling generator and provide a more fault-tolerant power system. This new generator called the Modular Stirling Radioisotope Generator (MSRG) employs multiple parallel Stirling convertor/controller strings, all of which share the heat from the General Purpose Heat Source (GPHS) modules. For this design, generators utilizing one to eight GPHS modules were analyzed, which provided about 50 to 450 W of direct current (DC) to the spacecraft, respectively. Four Stirling convertors are arranged around each GPHS module resulting in from 4 to 32 Stirling/controller strings. The convertors are balanced either individually or in pairs, and are radiatively coupled to the GPHS modules. Heat is rejected through the housing/radiator, which is similar in construction to the ASRG. Mass and power analysis for these systems indicate that specific

  9. Modular Power Standard for Space Explorations Missions

    NASA Technical Reports Server (NTRS)

    Oeftering, Richard C.; Gardner, Brent G.

    2016-01-01

    Future human space exploration will most likely be composed of assemblies of multiple modular spacecraft elements with interconnected electrical power systems. An electrical system composed of a standardized set modular building blocks provides significant development, integration, and operational cost advantages. The modular approach can also provide the flexibility to configure power systems to meet the mission needs. A primary goal of the Advanced Exploration Systems (AES) Modular Power System (AMPS) project is to establish a Modular Power Standard that is needed to realize these benefits. This paper is intended to give the space exploration community a "first look" at the evolving Modular Power Standard and invite their comments and technical contributions.

  10. Eigenvalue Spectra of Modular Networks

    NASA Astrophysics Data System (ADS)

    Peixoto, Tiago P.

    2013-08-01

    A large variety of dynamical processes that take place on networks can be expressed in terms of the spectral properties of some linear operator which reflects how the dynamical rules depend on the network topology. Often, such spectral features are theoretically obtained by considering only local node properties, such as degree distributions. Many networks, however, possess large-scale modular structures that can drastically influence their spectral characteristics and which are neglected in such simplified descriptions. Here, we obtain in a unified fashion the spectrum of a large family of operators, including the adjacency, Laplacian, and normalized Laplacian matrices, for networks with generic modular structure, in the limit of large degrees. We focus on the conditions necessary for the merging of the isolated eigenvalues with the continuous band of the spectrum, after which the planted modular structure can no longer be easily detected by spectral methods. This is a crucial transition point which determines when a modular structure is strong enough to affect a given dynamical process. We show that this transition happens in general at different points for the different matrices, and hence the detectability threshold can vary significantly, depending on the operator chosen. Equivalently, the sensitivity to the modular structure of the different dynamical processes associated with each matrix will be different, given the same large-scale structure present in the network. Furthermore, we show that, with the exception of the Laplacian matrix, the different transitions coalesce into the same point for the special case where the modules are homogeneous but separate otherwise.

  11. Hemodynamic responses can modulate the brain oscillations in low frequency

    NASA Astrophysics Data System (ADS)

    Lu, Feng-Mei; Wang, Yi-Feng; Yuan, Zhen

    2016-03-01

    Previous studies have showed that the steady-state responses were able to be used as an effective index for modulating the neural oscillations in the high frequency ranges (> 1 Hz). However, the neural oscillations in low frequency ranges (<1 Hz) remain unknown. In this study, a series of fNIRS experimental tests were conducted to validate if the low frequency bands (0.1 Hz - 0.8 Hz) steady-state hemoglobin responses (SSHbRs) could be evoked and modulate the neural oscillation during a serial reaction time (SRT) task.

  12. Product modular design incorporating preventive maintenance issues

    NASA Astrophysics Data System (ADS)

    Gao, Yicong; Feng, Yixiong; Tan, Jianrong

    2016-03-01

    Traditional modular design methods lead to product maintenance problems, because the module form of a system is created according to either the function requirements or the manufacturing considerations. For solving these problems, a new modular design method is proposed with the considerations of not only the traditional function related attributes, but also the maintenance related ones. First, modularity parameters and modularity scenarios for product modularity are defined. Then the reliability and economic assessment models of product modularity strategies are formulated with the introduction of the effective working age of modules. A mathematical model used to evaluate the difference among the modules of the product so that the optimal module of the product can be established. After that, a multi-objective optimization problem based on metrics for preventive maintenance interval different degrees and preventive maintenance economics is formulated for modular optimization. Multi-objective GA is utilized to rapidly approximate the Pareto set of optimal modularity strategy trade-offs between preventive maintenance cost and preventive maintenance interval difference degree. Finally, a coordinate CNC boring machine is adopted to depict the process of product modularity. In addition, two factorial design experiments based on the modularity parameters are constructed and analyzed. These experiments investigate the impacts of these parameters on the optimal modularity strategies and the structure of module. The research proposes a new modular design method, which may help to improve the maintainability of product in modular design.

  13. Modular process modeling for OPC

    NASA Astrophysics Data System (ADS)

    Keck, M. C.; Bodendorf, C.; Schmidtling, T.; Schlief, R.; Wildfeuer, R.; Zumpe, S.; Niehoff, M.

    2007-03-01

    Modular OPC modeling, describing mask, optics, resist and etch processes separately is an approach to keep efforts for OPC manageable. By exchanging single modules of a modular OPC model, a fast response to process changes during process development is possible. At the same time efforts can be reduced, since only single modular process steps have to be re-characterized as input for OPC modeling as the process is adjusted and optimized. Commercially available OPC tools for full chip processing typically make use of semi-empirical models. The goal of our work is to investigate to what extent these OPC tools can be applied for modeling of single process steps as separate modules. For an advanced gate level process we analyze the modeling accuracy over different process conditions (focus and dose) when combining models for each process step - optics, resist and etch - for differing single processes to a model describing the total process.

  14. Modular assembly of optical nanocircuits.

    PubMed

    Shi, Jinwei; Monticone, Francesco; Elias, Sarah; Wu, Yanwen; Ratchford, Daniel; Li, Xiaoqin; Alù, Andrea

    2014-05-29

    A key element enabling the microelectronic technology advances of the past decades has been the conceptualization of complex circuits with versatile functionalities as being composed of the proper combination of basic 'lumped' circuit elements (for example, inductors and capacitors). In contrast, modern nanophotonic systems are still far from a similar level of sophistication, partially because of the lack of modularization of their response in terms of basic building blocks. Here we demonstrate the design, assembly and characterization of relatively complex photonic nanocircuits by accurately positioning a number of metallic and dielectric nanoparticles acting as modular lumped elements. The nanoparticle clusters produce the desired spectral response described by simple circuit rules and are shown to be dynamically reconfigurable by modifying the direction or polarization of impinging signals. Our work represents an important step towards extending the powerful modular design tools of electronic circuits into nanophotonic systems.

  15. Modular multichannel surface plasmon spectrometer

    NASA Astrophysics Data System (ADS)

    Neuert, G.; Kufer, S.; Benoit, M.; Gaub, H. E.

    2005-05-01

    We have developed a modular multichannel surface plasmon resonance (SPR) spectrometer on the basis of a commercially available hybrid sensor chip. Due to its modularity this inexpensive and easy to use setup can readily be adapted to different experimental environments. High temperature stability is achieved through efficient thermal coupling of individual SPR units. With standard systems the performance of the multichannel instrument was evaluated. The absorption kinetics of a cysteamine monolayer, as well as the concentration dependence of the specific receptor-ligand interaction between biotin and streptavidin was measured.

  16. Modular multivariable control improves hydrocracking

    SciTech Connect

    Chia, T.L.; Lefkowitz, I.; Tamas, P.D.

    1996-10-01

    Modular multivariable control (MMC), a system of interconnected, single process variable controllers, can be a user-friendly, reliable and cost-effective alternative to centralized, large-scale multivariable control packages. MMC properties and features derive directly from the properties of the coordinated controller which, in turn, is based on internal model control technology. MMC was applied to a hydrocracking unit involving two process variables and three controller outputs. The paper describes modular multivariable control, MMC properties, tuning considerations, application at the DCS level, constraints handling, and process application and results.

  17. Inherent controllability in modular ALMRs

    SciTech Connect

    Sackett, J.I.; Sevy, R.H.; Wei, T.Y.C.

    1989-01-01

    As part of recent development efforts on advanced reactor designs ANL has proposed the IFR (Integral Fast Reactor) concept. The IFR concept is currently being applied to modular sized reactors which would be built in multiple power paks together with an integrated fuel cycle facility. It has been amply demonstrated that the concept as applied to the modular designs has significant advantages in regard to ATWS transients. Attention is now being focussed on determining whether or not those advantages deriving from the traits of the IFR can be translated to the operational/DBA (design basis accident) class of transients. 5 refs., 3 figs., 3 tabs.

  18. Modular Firewalls for Storage Areas

    NASA Technical Reports Server (NTRS)

    Fedor, O. H.; Owens, L. J.

    1986-01-01

    Giant honeycomb structures assembled in modular units. Flammable materials stored in cells. Walls insulated with firebrick to prevent spread of fire among cells. Portable, modular barrier withstands heat of combustion for limited time and confines combustion products horizontally to prevent fire from spreading. Barrier absorbs heat energy by ablation and not meant to be reused. Designed to keep fires from spreading among segments of solid rocket propellant in storage, barrier erected between storage units of other flammable or explosive materials; tanks of petroleum or liquid natural gas. Barrier adequate for most industrial purposes.

  19. Temporal structure of neuronal population oscillations with empirical model decomposition

    NASA Astrophysics Data System (ADS)

    Li, Xiaoli

    2006-08-01

    Frequency analysis of neuronal oscillation is very important for understanding the neural information processing and mechanism of disorder in the brain. This Letter addresses a new method to analyze the neuronal population oscillations with empirical mode decomposition (EMD). Following EMD of neuronal oscillation, a series of intrinsic mode functions (IMFs) are obtained, then Hilbert transform of IMFs can be used to extract the instantaneous time frequency structure of neuronal oscillation. The method is applied to analyze the neuronal oscillation in the hippocampus of epileptic rats in vivo, the results show the neuronal oscillations have different descriptions during the pre-ictal, seizure onset and ictal periods of the epileptic EEG at the different frequency band. This new method is very helpful to provide a view for the temporal structure of neural oscillation.

  20. Modular structure of functional networks in olfactory memory.

    PubMed

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

    2014-07-15

    ) accounted for most of the observed differences in signed modularity. Taken together, our results provided some evidence that the neural networks involved in odor recognition memory are organized into modules and that these modular partitions are linked to behavioral performance and individual strategies. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. Modular synthetic inverters from zinc finger proteins and small RNAs

    DOE PAGES

    Hsia, Justin; Holtz, William J.; Maharbiz, Michel M.; ...

    2016-02-17

    Synthetic zinc finger proteins (ZFPs) can be created to target promoter DNA sequences, repressing transcription. The binding of small RNA (sRNA) to ZFP mRNA creates an ultrasensitive response to generate higher effective Hill coefficients. Here we combined three “off the shelf” ZFPs and three sRNAs to create new modular inverters in E. coli and quantify their behavior using induction fold. We found a general ordering of the effects of the ZFPs and sRNAs on induction fold that mostly held true when combining these parts. We then attempted to construct a ring oscillator using our new inverters. In conclusion, our chosenmore » parts performed insufficiently to create oscillations, but we include future directions for improvement upon our work presented here.« less

  2. Modular synthetic inverters from zinc finger proteins and small RNAs

    SciTech Connect

    Hsia, Justin; Holtz, William J.; Maharbiz, Michel M.; Arcak, Murat; Keasling, Jay D.; Rao, Christopher V.

    2016-02-17

    Synthetic zinc finger proteins (ZFPs) can be created to target promoter DNA sequences, repressing transcription. The binding of small RNA (sRNA) to ZFP mRNA creates an ultrasensitive response to generate higher effective Hill coefficients. Here we combined three “off the shelf” ZFPs and three sRNAs to create new modular inverters in E. coli and quantify their behavior using induction fold. We found a general ordering of the effects of the ZFPs and sRNAs on induction fold that mostly held true when combining these parts. We then attempted to construct a ring oscillator using our new inverters. In conclusion, our chosen parts performed insufficiently to create oscillations, but we include future directions for improvement upon our work presented here.

  3. Safety measures implemented for modular functioning electrical stimulators.

    PubMed

    Chen, Chiun-Fan; Lai, Jin-Shin; Chen, Shih-Wei; Lin, Yin-Tsong; Kuo, Te-Son

    2009-01-01

    The modular architecture allows for greater flexibility in the building of neural prostheses with a variety of channels but may result in unpredictable accidents under circumstances such as sensor displacements, improper coordination of the connected modules and malfunction of any individual module. A novel fail-safe interface is offered as a solution that puts in place the necessary safety measures when building a module based functional electrical stimulator. By using a single reference line in the interconnecting bus of the modules, various commands would immediately be directed to each module so that proper actions may be taken.

  4. Modularity in Cognition: Framing the Debate

    ERIC Educational Resources Information Center

    Barrett, H. Clark; Kurzban, Robert

    2006-01-01

    Modularity has been the subject of intense debate in the cognitive sciences for more than 2 decades. In some cases, misunderstandings have impeded conceptual progress. Here the authors identify arguments about modularity that either have been abandoned or were never held by proponents of modular views of the mind. The authors review arguments that…

  5. 47 CFR 15.212 - Modular transmitters.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 47 Telecommunication 1 2014-10-01 2014-10-01 false Modular transmitters. 15.212 Section 15.212 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL RADIO FREQUENCY DEVICES Intentional Radiators § 15.212 Modular transmitters. (a) Single modular transmitters consist of a completely...

  6. 47 CFR 15.212 - Modular transmitters.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 1 2010-10-01 2010-10-01 false Modular transmitters. 15.212 Section 15.212 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL RADIO FREQUENCY DEVICES Intentional Radiators § 15.212 Modular transmitters. (a) Single modular transmitters consist of a completely...

  7. 47 CFR 15.212 - Modular transmitters.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 47 Telecommunication 1 2013-10-01 2013-10-01 false Modular transmitters. 15.212 Section 15.212 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL RADIO FREQUENCY DEVICES Intentional Radiators § 15.212 Modular transmitters. (a) Single modular transmitters consist of a completely...

  8. 47 CFR 15.212 - Modular transmitters.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 1 2011-10-01 2011-10-01 false Modular transmitters. 15.212 Section 15.212 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL RADIO FREQUENCY DEVICES Intentional Radiators § 15.212 Modular transmitters. (a) Single modular transmitters consist of a completely...

  9. 48 CFR 3417.70 - Modular contracting.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 48 Federal Acquisition Regulations System 7 2013-10-01 2012-10-01 true Modular contracting. 3417... REGULATION CONTRACTING METHODS AND CONTRACT TYPES SPECIAL CONTRACTING METHODS Modular Contracting 3417.70 Modular contracting. (a) FSA—May incrementally conduct successive procurements of modules of overall...

  10. The Modular Mind and Intrapersonal Communication Processes.

    ERIC Educational Resources Information Center

    Stacks, Don W.

    Based on a prior model on modularity of the brain, a new modular model of intrapersonal communication was developed which focuses on brain processing, encompassing both the structures and the functions of those structures in the creation of messages. The modular mind is a bio-social model of communication which presupposes a relationship between…

  11. Evolution and the Modularity of Mindreading.

    ERIC Educational Resources Information Center

    Moore, Chris

    1996-01-01

    Reviews Baron-Cohen's study of autism and an explanatory theory called modularity of mindreading, which proposed a domain-specific modular psychological model based on evolutionary, developmental, psychopathological, and neurobiological considerations. Enumerates problems with the modularity approach and emphasized the evolution of domain general…

  12. Modular Instruction Under Restricted Conditions.

    ERIC Educational Resources Information Center

    Utomo, Tjipto; Ruijter, Kees

    1984-01-01

    Describes the evaluation and reconstruction of a transport phenomena course given at the Bandung Institute of Technology which had a 70 percent failure rate. Discusses the teacher-paced modular instruction technique designed to replace the original course material and its results in terms of student performance over a three-year period. (JM)

  13. Rapidly Deployed Modular Telemetry System

    NASA Technical Reports Server (NTRS)

    Varnavas, Kosta A. (Inventor); Sims, William Herbert, III (Inventor)

    2013-01-01

    The present invention is a telemetry system, and more specifically is a rapidly deployed modular telemetry apparatus which utilizes of SDR technology and the FPGA programming capability to reduce the number of hardware components and programming required to deploy a telemetry system.

  14. STABILIZED OSCILLATOR

    DOEpatents

    Jessen, P.L.; Price, H.J.

    1958-03-18

    This patent relates to sine-wave generators and in particular describes a generator with a novel feedback circuit resulting in improved frequency stability. The generator comprises two triodes having a common cathode circuit connected to oscillate at a frequency and amplitude at which the loop galn of the circutt ls unity, and another pair of triodes having a common cathode circuit arranged as a conventional amplifier. A signal is conducted from the osciliator through a frequency selective network to the amplifier and fed back to the osciliator. The unique feature of the feedback circuit is the amplifier operates in the nonlinear portion of its tube characteristics thereby providing a relatively constant feedback voltage to the oscillator irrespective of the amplitude of its input signal.

  15. FEL Oscillators

    SciTech Connect

    George Neil

    2003-05-12

    FEL Oscillators have been around since 1977 providing not only a test bed for the physics of Free Electron Lasers and electron/photon interactions but as a workhorse of scientific research. More than 30 FEL oscillators are presently operating around the world spanning a wavelength range from the mm region to the ultraviolet using DC and rf linear accelerators and storage rings as electron sources. The characteristics that have driven the development of these sources are the desire for high peak and average power, high micropulse energies, wavelength tunability, timing flexibility, and wavelengths that are unavailable from more conventional laser sources. Substantial user programs have been performed using such sources encompassing medicine, biology, solid state research, atomic and molecular physics, effects of non-linear fields, surface science, polymer science, pulsed laser vapor deposition, to name just a few.

  16. Antiperiodic oscillations

    PubMed Central

    Freire, Joana G.; Cabeza, Cecilia; Marti, Arturo; Pöschel, Thorsten; Gallas, Jason A. C.

    2013-01-01

    The investigation of regular and irregular patterns in nonlinear oscillators is an outstanding problem in physics and in all natural sciences. In general, regularity is understood as tantamount to periodicity. However, there is now a flurry of works proving the existence of “antiperiodicity”, an unfamiliar type of regularity. Here we report the experimental observation and numerical corroboration of antiperiodic oscillations. In contrast to the isolated solutions presently known, we report infinite hierarchies of antiperiodic waveforms that can be tuned continuously and that form wide spiral-shaped stability phases in the control parameter plane. The waveform complexity increases towards the focal point common to all spirals, a key hub interconnecting them all. PMID:23739041

  17. Multidisciplinary Studies of Integrated Neural Network Systems

    DTIC Science & Technology

    1994-03-01

    high and low frequencies ........... 12 c. Cellular mechanisms of intensity processing in nucleus angularis ............... 12 D. Publications...Intelligent robotic control systems have been constructed with a hierarchical and modular organization, us- ing antagonistic actuation mechanisms and multi...terrestrial animal studied thus far [ 12]. Considerable progress has been made in determining the acoustic and neural bases of the head saccade (see

  18. Solar Oscillations

    NASA Technical Reports Server (NTRS)

    Duvall, Thomas

    2004-01-01

    Oscillations were first detected in the solar photosphere in 1962 by Leighton and students. In 1970 it was calculated that these oscillations, with a period near five minutes, were the manifestations of acoustic waves trapped in the interior. The subsequent measurements of the frequencies of global oscillation modes from the spatio-temporal power spectrum of the waves made possible the refinement of solar interior models. Over the years, increased understanding of the nuclear reaction rates, the opacity, the equation of state, convection, and gravitational settling have resulted. Mass flows shift the frequencies of modes leading to very accurate measurements of the interior rotation as a function of radius and latitude. In recent years, analogues of terrestrial seismology have led to a tomography of the interior, including measurements of global north-south flows and flow and wave speed measurements below features such as sunspots. The future of helioseismology seems bright with the approval of NASA's Solar Dynamics Observatory mission, to be launched in 2008.

  19. Quasispecies theory for evolution of modularity

    NASA Astrophysics Data System (ADS)

    Park, Jeong-Man; Niestemski, Liang Ren; Deem, Michael W.

    2015-01-01

    Biological systems are modular, and this modularity evolves over time and in different environments. A number of observations have been made of increased modularity in biological systems under increased environmental pressure. We here develop a quasispecies theory for the dynamics of modularity in populations of these systems. We show how the steady-state fitness in a randomly changing environment can be computed. We derive a fluctuation dissipation relation for the rate of change of modularity and use it to derive a relationship between rate of environmental changes and rate of growth of modularity. We also find a principle of least action for the evolved modularity at steady state. Finally, we compare our predictions to simulations of protein evolution and find them to be consistent.

  20. Quasispecies Theory for Evolution of Modularity

    PubMed Central

    Park, Jeong-Man; Niestemski, Liang Ren; Deem, Michael W.

    2015-01-01

    Biological systems are modular, and this modularity evolves over time and in different environments. A number of observations have been made of increased modularity in biological systems under increased environmental pressure. We here develop a quasispecies theory for the dynamics of modularity in populations of these systems. We show how the steady-state fitness in a randomly changing environment can be computed. We derive a fluctuation dissipation relation for the rate of change of modularity and use it to derive a relationship between rate of environmental changes and rate of growth of modularity. We also find a principle of least action for the evolved modularity at steady state. Finally, we compare our predictions to simulations of protein evolution and find them to be consistent. PMID:25679649

  1. Quasispecies theory for evolution of modularity.

    PubMed

    Park, Jeong-Man; Niestemski, Liang Ren; Deem, Michael W

    2015-01-01

    Biological systems are modular, and this modularity evolves over time and in different environments. A number of observations have been made of increased modularity in biological systems under increased environmental pressure. We here develop a quasispecies theory for the dynamics of modularity in populations of these systems. We show how the steady-state fitness in a randomly changing environment can be computed. We derive a fluctuation dissipation relation for the rate of change of modularity and use it to derive a relationship between rate of environmental changes and rate of growth of modularity. We also find a principle of least action for the evolved modularity at steady state. Finally, we compare our predictions to simulations of protein evolution and find them to be consistent.

  2. Functional Modularity of Background Activities in Normal and Epileptic Brain Networks

    NASA Astrophysics Data System (ADS)

    Chavez, M.; Valencia, M.; Navarro, V.; Latora, V.; Martinerie, J.

    2010-03-01

    We analyze the connectivity structure of weighted brain networks extracted from spontaneous magnetoencephalographic signals of healthy subjects and epileptic patients (suffering from absence seizures) recorded at rest. We find that, for the activities in the 5-14 Hz range, healthy brains exhibit a sparse connectivity, whereas the brain networks of patients display a rich connectivity with a clear modular structure. Our results suggest that modularity plays a key role in the functional organization of brain areas during normal and pathological neural activities at rest.

  3. Spintronic device modeling and evaluation using modular approach to spintronics

    NASA Astrophysics Data System (ADS)

    Ganguly, Samiran

    Spintronics technology finds itself in an exciting stage today. Riding on the backs of rapid growth and impressive advances in materials and phenomena, it has started to make headway in the memory industry as solid state magnetic memories (STT-MRAM) and is considered a possible candidate to replace the CMOS when its scaling reaches physical limits. It is necessary to bring all these advances together in a coherent fashion to explore and evaluate the potential of spintronic devices. This work creates a framework for this exploration and evaluation based on Modular Approach to Spintronics, which encapsulate the physics of transport of charge and spin through materials and the phenomenology of magnetic dynamics and interaction in benchmarked elemental modules. These modules can then be combined together to form spin-circuit models of complex spintronic devices and structures which can be simulated using SPICE like circuit simulators. In this work we demonstrate how Modular Approach to Spintronics can be used to build spin-circuit models of functional spintronic devices of all types: memory, logic, and oscillators. We then show how Modular Approach to Spintronics can help identify critical factors behind static and dynamic dissipation in spintronic devices and provide remedies by exploring the use of various alternative materials and phenomena. Lastly, we show the use of Modular Approach to Spintronics in exploring new paradigms of computing enabled by the inherent physics of spintronic devices. We hope that this work will encourage more research and experiments that will establish spintronics as a viable technology for continued advancement of electronics.

  4. Nonequilibrium landscape theory of neural networks.

    PubMed

    Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

    2013-11-05

    The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape-flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. 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. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments.

  5. Nonequilibrium landscape theory of neural networks

    PubMed Central

    Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

    2013-01-01

    The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape–flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. 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. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments. PMID:24145451

  6. Modular Stellarator Fusion Reactor concept

    SciTech Connect

    Miller, R.L.; Krakowski, R.A.

    1981-08-01

    A preliminary conceptual study is made of the Modular Stellarator Reactor (MSR). A steady-state ignited, DT-fueled, magnetic fusion reactor is proposed for use as a central electric-power station. The MSR concept combines the physics of the classic stellarator confinement topology with an innovative, modular-coil design. Parametric tradeoff calculations are described, leading to the selection of an interim design point for a 4-GWt plant based on Alcator transport scaling and an average beta value of 0.04 in an l = 2 system with a plasma aspect ratio of 11. The physics basis of the design point is described together with supporting magnetics, coil-force, and stress computations. The approach and results presented herein will be modified in the course of ongoing work to form a firmer basis for a detailed conceptual design of the MSR.

  7. Relaxation labeling using modular operators

    SciTech Connect

    Duncan, J.S.; Frei, W.

    1983-01-01

    Probabilistic relaxation labeling has been shown to be useful in image processing, pattern recognition, and artificial intelligence. The approaches taken to date have been encumbered with computationally extensive summations which generally prevent real-time operation and/or easy hardware implementation. The authors present a new and unique approach to the relaxation labeling problem using modular, VLSI-oriented hierarchical complex operators. One of the fundamental concepts of this work is the representation of the probability distribution of the possible labels for a given object (pixel) as an ellipse, which may be summed with neighboring object's distribution ellipses, resulting in a new, relaxed label space. The mathematical development of the elliptical approach will be presented and compared to more classical approaches, and a hardware block diagram that shows the implementation of the relaxation scheme using vlsi chips will be presented. Finally, results will be shown which illustrate applications of the modular scheme, iteratively, to both edges and lines. 13 references.

  8. Modular hydrodam: concept definition study

    SciTech Connect

    Not Available

    1981-07-01

    The purpose of this investigation was to explore the potential for developing economical new ultra low-head (6 to 10 ft) sites using an innovative concept known as the Modular Hydrodam (MH). This concept combines the benefits of shop fabrication, installation of equipment in truck transportable, waterproof power modules, and prefabricated gate sections that can be located between the power modules. The size and weight of the power module permits it to be fully assembled and checked out in the manufacturer's shop. The module can then be broken down into four pieces and shipped by truck to the site. Once in place, concrete ballast will be added, as necessary, to prevent flotation. The following aspects were investigated: tubular and cross flow turbines; modularized components; the use of a cable support system for horizontal stability of the dam and powerhouse; and construction in the wet as well as in the dry.

  9. Modular Platforms for Optofluidic Systems

    NASA Astrophysics Data System (ADS)

    Brammer, Marko; Mappes, Timo

    2014-01-01

    Optofluidics is increasingly gaining impact in a number of different fields of research, namely biology and medicine, environmental monitoring and green energy. However, the market for optofluidic products is still in the early development phase. In this manuscript, we discuss modular platforms as a potential concept to facilitate the transfer of optofluidic sensing systems to an industrial implementation. We present microfluidic and optical networks as a basis for the interconnection of optofluidic sensor modules. Finally, we show the potential for entire optofluidic networks

  10. PTERA - Modular Aircraft Flight Test

    NASA Image and Video Library

    2016-01-13

    Aerospace testing can be costly and time consuming but a new modular, subscale remotely piloted aircraft offers NASA researchers more affordable options for developing a wide range of cutting edge aviation and space technologies. The Prototype-Technology Evaluation and Research Aircraft (PTERA), developed by Area-I, Inc., of Kennesaw, Georgia, is an extremely versatile and high quality, yet inexpensive, flying laboratory bridging the gap between wind tunnels and crewed flight testing.

  11. Modular Platforms for Optofluidic Systems

    NASA Astrophysics Data System (ADS)

    Brammer, Marko; Mappes, Timo

    2013-02-01

    Optofluidics is increasingly gaining impact in a number of different fields of research, namely biology and medicine, environmental monitoring and green energy. However, the market for optofluidic products is still in the early development phase. In this manuscript, we discuss modular platforms as a potential concept to facilitate the transfer of optofluidic sensing systems to an industrial implementation. We present microfluidic and optical networks as a basis for the interconnection of optofluidic sensor modules. Finally, we show the potential for entire optofluidic networks.

  12. Modular Platforms for Optofluidic Systems

    NASA Astrophysics Data System (ADS)

    Brammer, Marko; Mappes, Timo

    2014-01-01

    Optofluidics is increasingly gaining impact in a number of different fields of research, namely biology and medicine, environmental monitoring and green energy. However, the market for optofluidic products is still in the early development phase. In this manuscript, we discuss modular platforms as a potential concept to facilitate the transfer of optofluidic sensing systems to an industrial implementation. We present microfluidic and optical networks as a basis for the interconnection of optofluidic sensor modules. Finally, we show the potential for entire optofluidic networks

  13. Multidimensional bioseparation with modular microfluidics

    DOEpatents

    Chirica, Gabriela S.; Renzi, Ronald F.

    2013-08-27

    A multidimensional chemical separation and analysis system is described including a prototyping platform and modular microfluidic components capable of rapid and convenient assembly, alteration and disassembly of numerous candidate separation systems. Partial or total computer control of the separation system is possible. Single or multiple alternative processing trains can be tested, optimized and/or run in parallel. Examples related to the separation and analysis of human bodily fluids are given.

  14. CAMAC modular programmable function generator

    SciTech Connect

    Turner, G.W.; Suehiro, S.; Hendricks, R.W.

    1980-12-01

    A CAMAC modular programmable function generator has been developed. The device contains a 1024 word by 12-bit memory, a 12-bit digital-to-analog converter with a 600 ns settling time, an 18-bit programmable frequency register, and two programmable trigger output registers. The trigger registers can produce programmed output logic transitions at various (binary) points in the output function curve, and are used to synchronize various other data acquisition devices with the function curve.

  15. Annotation: Tourette Syndrome--A Relentless Drumbeat--Driven by Misguided Brain Oscillations

    ERIC Educational Resources Information Center

    Leckman, James F.; Vaccarino, Flora M.; Kalanithi, Paul S. A.; Rothenberger, Aribert

    2006-01-01

    Objective: This annotation reviews recent evidence that points to the likely role of aberrant neural oscillations in the pathogenesis of Tourette syndrome (TS). Methods: The available anatomic and electrophysiological findings in TS are reviewed in the context of an emerging picture of the crucial role that neural oscillations play in maintaining…

  16. Annotation: Tourette Syndrome--A Relentless Drumbeat--Driven by Misguided Brain Oscillations

    ERIC Educational Resources Information Center

    Leckman, James F.; Vaccarino, Flora M.; Kalanithi, Paul S. A.; Rothenberger, Aribert

    2006-01-01

    Objective: This annotation reviews recent evidence that points to the likely role of aberrant neural oscillations in the pathogenesis of Tourette syndrome (TS). Methods: The available anatomic and electrophysiological findings in TS are reviewed in the context of an emerging picture of the crucial role that neural oscillations play in maintaining…

  17. Oscillating water column structural model

    SciTech Connect

    Copeland, Guild; Bull, Diana L; Jepsen, Richard Alan; Gordon, Margaret Ellen

    2014-09-01

    An oscillating water column (OWC) wave energy converter is a structure with an opening to the ocean below the free surface, i.e. a structure with a moonpool. Two structural models for a non-axisymmetric terminator design OWC, the Backward Bent Duct Buoy (BBDB) are discussed in this report. The results of this structural model design study are intended to inform experiments and modeling underway in support of the U.S. Department of Energy (DOE) initiated Reference Model Project (RMP). A detailed design developed by Re Vision Consulting used stiffeners and girders to stabilize the structure against the hydrostatic loads experienced by a BBDB device. Additional support plates were added to this structure to account for loads arising from the mooring line attachment points. A simplified structure was designed in a modular fashion. This simplified design allows easy alterations to the buoyancy chambers and uncomplicated analysis of resulting changes in buoyancy.

  18. Cyclic modular beta-sheets.

    PubMed

    Woods, R Jeremy; Brower, Justin O; Castellanos, Elena; Hashemzadeh, Mehrnoosh; Khakshoor, Omid; Russu, Wade A; Nowick, James S

    2007-03-07

    The development of peptide beta-hairpins is problematic, because folding depends on the amino acid sequence and changes to the sequence can significantly decrease folding. Robust beta-hairpins that can tolerate such changes are attractive tools for studying interactions involving protein beta-sheets and developing inhibitors of these interactions. This paper introduces a new class of peptide models of protein beta-sheets that addresses the problem of separating folding from the sequence. These model beta-sheets are macrocyclic peptides that fold in water to present a pentapeptide beta-strand along one edge; the other edge contains the tripeptide beta-strand mimic Hao [JACS 2000, 122, 7654] and two additional amino acids. The pentapeptide and Hao-containing peptide strands are connected by two delta-linked ornithine (deltaOrn) turns [JACS 2003, 125, 876]. Each deltaOrn turn contains a free alpha-amino group that permits the linking of individual modules to form divalent beta-sheets. These "cyclic modular beta-sheets" are synthesized by standard solid-phase peptide synthesis of a linear precursor followed by solution-phase cyclization. Eight cyclic modular beta-sheets 1a-1h containing sequences based on beta-amyloid and macrophage inflammatory protein 2 were synthesized and characterized by 1H NMR. Linked cyclic modular beta-sheet 2, which contains two modules of 1b, was also synthesized and characterized. 1H NMR studies show downfield alpha-proton chemical shifts, deltaOrn delta-proton magnetic anisotropy, and NOE cross-peaks that establish all compounds but 1c and 1g to be moderately or well folded into a conformation that resembles a beta-sheet. Pulsed-field gradient NMR diffusion experiments show little or no self-association at low (

  19. Modular microrobot for swimming in heterogeneous environments

    NASA Astrophysics Data System (ADS)

    Cheang, U. Kei; Meshkati, Meshkati; Fu, Henry; Kim, Minjun; Drexel University Team; University of Nevada, Reno Team

    2015-11-01

    One of the difficulties in navigating in vivo is to overcome many types of environments. This includes blood vessels of different diameters, fluids with different mechanical properties, and physical barriers. Inspired by conventional modular robotics, we demonstrate modular microrobotics using magnetic particles as the modular units to change size and shape through docking and undocking. Much like the vast variety of microorganisms navigating many different bio-environments, modular microswimmers have the ability to dynamically adapt different environments by reconfiguring the swimmers' physical characteristics. We model the docking as magnetic assembly and undocking mechanisms as deformation by hydrodynamic forces. We characterize the swimming capability of the modular microswimmer with different size and shapes. Finally, we demonstrate modular microrobotics by assembling a three-bead microswimmer into a nine-bead microswimmer, and then disassemble it into several independently swimming microswimmers..

  20. Modular Design in Treaty Verification Equipment

    SciTech Connect

    Macarthur, Duncan Whittemore; Benz, Jacob; Tolk, Keith; Weber, Tom

    2015-01-27

    It is widely believed that modular design is a good thing. However, there are often few explicit arguments, or even an agreed range of definitions, to back up this belief. In this paper, we examine the potential range of design modularity, the implications of various amounts of modularity, and the advantages and disadvantages of each level of modular construction. We conclude with a comparison of the advantages and disadvantages of each type, as well as discuss many caveats that should be observed to take advantage of the positive features of modularity and minimize the effects of the negative. The tradeoffs described in this paper will be evaluated during the conceptual design to determine what amount of modularity should be included.

  1. Modular workcells: modern methods for laboratory automation.

    PubMed

    Felder, R A

    1998-12-01

    Laboratory automation is beginning to become an indispensable survival tool for laboratories facing difficult market competition. However, estimates suggest that only 8% of laboratories will be able to afford total laboratory automation systems. Therefore, automation vendors have developed alternative hardware configurations called 'modular automation', to fit the smaller laboratory. Modular automation consists of consolidated analyzers, integrated analyzers, modular workcells, and pre- and post-analytical automation. These terms will be defined in this paper. Using a modular automation model, the automated core laboratory will become a site where laboratory data is evaluated by trained professionals to provide diagnostic information to practising physicians. Modem software information management and process control tools will complement modular hardware. Proper standardization that will allow vendor-independent modular configurations will assure success of this revolutionary new technology.

  2. Chaotic time series prediction using artificial neural networks

    SciTech Connect

    Bartlett, E.B.

    1991-12-31

    This paper describes the use of artificial neural networks to model the complex oscillations defined by a chaotic Verhuist animal population dynamic. A predictive artificial neural network model is developed and tested, and results of computer simulations are given. These results show that the artificial neural network model predicts the chaotic time series with various initial conditions, growth parameters, or noise.

  3. Chaotic time series prediction using artificial neural networks

    SciTech Connect

    Bartlett, E.B.

    1991-01-01

    This paper describes the use of artificial neural networks to model the complex oscillations defined by a chaotic Verhuist animal population dynamic. A predictive artificial neural network model is developed and tested, and results of computer simulations are given. These results show that the artificial neural network model predicts the chaotic time series with various initial conditions, growth parameters, or noise.

  4. Oscillator detector

    SciTech Connect

    Potter, B.M.

    1980-05-13

    An alien liquid detector employs a monitoring element and an oscillatory electronic circuit for maintaining the temperature of the monitoring element substantially above ambient temperature. The output wave form, eg., frequency of oscillation or wave shape, of the oscillatory circuit depends upon the temperaturedependent electrical characteristic of the monitoring element. A predetermined change in the output waveform allows water to be discriminated from another liquid, eg., oil. Features of the invention employing two thermistors in two oscillatory circuits include positioning one thermistor for contact with water and the other thermistor above the oil-water interface to detect a layer of oil if present. Unique oscillatory circuit arrangements are shown that achieve effective thermistor action with an economy of parts and energizing power. These include an operational amplifier employed in an astable multivibrator circuit, a discrete transistor-powered tank circuit, and use of an integrated circuit chip.

  5. Grid oscillators

    NASA Technical Reports Server (NTRS)

    Popovic, Zorana B.; Kim, Moonil; Rutledge, David B.

    1988-01-01

    Loading a two-dimensional grid with active devices offers a means of combining the power of solid-state oscillators in the microwave and millimeter-wave range. The grid structure allows a large number of negative resistance devices to be combined. This approach is attractive because the active devices do not require an external locking signal, and the combining is done in free space. In addition, the loaded grid is a planar structure amenable to monolithic integration. Measurements on a 25-MESFET grid at 9.7 GHz show power-combining and frequency-locking without an external locking signal, with an ERP of 37 W. Experimental far-field patterns agree with theoretical results obtained using reciprocity.

  6. Grid oscillators

    NASA Technical Reports Server (NTRS)

    Popovic, Zorana B.; Kim, Moonil; Rutledge, David B.

    1988-01-01

    Loading a two-dimensional grid with active devices offers a means of combining the power of solid-state oscillators in the microwave and millimeter-wave range. The grid structure allows a large number of negative resistance devices to be combined. This approach is attractive because the active devices do not require an external locking signal, and the combining is done in free space. In addition, the loaded grid is a planar structure amenable to monolithic integration. Measurements on a 25-MESFET grid at 9.7 GHz show power-combining and frequency-locking without an external locking signal, with an ERP of 37 W. Experimental far-field patterns agree with theoretical results obtained using reciprocity.

  7. Local bulk physics from intersecting modular Hamiltonians

    NASA Astrophysics Data System (ADS)

    Kabat, Daniel; Lifschytz, Gilad

    2017-06-01

    We show that bulk quantities localized on a minimal surface homologous to a boundary region correspond in the CFT to operators that commute with the modular Hamiltonian associated with the boundary region. If two such minimal surfaces intersect at a point in the bulk then CFT operators which commute with both extended modular Hamiltonians must be localized at the intersection point. We use this to construct local bulk operators purely from CFT considerations, without knowing the bulk metric, using intersecting modular Hamiltonians. For conformal field theories at zero and finite temperature the appropriate modular Hamiltonians are known explicitly and we recover known expressions for local bulk observables.

  8. Fragmentation: loss of global coherence or breakdown of modularity in functional brain architecture?

    PubMed Central

    van den Berg, Daan; Gong, Pulin; Breakspear, Michael; van Leeuwen, Cees

    2011-01-01

    Psychiatric illnesses characterized by disorganized cognition, such as schizophrenia, have been described in terms of fragmentation and hence understood as reduction in functional brain connectivity, particularly in prefrontal and parietal areas. However, as graph theory shows, relatively small numbers of nonlocal connections are sufficient to ensure global coherence in the modular small-world network structure of the brain. We reconsider fragmentation in this perspective. Computational studies have shown that for a given level of connectivity in a model of coupled nonlinear oscillators, modular small-world networks evolve from an initially random organization. Here we demonstrate that with decreasing connectivity, the probability of evolving into a modular small-world network breaks down at a critical point, which scales to the percolation function of random networks with a universal exponent of α = 1.17. Thus, according to the model, local modularity systematically breaks down before there is loss of global coherence in network connectivity. We, therefore, propose that fragmentation may involve, at least in its initial stages, the inability of a dynamically evolving network to sustain a modular small-world structure. The result is in a shift in the balance in schizophrenia from local to global functional connectivity. PMID:22479239

  9. Modular passive solar heating system

    SciTech Connect

    Hunter, B.D.

    1985-03-19

    A modular passive solar energy storage system comprises a plurality of heat tubes which are arranged to form a flat plate solar collector and are releasably connected to a water reservoir by, and are part of, double-walled heat exchangers which penetrate to the water reservoir and enhance the heat transfer characteristics between the collector and the reservoir. The flat plate collector-heat exchanger disassembly, the collector housing, and the reservoir are integrated into a relatively light weight, unitary structural system in which the reservoir is a primary structural element. In addition to light weight, the system features high efficiency and ease of assembly and maintenance.

  10. Modular design attitude control system

    NASA Technical Reports Server (NTRS)

    Chichester, F. D.

    1984-01-01

    A sequence of single axismodels and a series of reduced state linear observers of minimum order are used to reconstruct inaccessible variables pertaining to the modular attitude control of a rigid body flexible suspension model of a flexible spacecraft. The single axis models consist of two, three, four, and five rigid bodies, each interconnected by a flexible shaft passing through the mass centers of the bodies. Modal damping is added to each model. Reduced state linear observers are developed for synthesizing the inaccessible modal state variables for each modal model.

  11. Modular design attitude control system

    NASA Technical Reports Server (NTRS)

    Chichester, F. D.

    1983-01-01

    Application of modular control techniques to the attitude control of a prototype flexible spacecraft and a prototype flexible space platform was further developed by determining numerical values for the physical parameters of a four body approximation of the MSFC/hybrid deployable truss incorporated in the space platform model, generating sensitivity coefficients for the model of the flexible spacecraft, evaluating the changes in the digital computer simulation of the flexible spacecraft resulting from the addition of another rigid body to the model and comparing attitude control effectiveness with actuators on more than one rigid body of the model with that for the case in which the actuators were restricted to one body.

  12. Cascading dynamics in modular networks

    NASA Astrophysics Data System (ADS)

    Galstyan, Aram; Cohen, Paul

    2007-03-01

    In this paper we study a simple cascading process in a structured heterogeneous population, namely, a network composed of two loosely coupled communities. We demonstrate that under certain conditions the cascading dynamics in such a network has a two-tiered structure that characterizes activity spreading at different rates in the communities. We study the dynamics of the model using both simulations and an analytical approach based on annealed approximation and obtain good agreement between the two. Our results suggest that network modularity might have implications in various applications, such as epidemiology and viral marketing.

  13. Integrated modular engine - Reliability assessment

    NASA Astrophysics Data System (ADS)

    Parsley, R. C.; Ward, T. B.

    1992-07-01

    A major driver in the increased interest in integrated modular engine configurations is the desire for ultra reliability for future rocket propulsion systems. The concept of configuring multiple sets of turbomachinery networked to multiple thrust chamber assemblies has been identified as an approach with potential to achieve significant reliability enhancement. This paper summarizes the results of a reliability study comparing networked systems vs. discrete engine installations, both with and without major module and engine redundancy. The study was conducted for gas generator, expander, and staged combustion cycles. The results are representative of either booster or upper-stage applications and are indicative of either plug or nonplug installation philosophies.

  14. Oscillating Permanent Magnets.

    ERIC Educational Resources Information Center

    Michaelis, M. M.; Haines, C. M.

    1989-01-01

    Describes several ways to partially levitate permanent magnets. Computes field line geometries and oscillation frequencies. Provides several diagrams illustrating the mechanism of the oscillation. (YP)

  15. Time Series Decomposition into Oscillation Components and Phase Estimation.

    PubMed

    Matsuda, Takeru; Komaki, Fumiyasu

    2017-02-01

    Many time series are naturally considered as a superposition of several oscillation components. For example, electroencephalogram (EEG) time series include oscillation components such as alpha, beta, and gamma. We propose a method for decomposing time series into such oscillation components using state-space models. Based on the concept of random frequency modulation, gaussian linear state-space models for oscillation components are developed. In this model, the frequency of an oscillator fluctuates by noise. Time series decomposition is accomplished by this model like the Bayesian seasonal adjustment method. Since the model parameters are estimated from data by the empirical Bayes' method, the amplitudes and the frequencies of oscillation components are determined in a data-driven manner. Also, the appropriate number of oscillation components is determined with the Akaike information criterion (AIC). In this way, the proposed method provides a natural decomposition of the given time series into oscillation components. In neuroscience, the phase of neural time series plays an important role in neural information processing. The proposed method can be used to estimate the phase of each oscillation component and has several advantages over a conventional method based on the Hilbert transform. Thus, the proposed method enables an investigation of the phase dynamics of time series. Numerical results show that the proposed method succeeds in extracting intermittent oscillations like ripples and detecting the phase reset phenomena. We apply the proposed method to real data from various fields such as astronomy, ecology, tidology, and neuroscience.

  16. Predicting neural network firing pattern from phase resetting curve

    NASA Astrophysics Data System (ADS)

    Oprisan, Sorinel; Oprisan, Ana

    2007-04-01

    Autonomous neural networks called central pattern generators (CPG) are composed of endogenously bursting neurons and produce rhythmic activities, such as flying, swimming, walking, chewing, etc. Simplified CPGs for quadrupedal locomotion and swimming are modeled by a ring of neural oscillators such that the output of one oscillator constitutes the input for the subsequent neural oscillator. The phase response curve (PRC) theory discards the detailed conductance-based description of the component neurons of a network and reduces them to ``black boxes'' characterized by a transfer function, which tabulates the transient change in the intrinsic period of a neural oscillator subject to external stimuli. Based on open-loop PRC, we were able to successfully predict the phase-locked period and relative phase between neurons in a half-center network. We derived existence and stability criteria for heterogeneous ring neural networks that are in good agreement with experimental data.

  17. Revised Modularity Index to Measure Modularity of OSS Projects with Case Study of Freemind

    NASA Astrophysics Data System (ADS)

    WahjuRahardjoEmanuel, Andi; Jahja Surjawan, Daniel

    2012-12-01

    Open Source Software (OSS) Projects are gaining popularity worldwide. Studies by many researchers show that the important key success factor is modularity of the source code. This paper presents the revised Modularity Index which is a software metrics to measure the modularity level of a javabased OSS Projects. To show its effectiveness in analyzing OSS Project, the Modularity Index and its supporting software metrics are then used to analyze the evolution of Freemind mind mapping OSS Project. The analysis using Modularity Index and its supporting metrics shows the strength and weaknesses of the Freemind OSS Projects.

  18. The Iterative Structure Analysis of Montgomery Modular Multiplication

    NASA Astrophysics Data System (ADS)

    Jinbo, Wang

    2007-09-01

    Montgomery modular multiplication (MMM) plays a crucial role in the implementation of modular exponentiations of public-key cryptography. In this paper, we discuss the iterative structure and extend the iterative bound condition of MMM. It can be applied to complicated modular exponentiations. Based on the iterative condition of MMM, we can directly use non-modular additions, subtractions and even simple multiplications instead of the modular forms, which make modular exponentiation operation very efficient but more importantly iterative applicability of MMM.

  19. Decentralized and Modular Electrical Architecture

    NASA Astrophysics Data System (ADS)

    Elisabelar, Christian; Lebaratoux, Laurence

    2014-08-01

    This paper presents the studies made on the definition and design of a decentralized and modular electrical architecture that can be used for power distribution, active thermal control (ATC), standard inputs-outputs electrical interfaces.Traditionally implemented inside central unit like OBC or RTU, these interfaces can be dispatched in the satellite by using MicroRTU.CNES propose a similar approach of MicroRTU. The system is based on a bus called BRIO (Bus Réparti des IO), which is composed, by a power bus and a RS485 digital bus. BRIO architecture is made with several miniature terminals called BTCU (BRIO Terminal Control Unit) distributed in the spacecraft.The challenge was to design and develop the BTCU with very little volume, low consumption and low cost. The standard BTCU models are developed and qualified with a configuration dedicated to ATC, while the first flight model will fly on MICROSCOPE for PYRO actuations and analogue acquisitions. The design of the BTCU is made in order to be easily adaptable for all type of electric interface needs.Extension of this concept is envisaged for power conditioning and distribution unit, and a Modular PCDU based on BRIO concept is proposed.

  20. Compact stellarators with modular coils.

    PubMed

    Garabedian, P R

    2000-07-18

    Compact stellarator designs with modular coils and only two or three field periods are now available; these designs have both good stability and quasiaxial symmetry providing adequate transport for a magnetic fusion reactor. If the bootstrap current assumes theoretically predicted values a three field period configuration is optimal, but if that net current turns out to be lower, a device with two periods and just 12 modular coils might be better. There are also attractive designs with quasihelical symmetry and four or five periods whose properties depend less on the bootstrap current. Good performance requires that there be a satisfactory magnetic well in the vacuum field, which is a property lacking in a stellarator-tokamak hybrid that has been proposed for a proof of principle experiment. In this paper, we present an analysis of stability for these configurations that is based on a mountain pass theorem asserting that, if two solutions of the problem of magnetohydrodynamic equilibrium can be found, then there has to be an unstable solution. We compare results of our theory of equilibrium, stability, and transport with recently announced measurements from the large LHD experiment in Japan.

  1. Compact stellarators with modular coils

    PubMed Central

    Garabedian, P. R.

    2000-01-01

    Compact stellarator designs with modular coils and only two or three field periods are now available; these designs have both good stability and quasiaxial symmetry providing adequate transport for a magnetic fusion reactor. If the bootstrap current assumes theoretically predicted values a three field period configuration is optimal, but if that net current turns out to be lower, a device with two periods and just 12 modular coils might be better. There are also attractive designs with quasihelical symmetry and four or five periods whose properties depend less on the bootstrap current. Good performance requires that there be a satisfactory magnetic well in the vacuum field, which is a property lacking in a stellarator-tokamak hybrid that has been proposed for a proof of principle experiment. In this paper, we present an analysis of stability for these configurations that is based on a mountain pass theorem asserting that, if two solutions of the problem of magnetohydrodynamic equilibrium can be found, then there has to be an unstable solution. We compare results of our theory of equilibrium, stability, and transport with recently announced measurements from the large LHD experiment in Japan. PMID:10899993

  2. A modular BLSS simulation model

    NASA Technical Reports Server (NTRS)

    Rummel, John D.; Volk, Tyler

    1987-01-01

    A bioregenerative life support system (BLSS) for extraterrestrial use will be faced with coordination problems more acute than those in any ecosystem found on Earth. A related problem in BLSS design is providing an interface between the various life support processors, one that will allow for their coordination while still allowing for system expansion. A modular model is presented of a BLSS that interfaces system processors only with the material storage reservoirs, allowing those reservoirs to act as the principal buffers in the system and thus minimizing difficulties with processor coordination. The modular nature of the model allows independent development of the detailed submodels that exist within the model framework. Using this model, BLSS dynamics were investigated under normal conditions and under various failure modes. Partial and complete failures of various components, such as the waste processors or the plants themselves, drive transient responses in the model system, allowing the examination of the effectiveness of the system reservoirs as buffers. The results from simulations help to determine control strategies and BLSS design requirements. An evolved version could be used as an interactive control aid in a future BLSS.

  3. Learning modular policies for robotics.

    PubMed

    Neumann, Gerhard; Daniel, Christian; Paraschos, Alexandros; Kupcsik, Andras; Peters, Jan

    2014-01-01

    A promising idea for scaling robot learning to more complex tasks is to use elemental behaviors as building blocks to compose more complex behavior. Ideally, such building blocks are used in combination with a learning algorithm that is able to learn to select, adapt, sequence and co-activate the building blocks. While there has been a lot of work on approaches that support one of these requirements, no learning algorithm exists that unifies all these properties in one framework. In this paper we present our work on a unified approach for learning such a modular control architecture. We introduce new policy search algorithms that are based on information-theoretic principles and are able to learn to select, adapt and sequence the building blocks. Furthermore, we developed a new representation for the individual building block that supports co-activation and principled ways for adapting the movement. Finally, we summarize our experiments for learning modular control architectures in simulation and with real robots.

  4. Learning modular policies for robotics

    PubMed Central

    Neumann, Gerhard; Daniel, Christian; Paraschos, Alexandros; Kupcsik, Andras; Peters, Jan

    2014-01-01

    A promising idea for scaling robot learning to more complex tasks is to use elemental behaviors as building blocks to compose more complex behavior. Ideally, such building blocks are used in combination with a learning algorithm that is able to learn to select, adapt, sequence and co-activate the building blocks. While there has been a lot of work on approaches that support one of these requirements, no learning algorithm exists that unifies all these properties in one framework. In this paper we present our work on a unified approach for learning such a modular control architecture. We introduce new policy search algorithms that are based on information-theoretic principles and are able to learn to select, adapt and sequence the building blocks. Furthermore, we developed a new representation for the individual building block that supports co-activation and principled ways for adapting the movement. Finally, we summarize our experiments for learning modular control architectures in simulation and with real robots. PMID:24966830

  5. Modularity, noise, and natural selection.

    PubMed

    Marroig, Gabriel; Melo, Diogo A R; Garcia, Guilherme

    2012-05-01

    Most biological systems are formed by component parts that are to some degree interrelated. Groups of parts that are more associated among themselves and are relatively autonomous from others are called modules. One of the consequences of modularity is that biological systems usually present an unequal distribution of the genetic variation among traits. Estimating the covariance matrix that describes these systems is a difficult problem due to a number of factors such as poor sample sizes and measurement errors. We show that this problem will be exacerbated whenever matrix inversion is required, as in directional selection reconstruction analysis. We explore the consequences of varying degrees of modularity and signal-to-noise ratio on selection reconstruction. We then present and test the efficiency of available methods for controlling noise in matrix estimates. In our simulations, controlling matrices for noise vastly improves the reconstruction of selection gradients. We also perform an analysis of selection gradients reconstruction over a New World Monkeys skull database to illustrate the impact of noise on such analyses. Noise-controlled estimates render far more plausible interpretations that are in full agreement with previous results. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

  6. A modular approach toward extremely large apertures

    NASA Astrophysics Data System (ADS)

    Woods, A. A., Jr.

    1981-02-01

    Modular antenna construction can provide a significant increase in reflector aperture size over deployable reflectors. The modular approach allows reflective mesh surfaces to be supported by a minimum of structure. The kinematics of the selected deployable design approach were validated by the subscale demonstration model. Further design refinements on the module structural/joints and design optimization on intermodule joints are needed.

  7. Deployable modular mesh antenna - Concept and feasibility

    NASA Astrophysics Data System (ADS)

    Mitsugi, Jin; Yasaka, Tetsuo

    The feasibility of a 10m aperture deployable modular mesh antenna is evaluated by integrating the results of a statistical surface accuracy estimation and of surface shape adjustment experiments. It has been clarified that by combining seven 4m aperture modules, a 10m aperture deployable modular mesh antenna can be constructed, preserving the surface accuracy that is applicable to C band mission.

  8. Modular Building Institute 2000 Educational Showcase.

    ERIC Educational Resources Information Center

    Modular Building Inst., Charlottesville, VA.

    This publication contains brief articles concerned with modular school structures. The articles offer examples of such structures at actual schools. The articles in this issue are: (1) "Elementary K-8 Modular Courtyard"; (2) "School District #33, Chilliwack, BC"; (3) "New Elementary School for Briarwood, NY"; (4) "Addition to Queens Intermediate…

  9. Modular Buildings Are Here To Stay.

    ERIC Educational Resources Information Center

    Williams, Steven; Roman, Michael I.; Tiernan, Maury; Savage, Chuck; Airikka, Robert; Brosius, Jerry L.

    2000-01-01

    Presents several examples of modular building construction being used be school districts to support their need for more space, building flexibility, and enhancement of the learning environment. Comparisons with traditionally built school facilities are offered as are answers to commonly held myths concerning modular construction. (GR)

  10. Modular Construction: The Wave of the Future.

    ERIC Educational Resources Information Center

    Savage, Chuck

    1989-01-01

    Modular construction of school buildings offers speed of construction, with 100 percent contractor responsibility for the completed structures. Under negotiated terms, modular projects can be purchased outright or through long-term leasing arrangements that provide ownership at the end of the lease period. (MLF)

  11. Detectability thresholds of general modular graphs

    NASA Astrophysics Data System (ADS)

    Kawamoto, Tatsuro; Kabashima, Yoshiyuki

    2017-01-01

    We investigate the detectability thresholds of various modular structures in the stochastic block model. Our analysis reveals how the detectability threshold is related to the details of the modular pattern, including the hierarchy of the clusters. We show that certain planted structures are impossible to infer regardless of their fuzziness.

  12. 48 CFR 39.103 - Modular contracting.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 48 Federal Acquisition Regulations System 1 2013-10-01 2013-10-01 false Modular contracting. 39.103 Section 39.103 Federal Acquisition Regulations System FEDERAL ACQUISITION REGULATION SPECIAL... extent practicable, use modular contracting to acquire major systems (see 2.101) of...

  13. 48 CFR 39.103 - Modular contracting.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 48 Federal Acquisition Regulations System 1 2011-10-01 2011-10-01 false Modular contracting. 39.103 Section 39.103 Federal Acquisition Regulations System FEDERAL ACQUISITION REGULATION SPECIAL... extent practicable, use modular contracting to acquire major systems (see 2.101) of...

  14. A Modular Laser Graphics Projection System

    NASA Astrophysics Data System (ADS)

    Newswanger, Craig D.

    1984-05-01

    WED Enterprises has designed and built a modular projection system for the presentation of animated laser shows. This system was designed specifically for use in Disney theme shows. Its modular design allows it to be adapted to many show situations with simple hardware and software adjustments. The primary goals were superior animation, long life, low maintenance and stand alone operation.

  15. A topographical method for the development of neural networks for artificial brain evolution.

    PubMed

    Young Jung, Sung

    2005-01-01

    Developmental neural networks, which are constructed according to developmental rules (i.e., genes), have the potential to be differentiated into heteromorphic neural structures capable of performing various kinds of activities. The fact that the biological neural architectures are found to be highly repetitive, layered, and topographically organized has important consequences for neural development methods. The purpose of this article is to propose a neural development method that can construct topographical neural connections, that is, a topographical development method, to facilitate fast and efficient development. This is achieved by arborizing neural connections on a developmental tree that rarely produces dead connections. Modular gene expression and corresponding modular networks have an important role in a gradual evolutionary process. Gene expression for modular networks is also proposed here as a way to reduce the probability of fatal mutants created through gene alteration. The corresponding evolutionary experiment shows that various neural structures--layered, repetitive, modular, and complex ones like those in the biological brain--can be constructed and easily observed. It also demonstrates that due to the efficiency of the proposed method, large neural networks can be easily managed, thereby making it suitable for long duration evolutionary experiments.

  16. Modularity maximization using completely positive programming

    NASA Astrophysics Data System (ADS)

    Yazdanparast, Sakineh; Havens, Timothy C.

    2017-04-01

    Community detection is one of the most prominent problems of social network analysis. In this paper, a novel method for Modularity Maximization (MM) for community detection is presented which exploits the Alternating Direction Augmented Lagrangian (ADAL) method for maximizing a generalized form of Newman's modularity function. We first transform Newman's modularity function into a quadratic program and then use Completely Positive Programming (CPP) to map the quadratic program to a linear program, which provides the globally optimal maximum modularity partition. In order to solve the proposed CPP problem, a closed form solution using the ADAL merged with a rank minimization approach is proposed. The performance of the proposed method is evaluated on several real-world data sets used for benchmarks community detection. Simulation results shows the proposed technique provides outstanding results in terms of modularity value for crisp partitions.

  17. Finding network communities using modularity density

    NASA Astrophysics Data System (ADS)

    Botta, Federico; del Genio, Charo I.

    2016-12-01

    Many real-world complex networks exhibit a community structure, in which the modules correspond to actual functional units. Identifying these communities is a key challenge for scientists. A common approach is to search for the network partition that maximizes a quality function. Here, we present a detailed analysis of a recently proposed function, namely modularity density. We show that it does not incur in the drawbacks suffered by traditional modularity, and that it can identify networks without ground-truth community structure, deriving its analytical dependence on link density in generic random graphs. In addition, we show that modularity density allows an easy comparison between networks of different sizes, and we also present some limitations that methods based on modularity density may suffer from. Finally, we introduce an efficient, quadratic community detection algorithm based on modularity density maximization, validating its accuracy against theoretical predictions and on a set of benchmark networks.

  18. The emergence of modularity in biological systems

    NASA Astrophysics Data System (ADS)

    Lorenz, Dirk M.; Jeng, Alice; Deem, Michael W.

    2011-06-01

    In this review, we discuss modularity and hierarchy in biological systems. We review examples from protein structure, genetics, and biological networks of modular partitioning of the geometry of biological space. We review theories to explain modular organization of biology, with a focus on explaining how biology may spontaneously organize to a structured form. That is, we seek to explain how biology nucleated from among the many possibilities in chemistry. The emergence of modular organization of biological structure will be described as a symmetry-breaking phase transition, with modularity as the order parameter. Experimental support for this description will be reviewed. Examples will be presented from pathogen structure, metabolic networks, gene networks, and protein-protein interaction networks. Additional examples will be presented from ecological food networks, developmental pathways, physiology, and social networks.

  19. Neural and Cognitive Modeling with Networks of Leaky Integrator Units

    NASA Astrophysics Data System (ADS)

    Graben, Peter beim; Liebscher, Thomas; Kurths, Jürgen

    After reviewing several physiological findings on oscillations in the electroencephalogram (EEG) and their possible explanations by dynamical modeling, we present neural networks consisting of leaky integrator units as a universal paradigm for neural and cognitive modeling. In contrast to standard recurrent neural networks, leaky integrator units are described by ordinary differential equations living in continuous time. We present an algorithm to train the temporal behavior of leaky integrator networks by generalized back-propagation and discuss their physiological relevance. Eventually, we show how leaky integrator units can be used to build oscillators that may serve as models of brain oscillations and cognitive processes.

  20. Small Modular Reactors: Institutional Assessment

    SciTech Connect

    Joseph Perkowski, Ph.D.

    2012-06-01

    ? Objectives include, among others, a description of the basic development status of “small modular reactors” (SMRs) focused primarily on domestic activity; investigation of the domestic market appeal of modular reactors from the viewpoints of both key energy sector customers and also key stakeholders in the financial community; and consideration of how to proceed further with a pro-active "core group" of stakeholders substantially interested in modular nuclear deployment in order to provide the basis to expedite design/construction activity and regulatory approval. ? Information gathering was via available resources, both published and personal communications with key individual stakeholders; published information is limited to that already in public domain (no confidentiality); viewpoints from interviews are incorporated within. Discussions at both government-hosted and private-hosted SMR meetings are reflected herein. INL itself maintains a neutral view on all issues described. Note: as per prior discussion between INL and CAP, individual and highly knowledgeable senior-level stakeholders provided the bulk of insights herein, and the results of those interviews are the main source of the observations of this report. ? Attachment A is the list of individual stakeholders consulted to date, including some who provided significant earlier assessments of SMR institutional feasibility. ? Attachments B, C, and D are included to provide substantial context on the international status of SMR development; they are not intended to be comprehensive and are individualized due to the separate nature of the source materials. Attachment E is a summary of the DOE requirements for winning teams regarding the current SMR solicitation. Attachment F deserves separate consideration due to the relative maturity of the SMART SMR program underway in Korea. Attachment G provides illustrative SMR design features and is intended for background. Attachment H is included for overview

  1. A bioinspired modular aquatic robot

    NASA Astrophysics Data System (ADS)

    Tallapragada, Phanindra; Pollard, Beau

    2016-11-01

    Several bio inspired swimming robots exist which seek to emulate the morphology of fish and the flapping motion of the tail and fins or other appendages and body of aquatic creatures. The locomotion of such robots and the aquatic animals that they seek to emulate is determined to a large degree by the changes in the shape of the body, which produce periodic changes in the momentum of the body and the creation and interaction of the vorticity field in the fluid with the body. We demonstrate an underactuated robot which swims due to the periodic changes in the angular momentum of the robot effected by the motion of an internal rotor. The robot is modular, unactuated tail like segments can be easily added to the robot. These segments modulate the interaction of the body with the fluid to produce a variety of passive shape changes that can allow the robot to swim in different modes.

  2. Analytical Spectroscopy Using Modular Systems

    NASA Astrophysics Data System (ADS)

    Patterson, Brian M.; Danielson, Neil D.; Lorigan, Gary A.; Sommer, André J.

    2003-12-01

    This article describes the development of three analytical spectroscopy experiments that compare the determination of salicylic acid (SA) content in aspirin tablets. The experiments are based on UV vis, fluorescence, and Raman spectroscopies and utilize modular spectroscopic components. Students assemble their own instruments, optimize them with respect to signal-to-noise, generate calibration curves, determine the SA content in retail aspirin tablets, and assign features in the respective spectra to functional groups within the active material. Using this approach in the discovery-based setting, the students gain invaluable insight into method-specific parameters, such as instrumental components, sample preparation, and analytical capability. In addition, the students learn the fundamentals of fiber optics and signal processing using the low-cost CCD based spectroscopic components.

  3. BESST: A Miniature, Modular Radiometer

    NASA Technical Reports Server (NTRS)

    Warden, Robert; Good, William; Baldwin-Stevens, Erik

    2010-01-01

    A new radiometer assembly has been developed that incorporates modular design principles in order to provide flexibility and versatility. The assembly, shown in Figure 1, is made up of six modules plus a central cubical frame. A small thermal imaging detector is used to determine the temperature of remote objects. To improve the accuracy of the temperature reading, frequent calibration is required. The detector must view known temperature targets before viewing the remote object. Calibration is achieved by using a motorized fold mirror to select the desired scene the detector views. The motor steps the fold mirror through several positions, which allows the detector to view the calibration targets or the remote object. The details, features, and benefits of the radiometer are described in this paper.

  4. MODULAR MANIPULATOR FOR ROBOTICS APPLICATIONS

    SciTech Connect

    Joseph W. Geisinger, Ph.D.

    2001-07-31

    ARM Automation, Inc. is developing a framework of modular actuators that can address the DOE's wide range of robotics needs. The objective of this effort is to demonstrate the effectiveness of this technology by constructing a manipulator from these actuators within a glovebox for Automated Plutonium Processing (APP). At the end of the project, the system of actuators was used to construct several different manipulator configurations, which accommodate common glovebox tasks such as repackaging. The modular nature and quickconnects of this system simplify installation into ''hot'' boxes and any potential modifications or repair therein. This work focused on the development of self-contained robotic actuator modules including the embedded electronic controls for the purpose of building a manipulator system. Both of the actuators developed under this project contain the control electronics, sensors, motor, gear train, wiring, system communications and mechanical interfaces of a complete robotics servo device. Test actuators and accompanying DISC{trademark}s underwent validation testing at The University of Texas at Austin and ARM Automation, Inc. following final design and fabrication. The system also included custom links, an umbilical cord, an open architecture PC-based system controller, and operational software that permitted integration into a completely functional robotic manipulator system. The open architecture on which this system is based avoids proprietary interfaces and communication protocols which only serve to limit the capabilities and flexibility of automation equipment. The system was integrated and tested in the contractor's facility for intended performance and operations. The manipulator was tested using the full-scale equipment and process mock-ups. The project produced a practical and operational system including a quantitative evaluation of its performance and cost.

  5. Osmotrophy in modular Ediacara organisms

    PubMed Central

    Laflamme, Marc; Xiao, Shuhai; Kowalewski, Michał

    2009-01-01

    The Ediacara biota include macroscopic, morphologically complex soft-bodied organisms that appear globally in the late Ediacaran Period (575–542 Ma). The physiology, feeding strategies, and functional morphology of the modular Ediacara organisms (rangeomorphs and erniettomorphs) remain debated but are critical for understanding their ecology and phylogeny. Their modular construction triggered numerous hypotheses concerning their likely feeding strategies, ranging from micro-to-macrophagus feeding to photoautotrophy to osmotrophy. Macrophagus feeding in rangeomorphs and erniettomorphs is inconsistent with their lack of oral openings, and photoautotrophy in rangeomorphs is contradicted by their habitats below the photic zone. Here, we combine theoretical models and empirical data to evaluate the feasibility of osmotrophy, which requires high surface area to volume (SA/V) ratios, as a primary feeding strategy of rangeomorphs and erniettomorphs. Although exclusively osmotrophic feeding in modern ecosystems is restricted to microscopic bacteria, this study suggests that (i) fractal branching of rangeomorph modules resulted in SA/V ratios comparable to those observed in modern osmotrophic bacteria, and (ii) rangeomorphs, and particularly erniettomorphs, could have achieved osmotrophic SA/V ratios similar to bacteria, provided their bodies included metabolically inert material. Thus, specific morphological adaptations observed in rangeomorphs and erniettomorphs may have represented strategies for overcoming physiological constraints that typically make osmotrophy prohibitive for macroscopic life forms. These results support the viability of osmotrophic feeding in rangeomorphs and erniettomorphs, help explain their taphonomic peculiarities, and point to the possible importance of earliest macroorganisms for cycling dissolved organic carbon that may have been present in abundance during Ediacaran times. PMID:19706530

  6. Breakdown of the brain's functional network modularity with awareness.

    PubMed

    Godwin, Douglass; Barry, Robert L; Marois, René

    2015-03-24

    Neurobiological theories of awareness propose divergent accounts of the spatial extent of brain changes that support conscious perception. Whereas focal theories posit mostly local regional changes, global theories propose that awareness emerges from the propagation of neural signals across a broad extent of sensory and association cortex. Here we tested the scalar extent of brain changes associated with awareness using graph theoretical analysis applied to functional connectivity data acquired at ultra-high field while subjects performed a simple masked target detection task. We found that awareness of a visual target is associated with a degradation of the modularity of the brain's functional networks brought about by an increase in intermodular functional connectivity. These results provide compelling evidence that awareness is associated with truly global changes in the brain's functional connectivity.

  7. Fast modular network implementation for support vector machines.

    PubMed

    Huang, Guang-Bin; Mao, K Z; Siew, Chee-Kheong; Huang, De-Shuang

    2005-11-01

    Support vector machines (SVMs) have been extensively used. However, it is known that SVMs face difficulty in solving large complex problems due to the intensive computation involved in their training algorithms, which are at least quadratic with respect to the number of training examples. This paper proposes a new, simple, and efficient network architecture which consists of several SVMs each trained on a small subregion of the whole data sampling space and the same number of simple neural quantizer modules which inhibit the outputs of all the remote SVMs and only allow a single local SVM to fire (produce actual output) at any time. In principle, this region-computing based modular network method can significantly reduce the learning time of SVM algorithms without sacrificing much generalization performance. The experiments on a few real large complex benchmark problems demonstrate that our method can be significantly faster than single SVMs without losing much generalization performance.

  8. Size reduction of complex networks preserving modularity

    NASA Astrophysics Data System (ADS)

    Arenas, A.; Duch, J.; Fernández, A.; Gómez, S.

    2007-06-01

    The ubiquity of modular structure in real-world complex networks is the focus of attention in many trials to understand the interplay between network topology and functionality. The best approaches to the identification of modular structure are based on the optimization of a quality function known as modularity. However this optimization is a hard task provided that the computational complexity of the problem is in the non-deterministic polynomial-time hard (NP-hard) class. Here we propose an exact method for reducing the size of weighted (directed and undirected) complex networks while maintaining their modularity. This size reduction allows use of heuristic algorithms that optimize modularity for a better exploration of the modularity landscape. We compare the modularity obtained in several real complex-networks by using the extremal optimization algorithm, before and after the size reduction, showing the improvement obtained. We speculate that the proposed analytical size reduction could be extended to an exact coarse graining of the network in the scope of real-space renormalization.

  9. A Prototype for Modular Cell Engineering.

    PubMed

    Wilbanks, Brandon; Layton, Donovan; Garcia, Sergio; Trinh, Cong

    2017-10-10

    When aiming to produce a target chemical at high yield, titer, and productivity, various combinations of genetic parts available to build the target pathway can generate a large number of strains for characterization. This engineering approach will become increasingly laborious and expensive when seeking to develop desirable strains for optimal production of a large space of biochemicals due to extensive screening. Our recent theoretical development of modular cell (MODCELL) design principles can offer a promising solution for rapid generation of optimal strains by coupling a modular cell and exchangeable production modules in a plug-and-play fashion. In this study, we experimentally validated some designed properties of MODCELL by demonstrating: i) a modular (chassis) cell is required to couple with a production module, a heterologous ethanol pathway, as a testbed, ii) degree of coupling between the modular cell and production modules can be modulated to enhance growth and product synthesis, iii) a modular cell can be used as a host to select an optimal pyruvate decarboxylase (PDC) of the ethanol production module and to help identify a hypothetical PDC protein, and iv) adaptive laboratory evolution based on growth selection of the modular cell can enhance growth and product synthesis rates. We envision that the MODCELL design provides a powerful prototype for modular cell engineering to rapidly create optimal strains for synthesis of a large space of biochemicals.

  10. Size reduction of complex networks preserving modularity

    SciTech Connect

    Arenas, A.; Duch, J.; Fernandez, A.; Gomez, S.

    2008-12-24

    The ubiquity of modular structure in real-world complex networks is being the focus of attention in many trials to understand the interplay between network topology and functionality. The best approaches to the identification of modular structure are based on the optimization of a quality function known as modularity. However this optimization is a hard task provided that the computational complexity of the problem is in the NP-hard class. Here we propose an exact method for reducing the size of weighted (directed and undirected) complex networks while maintaining invariant its modularity. This size reduction allows the heuristic algorithms that optimize modularity for a better exploration of the modularity landscape. We compare the modularity obtained in several real complex-networks by using the Extremal Optimization algorithm, before and after the size reduction, showing the improvement obtained. We speculate that the proposed analytical size reduction could be extended to an exact coarse graining of the network in the scope of real-space renormalization.

  11. Rational design of efficient modular cells.

    PubMed

    Trinh, Cong T; Liu, Yan; Conner, David J

    2015-11-01

    The modular cell design principle is formulated to devise modular (chassis) cells. These cells can be assembled with exchangeable production modules in a plug-and-play fashion to build microbial cell factories for efficient combinatorial biosynthesis of novel molecules, requiring minimal iterative strain optimization steps. A modular cell is designed to be auxotrophic, containing core metabolic pathways that are necessary but insufficient to support cell growth and maintenance. To be functional, it must tightly couple with an exchangeable production module containing auxiliary metabolic pathways that not only complement cell growth but also enhance production of targeted molecules. We developed a MODCELL (modular cell) framework based on metabolic pathway analysis to implement the modular cell design principle. MODCELL identifies genetic modifications and requirements to construct modular cell candidates and their associated exchangeable production modules. By defining the degree of similarity and coupling metrics, MODCELL can evaluate which exchangeable production module(s) can be tightly coupled with a modular cell candidate. We first demonstrated how MODCELL works in a step-by-step manner for example metabolic networks, and then applied it to design modular Escherichia coli cells for efficient combinatorial biosynthesis of five alcohols (ethanol, propanol, isopropanol, butanol and isobutanol) and five butyrate esters (ethyl butyrate, propyl butyrate, isopropyl butyrate, butyl butyrate and isobutyl butyrate) from pentose sugars (arabinose and xylose) and hexose sugars (glucose, mannose, and galactose) under anaerobic conditions. We identified three modular cells, MODCELL1, MODCELL2 and MODCELL3, that can couple well with Group 1 of modules (ethanol, isobutanol, butanol, ethyl butyrate, isobutyl butyrate, butyl butyrate), Group 2 (isopropanol, isopropyl butyrate), and Group 3 (propanol, isopropanol), respectively. We validated the design of MODCELL1 for anaerobic

  12. Neural networks as a possible architecture for the distributed control of space systems

    NASA Technical Reports Server (NTRS)

    Fiesler, E.; Choudry, A.

    1987-01-01

    Researchers attempted to identify the features essential for large, complex, multi-modular multi-functional systems possessing a high level of interconnectivity. These features were studied in the context of neural networks with the aim of arriving at a possible architecture of the distributed control system-specific features of the neural networks and their applicability in space systems.

  13. Chemical oscillator as a generalized Rayleigh oscillator

    NASA Astrophysics Data System (ADS)

    Ghosh, Shyamolina; Ray, Deb Shankar

    2013-10-01

    We derive the conditions under which a set of arbitrary two dimensional autonomous kinetic equations can be reduced to the form of a generalized Rayleigh oscillator which admits of limit cycle solution. This is based on a linear transformation of field variables which can be found by inspection of the kinetic equations. We illustrate the scheme with the help of several chemical and bio-chemical oscillator models to show how they can be cast as a generalized Rayleigh oscillator.

  14. Generalized epidemic process on modular networks

    NASA Astrophysics Data System (ADS)

    Chung, Kihong; Baek, Yongjoo; Kim, Daniel; Ha, Meesoon; Jeong, Hawoong

    2014-05-01

    Social reinforcement and modular structure are two salient features observed in the spreading of behavior through social contacts. In order to investigate the interplay between these two features, we study the generalized epidemic process on modular networks with equal-sized finite communities and adjustable modularity. Using the analytical approach originally applied to clique-based random networks, we show that the system exhibits a bond-percolation type continuous phase transition for weak social reinforcement, whereas a discontinuous phase transition occurs for sufficiently strong social reinforcement. Our findings are numerically verified using the finite-size scaling analysis and the crossings of the bimodality coefficient.

  15. A Modular Approach to Redundant Robot Control

    SciTech Connect

    Anderson, R.J.

    1997-12-01

    This paper describes a modular approach for computing redundant robot kinematics. First some conventional redundant control methods are presented and shown to be `passive control laws`, i.e. they can be represented by a network consisting of passive elements. These networks are then put into modular form by applying scattering operator techniques. Additional subnetwork modules can then be added to further shape the motion. Modules for obstacle detection, joint limit avoidance, proximity sensing, and for imposing nonlinear velocity constraints are presented. The resulting redundant robot control system is modular, flexible and robust.

  16. The gravity duals of modular Hamiltonians

    NASA Astrophysics Data System (ADS)

    Jafferis, Daniel L.; Suh, S. Josephine

    2016-09-01

    In this work, we investigate modular Hamiltonians defined with respect to arbitrary spatial regions in quantum field theory states which have semi-classical gravity duals. We find prescriptions in the gravity dual for calculating the action of the modular Hamiltonian on its defining state, including its dual metric, and also on small excitations around the state. Curiously, use of the covariant holographic entanglement entropy formula leads us to the conclusion that the modular Hamiltonian, which in the quantum field theory acts only in the causal completion of the region, does not commute with bulk operators whose entire gauge-invariant description is space-like to the causal completion of the region.

  17. The gravity duals of modular Hamiltonians

    SciTech Connect

    Jafferis, Daniel L.; Suh, S. Josephine

    2016-09-12

    In this study, we investigate modular Hamiltonians defined with respect to arbitrary spatial regions in quantum field theory states which have semi-classical gravity duals. We find prescriptions in the gravity dual for calculating the action of the modular Hamiltonian on its defining state, including its dual metric, and also on small excitations around the state. Curiously, use of the covariant holographic entanglement entropy formula leads us to the conclusion that the modular Hamiltonian, which in the quantum field theory acts only in the causal completion of the region, does not commute with bulk operators whose entire gauge-invariant description is space-like to the causal completion of the region.

  18. Dysrhythmias of the respiratory oscillator

    NASA Astrophysics Data System (ADS)

    Paydarfar, David; Buerkel, Daniel M.

    1995-03-01

    Breathing is regulated by a central neural oscillator that produces rhythmic output to the respiratory muscles. Pathological disturbances in rhythm (dysrhythmias) are observed in the breathing pattern of children and adults with neurological and cardiopulmonary diseases. The mechanisms responsible for genesis of respiratory dysrhythmias are poorly understood. The present studies take a novel approach to this problem. The basic postulate is that the rhythm of the respiratory oscillator can be altered by a variety of stimuli. When the oscillator recovers its rhythm after such perturbations, its phase may be reset relative to the original rhythm. The amount of phase resetting is dependent upon stimulus parameters and the level of respiratory drive. The long-range hypothesis is that respiratory dysrhythmias can be induced by stimuli that impinge upon or arise within the respiratory oscillator with certain combinations of strength and timing relative to the respiratory cycle. Animal studies were performed in anesthetized or decerebrate preparations. Neural respiratory rhythmicity is represented by phrenic nerve activity, allowing use of open-loop experimental conditions which avoid negative chemical feedback associated with changes in ventilation. In animal experiments, respiratory dysrhythmias can be induced by stimuli having specific combinations of strength and timing. Newborn animals readily exhibit spontaneous dysrhythmias which become more prominent at lower respiratory drives. In human subjects, swallowing was studied as a physiological perturbation of respiratory rhythm, causing a pattern of phase resetting that is characterized topologically as type 0. Computational studies of the Bonhoeffer-van der Pol (BvP) equations, whose qualitative behavior is representative of many excitable systems, supports a unified interpretation of these experimental findings. Rhythmicity is observed when the BvP model exhibits recurrent periods of excitation alternating with

  19. Synchronization of genetic oscillators

    NASA Astrophysics Data System (ADS)

    Zhou, Tianshou; Zhang, Jiajun; Yuan, Zhanjiang; Chen, Luonan

    2008-09-01

    Synchronization of genetic or cellular oscillators is a central topic in understanding the rhythmicity of living organisms at both molecular and cellular levels. Here, we show how a collective rhythm across a population of genetic oscillators through synchronization-induced intercellular communication is achieved, and how an ensemble of independent genetic oscillators is synchronized by a common noisy signaling molecule. Our main purpose is to elucidate various synchronization mechanisms from the viewpoint of dynamics, by investigating the effects of various biologically plausible couplings, several kinds of noise, and external stimuli. To have a comprehensive understanding on the synchronization of genetic oscillators, we consider three classes of genetic oscillators: smooth oscillators (exhibiting sine-like oscillations), relaxation oscillators (displaying jump dynamics), and stochastic oscillators (noise-induced oscillation). For every class, we further study two cases: with intercellular communication (including phase-attractive and repulsive coupling) and without communication between cells. We find that an ensemble of smooth oscillators has different synchronization phenomena from those in the case of relaxation oscillators, where noise plays a different but key role in synchronization. To show differences in synchronization between them, we make comparisons in many aspects. We also show that a population of genetic stochastic oscillators have their own synchronization mechanisms. In addition, we present interesting phenomena, e.g., for relaxation-type stochastic oscillators coupled to a quorum-sensing mechanism, different noise intensities can induce different periodic motions (i.e., inhomogeneous limit cycles).

  20. Modular optimization code package: MOZAIK

    NASA Astrophysics Data System (ADS)

    Bekar, Kursat B.

    This dissertation addresses the development of a modular optimization code package, MOZAIK, for geometric shape optimization problems in nuclear engineering applications. MOZAIK's first mission, determining the optimal shape of the D2O moderator tank for the current and new beam tube configurations for the Penn State Breazeale Reactor's (PSBR) beam port facility, is used to demonstrate its capabilities and test its performance. MOZAIK was designed as a modular optimization sequence including three primary independent modules: the initializer, the physics and the optimizer, each having a specific task. By using fixed interface blocks among the modules, the code attains its two most important characteristics: generic form and modularity. The benefit of this modular structure is that the contents of the modules can be switched depending on the requirements of accuracy, computational efficiency, or compatibility with the other modules. Oak Ridge National Laboratory's discrete ordinates transport code TORT was selected as the transport solver in the physics module of MOZAIK, and two different optimizers, Min-max and Genetic Algorithms (GA), were implemented in the optimizer module of the code package. A distributed memory parallelism was also applied to MOZAIK via MPI (Message Passing Interface) to execute the physics module concurrently on a number of processors for various states in the same search. Moreover, dynamic scheduling was enabled to enhance load balance among the processors while running MOZAIK's physics module thus improving the parallel speedup and efficiency. In this way, the total computation time consumed by the physics module is reduced by a factor close to M, where M is the number of processors. This capability also encourages the use of MOZAIK for shape optimization problems in nuclear applications because many traditional codes related to radiation transport do not have parallel execution capability. A set of computational models based on the

  1. Topological measure locating the effective crossover between segregation and integration in a modular network.

    PubMed

    Adjari Rad, A; Sendiña-Nadal, I; Papo, D; Zanin, M; Buldú, J M; del Pozo, F; Boccaletti, S

    2012-06-01

    We introduce an easily computable topological measure which locates the effective crossover between segregation and integration in a modular network. Segregation corresponds to the degree of network modularity, while integration is expressed in terms of the algebraic connectivity of an associated hypergraph. The rigorous treatment of the simplified case of cliques of equal size that are gradually rewired until they become completely merged, allows us to show that this topological crossover can be made to coincide with a dynamical crossover from cluster to global synchronization of a system of coupled phase oscillators. The dynamical crossover is signaled by a peak in the product of the measures of intracluster and global synchronization, which we propose as a dynamical measure of complexity. This quantity is much easier to compute than the entropy (of the average frequencies of the oscillators), and displays a behavior which closely mimics that of the dynamical complexity index based on the latter. The proposed topological measure simultaneously provides information on the dynamical behavior, sheds light on the interplay between modularity and total integration, and shows how this affects the capability of the network to perform both local and distributed dynamical tasks.

  2. Holographic charge oscillations

    NASA Astrophysics Data System (ADS)

    Blake, Mike; Donos, Aristomenis; Tong, David

    2015-04-01

    The Reissner-Nordström black hole provides the prototypical description of a holographic system at finite density. We study the response of this system to the presence of a local, charged impurity. Below a critical temperature, the induced charge density, which screens the impurity, exhibits oscillations. These oscillations can be traced to the singularities in the density-density correlation function moving in the complex momentum plane. At finite temperature, the oscillations are very similar to the Friedel oscillations seen in Fermi liquids. However, at zero temperature the oscillations in the black hole background remain exponentially damped, while Friedel oscillations relax to a power-law.

  3. Linking Sleep Slow Oscillations with consciousness theories: new vistas on Slow Wave Sleep unconsciousness.

    PubMed

    Gemignani, Angelo; Menicucci, Danilo; Laurino, Marco; Piarulli, Andrea; Mastorci, Francesca; Sebastiani, Laura; Allegrini, Paolo

    2015-01-01

    We review current models of consciousness in the context of wakefulness and sleep. We show that recent results on Slow Wave Sleep, including our own works, naturally fit within consciousness models. In particular, Sleep Slow Oscillations, namely low-frequency (<1Hz) oscillations, contain electrophysiological properties (up and down states) able to elicit and quench neural integration during Slow Wave Sleep. The physiological unconsciousness related to the Sleep Slow Oscillation derives from the interplay between spontaneous or evoked wake-like activities (up states) and half-a-second's electrical silences (down states). Sleep Slow Oscillation induces unconsciousness via the formation of parallel and segregated neural activities.

  4. Modular Heat Exchanger With Integral Heat Pipe

    NASA Technical Reports Server (NTRS)

    Schreiber, Jeffrey G.

    1992-01-01

    Modular heat exchanger with integral heat pipe transports heat from source to Stirling engine. Alternative to heat exchangers depending on integrities of thousands of brazed joints, contains only 40 brazed tubes.

  5. Modular Solar Electric Power (MSEP) Systems (Presentation)

    SciTech Connect

    Hassani, V.

    2000-06-18

    This presentation discusses the development and deployment of Modular Solar Electric Power (MSEP) systems, the feasibility of application of existing binary power cycles to solar trough technology, and identification of next action items.

  6. Modular digital holographic fringe data processing system

    NASA Technical Reports Server (NTRS)

    Downward, J. G.; Vavra, P. C.; Schebor, F. S.; Vest, C. M.

    1985-01-01

    A software architecture suitable for reducing holographic fringe data into useful engineering data is developed and tested. The results, along with a detailed description of the proposed architecture for a Modular Digital Fringe Analysis System, are presented.

  7. The Modular Structure of Protein Networks

    NASA Astrophysics Data System (ADS)

    Rozenfeld, Hernán D.; Rybski, Diego; Havlin, Shlomo; Makse, Hernán A.

    2008-03-01

    The evolution of the human protein homology network (H-PHN) has led to a complex network that exhibits a surprisingly high level of modularity. Topologically, the H-PHN presents well connected groups (conformed by proteins of similar aminoacid structure) and weak connectivities between the groups. Here, we perform an empirical study of the H-PHN to characterize the degree of modularity in terms of scale-invariant laws using recently introduced box covering algorithms. We find that the exponent that determines the scale-invariance of the modularity is unexpectedly higher than the box dimension of the network. In addition, we perform a percolation analysis that gives insight into the evolutionary process that led to the modular organization and dynamics of the present H-PHN.

  8. Modular solar-heating system - design package

    NASA Technical Reports Server (NTRS)

    Sinton, D. S.

    1979-01-01

    Compilation contains design, performance, and hardware specifications in sufficient detail to fabricate or procure materials and install, operate, and maintain complete modular solar heating and hot water system for single family size dwellings.

  9. 47 CFR 15.212 - Modular transmitters.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... modular transmitter must have their own shielding. The physical crystal and tuning capacitors may be... shielded. The physical crystal and tuning capacitors may be located external to the shielded radio elements...

  10. Modular biowaste monitoring system conceptual design

    NASA Technical Reports Server (NTRS)

    Fogal, G. L.

    1974-01-01

    The objective of the study was to define requirements and generate a conceptual design for a Modular Biowaste Monitoring System for specifically supporting shuttle life science experimental and diagnostic programs.

  11. Modular, Intelligent Power Systems for Space Exploration

    NASA Technical Reports Server (NTRS)

    Button, Robert

    2006-01-01

    NASA's new Space Exploration Initiative demands that vehicles, habitats, and rovers achieve unprecedented levels of reliability, safety, effectiveness, and affordability. Modular and intelligent electrical power systems are critical to achieving those goals. Modular electrical power systems naturally increase reliability and safety through built-in fault tolerance. These modular systems also enable standardization across a multitude of systems, thereby greatly increasing affordability of the programs. Various technologies being developed to support this new paradigm for space power systems will be presented. Examples include the use of digital control in power electronics to enable better performance and advanced modularity functions such as distributed, master-less control and series input power conversion. Also, digital control and robust communication enables new levels of power system control, stability, fault detection, and health management. Summary results from recent development efforts are presented along with expected future technology development needs required to support NASA's ambitious space exploration goals.

  12. Modular modelling with Physiome standards.

    PubMed

    Cooling, Michael T; Nickerson, David P; Nielsen, Poul M F; Hunter, Peter J

    2016-12-01

    The complexity of computational models is increasing, supported by research in modelling tools and frameworks. But relatively little thought has gone into design principles for complex models. We propose a set of design principles for complex model construction with the Physiome standard modelling protocol CellML. By following the principles, models are generated that are extensible and are themselves suitable for reuse in larger models of increasing complexity. We illustrate these principles with examples including an architectural prototype linking, for the first time, electrophysiology, thermodynamically compliant metabolism, signal transduction, gene regulation and synthetic biology. The design principles complement other Physiome research projects, facilitating the application of virtual experiment protocols and model analysis techniques to assist the modelling community in creating libraries of composable, characterised and simulatable quantitative descriptions of physiology. The ability to produce and customise complex computational models has great potential to have a positive impact on human health. As the field develops towards whole-cell models and linking such models in multi-scale frameworks to encompass tissue, organ, or organism levels, reuse of previous modelling efforts will become increasingly necessary. Any modelling group wishing to reuse existing computational models as modules for their own work faces many challenges in the context of construction, storage, retrieval, documentation and analysis of such modules. Physiome standards, frameworks and tools seek to address several of these challenges, especially for models expressed in the modular protocol CellML. Aside from providing a general ability to produce modules, there has been relatively little research work on architectural principles of CellML models that will enable reuse at larger scales. To complement and support the existing tools and frameworks, we develop a set of principles to

  13. Optimal Network Modularity for Information Diffusion

    NASA Astrophysics Data System (ADS)

    Nematzadeh, Azadeh; Ferrara, Emilio; Flammini, Alessandro; Ahn, Yong-Yeol

    2014-08-01

    We investigate the impact of community structure on information diffusion with the linear threshold model. Our results demonstrate that modular structure may have counterintuitive effects on information diffusion when social reinforcement is present. We show that strong communities can facilitate global diffusion by enhancing local, intracommunity spreading. Using both analytic approaches and numerical simulations, we demonstrate the existence of an optimal network modularity, where global diffusion requires the minimal number of early adopters.

  14. Modular Programming Techniques for Distributed Computing Tasks

    DTIC Science & Technology

    2004-08-01

    Modular Programming Techniques for Distributed Computing Tasks Anthony Cowley, Hwa-Chow Hsu, Camillo J. Taylor GRASP Laboratory University of...network, distributed computing , software design 1. INTRODUCTION As efforts to field sensor networks, or teams of mobile robots, become more...TITLE AND SUBTITLE Modular Programming Techniques for Distributed Computing Tasks 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER

  15. [Importance of neurobiology for modular psychotherapy].

    PubMed

    Schmahl, C; Bohus, M

    2013-11-01

    In the context of continuing education in psychiatry and psychotherapy, modular psychotherapy is of special importance. In modular psychotherapy, general interventions, e.g. for regulation of emotions, have an important function. In this review examples are given to describe the importance of neurobiology for the understanding and the improvement of these mechanisms. In addition, the use of neurobiological investigations within classical psychotherapy trials in the fields of borderline personality disorder and posttraumatic stress disorder will be depicted.

  16. A 3-d modular gripper design tool

    SciTech Connect

    Brown, R.G.; Brost, R.C.

    1997-01-01

    Modular fixturing kits are precisely machined sets of components used for flexible, short-turnaround construction of fixtures for a variety of manufacturing purposes. A modular vise is a parallel-jaw vise, where each jaw is a modular fixture plate with a regular grid of precisely positioned holes. A modular vise can be used to locate and hold parts for machining, assembly, and inspection tasks. To fixture a part, one places pins in some of the holes so that when the vise is closed, the part is reliably located and completely constrained. The modular vise concept can be adapted easily to the design of modular parallel-jaw grippers for robots. By attaching a grid plate to each jaw of a parallel-jaw gripper, the authors gain the ability to easily construct high-quality grasps for a wide variety of parts from a standard set of hardware. Wallack and Canny developed a previous algorithm for planning planar grasp configurations for the modular vise. In this paper, the authors expand this work to produce a 3-d fixture/gripper design tool. They describe several analyses added to the planar algorithm to improve its utility, including a three-dimensional grasp quality metric based on geometric and force information, three-dimensional geometric loading analysis, and inter-gripper interference analysis to determine the compatibility of multiple grasps for handing the part from one gripper to another. Finally, the authors describe two applications which combine the utility of modular vise-style grasping with inter-gripper interference: The first is the design of a flexible part-handling subsystem for a part cleaning workcell under development at Sandia National Laboratories; the second is the automatic design of grippers that support the assembly of multiple products on a single assembly line.

  17. A 3-d modular gripper design tool

    SciTech Connect

    Brown, R.G.; Brost, R.C.

    1997-02-01

    Modular fixturing kits are sets of components used for flexible, rapid construction of fixtures. A modular vise is a parallel-jaw vise, each jaw of which is a modular fixture plate with a regular grid of precisely positioned holes. To fixture a part, one places pins in some of the holes so that when the vise is closed, the part is reliably located and completely constrained. The modular vise concept can be adapted easily to the design of modular parallel-jaw grippers for robots. By attaching a grid-plate to each jaw of a parallel-jaw gripper, one gains the ability to easily construct high-quality grasps for a wide variety of parts from a standard set of hardware. Wallack and Canny developed an algorithm for planning planar grasp configurations for the modular vise. In this paper, the authors expand this work to produce a 3-d fixture/gripper design tool. They describe several analyses they have added to the planar algorithm, including a 3-d grasp quality metric based on force information, 3-d geometric loading analysis, and inter-gripper interference analysis. Finally, the authors describe two applications of their code. One of these is an internal application at Sandia, while the other shows a potential use of the code for designing part of an agile assembly line.

  18. Evolution of Complex Modular Biological Networks

    PubMed Central

    Hintze, Arend; Adami, Christoph

    2008-01-01

    Biological networks have evolved to be highly functional within uncertain environments while remaining extremely adaptable. One of the main contributors to the robustness and evolvability of biological networks is believed to be their modularity of function, with modules defined as sets of genes that are strongly interconnected but whose function is separable from those of other modules. Here, we investigate the in silico evolution of modularity and robustness in complex artificial metabolic networks that encode an increasing amount of information about their environment while acquiring ubiquitous features of biological, social, and engineering networks, such as scale-free edge distribution, small-world property, and fault-tolerance. These networks evolve in environments that differ in their predictability, and allow us to study modularity from topological, information-theoretic, and gene-epistatic points of view using new tools that do not depend on any preconceived notion of modularity. We find that for our evolved complex networks as well as for the yeast protein–protein interaction network, synthetic lethal gene pairs consist mostly of redundant genes that lie close to each other and therefore within modules, while knockdown suppressor gene pairs are farther apart and often straddle modules, suggesting that knockdown rescue is mediated by alternative pathways or modules. The combination of network modularity tools together with genetic interaction data constitutes a powerful approach to study and dissect the role of modularity in the evolution and function of biological networks. PMID:18266463

  19. Managing in an age of modularity.

    PubMed

    Baldwin, C Y; Clark, K B

    1997-01-01

    Modularity is a familiar principle in the computer industry. Different companies can independently design and produce components, suck as disk drives or operating software, and those modules will fit together into a complex and smoothly functioning product because the module makers obey a given set of design rules. Modularity in manufacturing is already common in many companies. But now a number of them are beginning to extend the approach into the design of their products and services. Modularity in design should tremendously boost the rate of innovation in many industries as it did in the computer industry. As businesses as diverse as auto manufacturing and financial services move toward modular designs, the authors say, competitive dynamics will change enormously. No longer will assemblers control the final product: suppliers of key modules will gain leverage and even take on responsibility for design rules. Companies will compete either by specifying the dominant design rules (as Microsoft does) or by producing excellent modules (as disk drive maker Quantum does). Leaders in a modular industry will control less, so they will have to watch the competitive environment closely for opportunities to link up with other module makers. They will also need to know more: engineering details that seemed trivial at the corporate level may now play a large part in strategic decisions. Leaders will also become knowledge managers internally because they will need to coordinate the efforts of development groups in order to keep them focused on the modular strategies the company is pursuing.

  20. Synchronization-based computation through networks of coupled oscillators

    PubMed Central

    Malagarriga, Daniel; García-Vellisca, Mariano A.; Villa, Alessandro E. P.; Buldú, Javier M.; García-Ojalvo, Jordi; Pons, Antonio J.

    2015-01-01

    The mesoscopic activity of the brain is strongly dynamical, while at the same time exhibits remarkable computational capabilities. In order to examine how these two features coexist, here we show that the patterns of synchronized oscillations displayed by networks of neural mass models, representing cortical columns, can be used as substrates for Boolean-like computations. Our results reveal that the same neural mass network may process different combinations of dynamical inputs as different logical operations or combinations of them. This dynamical feature of the network allows it to process complex inputs in a very sophisticated manner. The results are reproduced experimentally with electronic circuits of coupled Chua oscillators, showing the robustness of this kind of computation to the intrinsic noise and parameter mismatch of the coupled oscillators. We also show that the information-processing capabilities of coupled oscillations go beyond the simple juxtaposition of logic gates. PMID:26300765

  1. Theory for the Emergence of Modularity in Complex Systems

    NASA Astrophysics Data System (ADS)

    Deem, Michael; Park, Jeong-Man

    2013-03-01

    Biological systems are modular, and this modularity evolves over time and in different environments. A number of observations have been made of increased modularity in biological systems under increased environmental pressure. We here develop a theory for the dynamics of modularity in these systems. We find a principle of least action for the evolved modularity at long times. In addition, we find a fluctuation dissipation relation for the rate of change of modularity at short times. We discuss a number of biological and social systems that can be understood with this framework. The modularity of the protein-protein interaction network increases when yeast are exposed to heat shock, and the modularity of the protein-protein networks in both yeast and E. coli appears to have increased over evolutionary time. Food webs in low-energy, stressful environments are more modular than those in plentiful environments, arid ecologies are more modular during droughts, and foraging of sea otters is more modular when food is limiting. The modularity of social networks changes over time: stock brokers instant messaging networks are more modular under stressful market conditions, criminal networks are more modular under increased police pressure, and world trade network modularity has decreased

  2. Modular Wideband Active Vibration Absorber

    NASA Technical Reports Server (NTRS)

    Smith, David R.; Zewari, Wahid; Lee, Kenneth Y.

    1999-01-01

    A comparison of space experiments with previous missions shows a common theme. Some of the recent experiments are based on the scientific fundamentals of instruments of prior years. However, the main distinguishing characteristic is the embodiment of advances in engineering and manufacturing in order to extract clearer and sharper images and extend the limits of measurement. One area of importance to future missions is providing vibration free observation platforms at acceptable costs. It has been shown by researchers that vibration problems cannot be eliminated by passive isolation techniques alone. Therefore, various organizations have conducted research in the area of combining active and passive vibration control techniques. The essence of this paper is to present progress in what is believed to be a new concept in this arena. It is based on the notion that if one active element in a vibration transmission path can provide a reasonable vibration attenuation, two active elements in series may provide more control options and better results. The paper presents the functions of a modular split shaft linear actuator developed by NASA's Goddard Space Flight Center and University of Massachusetts Lowell. It discusses some of the control possibilities facilitated by the device. Some preliminary findings and problems are also discussed.

  3. The TOTEM modular trigger system

    NASA Astrophysics Data System (ADS)

    Bagliesi, M. G.; Berretti, M.; Cecchi, R.; Greco, V.; Lami, S.; Latino, G.; Oliveri, E.; Pedreschi, E.; Scribano, A.; Spinella, F.; Turini, N.

    2010-05-01

    The TOTEM experiment will measure the total cross-section with the luminosity independent method and study elastic and diffractive scattering at the LHC. We are developing a modular trigger system, based on programmable logic, that will select meaningful events within 2.5 μs. The trigger algorithm is based on a tree structure in order to obtain information compression. The trigger primitive is generated directly on the readout chip, VFAT, that has a specific fast output that gives low resolution hits information. In two of the TOTEM detectors, Roman Pots and T2, a coincidence chip will perform track recognition directly on the detector readout boards, while for T1 the hits are transferred from the VFATs to the trigger hardware. Starting from more than 2000 bits delivered by the detector electronics, we extract, in a first step, six trigger patterns of 32 LVDS signals each; we build, then, on a dedicated board, a 1-bit (L1) trigger signal for the TOTEM experiment and 16 trigger bits to the CMS experiment global trigger system for future common data taking.

  4. Modular verification of concurrent systems

    SciTech Connect

    Sobel, A.E.K.

    1986-01-01

    During the last ten years, a number of authors have proposed verification techniques that allow one to prove properties of individual processes by using global assumptions about the behavior of the remaining processes in the distributed program. As a result, one must justify these global assumptions before drawing any conclusions regarding the correctness of the entire program. This justification is often the most difficult part of the proof and presents a serious obstacle to hierarchical program development. This thesis develops a new approach to the verification of concurrent systems. The approach is modular and supports compositional development of programs since the proofs of each individual process of a program are completely isolated from all others. The generality of this approach is illustrated by applying it to a representative set of contemporary concurrent programming languages, namely: CSP, ADA, Distributed Processes, and a shared variable language. In addition, it is also shown how the approach may be used to deal with a number of other constructs that have been proposed for inclusion in concurrent languages: FORK and JOIN primitives, nested monitor calls, path expressions, atomic transactions, and asynchronous message passing. These results allow argument that the approach is universal and can be used to design proof systems for any concurrent language.

  5. Saturation in coupled oscillators

    NASA Astrophysics Data System (ADS)

    Roman, Ahmed; Hanna, James

    2015-03-01

    We consider a weakly nonlinear system consisting of a resonantly forced oscillator coupled to an unforced oscillator. It has long been known that, for quadratic nonlinearities and a 2:1 resonance between the oscillators, a perturbative solution of the dynamics exhibits a phenomenon known as saturation. At low forcing, the forced oscillator responds, while the unforced oscillator is quiescent. Above a critical value of the forcing, the forced oscillator's steady-state amplitude reaches a plateau, while that of the unforced oscillator increases without bound. We show that, contrary to established folklore, saturation is not unique to quadratically nonlinear systems. We present conditions on the form of the nonlinear couplings and resonance that lead to saturation. Our results elucidate a mechanism for localization or diversion of energy in systems of coupled oscillators, and suggest new approaches for the control or suppression of vibrations in engineered systems.

  6. Basal Ganglia Beta Oscillations Accompany Cue Utilization

    PubMed Central

    Leventhal, Daniel K.; Gage, Gregory J.; Schmidt, Robert; Pettibone, Jeffrey R.; Case, Alaina C.; Berke, Joshua D.

    2012-01-01

    SUMMARY Beta oscillations in cortical-basal ganglia (BG) circuits have been implicated in normal movement suppression and motor impairment in Parkinson’s disease. To dissect the functional correlates of these rhythms we compared neural activity during four distinct variants of a cued choice task in rats. Brief beta (~20 Hz) oscillations occurred simultaneously throughout the cortical-BG network, both spontaneously and at precise moments of task performance. Beta phase was rapidly reset in response to salient cues, yet increases in beta power were not rigidly linked to cues, movements, or movement suppression. Rather, beta power was enhanced after cues were used to determine motor output. We suggest that beta oscillations reflect a postdecision stabilized state of cortical-BG networks, which normally reduces interference from alternative potential actions. The abnormally strong beta seen in Parkinson’s Disease may reflect overstabilization of these networks, producing pathological persistence of the current motor state. PMID:22325204

  7. Fitness, environmental changes and the growth of modularity- a quasispecies theory for the evolutionary dynamics of modularity

    NASA Astrophysics Data System (ADS)

    Niestemski, Liang; Park, Jeong-Man; Deem, Michael

    2015-03-01

    Although the modularity of a biological system is demonstrated and recognized, the evolution of the modularity is not well understood. We here present a quasispecies theory for the evolutionary dynamics of modularity. Complemented with numerical models, this analytical theory shows the calculation of the steady-state fitness in a randomly changing environment, the relationship between rate of environmental changes and rate of growth of modularity, as well as a principle of least action for the evolved modularity at steady state.

  8. Sculpting the Intrinsic Modular Organization of Spontaneous Brain Activity by Art

    PubMed Central

    Lin, Chia-Shu; Liu, Yong; Huang, Wei-Yuan; Lu, Chia-Feng; Teng, Shin; Ju, Tzong-Ching; He, Yong; Wu, Yu-Te; Jiang, Tianzi; Hsieh, Jen-Chuen

    2013-01-01

    Artistic training is a complex learning that requires the meticulous orchestration of sophisticated polysensory, motor, cognitive, and emotional elements of mental capacity to harvest an aesthetic creation. In this study, we investigated the architecture of the resting-state functional connectivity networks from professional painters, dancers and pianists. Using a graph-based network analysis, we focused on the art-related changes of modular organization and functional hubs in the resting-state functional connectivity network. We report that the brain architecture of artists consists of a hierarchical modular organization where art-unique and artistic form-specific brain states collectively mirror the mind states of virtuosos. We show that even in the resting state, this type of extraordinary and long-lasting training can macroscopically imprint a neural network system of spontaneous activity in which the related brain regions become functionally and topologically modularized in both domain-general and domain-specific manners. The attuned modularity reflects a resilient plasticity nurtured by long-term experience. PMID:23840527

  9. Sculpting the Intrinsic Modular Organization of Spontaneous Brain Activity by Art.

    PubMed

    Lin, Chia-Shu; Liu, Yong; Huang, Wei-Yuan; Lu, Chia-Feng; Teng, Shin; Ju, Tzong-Ching; He, Yong; Wu, Yu-Te; Jiang, Tianzi; Hsieh, Jen-Chuen

    2013-01-01

    Artistic training is a complex learning that requires the meticulous orchestration of sophisticated polysensory, motor, cognitive, and emotional elements of mental capacity to harvest an aesthetic creation. In this study, we investigated the architecture of the resting-state functional connectivity networks from professional painters, dancers and pianists. Using a graph-based network analysis, we focused on the art-related changes of modular organization and functional hubs in the resting-state functional connectivity network. We report that the brain architecture of artists consists of a hierarchical modular organization where art-unique and artistic form-specific brain states collectively mirror the mind states of virtuosos. We show that even in the resting state, this type of extraordinary and long-lasting training can macroscopically imprint a neural network system of spontaneous activity in which the related brain regions become functionally and topologically modularized in both domain-general and domain-specific manners. The attuned modularity reflects a resilient plasticity nurtured by long-term experience.

  10. Encoding via conjugate symmetries of slow oscillations for globally coupled oscillators.

    PubMed

    Ashwin, Peter; Borresen, Jon

    2004-08-01

    We study properties of the dynamics underlying slow cluster oscillations in two systems of five globally coupled oscillators. These slow oscillations are due to the appearance of structurally stable heteroclinic connections between cluster states in the noise-free dynamics. In the presence of low levels of noise they give rise to long periods of residence near cluster states interspersed with sudden transitions between them. Moreover, these transitions may occur between cluster states of the same symmetry, or between cluster states with conjugate symmetries given by some rearrangement of the oscillators. We consider the system of coupled phase oscillators studied by Hansel et al. [Phys. Rev. E 48, 3470 (1993)] in which one can observe slow, noise-driven oscillations that occur between two families of two cluster periodic states; in the noise-free case there is a robust attracting heteroclinic cycle connecting these families. The two families consist of symmetric images of two inequivalent periodic orbits that have the same symmetry. For N=5 oscillators, one of the periodic orbits has one unstable direction and the other has two unstable directions. Examining the behavior on the unstable manifold for the two unstable directions, we observe that the dimensionality of the manifold can give rise to switching between conjugate symmetry orbits. By applying small perturbations to the system we can easily steer it between a number of different marginally stable attractors. Finally, we show that similar behavior occurs in a system of phase-energy oscillators that are a natural extension of the phase model to two dimensional oscillators. We suggest that switching between conjugate symmetries is a very efficient method of encoding information into a globally coupled system of oscillators and may therefore be a good and simple model for the neural encoding of information.

  11. Development of a modular integrated control architecture for flexible manipulators. Final report

    SciTech Connect

    Burks, B.L.; Battiston, G.

    1994-12-08

    In April 1994, ORNL and SPAR completed the joint development of a manipulator controls architecture for flexible structure controls under a CRADA between the two organizations. The CRADA project entailed design and development of a new architecture based upon the Modular Integrated Control Architecture (MICA) previously developed by ORNL. The new architecture, dubbed MICA-II, uses an object-oriented coding philosophy to provide a highly modular and expandable architecture for robotic manipulator control. This architecture can be readily ported to control of many different manipulator systems. The controller also provides a user friendly graphical operator interface and display of many forms of data including system diagnostics. The capabilities of MICA-II were demonstrated during oscillation damping experiments using the Flexible Beam Experimental Test Bed at Hanford.

  12. Modular control during incline and level walking in humans.

    PubMed

    Janshen, Lars; Santuz, Alessandro; Ekizos, Antonis; Arampatzis, Adamantios

    2017-03-01

    The neuromuscular control of human movement can be described by a set of muscle synergies factorized from myoelectric signals. There is some evidence that the selection, activation and flexible combination of these basic activation patterns are of a neural origin. We investigated the muscle synergies during incline and level walking to evaluate changes in the modular organization of neuromuscular control related to changes in the mechanical demands. Our results revealed five fundamental (not further factorizable) synergies for both walking conditions but with different frequencies of appearance of the respective synergies during incline compared with level walking. Low similarities across conditions were observed in the timing of the activation patterns (motor primitives) and the weightings of the muscles within the respective elements (motor modules) for the synergies associated with the touchdown, mid-stance and early push-off phase. The changes in neuromuscular control could be attributed to changes in the mechanical demands in support, propulsion and medio-lateral stabilization of the body during incline compared with level walking. Our findings provide further evidence that the central nervous system flexibly uses a consistent set of neural control elements with a flexible temporal recruitment and modifications of the relative muscle weightings within each element to provide stable locomotion under varying mechanical demands during walking.

  13. Neural Networks

    DTIC Science & Technology

    1990-01-01

    FUNDING NUMBERS PROGRAM PROJECT TASK WORK UNIT ELEMENT NO. NO. NO. ACCESSION NO 11 TITLE (Include Security Classification) NEURAL NETWORKS 12. PERSONAL...SUB-GROUP Neural Networks Optical Architectures Nonlinear Optics Adaptation 19. ABSTRACT (Continue on reverse if necessary and identify by block number...341i Y C-odes , lo iii/(iv blank) 1. INTRODUCTION Neural networks are a type of distributed processing system [1

  14. Neuronal oscillations in sleep: insights from functional neuroimaging.

    PubMed

    Dang-Vu, Thien Thanh

    2012-09-01

    Recent functional neuroimaging studies have investigated brain activity patterns during sleep in humans, beyond the conventionally defined sleep stages. These works have characterized the neural activations related to the major brain oscillations of sleep, that is, spindles and slow waves during non-rapid-eye-movement sleep and ponto-geniculo-occipital waves during rapid-eye-movement sleep. These phasic events have been found associated with increases of brain activity in specific neural networks, which identify structures involved in the generation of sleep oscillations. Most importantly, these results confirm that, even during the deepest stages of sleep, neuronal network activities are sustained and organized by spontaneous brain oscillations of sleep. The understanding of the neural mechanisms underlying sleep oscillations is fundamental since increasing evidence suggests a pivotal role for these rhythms in the functional properties of sleep. In particular, interactions between the sleeping brain and the surrounding environment are closely modulated by neuronal oscillations of sleep. Functional neuroimaging studies have demonstrated that spindles distort the transmission of auditory information to the cortex, therefore isolating the brain from external disturbances during sleep. In contrast, slow waves evoked by acoustic stimulation--and also termed K-complexes--are associated with larger auditory cortex activation, thus reflecting an enhanced processing of external information during sleep. Future brain imaging studies of sleep should further explore the contribution of neuronal oscillations to the off-line consolidation of memory during sleep.

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

    PubMed

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

    2017-03-29

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

  16. Advanced Modular Inverter Technology Development

    SciTech Connect

    Adam Szczepanek

    2006-02-04

    Electric and hybrid-electric vehicle systems require an inverter to convert the direct current (DC) output of the energy generation/storage system (engine, fuel cells, or batteries) to the alternating current (AC) that vehicle propulsion motors use. Vehicle support systems, such as lights and air conditioning, also use the inverter AC output. Distributed energy systems require an inverter to provide the high quality AC output that energy system customers demand. Today's inverters are expensive due to the cost of the power electronics components, and system designers must also tailor the inverter for individual applications. Thus, the benefits of mass production are not available, resulting in high initial procurement costs as well as high inverter maintenance and repair costs. Electricore, Inc. (www.electricore.org) a public good 501 (c) (3) not-for-profit advanced technology development consortium assembled a highly qualified team consisting of AeroVironment Inc. (www.aerovironment.com) and Delphi Automotive Systems LLC (Delphi), (www.delphi.com), as equal tiered technical leads, to develop an advanced, modular construction, inverter packaging technology that will offer a 30% cost reduction over conventional designs adding to the development of energy conversion technologies for crosscutting applications in the building, industry, transportation, and utility sectors. The proposed inverter allows for a reduction of weight and size of power electronics in the above-mentioned sectors and is scalable over the range of 15 to 500kW. The main objective of this program was to optimize existing AeroVironment inverter technology to improve power density, reliability and producibility as well as develop new topology to reduce line filter size. The newly developed inverter design will be used in automotive and distribution generation applications. In the first part of this program the high-density power stages were redesigned, optimized and fabricated. One of the main tasks

  17. Teleoperated Modular Robots for Lunar Operations

    NASA Technical Reports Server (NTRS)

    Globus, Al; Hornby, Greg; Larchev, Greg; Hancher, Matt; Cannon, Howard; Lohn, Jason

    2004-01-01

    Solar system exploration is currently carried out by special purpose robots exquisitely designed for the anticipated tasks. However, all contingencies for in situ resource utilization (ISRU), human habitat preparation, and exploration will be difficult to anticipate. Furthermore, developing the necessary special purpose mechanisms for deployment and other capabilities is difficult and error prone. For example, the Galileo high gain antenna never opened, severely restricting the quantity of data returned by the spacecraft. Also, deployment hardware is used only once. To address these problems, we are developing teleoperated modular robots for lunar missions, including operations in transit from Earth. Teleoperation of lunar systems from Earth involves a three second speed-of-light delay, but experiment suggests that interactive operations are feasible.' Modular robots typically consist of many identical modules that pass power and data between them and can be reconfigured for different tasks providing great flexibility, inherent redundancy and graceful degradation as modules fail. Our design features a number of different hub, link, and joint modules to simplify the individual modules, lower structure cost, and provide specialized capabilities. Modular robots are well suited for space applications because of their extreme flexibility, inherent redundancy, high-density packing, and opportunities for mass production. Simple structural modules can be manufactured from lunar regolith in situ using molds or directed solar sintering. Software to direct and control modular robots is difficult to develop. We have used genetic algorithms to evolve both the morphology and control system for walking modular robots3 We are currently using evolvable system technology to evolve controllers for modular robots in the ISS glove box. Development of lunar modular robots will require software and physical simulators, including regolith simulation, to enable design and test of robot

  18. Endomorphisms on half-sided modular inclusions

    SciTech Connect

    Svegstrup, Rolf Dyre

    2006-12-15

    In algebraic quantum field theory we consider nets of von Neumann algebras indexed over regions of the space time. Wiesbrock [''Conformal quantum field theory and half-sided modular inclusions of von Neumann algebras,'' Commun. Math. Phys. 158, 537-543 (1993)] has shown that strongly additive nets of von Neumann algebras on the circle are in correspondence with standard half-sided modular inclusions. We show that a finite index endomorphism on a half-sided modular inclusion extends to a finite index endomorphism on the corresponding net of von Neumann algebras on the circle. Moreover, we present another approach to encoding endomorphisms on nets of von Neumann algebras on the circle into half-sided modular inclusions. There is a natural way to associate a weight to a Moebius covariant endomorphism. The properties of this weight have been studied by Bertozzini et al. [''Covariant sectors with infinite dimension and positivity of the energy,'' Commun. Math. Phys. 193, 471-492 (1998)]. In this paper we show the converse, namely, how to associate a Moebius covariant endomorphism to a given weight under certain assumptions, thus obtaining a correspondence between a class of weights on a half-sided modular inclusion and a subclass of the Moebius covariant endomorphisms on the associated net of von Neumann algebras. This allows us to treat Moebius covariant endomorphisms in terms of weights on half-sided modular inclusions. As our aim is to provide a framework for treating endomorphisms on nets of von Neumann algebras in terms of the apparently simpler objects of weights on half-sided modular inclusions, we lastly give some basic results for manipulations with such weights.

  19. Local modularity for community detection in complex networks

    NASA Astrophysics Data System (ADS)

    Xiang, Ju; Hu, Tao; Zhang, Yan; Hu, Ke; Li, Jian-Ming; Xu, Xiao-Ke; Liu, Cui-Cui; Chen, Shi

    2016-02-01

    Community detection is a topic of interest in the study of complex networks such as the protein-protein interaction networks and metabolic networks. In recent years, various methods were proposed to detect community structures of the networks. Here, a kind of local modularity with tunable parameter is derived from the Newman-Girvan modularity by a special self-loop strategy that depends on the community division of the networks. By the self-loop strategy, one can easily control the definition of modularity, and the resulting modularity can be optimized by using the existing modularity optimization algorithms. The local modularity is used as the target function for community detection, and a self-consistent method is proposed for the optimization of the local modularity. We analyze the behaviors of the local modularity and show the validity of the local modularity in detecting community structures on various networks.

  20. Robust modular product family design

    NASA Astrophysics Data System (ADS)

    Jiang, Lan; Allada, Venkat

    2001-10-01

    This paper presents a modified Taguchi methodology to improve the robustness of modular product families against changes in customer requirements. The general research questions posed in this paper are: (1) How to effectively design a product family (PF) that is robust enough to accommodate future customer requirements. (2) How far into the future should designers look to design a robust product family? An example of a simplified vacuum product family is used to illustrate our methodology. In the example, customer requirements are selected as signal factors; future changes of customer requirements are selected as noise factors; an index called quality characteristic (QC) is set to evaluate the product vacuum family; and the module instance matrix (M) is selected as control factor. Initially a relation between the objective function (QC) and the control factor (M) is established, and then the feasible M space is systemically explored using a simplex method to determine the optimum M and the corresponding QC values. Next, various noise levels at different time points are introduced into the system. For each noise level, the optimal values of M and QC are computed and plotted on a QC-chart. The tunable time period of the control factor (the module matrix, M) is computed using the QC-chart. The tunable time period represents the maximum time for which a given control factor can be used to satisfy current and future customer needs. Finally, a robustness index is used to break up the tunable time period into suitable time periods that designers should consider while designing product families.

  1. Modular Manufacturing Simulator: Users Manual

    NASA Technical Reports Server (NTRS)

    1997-01-01

    The Modular Manufacturing Simulator (MMS) has been developed for the beginning user of computer simulations. Consequently, the MMS cannot model complex systems that require branching and convergence logic. Once a user becomes more proficient in computer simulation and wants to add more complexity, the user is encouraged to use one of the many available commercial simulation systems. The (MMS) is based on the SSE5 that was developed in the early 1990's by the University of Alabama in Huntsville (UAH). A recent survey by MSFC indicated that the simulator has been a major contributor to the economic impact of the MSFC technology transfer program. Many manufacturers have requested additional features for the SSE5. Consequently, the following features have been added to the MMS that are not available in the SSE5: runs under Windows, print option for both input parameters and output statistics, operator can be fixed at a station or assigned to a group of stations, operator movement based on time limit, part limit, or work-in-process (WIP) limit at next station. The movement options for a moveable operators are: go to station with largest WIP, rabbit chase where operator moves in circular sequence between stations, and push/pull where operator moves back and forth between stations. This user's manual contains the necessary information for installing the MMS on a PC, a description of the various MMS commands, and the solutions to a number of sample problems using the MMS. Also included in the beginning of this report is a brief discussion of technology transfer.

  2. Covariant harmonic oscillators and coupled harmonic oscillators

    NASA Technical Reports Server (NTRS)

    Han, Daesoo; Kim, Young S.; Noz, Marilyn E.

    1995-01-01

    It is shown that the system of two coupled harmonic oscillators shares the basic symmetry properties with the covariant harmonic oscillator formalism which provides a concise description of the basic features of relativistic hadronic features observed in high-energy laboratories. It is shown also that the coupled oscillator system has the SL(4,r) symmetry in classical mechanics, while the present formulation of quantum mechanics can accommodate only the Sp(4,r) portion of the SL(4,r) symmetry. The possible role of the SL(4,r) symmetry in quantum mechanics is discussed.

  3. SHOCK-EXCITED OSCILLATOR

    DOEpatents

    Creveling, R.

    1957-12-17

    S> A shock-excited quartz crystal oscillator is described. The circuit was specifically designed for application in micro-time measuring work to provide an oscillator which immediately goes into oscillation upon receipt of a trigger pulse and abruptly ceases oscillation when a second pulse is received. To achieve the instant action, the crystal has a prestressing voltage applied across it. A monostable multivibrator receives the on and off trigger pulses and discharges a pulse through the crystal to initiate or terminate oscillation instantly.

  4. No warmup crystal oscillator

    NASA Technical Reports Server (NTRS)

    Phillips, D. H.

    1982-01-01

    During warmup, crystal oscillators often show a frequency offset as large as 1 part in 10 to the 5th power. If timing information is transferred to the oscillator and then the oscillator is allowed to warmup, a timing error greater than 1 millisecond will occur. For many applications, it is unsuitable to wait for the oscillator to warmup. For medium accuracy timing requirements where overall accuracies in the order of 1 millisecond are required, a no warmup crystal concept was developed. The concept utilizes two crystal oscillator, used sequentially to avoid using a crystal oscillator for timing much higher frequency accuracy once warmed up. The accuracy achieved with practical TCXOs at initial start over a range of temperatures is discussed. A second design utilizing two oven controlled oscillators is also discussed.

  5. Non-linear oscillations

    NASA Astrophysics Data System (ADS)

    Hagedorn, P.

    The mathematical pendulum is used to provide a survey of free and forced oscillations in damped and undamped systems. This simple model is employed to present illustrations for and comparisons between the various approximation schemes. A summary of the Liapunov stability theory is provided. The first and the second method of Liapunov are explained for autonomous as well as for nonautonomous systems. Here, a basic familiarity with the theory of linear oscillations is assumed. La Salle's theorem about the stability of invariant domains is explained in terms of illustrative examples. Self-excited oscillations are examined, taking into account such oscillations in mechanical and electrical systems, analytical approximation methods for the computation of self-excited oscillations, analytical criteria for the existence of limit cycles, forced oscillations in self-excited systems, and self-excited oscillations in systems with several degrees of freedom. Attention is given to Hamiltonian systems and an introduction to the theory of optimal control is provided.

  6. Global rhythmic activities in hippocampal neural fields and neural coding.

    PubMed

    Ventriglia, Francesco

    2006-01-01

    Global oscillations of the neural field represent some of the most interesting expressions of the hippocampal activity, being related also to learning and memory. To study oscillatory activities of the CA3 field in theta range, a model of this sub-field of Hippocampus has been formulated. The model describes the firing activity of CA3 neuronal populations within the frame of a kinetic theory of neural systems and it has been used for computer simulations. The results show that the propagation of activities induced in the neural field by hippocampal afferents occurs only in narrow time windows confined by inhibitory barrages, whose time-course follows the theta rhythm. Moreover, during each period of a theta wave, the entire CA3 field bears a firing activity with peculiar space-time patterns, a sort of specific imprint, which can induce effects with similar patterns on brain regions driven by the hippocampal formation. The simulation has also demonstrated the ability of medial septum to influence the global activity of the CA3 pyramidal population through the control of the population of inhibitory interneurons. At last, the possible involvement of global population oscillations in neural coding has been discussed.

  7. Modular organization of the brainstem noradrenaline system coordinates opposing learning states.

    PubMed

    Uematsu, Akira; Tan, Bao Zhen; Ycu, Edgar A; Cuevas, Jessica Sulkes; Koivumaa, Jenny; Junyent, Felix; Kremer, Eric J; Witten, Ilana B; Deisseroth, Karl; Johansen, Joshua P

    2017-09-18

    Noradrenaline modulates global brain states and diverse behaviors through what is traditionally believed to be a homogeneous cell population in the brainstem locus coeruleus (LC). However, it is unclear how LC coordinates disparate behavioral functions. We report a modular LC organization in rats, endowed with distinct neural projection patterns and coding properties for flexible specification of opposing behavioral learning states. LC projection mapping revealed functionally distinct cell modules with specific anatomical connectivity. An amygdala-projecting ensemble promoted aversive learning, while an independent medial prefrontal cortex-projecting ensemble extinguished aversive responses to enable flexible behavior. LC neurons displayed context-dependent inter-relationships, with moderate, discrete activation of distinct cell populations by fear or safety cues and robust, global recruitment of most cells by strong aversive stimuli. These results demonstrate a modular organization in LC in which combinatorial activation modes are coordinated with projection- and behavior-specific cell populations, enabling adaptive tuning of emotional responding and behavioral flexibility.

  8. Plasticity and modular control of locomotor patterns in neurological disorders with motor deficits

    PubMed Central

    Ivanenko, Y. P.; Cappellini, G.; Solopova, I. A.; Grishin, A. A.; MacLellan, M. J.; Poppele, R. E.; Lacquaniti, F.

    2013-01-01

    Human locomotor movements exhibit considerable variability and are highly complex in terms of both neural activation and biomechanical output. The building blocks with which the central nervous system constructs these motor patterns can be preserved in patients with various sensory-motor disorders. In particular, several studies highlighted a modular burst-like organization of the muscle activity. Here we review and discuss this issue with a particular emphasis on the various examples of adaptation of locomotor patterns in patients (with large fiber neuropathy, amputees, stroke and spinal cord injury). The results highlight plasticity and different solutions to reorganize muscle patterns in both peripheral and central nervous system lesions. The findings are discussed in a general context of compensatory gait mechanisms, spatiotemporal architecture and modularity of the locomotor program. PMID:24032016

  9. A modular approach to language production: models and facts.

    PubMed

    Valle-Lisboa, Juan C; Pomi, Andrés; Cabana, Álvaro; Elvevåg, Brita; Mizraji, Eduardo

    2014-06-01

    Numerous cortical disorders affect language. We explore the connection between the observed language behavior and the underlying substrates by adopting a neurocomputational approach. To represent the observed trajectories of the discourse in patients with disorganized speech and in healthy participants, we design a graphical representation for the discourse as a trajectory that allows us to visualize and measure the degree of order in the discourse as a function of the disorder of the trajectories. Our work assumes that many of the properties of language production and comprehension can be understood in terms of the dynamics of modular networks of neural associative memories. Based upon this assumption, we connect three theoretical and empirical domains: (1) neural models of language processing and production, (2) statistical methods used in the construction of functional brain images, and (3) corpus linguistic tools, such as Latent Semantic Analysis (henceforth LSA), that are used to discover the topic organization of language. We show how the neurocomputational models intertwine with LSA and the mathematical basis of functional neuroimaging. Within this framework we describe the properties of a context-dependent neural model, based on matrix associative memories, that performs goal-oriented linguistic behavior. We link these matrix associative memory models with the mathematics that underlie functional neuroimaging techniques and present the "functional brain images" emerging from the model. This provides us with a completely "transparent box" with which to analyze the implication of some statistical images. Finally, we use these models to explore the possibility that functional synaptic disconnection can lead to an increase in connectivity between the representations of concepts that could explain some of the alterations in discourse displayed by patients with schizophrenia.

  10. [Modular psychotherapy with children and adolescents].

    PubMed

    Schmidt, Stefanie J; Schimmelmann, Benno G

    2016-11-01

    The implementation of evidence-based psychotherapy with children and adolescents has been limited so far. This is mainly due to the fact that patients in service settings tend to have higher rates of comorbidities and more frequently changing therapy needs than those in research settings. Thus, modular psychotherapies are promising, as they allow the treatment protocol to be adapted to patients’ individual needs. Because no review on modular psychotherapy for children and adolescents exists, we conducted a systematic literature research. The results of the 15 randomized controlled trials identified demonstrate that modular psychotherapy is associated with significant reductions in symptom levels as well as with higher rates of diagnostic remission compared to control conditions. Because of the lack of evidence, future studies should investigate the incremental efficacy of modular approaches and test the validity of underlying theoretical models as well as of decision flowcharts. Modular psychotherapy approaches have the potential to personalize evidence-based interventions for children and adolescents across various therapeutical traditions, and to facilitate their implementation into clinical practice.

  11. Beta/Gamma Oscillations and Event-Related Potentials Indicate Aberrant Multisensory Processing in Schizophrenia.

    PubMed

    Balz, Johanna; Roa Romero, Yadira; Keil, Julian; Krebber, Martin; Niedeggen, Michael; Gallinat, Jürgen; Senkowski, Daniel

    2016-01-01

    Recent behavioral and neuroimaging studies have suggested multisensory processing deficits in patients with schizophrenia (SCZ). Thus far, the neural mechanisms underlying these deficits are not well understood. Previous studies with unisensory stimulation have shown altered neural oscillations in SCZ. As such, altered oscillations could contribute to aberrant multisensory processing in this patient group. To test this assumption, we conducted an electroencephalography (EEG) study in 15 SCZ and 15 control participants in whom we examined neural oscillations and event-related potentials (ERPs) in the sound-induced flash illusion (SIFI). In the SIFI multiple auditory stimuli that are presented alongside a single visual stimulus can induce the illusory percept of multiple visual stimuli. In SCZ and control participants we compared ERPs and neural oscillations between trials that induced an illusion and trials that did not induce an illusion. On the behavioral level, SCZ (55.7%) and control participants (55.4%) did not significantly differ in illusion rates. The analysis of ERPs revealed diminished amplitudes and altered multisensory processing in SCZ compared to controls around 135 ms after stimulus onset. Moreover, the analysis of neural oscillations revealed altered 25-35 Hz power after 100 to 150 ms over occipital scalp for SCZ compared to controls. Our findings extend previous observations of aberrant neural oscillations in unisensory perception paradigms. They suggest that altered ERPs and altered occipital beta/gamma band power reflect aberrant multisensory processing in SCZ.

  12. Beta/Gamma Oscillations and Event-Related Potentials Indicate Aberrant Multisensory Processing in Schizophrenia

    PubMed Central

    Balz, Johanna; Roa Romero, Yadira; Keil, Julian; Krebber, Martin; Niedeggen, Michael; Gallinat, Jürgen; Senkowski, Daniel

    2016-01-01

    Recent behavioral and neuroimaging studies have suggested multisensory processing deficits in patients with schizophrenia (SCZ). Thus far, the neural mechanisms underlying these deficits are not well understood. Previous studies with unisensory stimulation have shown altered neural oscillations in SCZ. As such, altered oscillations could contribute to aberrant multisensory processing in this patient group. To test this assumption, we conducted an electroencephalography (EEG) study in 15 SCZ and 15 control participants in whom we examined neural oscillations and event-related potentials (ERPs) in the sound-induced flash illusion (SIFI). In the SIFI multiple auditory stimuli that are presented alongside a single visual stimulus can induce the illusory percept of multiple visual stimuli. In SCZ and control participants we compared ERPs and neural oscillations between trials that induced an illusion and trials that did not induce an illusion. On the behavioral level, SCZ (55.7%) and control participants (55.4%) did not significantly differ in illusion rates. The analysis of ERPs revealed diminished amplitudes and altered multisensory processing in SCZ compared to controls around 135 ms after stimulus onset. Moreover, the analysis of neural oscillations revealed altered 25–35 Hz power after 100 to 150 ms over occipital scalp for SCZ compared to controls. Our findings extend previous observations of aberrant neural oscillations in unisensory perception paradigms. They suggest that altered ERPs and altered occipital beta/gamma band power reflect aberrant multisensory processing in SCZ. PMID:27999553

  13. An Integrated Modular Avionics Development Environment

    NASA Astrophysics Data System (ADS)

    Schoofs, T.; Santos, S.; Tatibana, C.; Anjos, J.; Rufino, J.; Windsor, J.

    2009-05-01

    The ARINC 653 standard has taken a leading role within the aeronautical industry in the development of safety-critical systems based upon the Integrated Modular Avionics (IMA) concept. The related cost savings in reduced integration, verification and validation effort has raised interest in the European space industry for developing a spacecraft IMA approach and for the definition of an ARINC 653-for-Space software framework. As part of this process, it is necessary to establish an effective way to develop, test and analyse on-board applications without having access to the final IMA target platform for all engineers. Target platforms are usually extremely expensive considering hardware and software prices as well as training costs. This paper describes the architecture of an Integrated Modular Avionics Development Environment (IMADE) based on the Linux Operating System and the ARINC 653 simulator for Modular On-Board Applications that was developed by Skysoft Portugal, S.A. In cooperation with ESA, 2007-2008.

  14. A modular PMAD system for small spacecraft

    NASA Astrophysics Data System (ADS)

    Button, Robert M.

    1997-01-01

    Current trends in satellite design are focused on developing small, reliable, and inexpensive spacecraft. To that end, a modular power management and distribution system (PMAD) is proposed which will help transition the aerospace industry towards an assembly line approach to building spacecraft. The modular system is based on an innovative DC voltage boost converter called the Series Connected Boost Unit (SCBU). The SCBU uses existing DC-DC converters and adds a unique series connection. This simple modification provides the SCBU topology with many advantages over existing boost converters. Efficiencies of 94-98%, power densities above 1,000 We/kg, and inherent fault tolerance are just a few of the characteristics presented. Limitations of the SCBU technology are presented, and it is shown that the SCBU makes an ideal photovoltaic array regulator. A modular design based on the series connected boost unit is outlined and functional descriptions of the components are given.

  15. The gravity duals of modular Hamiltonians

    DOE PAGES

    Jafferis, Daniel L.; Suh, S. Josephine

    2016-09-12

    In this study, we investigate modular Hamiltonians defined with respect to arbitrary spatial regions in quantum field theory states which have semi-classical gravity duals. We find prescriptions in the gravity dual for calculating the action of the modular Hamiltonian on its defining state, including its dual metric, and also on small excitations around the state. Curiously, use of the covariant holographic entanglement entropy formula leads us to the conclusion that the modular Hamiltonian, which in the quantum field theory acts only in the causal completion of the region, does not commute with bulk operators whose entire gauge-invariant description is space-likemore » to the causal completion of the region.« less

  16. A Modular PMAD System for Small Spacecraft

    NASA Technical Reports Server (NTRS)

    Button, Robert M.

    1998-01-01

    Current trends in satellite design are focused on developing small, reliable, and inexpensive spacecraft. To that end, a modular power management and distribution system (PMAD) is proposed which will help transition the aerospace industry towards an assembly line approach to building spacecraft. The modular system is based on an innovative DC voltage boost converter called the Series Connected Boost Regulator (SCBR). The SCBR uses existing DC-DC converters and adds a unique series connection. This simple modification provides the SCBR topology with many advantages over existing boost converters. Efficiencies of 94-98%, power densities above 1,000 We/kg, and inherent fault tolerance are just a few of the characteristics presented. Limitations of the SCBR technology are presented, and it is shown that the SCBR makes an ideal photovoltaic array regulator. A modular design based on the series connected boost unit is outlined and functional descriptions of the components are given.

  17. Large-scale brain functional modularity is reflected in slow electroencephalographic rhythms across the human non-rapid eye movement sleep cycle.

    PubMed

    Tagliazucchi, Enzo; von Wegner, Frederic; Morzelewski, Astrid; Brodbeck, Verena; Borisov, Sergey; Jahnke, Kolja; Laufs, Helmut

    2013-04-15

    Large-scale brain functional networks (measured with functional magnetic resonance imaging, fMRI) are organized into separated but interacting modules, an architecture supporting the integration of distinct dynamical processes. In this work we study how the aforementioned modular architecture changes with the progressive loss of vigilance occurring in the descent to deep sleep and we examine the relationship between the ensuing slow electroencephalographic rhythms and large-scale network modularity as measured with fMRI. Graph theoretical methods are used to analyze functional connectivity graphs obtained from fifty-five participants at wakefulness, light and deep sleep. Network modularity (a measure of functional segregation) was found to increase during deeper sleep stages but not in light sleep. By endowing functional networks with dynamical properties, we found a direct link between increased electroencephalographic (EEG) delta power (1-4 Hz) and a breakdown of inter-modular connectivity. Both EEG slowing and increased network modularity were found to quickly decrease during awakenings from deep sleep to wakefulness, in a highly coordinated fashion. Studying the modular structure itself by means of a permutation test, we revealed different module memberships when deep sleep was compared to wakefulness. Analysis of node roles in the modular structure revealed an increase in the number of locally well-connected nodes and a decrease in the number of globally well-connected hubs, which hinders interactions between separated functional modules. Our results reveal a well-defined sequence of changes in brain modular organization occurring during the descent to sleep and establish a close parallel between modularity alterations in large-scale functional networks (accessible through whole brain fMRI recordings) and the slowing of scalp oscillations (visible on EEG). The observed re-arrangement of connectivity might play an important role in the processes underlying loss

  18. [Modular tumor prostheses of the humerus].

    PubMed

    Funovics, P T; Dominkus, M

    2010-10-01

    The humerus is a common location of musculoskeletal tumors. Modular prostheses of the humerus, besides APC and biological reconstructions, allow restoration of resulting bone defects. The functional outcome is determined by the extent of bone and soft tissue loss. Anatomical shoulder prostheses have a limited abductor function, while shoulder function could be improved by an inverse prosthetic design and implants for ligament repair. Elbow prostheses provide satisfactory function. Our own results in 101 patients showed a 23% revision rate. The median overall survival was 171 months with an overall 5-year survival of 53%. With respect to good oncological outcomes modular reconstruction of the humerus is a feasible treatment option for cancer patients.

  19. Modular arrangement of regulatory RNA elements.

    PubMed

    Roßmanith, Johanna; Narberhaus, Franz

    2017-03-04

    Due to their simple architecture and control mechanism, regulatory RNA modules are attractive building blocks in synthetic biology. This is especially true for riboswitches, which are natural ligand-binding regulators of gene expression. The discovery of various tandem riboswitches inspired the design of combined RNA modules with activities not yet found in nature. Riboswitches were placed in tandem or in combination with a ribozyme or temperature-responsive RNA thermometer resulting in new functionalities. Here, we compare natural examples of tandem riboswitches with recently designed artificial RNA regulators suggesting substantial modularity of regulatory RNA elements. Challenges associated with modular RNA design are discussed.

  20. Proving relations between modular graph functions

    NASA Astrophysics Data System (ADS)

    Basu, Anirban

    2016-12-01

    We consider modular graph functions that arise in the low energy expansion of the four graviton amplitude in type II string theory. The vertices of these graphs are the positions of insertions of vertex operators on the toroidal worldsheet, while the links are the scalar Green functions connecting the vertices. Graphs with four and five links satisfy several non-trivial relations, which have been proved recently. We prove these relations by using elementary properties of Green functions and the details of the graphs. We also prove a relation between modular graph functions with six links.

  1. Modular arrangement of regulatory RNA elements

    PubMed Central

    Roßmanith, Johanna; Narberhaus, Franz

    2017-01-01

    ABSTRACT Due to their simple architecture and control mechanism, regulatory RNA modules are attractive building blocks in synthetic biology. This is especially true for riboswitches, which are natural ligand-binding regulators of gene expression. The discovery of various tandem riboswitches inspired the design of combined RNA modules with activities not yet found in nature. Riboswitches were placed in tandem or in combination with a ribozyme or temperature-responsive RNA thermometer resulting in new functionalities. Here, we compare natural examples of tandem riboswitches with recently designed artificial RNA regulators suggesting substantial modularity of regulatory RNA elements. Challenges associated with modular RNA design are discussed. PMID:28010165

  2. Both ongoing alpha and visually induced gamma oscillations show reliable diversity in their across-site phase-relations.

    PubMed

    van Ede, Freek; van Pelt, Stan; Fries, Pascal; Maris, Eric

    2015-03-01

    Neural oscillations have emerged as one of the major electrophysiological phenomena investigated in cognitive and systems neuroscience. These oscillations are typically studied with regard to their amplitude, phase, and/or phase coupling. Here we demonstrate the existence of another property that is intrinsic to neural oscillations but has hitherto remained largely unexplored in cognitive and systems neuroscience. This pertains to the notion that these oscillations show reliable diversity in their phase-relations between neighboring recording sites (phase-relation diversity). In contrast to most previous work, we demonstrate that this diversity is restricted neither to low-frequency oscillations nor to periods outside of sensory stimulation. On the basis of magnetoencephalographic (MEG) recordings in humans, we show that this diversity is prominent not only for ongoing alpha oscillations (8-12 Hz) but also for gamma oscillations (50-70 Hz) that are induced by sustained visual stimulation. We further show that this diversity provides a dimension within electrophysiological data that, provided a sufficiently high signal-to-noise ratio, does not covary with changes in amplitude. These observations place phase-relation diversity on the map as a prominent and general property of neural oscillations that, moreover, can be studied with noninvasive methods in healthy human volunteers. This opens important new avenues for investigating how neural oscillations contribute to the neural implementation of cognition and behavior. Copyright © 2015 the American Physiological Society.

  3. Oscillator-interference models of path integration do not require theta oscillations.

    PubMed

    Orchard, Jeff

    2015-03-01

    Navigation and path integration in rodents seems to involve place cells, grid cells, and theta oscillations (4-12 Hz) in the local field potential. Two main theories have been proposed to explain the neurological underpinnings of how these phenomena relate to navigation and to each other. Attractor network (AN) models revolve around the idea that local excitation and long-range inhibition connectivity can spontaneously generate grid-cell-like activity patterns. Oscillator interference (OI) models propose that spatial patterns of activity are caused by the interference patterns between neural oscillators. In rats, these oscillators have a frequency close to the theta frequency. Recent studies have shown that bats do not exhibit a theta cycle when they crawl, and yet they still have grid cells. This has been interpreted as a criticism of OI models. However, OI models do not require theta oscillations. We explain why the absence of theta oscillations does not contradict OI models and discuss how the two families of models might be distinguished experimentally.

  4. Paradoxes of neutrino oscillations

    SciTech Connect

    Akhmedov, E. Kh.; Smirnov, A. Yu.

    2009-08-15

    Despite the theory of neutrino oscillations being rather old, some of its basic issues are still being debated in the literature. We discuss a number of such issues, including the relevance of the 'same energy' and 'same momentum' assumptions, the role of quantum-mechanical uncertainty relations in neutrino oscillations, the dependence of the coherence and localization conditions that ensure the observability of neutrino oscillations on neutrino energy and momentum uncertainties, the question of (in)dependence of the oscillation probabilities on the neutrino production and detection processes, and the applicability limits of the stationary-source approximation. We also develop a novel approach to calculation of the oscillation probability in the wave-packet approach, based on the summation/integration conventions different from the standard one, which allows a new insight into the 'same energy' vs. 'same momentum' problem. We also discuss a number of apparently paradoxical features of the theory of neutrino oscillations.

  5. Workshop on Harmonic Oscillators

    NASA Technical Reports Server (NTRS)

    Han, D. (Editor); Kim, Y. S. (Editor); Zachary, W. W. (Editor)

    1993-01-01

    Proceedings of a workshop on Harmonic Oscillators held at the College Park Campus of the University of Maryland on March 25 - 28, 1992 are presented. The harmonic oscillator formalism is playing an important role in many branches of physics. This is the simplest mathematical device which can connect the basic principle of physics with what is observed in the real world. The harmonic oscillator is the bridge between pure and applied physics.

  6. Oscillations in stellar atmospheres

    NASA Technical Reports Server (NTRS)

    Costa, A.; Ringuelet, A. E.; Fontenla, J. M.

    1989-01-01

    Atmospheric excitation and propagation of oscillations are analyzed for typical pulsating stars. The linear, plane-parallel approach for the pulsating atmosphere gives a local description of the phenomenon. From the local analysis of oscillations, the minimum frequencies are obtained for radially propagating waves. The comparison of the minimum frequencies obtained for a variety of stellar types is in good agreement with the observed periods of the oscillations. The role of the atmosphere in the globar stellar pulsations is thus emphasized.

  7. Self-oscillation

    NASA Astrophysics Data System (ADS)

    Jenkins, Alejandro

    2013-04-01

    Physicists are very familiar with forced and parametric resonance, but usually not with self-oscillation, a property of certain dynamical systems that gives rise to a great variety of vibrations, both useful and destructive. In a self-oscillator, the driving force is controlled by the oscillation itself so that it acts in phase with the velocity, causing a negative damping that feeds energy into the vibration: no external rate needs to be adjusted to the resonant frequency. The famous collapse of the Tacoma Narrows bridge in 1940, often attributed by introductory physics texts to forced resonance, was actually a self-oscillation, as was the swaying of the London Millennium Footbridge in 2000. Clocks are self-oscillators, as are bowed and wind musical instruments. The heart is a “relaxation oscillator”, i.e., a non-sinusoidal self-oscillator whose period is determined by sudden, nonlinear switching at thresholds. We review the general criterion that determines whether a linear system can self-oscillate. We then describe the limiting cycles of the simplest nonlinear self-oscillators, as well as the ability of two or more coupled self-oscillators to become spontaneously synchronized (“entrained”). We characterize the operation of motors as self-oscillation and prove a theorem about their limit efficiency, of which Carnot’s theorem for heat engines appears as a special case. We briefly discuss how self-oscillation applies to servomechanisms, Cepheid variable stars, lasers, and the macroeconomic business cycle, among other applications. Our emphasis throughout is on the energetics of self-oscillation, often neglected by the literature on nonlinear dynamical systems.

  8. Oscillations in stellar atmospheres

    NASA Technical Reports Server (NTRS)

    Costa, A.; Ringuelet, A. E.; Fontenla, J. M.

    1989-01-01

    Atmospheric excitation and propagation of oscillations are analyzed for typical pulsating stars. The linear, plane-parallel approach for the pulsating atmosphere gives a local description of the phenomenon. From the local analysis of oscillations, the minimum frequencies are obtained for radially propagating waves. The comparison of the minimum frequencies obtained for a variety of stellar types is in good agreement with the observed periods of the oscillations. The role of the atmosphere in the globar stellar pulsations is thus emphasized.

  9. Modular Apparatus and Method for Attaching Multiple Devices

    NASA Technical Reports Server (NTRS)

    Okojie, Robert S (Inventor)

    2015-01-01

    A modular apparatus for attaching sensors and electronics is disclosed. The modular apparatus includes a square recess including a plurality of cavities and a reference cavity such that a pressure sensor can be connected to the modular apparatus. The modular apparatus also includes at least one voltage input hole and at least one voltage output hole operably connected to each of the plurality of cavities such that voltage can be applied to the pressure sensor and received from the pressure sensor.

  10. 46 CFR 181.450 - Independent modular smoke detecting units.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 46 Shipping 7 2011-10-01 2011-10-01 false Independent modular smoke detecting units. 181.450... Independent modular smoke detecting units. (a) An independent modular smoke detecting unit must: (1) Meet UL 217 (incorporated by reference, see 46 CFR 175.600) and be listed as a “Single Station Smoke detector...

  11. 46 CFR 181.450 - Independent modular smoke detecting units.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 46 Shipping 7 2010-10-01 2010-10-01 false Independent modular smoke detecting units. 181.450... Independent modular smoke detecting units. (a) An independent modular smoke detecting unit must: (1) Meet UL 217 (incorporated by reference, see 46 CFR 175.600) and be listed as a “Single Station Smoke detector...

  12. 46 CFR 181.450 - Independent modular smoke detecting units.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 46 Shipping 7 2013-10-01 2013-10-01 false Independent modular smoke detecting units. 181.450... Independent modular smoke detecting units. (a) An independent modular smoke detecting unit must: (1) Meet UL 217 (incorporated by reference, see 46 CFR 175.600) and be listed as a “Single Station Smoke...

  13. 46 CFR 181.450 - Independent modular smoke detecting units.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 46 Shipping 7 2012-10-01 2012-10-01 false Independent modular smoke detecting units. 181.450... Independent modular smoke detecting units. (a) An independent modular smoke detecting unit must: (1) Meet UL 217 (incorporated by reference, see 46 CFR 175.600) and be listed as a “Single Station Smoke...

  14. 46 CFR 181.450 - Independent modular smoke detecting units.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 46 Shipping 7 2014-10-01 2014-10-01 false Independent modular smoke detecting units. 181.450... Independent modular smoke detecting units. (a) An independent modular smoke detecting unit must: (1) Meet UL 217 (incorporated by reference, see 46 CFR 175.600) and be listed as a “Single Station Smoke...

  15. On Classification of Modular Categories by Rank: Table A.1

    SciTech Connect

    Bruillard, Paul; Ng, Siu-Hung; Rowell, Eric C.; Wang, Zhenghan

    2016-04-10

    The feasibility of a classification-by-rank program for modular categories follows from the Rank-Finiteness Theorem. We develop arithmetic, representation theoretic and algebraic methods for classifying modular categories by rank. As an application, we determine all possible fusion rules for all rank=5 modular categories and describe the corresponding monoidal equivalence classes.

  16. Atypical neural synchronization to speech envelope modulations in dyslexia.

    PubMed

    De Vos, Astrid; Vanvooren, Sophie; Vanderauwera, Jolijn; Ghesquière, Pol; Wouters, Jan

    2017-01-01

    A fundamental deficit in the synchronization of neural oscillations to temporal information in speech could underlie phonological processing problems in dyslexia. In this study, the hypothesis of a neural synchronization impairment is investigated more specifically as a function of different neural oscillatory bands and temporal information rates in speech. Auditory steady-state responses to 4, 10, 20 and 40Hz modulations were recorded in normal reading and dyslexic adolescents to measure neural synchronization of theta, alpha, beta and low-gamma oscillations to syllabic and phonemic rate information. In comparison to normal readers, dyslexic readers showed reduced non-synchronized theta activity, reduced synchronized alpha activity and enhanced synchronized beta activity. Positive correlations between alpha synchronization and phonological skills were found in normal readers, but were absent in dyslexic readers. In contrast, dyslexic readers exhibited positive correlations between beta synchronization and phonological skills. Together, these results suggest that auditory neural synchronization of alpha and beta oscillations is atypical in dyslexia, indicating deviant neural processing of both syllabic and phonemic rate information. Impaired synchronization of alpha oscillations in particular demonstrated to be the most prominent neural anomaly possibly hampering speech and phonological processing in dyslexic readers. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. Honeywell Modular Automation System Computer Software Documentation

    SciTech Connect

    CUNNINGHAM, L.T.

    1999-09-27

    This document provides a Computer Software Documentation for a new Honeywell Modular Automation System (MAS) being installed in the Plutonium Finishing Plant (PFP). This system will be used to control new thermal stabilization furnaces in HA-211 and vertical denitration calciner in HC-230C-2.

  18. Modularity, Working Memory and Language Acquisition

    ERIC Educational Resources Information Center

    Baddeley, Alan D.

    2017-01-01

    The concept of modularity is used to contrast the approach to working memory proposed by Truscott with the Baddeley and Hitch multicomponent model. This proposes four sub components comprising the "central executive," an executive control system of limited attentional capacity that utilises storage based on separate but interlinked…

  19. Modular learning models in forecasting natural phenomena.

    PubMed

    Solomatine, D P; Siek, M B

    2006-03-01

    Modular model is a particular type of committee machine and is comprised of a set of specialized (local) models each of which is responsible for a particular region of the input space, and may be trained on a subset of training set. Many algorithms for allocating such regions to local models typically do this in automatic fashion. In forecasting natural processes, however, domain experts want to bring in more knowledge into such allocation, and to have certain control over the choice of models. This paper presents a number of approaches to building modular models based on various types of splits of training set and combining the models' outputs (hard splits, statistically and deterministically driven soft combinations of models, 'fuzzy committees', etc.). An issue of including a domain expert into the modeling process is also discussed, and new algorithms in the class of model trees (piece-wise linear modular regression models) are presented. Comparison of the algorithms based on modular local modeling to the more traditional 'global' learning models on a number of benchmark tests and river flow forecasting problems shows their higher accuracy and transparency of the resulting models.

  20. Modular Building Institute 2001 Educational Showcase.

    ERIC Educational Resources Information Center

    Modular Building Inst., Charlottesville, VA.

    This publication contains brief articles concerned with modular school structures. Some articles offer examples of such structures at actual schools. The articles in this issue are: (1) "An Architect's Perspective: Convincing a Skeptic" (Robert M. Iamello); (2) "66 Portables for San Mateo High" (Steven Williams); (3) "Case Study: Charter Schools"…